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org.apache.hadoop.hive.ql.parse.CalcitePlanner Maven / Gradle / Ivy
/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.hadoop.hive.ql.parse;
import java.io.IOException;
import java.lang.reflect.Field;
import java.lang.reflect.InvocationTargetException;
import java.lang.reflect.UndeclaredThrowableException;
import java.math.BigDecimal;
import java.util.AbstractMap.SimpleEntry;
import java.util.ArrayDeque;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.BitSet;
import java.util.Collection;
import java.util.Collections;
import java.util.Deque;
import java.util.EnumSet;
import java.util.HashMap;
import java.util.HashSet;
import java.util.Iterator;
import java.util.LinkedHashMap;
import java.util.LinkedList;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.Set;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.atomic.AtomicInteger;
import javax.sql.DataSource;
import com.google.common.collect.Iterables;
import org.antlr.runtime.ClassicToken;
import org.antlr.runtime.CommonToken;
import org.antlr.runtime.tree.Tree;
import org.antlr.runtime.tree.TreeVisitor;
import org.antlr.runtime.tree.TreeVisitorAction;
import org.apache.calcite.adapter.druid.DruidQuery;
import org.apache.calcite.adapter.druid.DruidSchema;
import org.apache.calcite.adapter.druid.DruidTable;
import org.apache.calcite.adapter.jdbc.JdbcConvention;
import org.apache.calcite.adapter.jdbc.JdbcSchema;
import org.apache.calcite.adapter.jdbc.JdbcTable;
import org.apache.calcite.config.CalciteConnectionConfig;
import org.apache.calcite.config.CalciteConnectionConfigImpl;
import org.apache.calcite.config.CalciteConnectionProperty;
import org.apache.calcite.interpreter.BindableConvention;
import org.apache.calcite.plan.RelOptCluster;
import org.apache.calcite.plan.RelOptMaterialization;
import org.apache.calcite.plan.RelOptPlanner;
import org.apache.calcite.plan.RelOptRule;
import org.apache.calcite.plan.RelOptSchema;
import org.apache.calcite.plan.RelOptUtil;
import org.apache.calcite.plan.RelTraitSet;
import org.apache.calcite.plan.hep.HepMatchOrder;
import org.apache.calcite.plan.hep.HepPlanner;
import org.apache.calcite.plan.hep.HepProgram;
import org.apache.calcite.plan.hep.HepProgramBuilder;
import org.apache.calcite.rel.RelCollation;
import org.apache.calcite.rel.RelCollationImpl;
import org.apache.calcite.rel.RelCollations;
import org.apache.calcite.rel.RelFieldCollation;
import org.apache.calcite.rel.RelNode;
import org.apache.calcite.rel.RelVisitor;
import org.apache.calcite.rel.core.Aggregate;
import org.apache.calcite.rel.core.AggregateCall;
import org.apache.calcite.rel.core.Filter;
import org.apache.calcite.rel.core.JoinRelType;
import org.apache.calcite.rel.core.Project;
import org.apache.calcite.rel.core.SetOp;
import org.apache.calcite.rel.core.TableScan;
import org.apache.calcite.rel.metadata.CachingRelMetadataProvider;
import org.apache.calcite.rel.metadata.ChainedRelMetadataProvider;
import org.apache.calcite.rel.metadata.DefaultRelMetadataProvider;
import org.apache.calcite.rel.metadata.JaninoRelMetadataProvider;
import org.apache.calcite.rel.metadata.RelMetadataProvider;
import org.apache.calcite.rel.metadata.RelMetadataQuery;
import org.apache.calcite.rel.rules.FilterMergeRule;
import org.apache.calcite.rel.rules.JoinToMultiJoinRule;
import org.apache.calcite.rel.rules.LoptOptimizeJoinRule;
import org.apache.calcite.rel.rules.ProjectMergeRule;
import org.apache.calcite.rel.rules.ProjectRemoveRule;
import org.apache.calcite.rel.type.RelDataType;
import org.apache.calcite.rel.type.RelDataTypeFactory;
import org.apache.calcite.rel.type.RelDataTypeField;
import org.apache.calcite.rel.type.RelDataTypeImpl;
import org.apache.calcite.rex.RexBuilder;
import org.apache.calcite.rex.RexCall;
import org.apache.calcite.rex.RexExecutor;
import org.apache.calcite.rex.RexFieldCollation;
import org.apache.calcite.rex.RexInputRef;
import org.apache.calcite.rex.RexNode;
import org.apache.calcite.rex.RexUtil;
import org.apache.calcite.rex.RexWindowBound;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.calcite.sql.SqlAggFunction;
import org.apache.calcite.sql.SqlCall;
import org.apache.calcite.sql.SqlDialect;
import org.apache.calcite.sql.SqlDialectFactoryImpl;
import org.apache.calcite.sql.SqlExplainLevel;
import org.apache.calcite.sql.SqlKind;
import org.apache.calcite.sql.SqlLiteral;
import org.apache.calcite.sql.SqlNode;
import org.apache.calcite.sql.SqlOperator;
import org.apache.calcite.sql.SqlWindow;
import org.apache.calcite.sql.parser.SqlParserPos;
import org.apache.calcite.sql.type.ArraySqlType;
import org.apache.calcite.sql.type.SqlTypeName;
import org.apache.calcite.sql.validate.SqlValidatorUtil;
import org.apache.calcite.tools.Frameworks;
import org.apache.calcite.util.CompositeList;
import org.apache.calcite.util.ImmutableBitSet;
import org.apache.calcite.util.ImmutableIntList;
import org.apache.calcite.util.Pair;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.hive.common.ObjectPair;
import org.apache.hadoop.hive.common.ValidTxnList;
import org.apache.hadoop.hive.common.ValidTxnWriteIdList;
import org.apache.hadoop.hive.conf.Constants;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.conf.HiveConf.ConfVars;
import org.apache.hadoop.hive.conf.HiveConf.StrictChecks;
import org.apache.hadoop.hive.metastore.Warehouse;
import org.apache.hadoop.hive.metastore.api.FieldSchema;
import org.apache.hadoop.hive.ql.Context;
import org.apache.hadoop.hive.ql.ErrorMsg;
import org.apache.hadoop.hive.ql.QueryProperties;
import org.apache.hadoop.hive.ql.QueryState;
import org.apache.hadoop.hive.ql.exec.ColumnInfo;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.FunctionInfo;
import org.apache.hadoop.hive.ql.exec.FunctionRegistry;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorFactory;
import org.apache.hadoop.hive.ql.exec.RowSchema;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.log.PerfLogger;
import org.apache.hadoop.hive.ql.metadata.Hive;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.metadata.NotNullConstraint;
import org.apache.hadoop.hive.ql.metadata.PrimaryKeyInfo;
import org.apache.hadoop.hive.ql.metadata.Table;
import org.apache.hadoop.hive.ql.metadata.VirtualColumn;
import org.apache.hadoop.hive.ql.optimizer.calcite.CalciteSemanticException;
import org.apache.hadoop.hive.ql.optimizer.calcite.CalciteSemanticException.UnsupportedFeature;
import org.apache.hadoop.hive.ql.optimizer.calcite.CalciteSubquerySemanticException;
import org.apache.hadoop.hive.ql.optimizer.calcite.CalciteViewSemanticException;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveCalciteUtil;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveConfPlannerContext;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveDefaultRelMetadataProvider;
import org.apache.hadoop.hive.ql.optimizer.calcite.HivePlannerContext;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveRelFactories;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveRelOpMaterializationValidator;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveRexExecutorImpl;
import org.apache.hadoop.hive.ql.optimizer.calcite.HiveTypeSystemImpl;
import org.apache.hadoop.hive.ql.optimizer.calcite.RelOptHiveTable;
import org.apache.hadoop.hive.ql.optimizer.calcite.TraitsUtil;
import org.apache.hadoop.hive.ql.optimizer.calcite.cost.HiveAlgorithmsConf;
import org.apache.hadoop.hive.ql.optimizer.calcite.cost.HiveVolcanoPlanner;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveAggregate;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveExcept;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveFilter;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveGroupingID;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveIntersect;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.jdbc.HiveJdbcConverter;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveJoin;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveProject;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveRelNode;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveSemiJoin;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveSortLimit;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveTableFunctionScan;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveTableScan;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.HiveUnion;
import org.apache.hadoop.hive.ql.optimizer.calcite.reloperators.jdbc.JdbcHiveTableScan;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveAggregateJoinTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveAggregateProjectMergeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveAggregatePullUpConstantsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveAggregateReduceFunctionsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveAggregateReduceRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveDruidRules;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveExceptRewriteRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveExpandDistinctAggregatesRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterAggregateTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterJoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterProjectTSTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterProjectTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterSetOpTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveFilterSortTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveInsertExchange4JoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveIntersectMergeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveIntersectRewriteRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveJoinAddNotNullRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveJoinCommuteRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveJoinProjectTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveJoinPushTransitivePredicatesRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveJoinToMultiJoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HivePartitionPruneRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HivePointLookupOptimizerRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HivePreFilteringRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveProjectFilterPullUpConstantsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveProjectMergeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveProjectOverIntersectRemoveRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveProjectSortTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveReduceExpressionsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveReduceExpressionsWithStatsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveRelDecorrelator;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveRelFieldTrimmer;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveRemoveGBYSemiJoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveRemoveSqCountCheck;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveRulesRegistry;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSemiJoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortJoinReduceRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortLimitPullUpConstantsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortMergeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortProjectTransposeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortRemoveRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSortUnionReduceRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveSubQueryRemoveRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveUnionMergeRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveUnionPullUpConstantsRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.HiveWindowingFixRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCAggregationPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCFilterJoinRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCFilterPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCExtractJoinFilterRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCJoinPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCProjectPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCSortPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCUnionPushDownRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.jdbc.JDBCAbstractSplitFilterRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.views.HiveAggregateIncrementalRewritingRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.views.HiveMaterializedViewRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.views.HiveNoAggregateIncrementalRewritingRule;
import org.apache.hadoop.hive.ql.optimizer.calcite.rules.views.MaterializedViewRewritingRelVisitor;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.ASTBuilder;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.ASTConverter;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.HiveOpConverter;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.JoinCondTypeCheckProcFactory;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.JoinTypeCheckCtx;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.PlanModifierForReturnPath;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.RexNodeConverter;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.SqlFunctionConverter;
import org.apache.hadoop.hive.ql.optimizer.calcite.translator.TypeConverter;
import org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.OrderExpression;
import org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.OrderSpec;
import org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.PartitionExpression;
import org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.PartitionSpec;
import org.apache.hadoop.hive.ql.parse.QBExpr.Opcode;
import org.apache.hadoop.hive.ql.parse.WindowingSpec.BoundarySpec;
import org.apache.hadoop.hive.ql.parse.WindowingSpec.WindowExpressionSpec;
import org.apache.hadoop.hive.ql.parse.WindowingSpec.WindowFunctionSpec;
import org.apache.hadoop.hive.ql.parse.WindowingSpec.WindowSpec;
import org.apache.hadoop.hive.ql.parse.WindowingSpec.WindowType;
import org.apache.hadoop.hive.ql.plan.ExprNodeColumnDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeConstantDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeDescUtils;
import org.apache.hadoop.hive.ql.plan.GroupByDesc;
import org.apache.hadoop.hive.ql.plan.HiveOperation;
import org.apache.hadoop.hive.ql.plan.SelectDesc;
import org.apache.hadoop.hive.ql.session.SessionState;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator.Mode;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFArray;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDTF;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDTFInline;
import org.apache.hadoop.hive.serde.serdeConstants;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.StandardStructObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.StructField;
import org.apache.hadoop.hive.serde2.objectinspector.StructObjectInspector;
import org.apache.hadoop.hive.serde2.typeinfo.ListTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.StructTypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils;
import org.joda.time.Interval;
import com.google.common.base.Function;
import com.google.common.collect.ArrayListMultimap;
import com.google.common.collect.ImmutableList;
import com.google.common.collect.ImmutableList.Builder;
import com.google.common.collect.ImmutableMap;
import com.google.common.collect.Lists;
import com.google.common.collect.Multimap;
public class CalcitePlanner extends SemanticAnalyzer {
private final AtomicInteger noColsMissingStats = new AtomicInteger(0);
private SemanticException semanticException;
private boolean runCBO = true;
private boolean disableSemJoinReordering = true;
private EnumSet profilesCBO;
public CalcitePlanner(QueryState queryState) throws SemanticException {
super(queryState);
if (!HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_CBO_ENABLED)) {
runCBO = false;
disableSemJoinReordering = false;
}
}
public void resetCalciteConfiguration() {
if (HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_CBO_ENABLED)) {
runCBO = true;
disableSemJoinReordering = true;
}
}
@Override
@SuppressWarnings("nls")
public void analyzeInternal(ASTNode ast) throws SemanticException {
if (runCBO) {
super.analyzeInternal(ast, new PlannerContextFactory() {
@Override
public PlannerContext create() {
return new PreCboCtx();
}
});
} else {
super.analyzeInternal(ast);
}
}
/**
* This method is useful if we want to obtain the logical plan after being parsed and
* optimized by Calcite.
*
* @return the Calcite plan for the query, null if it could not be generated
*/
public RelNode genLogicalPlan(ASTNode ast) throws SemanticException {
LOG.info("Starting generating logical plan");
PreCboCtx cboCtx = new PreCboCtx();
//change the location of position alias process here
processPositionAlias(ast);
if (!genResolvedParseTree(ast, cboCtx)) {
return null;
}
ASTNode queryForCbo = ast;
if (cboCtx.type == PreCboCtx.Type.CTAS || cboCtx.type == PreCboCtx.Type.VIEW) {
queryForCbo = cboCtx.nodeOfInterest; // nodeOfInterest is the query
}
runCBO = canCBOHandleAst(queryForCbo, getQB(), cboCtx);
if (!runCBO) {
return null;
}
profilesCBO = obtainCBOProfiles(queryProperties);
disableJoinMerge = true;
final RelNode resPlan = logicalPlan();
LOG.info("Finished generating logical plan");
return resPlan;
}
public static RelOptPlanner createPlanner(HiveConf conf) {
return createPlanner(conf, new HashSet(), new HashSet());
}
private static RelOptPlanner createPlanner(
HiveConf conf, Set corrScalarRexSQWithAgg, Set scalarAggNoGbyNoWin) {
final Double maxSplitSize = (double) HiveConf.getLongVar(
conf, HiveConf.ConfVars.MAPREDMAXSPLITSIZE);
final Double maxMemory = (double) HiveConf.getLongVar(
conf, HiveConf.ConfVars.HIVECONVERTJOINNOCONDITIONALTASKTHRESHOLD);
HiveAlgorithmsConf algorithmsConf = new HiveAlgorithmsConf(maxSplitSize, maxMemory);
HiveRulesRegistry registry = new HiveRulesRegistry();
Properties calciteConfigProperties = new Properties();
calciteConfigProperties.setProperty(
CalciteConnectionProperty.TIME_ZONE.camelName(),
conf.getLocalTimeZone().getId());
calciteConfigProperties.setProperty(
CalciteConnectionProperty.MATERIALIZATIONS_ENABLED.camelName(),
Boolean.FALSE.toString());
CalciteConnectionConfig calciteConfig = new CalciteConnectionConfigImpl(calciteConfigProperties);
boolean isCorrelatedColumns = HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_STATS_CORRELATED_MULTI_KEY_JOINS);
boolean heuristicMaterializationStrategy = HiveConf.getVar(conf,
HiveConf.ConfVars.HIVE_MATERIALIZED_VIEW_REWRITING_SELECTION_STRATEGY).equals("heuristic");
HivePlannerContext confContext = new HivePlannerContext(algorithmsConf, registry, calciteConfig,
corrScalarRexSQWithAgg, scalarAggNoGbyNoWin,
new HiveConfPlannerContext(isCorrelatedColumns, heuristicMaterializationStrategy));
return HiveVolcanoPlanner.createPlanner(confContext);
}
@Override
@SuppressWarnings("rawtypes")
Operator genOPTree(ASTNode ast, PlannerContext plannerCtx) throws SemanticException {
Operator sinkOp = null;
boolean skipCalcitePlan = false;
if (!runCBO) {
skipCalcitePlan = true;
} else {
PreCboCtx cboCtx = (PreCboCtx) plannerCtx;
List oldHints = new ArrayList<>();
// Cache the hints before CBO runs and removes them.
// Use the hints later in top level QB.
getHintsFromQB(getQB(), oldHints);
// Note: for now, we don't actually pass the queryForCbo to CBO, because
// it accepts qb, not AST, and can also access all the private stuff in
// SA. We rely on the fact that CBO ignores the unknown tokens (create
// table, destination), so if the query is otherwise ok, it is as if we
// did remove those and gave CBO the proper AST. That is kinda hacky.
ASTNode queryForCbo = ast;
if (cboCtx.type == PreCboCtx.Type.CTAS || cboCtx.type == PreCboCtx.Type.VIEW) {
queryForCbo = cboCtx.nodeOfInterest; // nodeOfInterest is the query
}
runCBO = canCBOHandleAst(queryForCbo, getQB(), cboCtx);
if (queryProperties.hasMultiDestQuery()) {
handleMultiDestQuery(ast, cboCtx);
}
if (runCBO) {
profilesCBO = obtainCBOProfiles(queryProperties);
disableJoinMerge = true;
boolean reAnalyzeAST = false;
final boolean materializedView = getQB().isMaterializedView();
try {
if (this.conf.getBoolVar(HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP)) {
if (cboCtx.type == PreCboCtx.Type.VIEW && !materializedView) {
throw new SemanticException("Create view is not supported in cbo return path.");
}
sinkOp = getOptimizedHiveOPDag();
if (oldHints.size() > 0) {
LOG.debug("Propagating hints to QB: " + oldHints);
getQB().getParseInfo().setHintList(oldHints);
}
LOG.info("CBO Succeeded; optimized logical plan.");
this.ctx.setCboInfo("Plan optimized by CBO.");
this.ctx.setCboSucceeded(true);
} else {
// 1. Gen Optimized AST
ASTNode newAST = getOptimizedAST();
// 1.1. Fix up the query for insert/ctas/materialized views
newAST = fixUpAfterCbo(ast, newAST, cboCtx);
// 1.2. Fix up the query for materialization rebuild
if (mvRebuildMode == MaterializationRebuildMode.AGGREGATE_REBUILD) {
fixUpASTAggregateIncrementalRebuild(newAST);
} else if (mvRebuildMode == MaterializationRebuildMode.NO_AGGREGATE_REBUILD) {
fixUpASTNoAggregateIncrementalRebuild(newAST);
}
// 2. Regen OP plan from optimized AST
if (cboCtx.type == PreCboCtx.Type.VIEW && !materializedView) {
try {
handleCreateViewDDL(newAST);
} catch (SemanticException e) {
throw new CalciteViewSemanticException(e.getMessage());
}
} else if (cboCtx.type == PreCboCtx.Type.VIEW && materializedView) {
// Store text of the ORIGINAL QUERY
String originalText = ctx.getTokenRewriteStream().toString(
cboCtx.nodeOfInterest.getTokenStartIndex(),
cboCtx.nodeOfInterest.getTokenStopIndex());
unparseTranslator.applyTranslations(ctx.getTokenRewriteStream());
String expandedText = ctx.getTokenRewriteStream().toString(
cboCtx.nodeOfInterest.getTokenStartIndex(),
cboCtx.nodeOfInterest.getTokenStopIndex());
// Redo create-table/view analysis, because it's not part of
// doPhase1.
// Use the REWRITTEN AST
init(false);
setAST(newAST);
newAST = reAnalyzeViewAfterCbo(newAST);
createVwDesc.setViewOriginalText(originalText);
createVwDesc.setViewExpandedText(expandedText);
viewSelect = newAST;
viewsExpanded = new ArrayList<>();
viewsExpanded.add(createVwDesc.getViewName());
} else if (cboCtx.type == PreCboCtx.Type.CTAS) {
// CTAS
init(false);
setAST(newAST);
newAST = reAnalyzeCTASAfterCbo(newAST);
} else {
// All others
init(false);
}
if (oldHints.size() > 0) {
if (getQB().getParseInfo().getHints() != null) {
LOG.warn("Hints are not null in the optimized tree; "
+ "after CBO " + getQB().getParseInfo().getHints().dump());
} else {
LOG.debug("Propagating hints to QB: " + oldHints);
getQB().getParseInfo().setHintList(oldHints);
}
}
Phase1Ctx ctx_1 = initPhase1Ctx();
if (!doPhase1(newAST, getQB(), ctx_1, null)) {
throw new RuntimeException("Couldn't do phase1 on CBO optimized query plan");
}
// unfortunately making prunedPartitions immutable is not possible
// here with SemiJoins not all tables are costed in CBO, so their
// PartitionList is not evaluated until the run phase.
getMetaData(getQB());
disableJoinMerge = defaultJoinMerge;
sinkOp = genPlan(getQB());
LOG.info("CBO Succeeded; optimized logical plan.");
this.ctx.setCboInfo("Plan optimized by CBO.");
this.ctx.setCboSucceeded(true);
if (LOG.isTraceEnabled()) {
LOG.trace(newAST.dump());
}
}
} catch (Exception e) {
boolean isMissingStats = noColsMissingStats.get() > 0;
if (isMissingStats) {
LOG.error("CBO failed due to missing column stats (see previous errors), skipping CBO");
this.ctx
.setCboInfo("Plan not optimized by CBO due to missing statistics. Please check log for more details.");
} else {
LOG.error("CBO failed, skipping CBO. ", e);
if (e instanceof CalciteSemanticException) {
CalciteSemanticException calciteSemanticException = (CalciteSemanticException) e;
UnsupportedFeature unsupportedFeature = calciteSemanticException
.getUnsupportedFeature();
if (unsupportedFeature != null) {
this.ctx.setCboInfo("Plan not optimized by CBO due to missing feature ["
+ unsupportedFeature + "].");
} else {
this.ctx.setCboInfo("Plan not optimized by CBO.");
}
} else {
this.ctx.setCboInfo("Plan not optimized by CBO.");
}
}
if( e instanceof CalciteSubquerySemanticException) {
// non-cbo path retries to execute subqueries and throws completely different exception/error
// to eclipse the original error message
// so avoid executing subqueries on non-cbo
throw new SemanticException(e);
}
else if( e instanceof CalciteViewSemanticException) {
// non-cbo path retries to execute create view and
// we believe it will throw the same error message
throw new SemanticException(e);
}
else if (!conf.getBoolVar(ConfVars.HIVE_IN_TEST) || isMissingStats
|| e instanceof CalciteSemanticException ) {
reAnalyzeAST = true;
} else if (e instanceof SemanticException && !conf.getBoolVar(ConfVars.HIVE_IN_TEST)) {
// although, its likely to be a valid exception, we will retry
// with cbo off anyway.
// for tests we would like to avoid retrying to catch cbo failures
reAnalyzeAST = true;
} else if (e instanceof RuntimeException) {
throw (RuntimeException) e;
} else if (e instanceof SemanticException) {
throw e;
} else {
throw new SemanticException(e);
}
} finally {
runCBO = false;
disableJoinMerge = defaultJoinMerge;
disableSemJoinReordering = false;
if (reAnalyzeAST) {
init(true);
prunedPartitions.clear();
// Assumption: At this point Parse Tree gen & resolution will always
// be true (since we started out that way).
super.genResolvedParseTree(ast, new PlannerContext());
skipCalcitePlan = true;
}
}
} else {
this.ctx.setCboInfo("Plan not optimized by CBO.");
skipCalcitePlan = true;
}
}
if (skipCalcitePlan) {
sinkOp = super.genOPTree(ast, plannerCtx);
}
return sinkOp;
}
private void handleCreateViewDDL(ASTNode newAST) throws SemanticException {
saveViewDefinition();
String originalText = createVwDesc.getViewOriginalText();
String expandedText = createVwDesc.getViewExpandedText();
List schema = createVwDesc.getSchema();
List partitionColumns = createVwDesc.getPartCols();
init(false);
setAST(newAST);
newAST = reAnalyzeViewAfterCbo(newAST);
createVwDesc.setViewOriginalText(originalText);
createVwDesc.setViewExpandedText(expandedText);
createVwDesc.setSchema(schema);
createVwDesc.setPartCols(partitionColumns);
}
/*
* Tries to optimize FROM clause of multi-insert. No attempt to optimize insert clauses of the query.
* Returns true if rewriting is successful, false otherwise.
*/
private void handleMultiDestQuery(ASTNode ast, PreCboCtx cboCtx) throws SemanticException {
// Not supported by CBO
if (!runCBO) {
return;
}
// Currently, we only optimized the query the content of the FROM clause
// for multi-insert queries. Thus, nodeOfInterest is the FROM clause
if (isJoinToken(cboCtx.nodeOfInterest)) {
// Join clause: rewriting is needed
ASTNode subq = rewriteASTForMultiInsert(ast, cboCtx.nodeOfInterest);
if (subq != null) {
// We could rewrite into a subquery
cboCtx.nodeOfInterest = (ASTNode) subq.getChild(0);
QB newQB = new QB(null, "", false);
Phase1Ctx ctx_1 = initPhase1Ctx();
doPhase1(cboCtx.nodeOfInterest, newQB, ctx_1, null);
setQB(newQB);
getMetaData(getQB());
} else {
runCBO = false;
}
} else if (cboCtx.nodeOfInterest.getToken().getType() == HiveParser.TOK_SUBQUERY) {
// Subquery: no rewriting needed
ASTNode subq = cboCtx.nodeOfInterest;
// First child is subquery, second child is alias
// We set the node of interest and QB to the subquery
// We do not need to generate the QB again, but rather we use it directly
cboCtx.nodeOfInterest = (ASTNode) subq.getChild(0);
String subQAlias = unescapeIdentifier(subq.getChild(1).getText());
final QB newQB = getQB().getSubqForAlias(subQAlias).getQB();
newQB.getParseInfo().setAlias("");
newQB.getParseInfo().setIsSubQ(false);
setQB(newQB);
} else {
// No need to run CBO (table ref or virtual table) or not supported
runCBO = false;
}
}
private ASTNode rewriteASTForMultiInsert(ASTNode query, ASTNode nodeOfInterest) {
// 1. gather references from original query
// This is a map from aliases to references.
// We keep all references as we will need to modify them after creating
// the subquery
final Multimap aliasNodes = ArrayListMultimap.create();
// To know if we need to bail out
final AtomicBoolean notSupported = new AtomicBoolean(false);
TreeVisitorAction action = new TreeVisitorAction() {
@Override
public Object pre(Object t) {
if (!notSupported.get()) {
if (ParseDriver.adaptor.getType(t) == HiveParser.TOK_ALLCOLREF) {
// TODO: this is a limitation of the AST rewriting approach that we will
// not be able to overcome till proper integration of full multi-insert
// queries with Calcite is implemented.
// The current rewriting gather references from insert clauses and then
// updates them with the new subquery references. However, if insert
// clauses use * or tab.*, we cannot resolve the columns that we are
// referring to. Thus, we just bail out and those queries will not be
// currently optimized by Calcite.
// An example of such query is:
// FROM T_A a LEFT JOIN T_B b ON a.id = b.id
// INSERT OVERWRITE TABLE join_result_1
// SELECT a.*, b.*
// INSERT OVERWRITE TABLE join_result_3
// SELECT a.*, b.*;
notSupported.set(true);
} else if (ParseDriver.adaptor.getType(t) == HiveParser.DOT) {
Object c = ParseDriver.adaptor.getChild(t, 0);
if (c != null && ParseDriver.adaptor.getType(c) == HiveParser.TOK_TABLE_OR_COL) {
aliasNodes.put(((ASTNode) t).toStringTree(), t);
}
} else if (ParseDriver.adaptor.getType(t) == HiveParser.TOK_TABLE_OR_COL) {
Object p = ParseDriver.adaptor.getParent(t);
if (p == null || ParseDriver.adaptor.getType(p) != HiveParser.DOT) {
aliasNodes.put(((ASTNode) t).toStringTree(), t);
}
}
}
return t;
}
@Override
public Object post(Object t) {
return t;
}
};
TreeVisitor tv = new TreeVisitor(ParseDriver.adaptor);
// We will iterate through the children: if it is an INSERT, we will traverse
// the subtree to gather the references
for (int i = 0; i < query.getChildCount(); i++) {
ASTNode child = (ASTNode) query.getChild(i);
if (ParseDriver.adaptor.getType(child) != HiveParser.TOK_INSERT) {
// If it is not an INSERT, we do not need to anything
continue;
}
tv.visit(child, action);
}
if (notSupported.get()) {
// Bail out
return null;
}
// 2. rewrite into query
// TOK_QUERY
// TOK_FROM
// join
// TOK_INSERT
// TOK_DESTINATION
// TOK_DIR
// TOK_TMP_FILE
// TOK_SELECT
// refs
ASTNode from = new ASTNode(new CommonToken(HiveParser.TOK_FROM, "TOK_FROM"));
from.addChild((ASTNode) ParseDriver.adaptor.dupTree(nodeOfInterest));
ASTNode destination = new ASTNode(new CommonToken(HiveParser.TOK_DESTINATION, "TOK_DESTINATION"));
ASTNode dir = new ASTNode(new CommonToken(HiveParser.TOK_DIR, "TOK_DIR"));
ASTNode tmpFile = new ASTNode(new CommonToken(HiveParser.TOK_TMP_FILE, "TOK_TMP_FILE"));
dir.addChild(tmpFile);
destination.addChild(dir);
ASTNode select = new ASTNode(new CommonToken(HiveParser.TOK_SELECT, "TOK_SELECT"));
int num = 0;
for (Collection selectIdentifier : aliasNodes.asMap().values()) {
Iterator it = selectIdentifier.iterator();
ASTNode node = (ASTNode) it.next();
// Add select expression
ASTNode selectExpr = new ASTNode(new CommonToken(HiveParser.TOK_SELEXPR, "TOK_SELEXPR"));
selectExpr.addChild((ASTNode) ParseDriver.adaptor.dupTree(node)); // Identifier
String colAlias = "col" + num;
selectExpr.addChild(new ASTNode(new CommonToken(HiveParser.Identifier, colAlias))); // Alias
select.addChild(selectExpr);
// Rewrite all INSERT references (all the node values for this key)
ASTNode colExpr = new ASTNode(new CommonToken(HiveParser.TOK_TABLE_OR_COL, "TOK_TABLE_OR_COL"));
colExpr.addChild(new ASTNode(new CommonToken(HiveParser.Identifier, colAlias)));
replaceASTChild(node, colExpr);
while (it.hasNext()) {
// Loop to rewrite rest of INSERT references
node = (ASTNode) it.next();
colExpr = new ASTNode(new CommonToken(HiveParser.TOK_TABLE_OR_COL, "TOK_TABLE_OR_COL"));
colExpr.addChild(new ASTNode(new CommonToken(HiveParser.Identifier, colAlias)));
replaceASTChild(node, colExpr);
}
num++;
}
ASTNode insert = new ASTNode(new CommonToken(HiveParser.TOK_INSERT, "TOK_INSERT"));
insert.addChild(destination);
insert.addChild(select);
ASTNode newQuery = new ASTNode(new CommonToken(HiveParser.TOK_QUERY, "TOK_QUERY"));
newQuery.addChild(from);
newQuery.addChild(insert);
// 3. create subquery
ASTNode subq = new ASTNode(new CommonToken(HiveParser.TOK_SUBQUERY, "TOK_SUBQUERY"));
subq.addChild(newQuery);
subq.addChild(new ASTNode(new CommonToken(HiveParser.Identifier, "subq")));
replaceASTChild(nodeOfInterest, subq);
// 4. return subquery
return subq;
}
/**
* Can CBO handle the given AST?
*
* @param ast
* Top level AST
* @param qb
* top level QB corresponding to the AST
* @param cboCtx
* @return boolean
*
* Assumption: obtainCBOProfiles(QueryProperties queryProperties) {
EnumSet profilesCBO = EnumSet.noneOf(ExtendedCBOProfile.class);
// If the query contains more than one join
if (queryProperties.getJoinCount() > 1) {
profilesCBO.add(ExtendedCBOProfile.JOIN_REORDERING);
}
// If the query contains windowing processing
if (queryProperties.hasWindowing()) {
profilesCBO.add(ExtendedCBOProfile.WINDOWING_POSTPROCESSING);
}
return profilesCBO;
}
@Override
boolean isCBOExecuted() {
return runCBO;
}
@Override
boolean isCBOSupportedLateralView(ASTNode lateralView) {
// Lateral view AST has the following shape:
// ^(TOK_LATERAL_VIEW
// ^(TOK_SELECT ^(TOK_SELEXPR ^(TOK_FUNCTION Identifier params) identifier* tableAlias)))
if (lateralView.getToken().getType() == HiveParser.TOK_LATERAL_VIEW_OUTER) {
// LATERAL VIEW OUTER not supported in CBO
return false;
}
// Only INLINE followed by ARRAY supported in CBO
ASTNode lvFunc = (ASTNode) lateralView.getChild(0).getChild(0).getChild(0);
String lvFuncName = lvFunc.getChild(0).getText();
if (lvFuncName.compareToIgnoreCase(
GenericUDTFInline.class.getAnnotation(Description.class).name()) != 0) {
return false;
}
if (lvFunc.getChildCount() != 2) {
return false;
}
ASTNode innerFunc = (ASTNode) lvFunc.getChild(1);
if (innerFunc.getToken().getType() != HiveParser.TOK_FUNCTION ||
innerFunc.getChild(0).getText().compareToIgnoreCase(
GenericUDFArray.class.getAnnotation(Description.class).name()) != 0) {
return false;
}
return true;
}
@Override
boolean continueJoinMerge() {
return !(runCBO && disableSemJoinReordering);
}
@Override
Table materializeCTE(String cteName, CTEClause cte) throws HiveException {
ASTNode createTable = new ASTNode(new ClassicToken(HiveParser.TOK_CREATETABLE));
ASTNode tableName = new ASTNode(new ClassicToken(HiveParser.TOK_TABNAME));
tableName.addChild(new ASTNode(new ClassicToken(HiveParser.Identifier, cteName)));
ASTNode temporary = new ASTNode(new ClassicToken(HiveParser.KW_TEMPORARY, MATERIALIZATION_MARKER));
createTable.addChild(tableName);
createTable.addChild(temporary);
createTable.addChild(cte.cteNode);
CalcitePlanner analyzer = new CalcitePlanner(queryState);
analyzer.initCtx(ctx);
analyzer.init(false);
// should share cte contexts
analyzer.aliasToCTEs.putAll(aliasToCTEs);
HiveOperation operation = queryState.getHiveOperation();
try {
analyzer.analyzeInternal(createTable);
} finally {
queryState.setCommandType(operation);
}
Table table = analyzer.tableDesc.toTable(conf);
Path location = table.getDataLocation();
try {
location.getFileSystem(conf).mkdirs(location);
} catch (IOException e) {
throw new HiveException(e);
}
table.setMaterializedTable(true);
LOG.info(cteName + " will be materialized into " + location);
cte.table = table;
cte.source = analyzer;
ctx.addMaterializedTable(cteName, table);
// For CalcitePlanner, store qualified name too
ctx.addMaterializedTable(table.getFullyQualifiedName(), table);
return table;
}
private void fixUpASTAggregateIncrementalRebuild(ASTNode newAST) throws SemanticException {
// Replace INSERT OVERWRITE by MERGE equivalent rewriting.
// Here we need to do this complex AST rewriting that generates the same plan
// that a MERGE clause would generate because CBO does not support MERGE yet.
// TODO: Support MERGE as first class member in CBO to simplify this logic.
// 1) Replace INSERT OVERWRITE by INSERT
ASTNode updateNode = new ASTSearcher().simpleBreadthFirstSearch(
newAST, HiveParser.TOK_QUERY, HiveParser.TOK_INSERT);
ASTNode destinationNode = (ASTNode) updateNode.getChild(0);
ASTNode newInsertInto = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_INSERT_INTO, "TOK_INSERT_INTO");
newInsertInto.addChildren(destinationNode.getChildren());
ASTNode destinationParentNode = (ASTNode) destinationNode.getParent();
int childIndex = destinationNode.childIndex;
destinationParentNode.deleteChild(childIndex);
destinationParentNode.insertChild(childIndex, newInsertInto);
// 1.1) Extract name as we will need it afterwards:
// TOK_DESTINATION TOK_TAB TOK_TABNAME
ASTNode materializationNode = new ASTSearcher().simpleBreadthFirstSearch(
newInsertInto, HiveParser.TOK_INSERT_INTO, HiveParser.TOK_TAB, HiveParser.TOK_TABNAME);
// 2) Copy INSERT branch and duplicate it, the first branch will be the UPDATE
// for the MERGE statement while the new branch will be the INSERT for the
// MERGE statement
ASTNode updateParent = (ASTNode) updateNode.getParent();
ASTNode insertNode = (ASTNode) ParseDriver.adaptor.dupTree(updateNode);
insertNode.setParent(updateParent);
updateParent.addChild(insertNode);
// 3) Create ROW_ID column in select clause from left input for the RIGHT OUTER JOIN.
// This is needed for the UPDATE clause. Hence, we find the following node:
// TOK_QUERY
// TOK_FROM
// TOK_RIGHTOUTERJOIN
// TOK_SUBQUERY
// TOK_QUERY
// ...
// TOK_INSERT
// ...
// TOK_SELECT
// And then we create the following child node:
// TOK_SELEXPR
// .
// TOK_TABLE_OR_COL
// cmv_mat_view
// ROW__ID
ASTNode subqueryNodeInputROJ = new ASTSearcher().simpleBreadthFirstSearch(
newAST, HiveParser.TOK_QUERY, HiveParser.TOK_FROM, HiveParser.TOK_RIGHTOUTERJOIN,
HiveParser.TOK_SUBQUERY);
ASTNode selectNodeInputROJ = new ASTSearcher().simpleBreadthFirstSearch(
subqueryNodeInputROJ, HiveParser.TOK_SUBQUERY, HiveParser.TOK_QUERY,
HiveParser.TOK_INSERT, HiveParser.TOK_SELECT);
ASTNode selectExprNodeInputROJ = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_SELEXPR, "TOK_SELEXPR");
ASTNode dotNodeInputROJ = (ASTNode) ParseDriver.adaptor.create(
HiveParser.DOT, ".");
ASTNode columnTokNodeInputROJ = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_TABLE_OR_COL, "TOK_TABLE_OR_COL");
ASTNode tableNameNodeInputROJ = (ASTNode) ParseDriver.adaptor.create(
HiveParser.Identifier, Warehouse.getQualifiedName(
materializationNode.getChild(0).getText(),
materializationNode.getChild(1).getText()));
ASTNode rowIdNodeInputROJ = (ASTNode) ParseDriver.adaptor.create(
HiveParser.Identifier, VirtualColumn.ROWID.getName());
ParseDriver.adaptor.addChild(selectNodeInputROJ, selectExprNodeInputROJ);
ParseDriver.adaptor.addChild(selectExprNodeInputROJ, dotNodeInputROJ);
ParseDriver.adaptor.addChild(dotNodeInputROJ, columnTokNodeInputROJ);
ParseDriver.adaptor.addChild(dotNodeInputROJ, rowIdNodeInputROJ);
ParseDriver.adaptor.addChild(columnTokNodeInputROJ, tableNameNodeInputROJ);
// 4) Transform first INSERT branch into an UPDATE
// 4.1) Adding ROW__ID field
ASTNode selectNodeInUpdate = (ASTNode) updateNode.getChild(1);
if (selectNodeInUpdate.getType() != HiveParser.TOK_SELECT) {
throw new SemanticException("TOK_SELECT expected in incremental rewriting");
}
ASTNode selectExprNodeInUpdate = (ASTNode) ParseDriver.adaptor.dupNode(selectExprNodeInputROJ);
ASTNode dotNodeInUpdate = (ASTNode) ParseDriver.adaptor.dupNode(dotNodeInputROJ);
ASTNode columnTokNodeInUpdate = (ASTNode) ParseDriver.adaptor.dupNode(columnTokNodeInputROJ);
ASTNode tableNameNodeInUpdate = (ASTNode) ParseDriver.adaptor.dupNode(subqueryNodeInputROJ.getChild(1));
ASTNode rowIdNodeInUpdate = (ASTNode) ParseDriver.adaptor.dupNode(rowIdNodeInputROJ);
ParseDriver.adaptor.addChild(selectExprNodeInUpdate, dotNodeInUpdate);
ParseDriver.adaptor.addChild(dotNodeInUpdate, columnTokNodeInUpdate);
ParseDriver.adaptor.addChild(dotNodeInUpdate, rowIdNodeInUpdate);
ParseDriver.adaptor.addChild(columnTokNodeInUpdate, tableNameNodeInUpdate);
selectNodeInUpdate.insertChild(0, ParseDriver.adaptor.dupTree(selectExprNodeInUpdate));
// 4.2) Modifying filter condition. The incremental rewriting rule generated an OR
// clause where first disjunct contains the condition for the UPDATE branch.
// TOK_WHERE
// or
// and <- DISJUNCT FOR
// =
// .
// TOK_TABLE_OR_COL
// $hdt$_0
// a
// .
// TOK_TABLE_OR_COL
// $hdt$_1
// a
// =
// .
// TOK_TABLE_OR_COL
// $hdt$_0
// c
// .
// TOK_TABLE_OR_COL
// $hdt$_1
// c
// and <- DISJUNCT FOR
// TOK_FUNCTION
// isnull
// .
// TOK_TABLE_OR_COL
// $hdt$_0
// a
// TOK_FUNCTION
// isnull
// .
// TOK_TABLE_OR_COL
// $hdt$_0
// c
ASTNode whereClauseInUpdate = null;
for (int i = 0; i < updateNode.getChildren().size(); i++) {
if (updateNode.getChild(i).getType() == HiveParser.TOK_WHERE) {
whereClauseInUpdate = (ASTNode) updateNode.getChild(i);
break;
}
}
if (whereClauseInUpdate == null) {
throw new SemanticException("TOK_WHERE expected in incremental rewriting");
}
if (whereClauseInUpdate.getChild(0).getType() != HiveParser.KW_OR) {
throw new SemanticException("OR clause expected below TOK_WHERE in incremental rewriting");
}
// We bypass the OR clause and select the first disjunct
ASTNode newCondInUpdate = (ASTNode) whereClauseInUpdate.getChild(0).getChild(0);
ParseDriver.adaptor.setChild(whereClauseInUpdate, 0, newCondInUpdate);
// 4.3) Finally, we add SORT clause, this is needed for the UPDATE.
// TOK_SORTBY
// TOK_TABSORTCOLNAMEASC
// TOK_NULLS_FIRST
// .
// TOK_TABLE_OR_COL
// cmv_basetable_2
// ROW__ID
ASTNode sortExprNode = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_SORTBY, "TOK_SORTBY");
ASTNode orderExprNode = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_TABSORTCOLNAMEASC, "TOK_TABSORTCOLNAMEASC");
ASTNode nullsOrderExprNode = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_NULLS_FIRST, "TOK_NULLS_FIRST");
ASTNode dotNodeInSort = (ASTNode) ParseDriver.adaptor.dupTree(dotNodeInUpdate);
ParseDriver.adaptor.addChild(updateNode, sortExprNode);
ParseDriver.adaptor.addChild(sortExprNode, orderExprNode);
ParseDriver.adaptor.addChild(orderExprNode, nullsOrderExprNode);
ParseDriver.adaptor.addChild(nullsOrderExprNode, dotNodeInSort);
// 5) Modify INSERT branch condition. In particular, we need to modify the
// WHERE clause and pick up the second disjunct from the OR operation.
ASTNode whereClauseInInsert = null;
for (int i = 0; i < insertNode.getChildren().size(); i++) {
if (insertNode.getChild(i).getType() == HiveParser.TOK_WHERE) {
whereClauseInInsert = (ASTNode) insertNode.getChild(i);
break;
}
}
if (whereClauseInInsert == null) {
throw new SemanticException("TOK_WHERE expected in incremental rewriting");
}
if (whereClauseInInsert.getChild(0).getType() != HiveParser.KW_OR) {
throw new SemanticException("OR clause expected below TOK_WHERE in incremental rewriting");
}
// We bypass the OR clause and select the second disjunct
ASTNode newCondInInsert = (ASTNode) whereClauseInInsert.getChild(0).getChild(1);
ParseDriver.adaptor.setChild(whereClauseInInsert, 0, newCondInInsert);
// 6) Now we set some tree properties related to multi-insert
// operation with INSERT/UPDATE
ctx.setOperation(Context.Operation.MERGE);
ctx.addDestNamePrefix(1, Context.DestClausePrefix.UPDATE);
ctx.addDestNamePrefix(2, Context.DestClausePrefix.INSERT);
}
private void fixUpASTNoAggregateIncrementalRebuild(ASTNode newAST) throws SemanticException {
// Replace INSERT OVERWRITE by INSERT INTO
// AST tree will have this shape:
// TOK_QUERY
// TOK_FROM
// ...
// TOK_INSERT
// TOK_DESTINATION <- THIS TOKEN IS REPLACED BY 'TOK_INSERT_INTO'
// TOK_TAB
// TOK_TABNAME
// default.cmv_mat_view
// TOK_SELECT
// ...
ASTNode dest = new ASTSearcher().simpleBreadthFirstSearch(newAST, HiveParser.TOK_QUERY,
HiveParser.TOK_INSERT, HiveParser.TOK_DESTINATION);
ASTNode newChild = (ASTNode) ParseDriver.adaptor.create(
HiveParser.TOK_INSERT_INTO, "TOK_INSERT_INTO");
newChild.addChildren(dest.getChildren());
ASTNode destParent = (ASTNode) dest.getParent();
int childIndex = dest.childIndex;
destParent.deleteChild(childIndex);
destParent.insertChild(childIndex, newChild);
}
@Override
String fixCtasColumnName(String colName) {
if (runCBO) {
int lastDot = colName.lastIndexOf('.');
if (lastDot < 0)
return colName; // alias is not fully qualified
String nqColumnName = colName.substring(lastDot + 1);
STATIC_LOG.debug("Replacing " + colName + " (produced by CBO) by " + nqColumnName);
return nqColumnName;
}
return super.fixCtasColumnName(colName);
}
/**
* The context that doPhase1 uses to populate information pertaining to CBO
* (currently, this is used for CTAS and insert-as-select).
*/
static class PreCboCtx extends PlannerContext {
enum Type {
NONE, INSERT, MULTI_INSERT, CTAS, VIEW, UNEXPECTED
}
private ASTNode nodeOfInterest;
private Type type = Type.NONE;
private void set(Type type, ASTNode ast) {
if (this.type != Type.NONE) {
STATIC_LOG.warn("Setting " + type + " when already " + this.type + "; node " + ast.dump()
+ " vs old node " + nodeOfInterest.dump());
this.type = Type.UNEXPECTED;
return;
}
this.type = type;
this.nodeOfInterest = ast;
}
@Override
void setCTASToken(ASTNode child) {
set(PreCboCtx.Type.CTAS, child);
}
@Override
void setViewToken(ASTNode child) {
set(PreCboCtx.Type.VIEW, child);
}
@Override
void setInsertToken(ASTNode ast, boolean isTmpFileDest) {
if (!isTmpFileDest) {
set(PreCboCtx.Type.INSERT, ast);
}
}
@Override
void setMultiInsertToken(ASTNode child) {
set(PreCboCtx.Type.MULTI_INSERT, child);
}
@Override
void resetToken() {
this.type = Type.NONE;
this.nodeOfInterest = null;
}
}
ASTNode fixUpAfterCbo(ASTNode originalAst, ASTNode newAst, PreCboCtx cboCtx)
throws SemanticException {
switch (cboCtx.type) {
case NONE:
// nothing to do
return newAst;
case CTAS:
case VIEW: {
// Patch the optimized query back into original CTAS AST, replacing the
// original query.
replaceASTChild(cboCtx.nodeOfInterest, newAst);
return originalAst;
}
case INSERT: {
// We need to patch the dest back to original into new query.
// This makes assumptions about the structure of the AST.
ASTNode newDest = new ASTSearcher().simpleBreadthFirstSearch(newAst, HiveParser.TOK_QUERY,
HiveParser.TOK_INSERT, HiveParser.TOK_DESTINATION);
if (newDest == null) {
LOG.error("Cannot find destination after CBO; new ast is " + newAst.dump());
throw new SemanticException("Cannot find destination after CBO");
}
replaceASTChild(newDest, cboCtx.nodeOfInterest);
return newAst;
}
case MULTI_INSERT: {
// Patch the optimized query back into original FROM clause.
replaceASTChild(cboCtx.nodeOfInterest, newAst);
return originalAst;
}
default:
throw new AssertionError("Unexpected type " + cboCtx.type);
}
}
ASTNode reAnalyzeCTASAfterCbo(ASTNode newAst) throws SemanticException {
// analyzeCreateTable uses this.ast, but doPhase1 doesn't, so only reset it
// here.
newAst = analyzeCreateTable(newAst, getQB(), null);
if (newAst == null) {
LOG.error("analyzeCreateTable failed to initialize CTAS after CBO;" + " new ast is "
+ getAST().dump());
throw new SemanticException("analyzeCreateTable failed to initialize CTAS after CBO");
}
return newAst;
}
ASTNode reAnalyzeViewAfterCbo(ASTNode newAst) throws SemanticException {
// analyzeCreateView uses this.ast, but doPhase1 doesn't, so only reset it
// here.
newAst = analyzeCreateView(newAst, getQB(), null);
if (newAst == null) {
LOG.error("analyzeCreateTable failed to initialize materialized view after CBO;" + " new ast is "
+ getAST().dump());
throw new SemanticException("analyzeCreateTable failed to initialize materialized view after CBO");
}
return newAst;
}
public static class ASTSearcher {
private final LinkedList searchQueue = new LinkedList();
/**
* Performs breadth-first search of the AST for a nested set of tokens. Tokens
* don't have to be each others' direct children, they can be separated by
* layers of other tokens. For each token in the list, the first one found is
* matched and there's no backtracking; thus, if AST has multiple instances of
* some token, of which only one matches, it is not guaranteed to be found. We
* use this for simple things. Not thread-safe - reuses searchQueue.
*/
public ASTNode simpleBreadthFirstSearch(ASTNode ast, int... tokens) {
searchQueue.clear();
searchQueue.add(ast);
for (int i = 0; i < tokens.length; ++i) {
boolean found = false;
int token = tokens[i];
while (!searchQueue.isEmpty() && !found) {
ASTNode next = searchQueue.poll();
found = next.getType() == token;
if (found) {
if (i == tokens.length - 1)
return next;
searchQueue.clear();
}
for (int j = 0; j < next.getChildCount(); ++j) {
searchQueue.add((ASTNode) next.getChild(j));
}
}
if (!found)
return null;
}
return null;
}
public ASTNode depthFirstSearch(ASTNode ast, int token) {
searchQueue.clear();
searchQueue.add(ast);
while (!searchQueue.isEmpty()) {
ASTNode next = searchQueue.poll();
if (next.getType() == token) return next;
for (int j = 0; j < next.getChildCount(); ++j) {
searchQueue.add((ASTNode) next.getChild(j));
}
}
return null;
}
public ASTNode simpleBreadthFirstSearchAny(ASTNode ast, int... tokens) {
searchQueue.clear();
searchQueue.add(ast);
while (!searchQueue.isEmpty()) {
ASTNode next = searchQueue.poll();
for (int i = 0; i < tokens.length; ++i) {
if (next.getType() == tokens[i]) return next;
}
for (int i = 0; i < next.getChildCount(); ++i) {
searchQueue.add((ASTNode) next.getChild(i));
}
}
return null;
}
public void reset() {
searchQueue.clear();
}
}
private static void replaceASTChild(ASTNode child, ASTNode newChild) {
ASTNode parent = (ASTNode) child.parent;
int childIndex = child.childIndex;
parent.deleteChild(childIndex);
parent.insertChild(childIndex, newChild);
}
/**
* Get optimized logical plan for the given QB tree in the semAnalyzer.
*
* @return
* @throws SemanticException
*/
RelNode logicalPlan() throws SemanticException {
RelNode optimizedOptiqPlan = null;
CalcitePlannerAction calcitePlannerAction = null;
if (this.columnAccessInfo == null) {
this.columnAccessInfo = new ColumnAccessInfo();
}
calcitePlannerAction = new CalcitePlannerAction(
prunedPartitions,
ctx.getOpContext().getColStatsCache(),
this.columnAccessInfo);
try {
optimizedOptiqPlan = Frameworks.withPlanner(calcitePlannerAction, Frameworks
.newConfigBuilder().typeSystem(new HiveTypeSystemImpl()).build());
} catch (Exception e) {
rethrowCalciteException(e);
throw new AssertionError("rethrowCalciteException didn't throw for " + e.getMessage());
}
return optimizedOptiqPlan;
}
/**
* Get Optimized AST for the given QB tree in the semAnalyzer.
*
* @return Optimized operator tree translated in to Hive AST
* @throws SemanticException
*/
ASTNode getOptimizedAST() throws SemanticException {
RelNode optimizedOptiqPlan = logicalPlan();
ASTNode optiqOptimizedAST = ASTConverter.convert(optimizedOptiqPlan, resultSchema,
HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_COLUMN_ALIGNMENT));
return optiqOptimizedAST;
}
/**
* Get Optimized Hive Operator DAG for the given QB tree in the semAnalyzer.
*
* @return Optimized Hive operator tree
* @throws SemanticException
*/
Operator getOptimizedHiveOPDag() throws SemanticException {
RelNode optimizedOptiqPlan = null;
CalcitePlannerAction calcitePlannerAction = null;
if (this.columnAccessInfo == null) {
this.columnAccessInfo = new ColumnAccessInfo();
}
calcitePlannerAction = new CalcitePlannerAction(
prunedPartitions,
ctx.getOpContext().getColStatsCache(),
this.columnAccessInfo);
try {
optimizedOptiqPlan = Frameworks.withPlanner(calcitePlannerAction, Frameworks
.newConfigBuilder().typeSystem(new HiveTypeSystemImpl()).build());
} catch (Exception e) {
rethrowCalciteException(e);
throw new AssertionError("rethrowCalciteException didn't throw for " + e.getMessage());
}
RelNode modifiedOptimizedOptiqPlan = PlanModifierForReturnPath.convertOpTree(
optimizedOptiqPlan, resultSchema, this.getQB().getTableDesc() != null);
LOG.debug("Translating the following plan:\n" + RelOptUtil.toString(modifiedOptimizedOptiqPlan));
Operator hiveRoot = new HiveOpConverter(this, conf, unparseTranslator, topOps)
.convert(modifiedOptimizedOptiqPlan);
RowResolver hiveRootRR = genRowResolver(hiveRoot, getQB());
opParseCtx.put(hiveRoot, new OpParseContext(hiveRootRR));
String dest = getQB().getParseInfo().getClauseNames().iterator().next();
if (getQB().getParseInfo().getDestSchemaForClause(dest) != null
&& this.getQB().getTableDesc() == null) {
Operator selOp = handleInsertStatement(dest, hiveRoot, hiveRootRR, getQB());
return genFileSinkPlan(dest, getQB(), selOp);
} else {
return genFileSinkPlan(dest, getQB(), hiveRoot);
}
}
// This function serves as the wrapper of handleInsertStatementSpec in
// SemanticAnalyzer
Operator handleInsertStatement(String dest, Operator input, RowResolver inputRR, QB qb)
throws SemanticException {
ArrayList colList = new ArrayList();
ArrayList columns = inputRR.getColumnInfos();
for (int i = 0; i < columns.size(); i++) {
ColumnInfo col = columns.get(i);
colList.add(new ExprNodeColumnDesc(col));
}
ASTNode selExprList = qb.getParseInfo().getSelForClause(dest);
RowResolver out_rwsch = handleInsertStatementSpec(colList, dest, inputRR, inputRR, qb,
selExprList);
ArrayList columnNames = new ArrayList();
Map colExprMap = new HashMap();
for (int i = 0; i < colList.size(); i++) {
String outputCol = getColumnInternalName(i);
colExprMap.put(outputCol, colList.get(i));
columnNames.add(outputCol);
}
Operator output = putOpInsertMap(OperatorFactory.getAndMakeChild(new SelectDesc(colList,
columnNames), new RowSchema(out_rwsch.getColumnInfos()), input), out_rwsch);
output.setColumnExprMap(colExprMap);
return output;
}
/***
* Unwraps Calcite Invocation exceptions coming meta data provider chain and
* obtains the real cause.
*
* @param e
*/
private void rethrowCalciteException(Exception e) throws SemanticException {
Throwable first = (semanticException != null) ? semanticException : e, current = first, cause = current
.getCause();
while (cause != null) {
Throwable causeOfCause = cause.getCause();
if (current == first && causeOfCause == null && isUselessCause(first)) {
// "cause" is a root cause, and "e"/"first" is a useless
// exception it's wrapped in.
first = cause;
break;
} else if (causeOfCause != null && isUselessCause(cause)
&& ExceptionHelper.resetCause(current, causeOfCause)) {
// "cause" was a useless intermediate cause and was replace it
// with its own cause.
cause = causeOfCause;
continue; // do loop once again with the new cause of "current"
}
current = cause;
cause = current.getCause();
}
if (first instanceof RuntimeException) {
throw (RuntimeException) first;
} else if (first instanceof SemanticException) {
throw (SemanticException) first;
}
throw new RuntimeException(first);
}
private static class ExceptionHelper {
private static final Field CAUSE_FIELD = getField(Throwable.class, "cause"),
TARGET_FIELD = getField(InvocationTargetException.class, "target"),
MESSAGE_FIELD = getField(Throwable.class, "detailMessage");
private static Field getField(Class clazz, String name) {
try {
Field f = clazz.getDeclaredField(name);
f.setAccessible(true);
return f;
} catch (Throwable t) {
return null;
}
}
public static boolean resetCause(Throwable target, Throwable newCause) {
try {
if (MESSAGE_FIELD == null)
return false;
Field field = (target instanceof InvocationTargetException) ? TARGET_FIELD : CAUSE_FIELD;
if (field == null)
return false;
Throwable oldCause = target.getCause();
String oldMsg = target.getMessage();
field.set(target, newCause);
if (oldMsg != null && oldMsg.equals(oldCause.toString())) {
MESSAGE_FIELD.set(target, newCause == null ? null : newCause.toString());
}
} catch (Throwable se) {
return false;
}
return true;
}
}
private boolean isUselessCause(Throwable t) {
return t instanceof RuntimeException || t instanceof InvocationTargetException
|| t instanceof UndeclaredThrowableException;
}
private RowResolver genRowResolver(Operator op, QB qb) {
RowResolver rr = new RowResolver();
String subqAlias = (qb.getAliases().size() == 1 && qb.getSubqAliases().size() == 1) ? qb
.getAliases().get(0) : null;
for (ColumnInfo ci : op.getSchema().getSignature()) {
try {
rr.putWithCheck((subqAlias != null) ? subqAlias : ci.getTabAlias(),
ci.getAlias() != null ? ci.getAlias() : ci.getInternalName(), ci.getInternalName(),
new ColumnInfo(ci));
} catch (SemanticException e) {
throw new RuntimeException(e);
}
}
return rr;
}
private enum ExtendedCBOProfile {
JOIN_REORDERING,
WINDOWING_POSTPROCESSING;
}
/**
* Code responsible for Calcite plan generation and optimization.
*/
private class CalcitePlannerAction implements Frameworks.PlannerAction {
private RelOptCluster cluster;
private RelOptSchema relOptSchema;
private final Map partitionCache;
private final Map colStatsCache;
private final ColumnAccessInfo columnAccessInfo;
private Map viewProjectToTableSchema;
//correlated vars across subqueries within same query needs to have different ID
// this will be used in RexNodeConverter to create cor var
private int subqueryId;
// this is to keep track if a subquery is correlated and contains aggregate
// since this is special cased when it is rewritten in SubqueryRemoveRule
Set corrScalarRexSQWithAgg = new HashSet();
Set scalarAggNoGbyNoWin = new HashSet();
// TODO: Do we need to keep track of RR, ColNameToPosMap for every op or
// just last one.
LinkedHashMap relToHiveRR = new LinkedHashMap();
LinkedHashMap> relToHiveColNameCalcitePosMap = new LinkedHashMap>();
CalcitePlannerAction(
Map partitionCache,
Map colStatsCache,
ColumnAccessInfo columnAccessInfo) {
this.partitionCache = partitionCache;
this.colStatsCache = colStatsCache;
this.columnAccessInfo = columnAccessInfo;
}
@Override
public RelNode apply(RelOptCluster cluster, RelOptSchema relOptSchema, SchemaPlus rootSchema) {
RelNode calciteGenPlan = null;
RelNode calcitePreCboPlan = null;
RelNode calciteOptimizedPlan = null;
subqueryId = -1;
/*
* recreate cluster, so that it picks up the additional traitDef
*/
RelOptPlanner planner = createPlanner(conf, corrScalarRexSQWithAgg, scalarAggNoGbyNoWin);
final RexBuilder rexBuilder = cluster.getRexBuilder();
final RelOptCluster optCluster = RelOptCluster.create(planner, rexBuilder);
this.cluster = optCluster;
this.relOptSchema = relOptSchema;
PerfLogger perfLogger = SessionState.getPerfLogger();
// 1. Gen Calcite Plan
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
try {
calciteGenPlan = genLogicalPlan(getQB(), true, null, null);
// if it is to create view, we do not use table alias
resultSchema = SemanticAnalyzer.convertRowSchemaToResultSetSchema(
relToHiveRR.get(calciteGenPlan),
getQB().isView() ? false : HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVE_RESULTSET_USE_UNIQUE_COLUMN_NAMES));
} catch (SemanticException e) {
semanticException = e;
throw new RuntimeException(e);
}
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Plan generation");
// Validate query materialization (materialized views, query results caching.
// This check needs to occur before constant folding, which may remove some
// function calls from the query plan.
HiveRelOpMaterializationValidator matValidator = new HiveRelOpMaterializationValidator();
matValidator.validateQueryMaterialization(calciteGenPlan);
if (!matValidator.isValidMaterialization()) {
String reason = matValidator.getInvalidMaterializationReason();
setInvalidQueryMaterializationReason(reason);
}
// Create executor
RexExecutor executorProvider = new HiveRexExecutorImpl(optCluster);
calciteGenPlan.getCluster().getPlanner().setExecutor(executorProvider);
// We need to get the ColumnAccessInfo and viewToTableSchema for views.
HiveRelFieldTrimmer fieldTrimmer = new HiveRelFieldTrimmer(null,
HiveRelFactories.HIVE_BUILDER.create(optCluster, null), this.columnAccessInfo,
this.viewProjectToTableSchema);
fieldTrimmer.trim(calciteGenPlan);
// Create and set MD provider
HiveDefaultRelMetadataProvider mdProvider = new HiveDefaultRelMetadataProvider(conf);
RelMetadataQuery.THREAD_PROVIDERS.set(
JaninoRelMetadataProvider.of(mdProvider.getMetadataProvider()));
//Remove subquery
LOG.debug("Plan before removing subquery:\n" + RelOptUtil.toString(calciteGenPlan));
calciteGenPlan = hepPlan(calciteGenPlan, false, mdProvider.getMetadataProvider(), null,
new HiveSubQueryRemoveRule(conf));
LOG.debug("Plan just after removing subquery:\n" + RelOptUtil.toString(calciteGenPlan));
calciteGenPlan = HiveRelDecorrelator.decorrelateQuery(calciteGenPlan);
LOG.debug("Plan after decorrelation:\n" + RelOptUtil.toString(calciteGenPlan));
// 2. Apply pre-join order optimizations
calcitePreCboPlan = applyPreJoinOrderingTransforms(calciteGenPlan,
mdProvider.getMetadataProvider(), executorProvider);
// 3. Materialized view based rewriting
// We disable it for CTAS and MV creation queries (trying to avoid any problem
// due to data freshness)
if (conf.getBoolVar(ConfVars.HIVE_MATERIALIZED_VIEW_ENABLE_AUTO_REWRITING) &&
!getQB().isMaterializedView() && !ctx.isLoadingMaterializedView() && !getQB().isCTAS()) {
calcitePreCboPlan = applyMaterializedViewRewriting(planner,
calcitePreCboPlan, mdProvider.getMetadataProvider(), executorProvider);
}
// 4. Apply join order optimizations: reordering MST algorithm
// If join optimizations failed because of missing stats, we continue with
// the rest of optimizations
if (profilesCBO.contains(ExtendedCBOProfile.JOIN_REORDERING)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
try {
List list = Lists.newArrayList();
list.add(mdProvider.getMetadataProvider());
RelTraitSet desiredTraits = optCluster
.traitSetOf(HiveRelNode.CONVENTION, RelCollations.EMPTY);
HepProgramBuilder hepPgmBldr = new HepProgramBuilder().addMatchOrder(HepMatchOrder.BOTTOM_UP);
hepPgmBldr.addRuleInstance(new JoinToMultiJoinRule(HiveJoin.class));
hepPgmBldr.addRuleInstance(new LoptOptimizeJoinRule(HiveRelFactories.HIVE_BUILDER));
HepProgram hepPgm = hepPgmBldr.build();
HepPlanner hepPlanner = new HepPlanner(hepPgm);
hepPlanner.registerMetadataProviders(list);
RelMetadataProvider chainedProvider = ChainedRelMetadataProvider.of(list);
optCluster.setMetadataProvider(new CachingRelMetadataProvider(chainedProvider, hepPlanner));
RelNode rootRel = calcitePreCboPlan;
hepPlanner.setRoot(rootRel);
if (!calcitePreCboPlan.getTraitSet().equals(desiredTraits)) {
rootRel = hepPlanner.changeTraits(calcitePreCboPlan, desiredTraits);
}
hepPlanner.setRoot(rootRel);
calciteOptimizedPlan = hepPlanner.findBestExp();
} catch (Exception e) {
boolean isMissingStats = noColsMissingStats.get() > 0;
if (isMissingStats) {
LOG.warn("Missing column stats (see previous messages), skipping join reordering in CBO");
noColsMissingStats.set(0);
calciteOptimizedPlan = calcitePreCboPlan;
disableSemJoinReordering = false;
} else {
throw e;
}
}
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Join Reordering");
} else {
calciteOptimizedPlan = calcitePreCboPlan;
disableSemJoinReordering = false;
}
// 5. Run other optimizations that do not need stats
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, ProjectRemoveRule.INSTANCE, HiveUnionMergeRule.INSTANCE,
HiveAggregateProjectMergeRule.INSTANCE, HiveProjectMergeRule.INSTANCE_NO_FORCE, HiveJoinCommuteRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Optimizations without stats 1");
// 6. Run aggregate-join transpose (cost based)
// If it failed because of missing stats, we continue with
// the rest of optimizations
if (conf.getBoolVar(ConfVars.AGGR_JOIN_TRANSPOSE)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
try {
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, HiveAggregateJoinTransposeRule.INSTANCE);
} catch (Exception e) {
boolean isMissingStats = noColsMissingStats.get() > 0;
if (isMissingStats) {
LOG.warn("Missing column stats (see previous messages), skipping aggregate-join transpose in CBO");
noColsMissingStats.set(0);
} else {
throw e;
}
}
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Aggregate join transpose");
}
// 7.convert Join + GBy to semijoin
// run this rule at later stages, since many calcite rules cant deal with semijoin
if (conf.getBoolVar(ConfVars.SEMIJOIN_CONVERSION)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HiveSemiJoinRule.INSTANCE_PROJECT, HiveSemiJoinRule.INSTANCE_AGGREGATE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Semijoin conversion");
}
// 8. convert SemiJoin + GBy to SemiJoin
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HiveRemoveGBYSemiJoinRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Removal of gby from semijoin");
// 9. Get rid of sq_count_check if group by key is constant (HIVE-)
if (conf.getBoolVar(ConfVars.HIVE_REMOVE_SQ_COUNT_CHECK)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan =
hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HiveRemoveSqCountCheck.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Removing sq_count_check UDF ");
}
// 10. Run rule to fix windowing issue when it is done over
// aggregation columns (HIVE-10627)
if (profilesCBO.contains(ExtendedCBOProfile.WINDOWING_POSTPROCESSING)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, HiveWindowingFixRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Window fixing rule");
}
// 11. Apply Druid transformation rules
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP,
HiveDruidRules.FILTER,
HiveDruidRules.PROJECT_FILTER_TRANSPOSE,
HiveDruidRules.AGGREGATE_FILTER_TRANSPOSE,
HiveDruidRules.AGGREGATE_PROJECT,
HiveDruidRules.PROJECT,
HiveDruidRules.AGGREGATE,
HiveDruidRules.POST_AGGREGATION_PROJECT,
HiveDruidRules.FILTER_AGGREGATE_TRANSPOSE,
HiveDruidRules.FILTER_PROJECT_TRANSPOSE,
HiveDruidRules.HAVING_FILTER_RULE,
HiveDruidRules.SORT_PROJECT_TRANSPOSE,
HiveDruidRules.SORT,
HiveDruidRules.PROJECT_SORT_TRANSPOSE
);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Druid transformation rules");
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, true, mdProvider.getMetadataProvider(), null,
HepMatchOrder.TOP_DOWN,
JDBCExtractJoinFilterRule.INSTANCE,
JDBCAbstractSplitFilterRule.SPLIT_FILTER_ABOVE_JOIN,
JDBCAbstractSplitFilterRule.SPLIT_FILTER_ABOVE_CONVERTER,
JDBCFilterJoinRule.INSTANCE,
JDBCJoinPushDownRule.INSTANCE, JDBCUnionPushDownRule.INSTANCE,
JDBCFilterPushDownRule.INSTANCE, JDBCProjectPushDownRule.INSTANCE,
JDBCAggregationPushDownRule.INSTANCE, JDBCSortPushDownRule.INSTANCE
);
// 12. Run rules to aid in translation from Calcite tree to Hive tree
if (HiveConf.getBoolVar(conf, ConfVars.HIVE_CBO_RETPATH_HIVEOP)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
// 12.1. Merge join into multijoin operators (if possible)
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, true, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, HiveJoinProjectTransposeRule.BOTH_PROJECT_INCLUDE_OUTER,
HiveJoinProjectTransposeRule.LEFT_PROJECT_INCLUDE_OUTER,
HiveJoinProjectTransposeRule.RIGHT_PROJECT_INCLUDE_OUTER,
HiveJoinToMultiJoinRule.INSTANCE, HiveProjectMergeRule.INSTANCE);
// The previous rules can pull up projections through join operators,
// thus we run the field trimmer again to push them back down
fieldTrimmer = new HiveRelFieldTrimmer(null,
HiveRelFactories.HIVE_BUILDER.create(optCluster, null));
calciteOptimizedPlan = fieldTrimmer.trim(calciteOptimizedPlan);
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, ProjectRemoveRule.INSTANCE,
new ProjectMergeRule(false, HiveRelFactories.HIVE_BUILDER));
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, true, mdProvider.getMetadataProvider(), null,
HiveFilterProjectTSTransposeRule.INSTANCE, HiveFilterProjectTSTransposeRule.INSTANCE_DRUID,
HiveProjectFilterPullUpConstantsRule.INSTANCE);
// 12.2. Introduce exchange operators below join/multijoin operators
calciteOptimizedPlan = hepPlan(calciteOptimizedPlan, false, mdProvider.getMetadataProvider(), null,
HepMatchOrder.BOTTOM_UP, HiveInsertExchange4JoinRule.EXCHANGE_BELOW_JOIN,
HiveInsertExchange4JoinRule.EXCHANGE_BELOW_MULTIJOIN);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: Translation from Calcite tree to Hive tree");
}
if (LOG.isDebugEnabled() && !conf.getBoolVar(ConfVars.HIVE_IN_TEST)) {
LOG.debug("CBO Planning details:\n");
LOG.debug("Original Plan:\n" + RelOptUtil.toString(calciteGenPlan));
LOG.debug("Plan After PPD, PartPruning, ColumnPruning:\n"
+ RelOptUtil.toString(calcitePreCboPlan));
LOG.debug("Plan After Join Reordering:\n"
+ RelOptUtil.toString(calciteOptimizedPlan, SqlExplainLevel.ALL_ATTRIBUTES));
}
return calciteOptimizedPlan;
}
/**
* Perform all optimizations before Join Ordering.
*
* @param basePlan
* original plan
* @param mdProvider
* meta data provider
* @param executorProvider
* executor
* @return
*/
private RelNode applyPreJoinOrderingTransforms(RelNode basePlan, RelMetadataProvider mdProvider, RexExecutor executorProvider) {
// TODO: Decorelation of subquery should be done before attempting
// Partition Pruning; otherwise Expression evaluation may try to execute
// corelated sub query.
PerfLogger perfLogger = SessionState.getPerfLogger();
final int maxCNFNodeCount = conf.getIntVar(HiveConf.ConfVars.HIVE_CBO_CNF_NODES_LIMIT);
final int minNumORClauses = conf.getIntVar(HiveConf.ConfVars.HIVEPOINTLOOKUPOPTIMIZERMIN);
//0. SetOp rewrite
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, true, mdProvider, null, HepMatchOrder.BOTTOM_UP,
HiveProjectOverIntersectRemoveRule.INSTANCE, HiveIntersectMergeRule.INSTANCE,
HiveUnionMergeRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: HiveProjectOverIntersectRemoveRule, HiveIntersectMerge and HiveUnionMergeRule rules");
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, false, mdProvider, executorProvider, HepMatchOrder.BOTTOM_UP,
HiveIntersectRewriteRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: HiveIntersectRewrite rule");
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, false, mdProvider, executorProvider, HepMatchOrder.BOTTOM_UP,
HiveExceptRewriteRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: HiveExceptRewrite rule");
//1. Distinct aggregate rewrite
// Run this optimization early, since it is expanding the operator pipeline.
if (!conf.getVar(HiveConf.ConfVars.HIVE_EXECUTION_ENGINE).equals("mr") &&
conf.getBoolVar(HiveConf.ConfVars.HIVEOPTIMIZEDISTINCTREWRITE)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
// Its not clear, if this rewrite is always performant on MR, since extra map phase
// introduced for 2nd MR job may offset gains of this multi-stage aggregation.
// We need a cost model for MR to enable this on MR.
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider, HiveExpandDistinctAggregatesRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Distinct aggregate rewrite");
}
// 2. Try factoring out common filter elements & separating deterministic
// vs non-deterministic UDF. This needs to run before PPD so that PPD can
// add on-clauses for old style Join Syntax
// Ex: select * from R1 join R2 where ((R1.x=R2.x) and R1.y<10) or
// ((R1.x=R2.x) and R1.z=10)) and rand(1) < 0.1
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, false, mdProvider, executorProvider, HepMatchOrder.ARBITRARY,
new HivePreFilteringRule(maxCNFNodeCount));
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, factor out common filter elements and separating deterministic vs non-deterministic UDF");
// 3. Run exhaustive PPD, add not null filters, transitive inference,
// constant propagation, constant folding
List rules = Lists.newArrayList();
if (conf.getBoolVar(HiveConf.ConfVars.HIVEOPTPPD_WINDOWING)) {
rules.add(HiveFilterProjectTransposeRule.INSTANCE_DETERMINISTIC_WINDOWING);
} else {
rules.add(HiveFilterProjectTransposeRule.INSTANCE_DETERMINISTIC);
}
rules.add(HiveFilterSetOpTransposeRule.INSTANCE);
rules.add(HiveFilterSortTransposeRule.INSTANCE);
rules.add(HiveFilterJoinRule.JOIN);
rules.add(HiveFilterJoinRule.FILTER_ON_JOIN);
rules.add(new HiveFilterAggregateTransposeRule(Filter.class, HiveRelFactories.HIVE_BUILDER,
Aggregate.class));
rules.add(new FilterMergeRule(HiveRelFactories.HIVE_BUILDER));
if (conf.getBoolVar(HiveConf.ConfVars.HIVE_OPTIMIZE_REDUCE_WITH_STATS)) {
rules.add(HiveReduceExpressionsWithStatsRule.INSTANCE);
}
rules.add(HiveProjectFilterPullUpConstantsRule.INSTANCE);
rules.add(HiveReduceExpressionsRule.PROJECT_INSTANCE);
rules.add(HiveReduceExpressionsRule.FILTER_INSTANCE);
rules.add(HiveReduceExpressionsRule.JOIN_INSTANCE);
rules.add(HiveAggregateReduceFunctionsRule.INSTANCE);
rules.add(HiveAggregateReduceRule.INSTANCE);
if (conf.getBoolVar(HiveConf.ConfVars.HIVEPOINTLOOKUPOPTIMIZER)) {
rules.add(new HivePointLookupOptimizerRule.FilterCondition(minNumORClauses));
rules.add(new HivePointLookupOptimizerRule.JoinCondition(minNumORClauses));
}
rules.add(HiveJoinAddNotNullRule.INSTANCE_JOIN);
rules.add(HiveJoinAddNotNullRule.INSTANCE_SEMIJOIN);
rules.add(HiveJoinPushTransitivePredicatesRule.INSTANCE_JOIN);
rules.add(HiveJoinPushTransitivePredicatesRule.INSTANCE_SEMIJOIN);
rules.add(HiveSortMergeRule.INSTANCE);
rules.add(HiveSortLimitPullUpConstantsRule.INSTANCE);
rules.add(HiveUnionPullUpConstantsRule.INSTANCE);
rules.add(HiveAggregatePullUpConstantsRule.INSTANCE);
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider, HepMatchOrder.BOTTOM_UP,
rules.toArray(new RelOptRule[rules.size()]));
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, PPD, not null predicates, transitive inference, constant folding");
// 4. Push down limit through outer join
// NOTE: We run this after PPD to support old style join syntax.
// Ex: select * from R1 left outer join R2 where ((R1.x=R2.x) and R1.y<10) or
// ((R1.x=R2.x) and R1.z=10)) and rand(1) < 0.1 order by R1.x limit 10
if (conf.getBoolVar(HiveConf.ConfVars.HIVE_OPTIMIZE_LIMIT_TRANSPOSE)) {
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
// This should be a cost based decision, but till we enable the extended cost
// model, we will use the given value for the variable
final float reductionProportion = HiveConf.getFloatVar(conf,
HiveConf.ConfVars.HIVE_OPTIMIZE_LIMIT_TRANSPOSE_REDUCTION_PERCENTAGE);
final long reductionTuples = HiveConf.getLongVar(conf,
HiveConf.ConfVars.HIVE_OPTIMIZE_LIMIT_TRANSPOSE_REDUCTION_TUPLES);
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider, HiveSortMergeRule.INSTANCE,
HiveSortProjectTransposeRule.INSTANCE, HiveSortJoinReduceRule.INSTANCE,
HiveSortUnionReduceRule.INSTANCE);
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider, HepMatchOrder.BOTTOM_UP,
new HiveSortRemoveRule(reductionProportion, reductionTuples),
HiveProjectSortTransposeRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Push down limit through outer join");
}
// 5. Push Down Semi Joins
//TODO: Enable this later
/*perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider, SemiJoinJoinTransposeRule.INSTANCE,
SemiJoinFilterTransposeRule.INSTANCE, SemiJoinProjectTransposeRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Push Down Semi Joins"); */
// 6. Apply Partition Pruning
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, false, mdProvider, executorProvider, new HivePartitionPruneRule(conf));
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Partition Pruning");
// 7. Projection Pruning (this introduces select above TS & hence needs to be run last due to PP)
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
HiveRelFieldTrimmer fieldTrimmer = new HiveRelFieldTrimmer(null,
HiveRelFactories.HIVE_BUILDER.create(cluster, null),
profilesCBO.contains(ExtendedCBOProfile.JOIN_REORDERING));
basePlan = fieldTrimmer.trim(basePlan);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Projection Pruning");
// 8. Merge, remove and reduce Project if possible
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, false, mdProvider, executorProvider,
HiveProjectMergeRule.INSTANCE, ProjectRemoveRule.INSTANCE, HiveSortMergeRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Merge Project-Project, Merge Sort-Sort");
// 9. Rerun PPD through Project as column pruning would have introduced
// DT above scans; By pushing filter just above TS, Hive can push it into
// storage (incase there are filters on non partition cols). This only
// matches FIL-PROJ-TS
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
basePlan = hepPlan(basePlan, true, mdProvider, executorProvider,
HiveFilterProjectTSTransposeRule.INSTANCE, HiveFilterProjectTSTransposeRule.INSTANCE_DRUID,
HiveProjectFilterPullUpConstantsRule.INSTANCE);
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER,
"Calcite: Prejoin ordering transformation, Rerun PPD");
return basePlan;
}
private RelNode applyMaterializedViewRewriting(RelOptPlanner planner, RelNode basePlan,
RelMetadataProvider mdProvider, RexExecutor executorProvider) {
final RelOptCluster optCluster = basePlan.getCluster();
final PerfLogger perfLogger = SessionState.getPerfLogger();
perfLogger.PerfLogBegin(this.getClass().getName(), PerfLogger.OPTIMIZER);
final RelNode calcitePreMVRewritingPlan = basePlan;
// Add views to planner
List materializations = new ArrayList<>();
try {
// Extract tables used by the query which will in turn be used to generate
// the corresponding txn write ids
List tablesUsed = new ArrayList<>();
new RelVisitor() {
@Override
public void visit(RelNode node, int ordinal, RelNode parent) {
if (node instanceof TableScan) {
TableScan ts = (TableScan) node;
tablesUsed.add(((RelOptHiveTable) ts.getTable()).getHiveTableMD().getFullyQualifiedName());
}
super.visit(node, ordinal, parent);
}
}.go(basePlan);
final String validTxnsList = conf.get(ValidTxnList.VALID_TXNS_KEY);
ValidTxnWriteIdList txnWriteIds = null;
if (validTxnsList != null && !validTxnsList.isEmpty()) {
txnWriteIds = getTxnMgr().getValidWriteIds(tablesUsed, validTxnsList);
}
if (mvRebuildMode != MaterializationRebuildMode.NONE) {
// We only retrieve the materialization corresponding to the rebuild. In turn,
// we pass 'true' for the forceMVContentsUpToDate parameter, as we cannot allow the
// materialization contents to be stale for a rebuild if we want to use it.
materializations = Hive.get().getValidMaterializedView(mvRebuildDbName, mvRebuildName,
true, txnWriteIds);
} else {
// This is not a rebuild, we retrieve all the materializations. In turn, we do not need
// to force the materialization contents to be up-to-date, as this is not a rebuild, and
// we apply the user parameters (HIVE_MATERIALIZED_VIEW_REWRITING_TIME_WINDOW) instead.
materializations = Hive.get().getAllValidMaterializedViews(false, txnWriteIds);
}
// We need to use the current cluster for the scan operator on views,
// otherwise the planner will throw an Exception (different planners)
materializations = Lists.transform(materializations,
new Function() {
@Override
public RelOptMaterialization apply(RelOptMaterialization materialization) {
final RelNode viewScan = materialization.tableRel;
final RelNode newViewScan;
if (viewScan instanceof Project) {
// There is a Project on top (due to nullability)
final Project pq = (Project) viewScan;
newViewScan = HiveProject.create(optCluster, copyNodeScan(pq.getInput()),
pq.getChildExps(), pq.getRowType(), Collections. emptyList());
} else {
newViewScan = copyNodeScan(viewScan);
}
return new RelOptMaterialization(newViewScan, materialization.queryRel, null,
materialization.qualifiedTableName);
}
private RelNode copyNodeScan(RelNode scan) {
final RelNode newScan;
if (scan instanceof DruidQuery) {
final DruidQuery dq = (DruidQuery) scan;
// Ideally we should use HiveRelNode convention. However, since Volcano planner
// throws in that case because DruidQuery does not implement the interface,
// we set it as Bindable. Currently, we do not use convention in Hive, hence that
// should be fine.
// TODO: If we want to make use of convention (e.g., while directly generating operator
// tree instead of AST), this should be changed.
newScan = DruidQuery.create(optCluster, optCluster.traitSetOf(BindableConvention.INSTANCE),
scan.getTable(), dq.getDruidTable(),
ImmutableList.of(dq.getTableScan()));
} else {
newScan = new HiveTableScan(optCluster, optCluster.traitSetOf(HiveRelNode.CONVENTION),
(RelOptHiveTable) scan.getTable(), scan.getTable().getQualifiedName().get(0),
null, false, false);
}
return newScan;
}
}
);
} catch (HiveException e) {
LOG.warn("Exception loading materialized views", e);
}
if (!materializations.isEmpty()) {
// Use Calcite cost model for view rewriting
optCluster.invalidateMetadataQuery();
RelMetadataQuery.THREAD_PROVIDERS.set(JaninoRelMetadataProvider.of(DefaultRelMetadataProvider.INSTANCE));
// Add materializations to planner
for (RelOptMaterialization materialization : materializations) {
planner.addMaterialization(materialization);
}
// Add view-based rewriting rules to planner
planner.addRule(HiveMaterializedViewRule.INSTANCE_PROJECT_FILTER);
planner.addRule(HiveMaterializedViewRule.INSTANCE_FILTER);
planner.addRule(HiveMaterializedViewRule.INSTANCE_PROJECT_JOIN);
planner.addRule(HiveMaterializedViewRule.INSTANCE_JOIN);
planner.addRule(HiveMaterializedViewRule.INSTANCE_PROJECT_AGGREGATE);
planner.addRule(HiveMaterializedViewRule.INSTANCE_AGGREGATE);
// Optimize plan
planner.setRoot(basePlan);
basePlan = planner.findBestExp();
// Remove view-based rewriting rules from planner
planner.clear();
// Restore default cost model
optCluster.invalidateMetadataQuery();
RelMetadataQuery.THREAD_PROVIDERS.set(JaninoRelMetadataProvider.of(mdProvider));
perfLogger.PerfLogEnd(this.getClass().getName(), PerfLogger.OPTIMIZER, "Calcite: View-based rewriting");
if (calcitePreMVRewritingPlan != basePlan) {
// A rewriting was produced, we will check whether it was part of an incremental rebuild
// to try to replace INSERT OVERWRITE by INSERT
if (mvRebuildMode == MaterializationRebuildMode.INSERT_OVERWRITE_REBUILD &&
HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_MATERIALIZED_VIEW_REWRITING_INCREMENTAL) &&
HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_MATERIALIZED_VIEW_REBUILD_INCREMENTAL)) {
// First we need to check if it is valid to convert to MERGE/INSERT INTO.
// If we succeed, we modify the plan and afterwards the AST.
// MV should be an acid table.
MaterializedViewRewritingRelVisitor visitor = new MaterializedViewRewritingRelVisitor();
visitor.go(basePlan);
if (visitor.isRewritingAllowed()) {
// Trigger rewriting to remove UNION branch with MV
if (visitor.isContainsAggregate()) {
basePlan = hepPlan(basePlan, false, mdProvider, null,
HepMatchOrder.TOP_DOWN, HiveAggregateIncrementalRewritingRule.INSTANCE);
mvRebuildMode = MaterializationRebuildMode.AGGREGATE_REBUILD;
} else {
basePlan = hepPlan(basePlan, false, mdProvider, null,
HepMatchOrder.TOP_DOWN, HiveNoAggregateIncrementalRewritingRule.INSTANCE);
mvRebuildMode = MaterializationRebuildMode.NO_AGGREGATE_REBUILD;
}
}
}
// Now we trigger some needed optimization rules again
basePlan = applyPreJoinOrderingTransforms(basePlan, mdProvider, executorProvider);
}
}
return basePlan;
}
/**
* Run the HEP Planner with the given rule set.
*
* @param basePlan
* @param followPlanChanges
* @param mdProvider
* @param executorProvider
* @param rules
* @return optimized RelNode
*/
private RelNode hepPlan(RelNode basePlan, boolean followPlanChanges,
RelMetadataProvider mdProvider, RexExecutor executorProvider, RelOptRule... rules) {
return hepPlan(basePlan, followPlanChanges, mdProvider, executorProvider,
HepMatchOrder.TOP_DOWN, rules);
}
/**
* Run the HEP Planner with the given rule set.
*
* @param basePlan
* @param followPlanChanges
* @param mdProvider
* @param executorProvider
* @param order
* @param rules
* @return optimized RelNode
*/
private RelNode hepPlan(RelNode basePlan, boolean followPlanChanges,
RelMetadataProvider mdProvider, RexExecutor executorProvider, HepMatchOrder order,
RelOptRule... rules) {
RelNode optimizedRelNode = basePlan;
HepProgramBuilder programBuilder = new HepProgramBuilder();
if (followPlanChanges) {
programBuilder.addMatchOrder(order);
programBuilder = programBuilder.addRuleCollection(ImmutableList.copyOf(rules));
} else {
// TODO: Should this be also TOP_DOWN?
for (RelOptRule r : rules)
programBuilder.addRuleInstance(r);
}
// Create planner and copy context
HepPlanner planner = new HepPlanner(programBuilder.build(),
basePlan.getCluster().getPlanner().getContext());
List list = Lists.newArrayList();
list.add(mdProvider);
planner.registerMetadataProviders(list);
RelMetadataProvider chainedProvider = ChainedRelMetadataProvider.of(list);
basePlan.getCluster().setMetadataProvider(
new CachingRelMetadataProvider(chainedProvider, planner));
if (executorProvider != null) {
// basePlan.getCluster.getPlanner is the VolcanoPlanner from apply()
// both planners need to use the correct executor
basePlan.getCluster().getPlanner().setExecutor(executorProvider);
planner.setExecutor(executorProvider);
}
planner.setRoot(basePlan);
optimizedRelNode = planner.findBestExp();
return optimizedRelNode;
}
@SuppressWarnings("nls")
private RelNode genSetOpLogicalPlan(Opcode opcode, String alias, String leftalias, RelNode leftRel,
String rightalias, RelNode rightRel) throws SemanticException {
// 1. Get Row Resolvers, Column map for original left and right input of
// SetOp Rel
RowResolver leftRR = this.relToHiveRR.get(leftRel);
RowResolver rightRR = this.relToHiveRR.get(rightRel);
HashMap leftmap = leftRR.getFieldMap(leftalias);
HashMap rightmap = rightRR.getFieldMap(rightalias);
// 2. Validate that SetOp is feasible according to Hive (by using type
// info from RR)
if (leftmap.size() != rightmap.size()) {
throw new SemanticException("Schema of both sides of union should match.");
}
ASTNode tabref = getQB().getAliases().isEmpty() ? null : getQB().getParseInfo()
.getSrcForAlias(getQB().getAliases().get(0));
// 3. construct SetOp Output RR using original left & right Input
RowResolver setOpOutRR = new RowResolver();
Iterator> lIter = leftmap.entrySet().iterator();
Iterator> rIter = rightmap.entrySet().iterator();
while (lIter.hasNext()) {
Map.Entry lEntry = lIter.next();
Map.Entry rEntry = rIter.next();
ColumnInfo lInfo = lEntry.getValue();
ColumnInfo rInfo = rEntry.getValue();
String field = lEntry.getKey();
// try widening conversion, otherwise fail union
TypeInfo commonTypeInfo = FunctionRegistry.getCommonClassForUnionAll(lInfo.getType(),
rInfo.getType());
if (commonTypeInfo == null) {
throw new SemanticException(generateErrorMessage(tabref,
"Schema of both sides of setop should match: Column " + field
+ " is of type " + lInfo.getType().getTypeName()
+ " on first table and type " + rInfo.getType().getTypeName()
+ " on second table"));
}
ColumnInfo setOpColInfo = new ColumnInfo(lInfo);
setOpColInfo.setType(commonTypeInfo);
setOpOutRR.put(alias, field, setOpColInfo);
}
// 4. Determine which columns requires cast on left/right input (Calcite
// requires exact types on both sides of SetOp)
boolean leftNeedsTypeCast = false;
boolean rightNeedsTypeCast = false;
List leftProjs = new ArrayList();
List rightProjs = new ArrayList();
List leftRowDT = leftRel.getRowType().getFieldList();
List rightRowDT = rightRel.getRowType().getFieldList();
RelDataType leftFieldDT;
RelDataType rightFieldDT;
RelDataType unionFieldDT;
for (int i = 0; i < leftRowDT.size(); i++) {
leftFieldDT = leftRowDT.get(i).getType();
rightFieldDT = rightRowDT.get(i).getType();
if (!leftFieldDT.equals(rightFieldDT)) {
unionFieldDT = TypeConverter.convert(setOpOutRR.getColumnInfos().get(i).getType(),
cluster.getTypeFactory());
if (!unionFieldDT.equals(leftFieldDT)) {
leftNeedsTypeCast = true;
}
leftProjs.add(cluster.getRexBuilder().ensureType(unionFieldDT,
cluster.getRexBuilder().makeInputRef(leftFieldDT, i), true));
if (!unionFieldDT.equals(rightFieldDT)) {
rightNeedsTypeCast = true;
}
rightProjs.add(cluster.getRexBuilder().ensureType(unionFieldDT,
cluster.getRexBuilder().makeInputRef(rightFieldDT, i), true));
} else {
leftProjs.add(cluster.getRexBuilder().ensureType(leftFieldDT,
cluster.getRexBuilder().makeInputRef(leftFieldDT, i), true));
rightProjs.add(cluster.getRexBuilder().ensureType(rightFieldDT,
cluster.getRexBuilder().makeInputRef(rightFieldDT, i), true));
}
}
// 5. Introduce Project Rel above original left/right inputs if cast is
// needed for type parity
RelNode setOpLeftInput = leftRel;
RelNode setOpRightInput = rightRel;
if (leftNeedsTypeCast) {
setOpLeftInput = HiveProject.create(leftRel, leftProjs, leftRel.getRowType()
.getFieldNames());
}
if (rightNeedsTypeCast) {
setOpRightInput = HiveProject.create(rightRel, rightProjs, rightRel.getRowType()
.getFieldNames());
}
// 6. Construct SetOp Rel
Builder bldr = new ImmutableList.Builder();
bldr.add(setOpLeftInput);
bldr.add(setOpRightInput);
SetOp setOpRel = null;
switch (opcode) {
case UNION:
setOpRel = new HiveUnion(cluster, TraitsUtil.getDefaultTraitSet(cluster), bldr.build());
break;
case INTERSECT:
setOpRel = new HiveIntersect(cluster, TraitsUtil.getDefaultTraitSet(cluster), bldr.build(),
false);
break;
case INTERSECTALL:
setOpRel = new HiveIntersect(cluster, TraitsUtil.getDefaultTraitSet(cluster), bldr.build(),
true);
break;
case EXCEPT:
setOpRel = new HiveExcept(cluster, TraitsUtil.getDefaultTraitSet(cluster), bldr.build(),
false);
break;
case EXCEPTALL:
setOpRel = new HiveExcept(cluster, TraitsUtil.getDefaultTraitSet(cluster), bldr.build(),
true);
break;
default:
throw new SemanticException(ErrorMsg.UNSUPPORTED_SET_OPERATOR.getMsg(opcode.toString()));
}
relToHiveRR.put(setOpRel, setOpOutRR);
relToHiveColNameCalcitePosMap.put(setOpRel,
this.buildHiveToCalciteColumnMap(setOpOutRR, setOpRel));
return setOpRel;
}
private RelNode genJoinRelNode(RelNode leftRel, String leftTableAlias, RelNode rightRel, String rightTableAlias, JoinType hiveJoinType,
ASTNode joinCond) throws SemanticException {
RowResolver leftRR = this.relToHiveRR.get(leftRel);
RowResolver rightRR = this.relToHiveRR.get(rightRel);
// 1. Construct ExpressionNodeDesc representing Join Condition
RexNode calciteJoinCond = null;
List namedColumns = null;
if (joinCond != null) {
JoinTypeCheckCtx jCtx = new JoinTypeCheckCtx(leftRR, rightRR, hiveJoinType);
RowResolver input = RowResolver.getCombinedRR(leftRR, rightRR);
// named columns join
// TODO: we can also do the same for semi join but it seems that other
// DBMS does not support it yet.
if (joinCond.getType() == HiveParser.TOK_TABCOLNAME
&& !hiveJoinType.equals(JoinType.LEFTSEMI)) {
namedColumns = new ArrayList<>();
// We will transform using clause and make it look like an on-clause.
// So, lets generate a valid on-clause AST from using.
ASTNode and = (ASTNode) ParseDriver.adaptor.create(HiveParser.KW_AND, "and");
ASTNode equal = null;
int count = 0;
for (Node child : joinCond.getChildren()) {
String columnName = ((ASTNode) child).getText();
// dealing with views
if (unparseTranslator != null && unparseTranslator.isEnabled()) {
unparseTranslator.addIdentifierTranslation((ASTNode) child);
}
namedColumns.add(columnName);
ASTNode left = ASTBuilder.qualifiedName(leftTableAlias, columnName);
ASTNode right = ASTBuilder.qualifiedName(rightTableAlias, columnName);
equal = (ASTNode) ParseDriver.adaptor.create(HiveParser.EQUAL, "=");
ParseDriver.adaptor.addChild(equal, left);
ParseDriver.adaptor.addChild(equal, right);
ParseDriver.adaptor.addChild(and, equal);
count++;
}
joinCond = count > 1 ? and : equal;
} else if (unparseTranslator != null && unparseTranslator.isEnabled()) {
genAllExprNodeDesc(joinCond, input, jCtx);
}
Map exprNodes = JoinCondTypeCheckProcFactory.genExprNode(joinCond,
jCtx);
if (jCtx.getError() != null) {
throw new SemanticException(SemanticAnalyzer.generateErrorMessage(jCtx.getErrorSrcNode(),
jCtx.getError()));
}
ExprNodeDesc joinCondnExprNode = exprNodes.get(joinCond);
List inputRels = new ArrayList();
inputRels.add(leftRel);
inputRels.add(rightRel);
calciteJoinCond = RexNodeConverter.convert(cluster, joinCondnExprNode, inputRels,
relToHiveRR, relToHiveColNameCalcitePosMap, false);
} else {
calciteJoinCond = cluster.getRexBuilder().makeLiteral(true);
}
// 2. Validate that join condition is legal (i.e no function refering to
// both sides of join, only equi join)
// TODO: Join filter handling (only supported for OJ by runtime or is it
// supported for IJ as well)
// 3. Construct Join Rel Node and RowResolver for the new Join Node
boolean leftSemiJoin = false;
JoinRelType calciteJoinType;
switch (hiveJoinType) {
case LEFTOUTER:
calciteJoinType = JoinRelType.LEFT;
break;
case RIGHTOUTER:
calciteJoinType = JoinRelType.RIGHT;
break;
case FULLOUTER:
calciteJoinType = JoinRelType.FULL;
break;
case LEFTSEMI:
calciteJoinType = JoinRelType.INNER;
leftSemiJoin = true;
break;
case INNER:
default:
calciteJoinType = JoinRelType.INNER;
break;
}
RelNode topRel = null;
RowResolver topRR = null;
if (leftSemiJoin) {
List sysFieldList = new ArrayList();
List leftJoinKeys = new ArrayList();
List rightJoinKeys = new ArrayList();
RexNode nonEquiConds = RelOptUtil.splitJoinCondition(sysFieldList, leftRel, rightRel,
calciteJoinCond, leftJoinKeys, rightJoinKeys, null, null);
RelNode[] inputRels = new RelNode[] { leftRel, rightRel };
final List leftKeys = new ArrayList();
final List rightKeys = new ArrayList();
RexNode remainingEquiCond = HiveCalciteUtil.projectNonColumnEquiConditions(HiveRelFactories.HIVE_PROJECT_FACTORY,
inputRels, leftJoinKeys, rightJoinKeys, 0, leftKeys, rightKeys);
// Adjust right input fields in nonEquiConds if previous call modified the input
if (inputRels[0] != leftRel) {
nonEquiConds = RexUtil.shift(nonEquiConds, leftRel.getRowType().getFieldCount(),
inputRels[0].getRowType().getFieldCount() - leftRel.getRowType().getFieldCount());
}
calciteJoinCond = remainingEquiCond != null ?
RexUtil.composeConjunction(cluster.getRexBuilder(),
ImmutableList.of(remainingEquiCond, nonEquiConds), false) :
nonEquiConds;
topRel = HiveSemiJoin.getSemiJoin(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
inputRels[0], inputRels[1], calciteJoinCond, ImmutableIntList.copyOf(leftKeys),
ImmutableIntList.copyOf(rightKeys));
// Create join RR: we need to check whether we need to update left RR in case
// previous call to projectNonColumnEquiConditions updated it
if (inputRels[0] != leftRel) {
RowResolver newLeftRR = new RowResolver();
if (!RowResolver.add(newLeftRR, leftRR)) {
LOG.warn("Duplicates detected when adding columns to RR: see previous message");
}
for (int i = leftRel.getRowType().getFieldCount();
i < inputRels[0].getRowType().getFieldCount(); i++) {
ColumnInfo oColInfo = new ColumnInfo(
SemanticAnalyzer.getColumnInternalName(i),
TypeConverter.convert(inputRels[0].getRowType().getFieldList().get(i).getType()),
null, false);
newLeftRR.put(oColInfo.getTabAlias(), oColInfo.getInternalName(), oColInfo);
}
RowResolver joinRR = new RowResolver();
if (!RowResolver.add(joinRR, newLeftRR)) {
LOG.warn("Duplicates detected when adding columns to RR: see previous message");
}
relToHiveColNameCalcitePosMap.put(topRel, this.buildHiveToCalciteColumnMap(joinRR, topRel));
relToHiveRR.put(topRel, joinRR);
// Introduce top project operator to remove additional column(s) that have
// been introduced
List topFields = new ArrayList();
List topFieldNames = new ArrayList();
for (int i = 0; i < leftRel.getRowType().getFieldCount(); i++) {
final RelDataTypeField field = leftRel.getRowType().getFieldList().get(i);
topFields.add(leftRel.getCluster().getRexBuilder().makeInputRef(field.getType(), i));
topFieldNames.add(field.getName());
}
topRel = HiveRelFactories.HIVE_PROJECT_FACTORY.createProject(topRel, topFields, topFieldNames);
}
topRR = new RowResolver();
if (!RowResolver.add(topRR, leftRR)) {
LOG.warn("Duplicates detected when adding columns to RR: see previous message");
}
} else {
topRel = HiveJoin.getJoin(cluster, leftRel, rightRel, calciteJoinCond, calciteJoinType);
topRR = RowResolver.getCombinedRR(leftRR, rightRR);
if (namedColumns != null) {
List tableAliases = new ArrayList<>();
tableAliases.add(leftTableAlias);
tableAliases.add(rightTableAlias);
topRR.setNamedJoinInfo(new NamedJoinInfo(tableAliases, namedColumns, hiveJoinType));
}
}
// 4. Add new rel & its RR to the maps
relToHiveColNameCalcitePosMap.put(topRel, this.buildHiveToCalciteColumnMap(topRR, topRel));
relToHiveRR.put(topRel, topRR);
return topRel;
}
/**
* Generate Join Logical Plan Relnode by walking through the join AST.
*
* @param aliasToRel
* Alias(Table/Relation alias) to RelNode; only read and not
* written in to by this method
* @return
* @throws SemanticException
*/
private RelNode genJoinLogicalPlan(ASTNode joinParseTree, Map aliasToRel)
throws SemanticException {
RelNode leftRel = null;
RelNode rightRel = null;
JoinType hiveJoinType = null;
if (joinParseTree.getToken().getType() == HiveParser.TOK_UNIQUEJOIN) {
String msg = String.format("UNIQUE JOIN is currently not supported in CBO,"
+ " turn off cbo to use UNIQUE JOIN.");
LOG.debug(msg);
throw new CalciteSemanticException(msg, UnsupportedFeature.Unique_join);
}
// 1. Determine Join Type
// TODO: What about TOK_CROSSJOIN, TOK_MAPJOIN
switch (joinParseTree.getToken().getType()) {
case HiveParser.TOK_LEFTOUTERJOIN:
hiveJoinType = JoinType.LEFTOUTER;
break;
case HiveParser.TOK_RIGHTOUTERJOIN:
hiveJoinType = JoinType.RIGHTOUTER;
break;
case HiveParser.TOK_FULLOUTERJOIN:
hiveJoinType = JoinType.FULLOUTER;
break;
case HiveParser.TOK_LEFTSEMIJOIN:
hiveJoinType = JoinType.LEFTSEMI;
break;
default:
hiveJoinType = JoinType.INNER;
break;
}
// 2. Get Left Table Alias
ASTNode left = (ASTNode) joinParseTree.getChild(0);
String leftTableAlias = null;
if ((left.getToken().getType() == HiveParser.TOK_TABREF)
|| (left.getToken().getType() == HiveParser.TOK_SUBQUERY)
|| (left.getToken().getType() == HiveParser.TOK_PTBLFUNCTION)) {
String tableName = SemanticAnalyzer.getUnescapedUnqualifiedTableName(
(ASTNode) left.getChild(0)).toLowerCase();
leftTableAlias = left.getChildCount() == 1 ? tableName : SemanticAnalyzer
.unescapeIdentifier(left.getChild(left.getChildCount() - 1).getText().toLowerCase());
// ptf node form is: ^(TOK_PTBLFUNCTION $name $alias?
// partitionTableFunctionSource partitioningSpec? expression*)
// guranteed to have an lias here: check done in processJoin
leftTableAlias = (left.getToken().getType() == HiveParser.TOK_PTBLFUNCTION) ? SemanticAnalyzer
.unescapeIdentifier(left.getChild(1).getText().toLowerCase()) : leftTableAlias;
leftRel = aliasToRel.get(leftTableAlias);
} else if (SemanticAnalyzer.isJoinToken(left)) {
leftRel = genJoinLogicalPlan(left, aliasToRel);
} else if (left.getToken().getType() == HiveParser.TOK_LATERAL_VIEW) {
leftRel = genLateralViewPlans(left, aliasToRel);
} else {
assert (false);
}
// 3. Get Right Table Alias
ASTNode right = (ASTNode) joinParseTree.getChild(1);
String rightTableAlias = null;
if ((right.getToken().getType() == HiveParser.TOK_TABREF)
|| (right.getToken().getType() == HiveParser.TOK_SUBQUERY)
|| (right.getToken().getType() == HiveParser.TOK_PTBLFUNCTION)) {
String tableName = SemanticAnalyzer.getUnescapedUnqualifiedTableName(
(ASTNode) right.getChild(0)).toLowerCase();
rightTableAlias = right.getChildCount() == 1 ? tableName : SemanticAnalyzer
.unescapeIdentifier(right.getChild(right.getChildCount() - 1).getText().toLowerCase());
// ptf node form is: ^(TOK_PTBLFUNCTION $name $alias?
// partitionTableFunctionSource partitioningSpec? expression*)
// guranteed to have an lias here: check done in processJoin
rightTableAlias = (right.getToken().getType() == HiveParser.TOK_PTBLFUNCTION) ? SemanticAnalyzer
.unescapeIdentifier(right.getChild(1).getText().toLowerCase()) : rightTableAlias;
rightRel = aliasToRel.get(rightTableAlias);
} else if (right.getToken().getType() == HiveParser.TOK_LATERAL_VIEW) {
rightRel = genLateralViewPlans(right, aliasToRel);
} else {
assert (false);
}
// 4. Get Join Condn
ASTNode joinCond = (ASTNode) joinParseTree.getChild(2);
// 5. Create Join rel
return genJoinRelNode(leftRel, leftTableAlias, rightRel, rightTableAlias, hiveJoinType, joinCond);
}
private RelNode genTableLogicalPlan(String tableAlias, QB qb) throws SemanticException {
RowResolver rr = new RowResolver();
RelNode tableRel = null;
try {
// 1. If the table has a Sample specified, bail from Calcite path.
// 2. if returnpath is on and hivetestmode is on bail
if (qb.getParseInfo().getTabSample(tableAlias) != null
|| getNameToSplitSampleMap().containsKey(tableAlias)
|| (conf.getBoolVar(HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP)) && (conf.getBoolVar(HiveConf.ConfVars.HIVETESTMODE)) ) {
String msg = String.format("Table Sample specified for %s."
+ " Currently we don't support Table Sample clauses in CBO,"
+ " turn off cbo for queries on tableSamples.", tableAlias);
LOG.debug(msg);
throw new CalciteSemanticException(msg, UnsupportedFeature.Table_sample_clauses);
}
// 2. Get Table Metadata
Table tabMetaData = qb.getMetaData().getSrcForAlias(tableAlias);
// 3. Get Table Logical Schema (Row Type)
// NOTE: Table logical schema = Non Partition Cols + Partition Cols +
// Virtual Cols
// 3.1 Add Column info for non partion cols (Object Inspector fields)
@SuppressWarnings("deprecation")
StructObjectInspector rowObjectInspector = (StructObjectInspector) tabMetaData.getDeserializer()
.getObjectInspector();
List fields = rowObjectInspector.getAllStructFieldRefs();
ColumnInfo colInfo;
String colName;
ArrayList cInfoLst = new ArrayList();
for (int i = 0; i < fields.size(); i++) {
colName = fields.get(i).getFieldName();
colInfo = new ColumnInfo(
fields.get(i).getFieldName(),
TypeInfoUtils.getTypeInfoFromObjectInspector(fields.get(i).getFieldObjectInspector()),
tableAlias, false);
colInfo.setSkewedCol((SemanticAnalyzer.isSkewedCol(tableAlias, qb, colName)) ? true
: false);
rr.put(tableAlias, colName, colInfo);
cInfoLst.add(colInfo);
}
// TODO: Fix this
ArrayList nonPartitionColumns = new ArrayList(cInfoLst);
ArrayList partitionColumns = new ArrayList();
// 3.2 Add column info corresponding to partition columns
for (FieldSchema part_col : tabMetaData.getPartCols()) {
colName = part_col.getName();
colInfo = new ColumnInfo(colName,
TypeInfoFactory.getPrimitiveTypeInfo(part_col.getType()), tableAlias, true);
rr.put(tableAlias, colName, colInfo);
cInfoLst.add(colInfo);
partitionColumns.add(colInfo);
}
final TableType tableType = obtainTableType(tabMetaData);
// 3.3 Add column info corresponding to virtual columns
List virtualCols = new ArrayList();
if (tableType == TableType.NATIVE) {
Iterator vcs = VirtualColumn.getRegistry(conf).iterator();
while (vcs.hasNext()) {
VirtualColumn vc = vcs.next();
colInfo = new ColumnInfo(vc.getName(), vc.getTypeInfo(), tableAlias, true,
vc.getIsHidden());
rr.put(tableAlias, vc.getName().toLowerCase(), colInfo);
cInfoLst.add(colInfo);
virtualCols.add(vc);
}
}
// 4. Build operator
if (tableType == TableType.DRUID ||
(tableType == TableType.JDBC && tabMetaData.getProperty("hive.sql.table") != null)) {
// Create case sensitive columns list
List originalColumnNames =
((StandardStructObjectInspector)rowObjectInspector).getOriginalColumnNames();
List cIList = new ArrayList(originalColumnNames.size());
for (int i = 0; i < rr.getColumnInfos().size(); i++) {
cIList.add(new ColumnInfo(originalColumnNames.get(i), rr.getColumnInfos().get(i).getType(),
tableAlias, false));
}
// Build row type from field
RelDataType rowType = TypeConverter.getType(cluster, cIList);
// Build RelOptAbstractTable
String fullyQualifiedTabName = tabMetaData.getDbName();
if (fullyQualifiedTabName != null && !fullyQualifiedTabName.isEmpty()) {
fullyQualifiedTabName = fullyQualifiedTabName + "." + tabMetaData.getTableName();
}
else {
fullyQualifiedTabName = tabMetaData.getTableName();
}
if (tableType == TableType.DRUID) {
// Build Druid query
String address = HiveConf.getVar(conf,
HiveConf.ConfVars.HIVE_DRUID_BROKER_DEFAULT_ADDRESS);
String dataSource = tabMetaData.getParameters().get(Constants.DRUID_DATA_SOURCE);
Set metrics = new HashSet<>();
RexBuilder rexBuilder = cluster.getRexBuilder();
RelDataTypeFactory dtFactory = rexBuilder.getTypeFactory();
List druidColTypes = new ArrayList<>();
List druidColNames = new ArrayList<>();
//@TODO FIX this, we actually do not need this anymore,
// in addition to that Druid allow numeric dimensions now so this check is not accurate
for (RelDataTypeField field : rowType.getFieldList()) {
if (DruidTable.DEFAULT_TIMESTAMP_COLUMN.equals(field.getName())) {
// Druid's time column is always not null.
druidColTypes.add(dtFactory.createTypeWithNullability(field.getType(), false));
} else {
druidColTypes.add(field.getType());
}
druidColNames.add(field.getName());
if (field.getName().equals(DruidTable.DEFAULT_TIMESTAMP_COLUMN)) {
// timestamp
continue;
}
if (field.getType().getSqlTypeName() == SqlTypeName.VARCHAR) {
// dimension
continue;
}
metrics.add(field.getName());
}
List intervals = Arrays.asList(DruidTable.DEFAULT_INTERVAL);
rowType = dtFactory.createStructType(druidColTypes, druidColNames);
DruidTable druidTable = new DruidTable(new DruidSchema(address, address, false),
dataSource, RelDataTypeImpl.proto(rowType), metrics, DruidTable.DEFAULT_TIMESTAMP_COLUMN,
intervals, null, null);
RelOptHiveTable optTable = new RelOptHiveTable(relOptSchema, fullyQualifiedTabName,
rowType, tabMetaData, nonPartitionColumns, partitionColumns, virtualCols, conf,
partitionCache, colStatsCache, noColsMissingStats);
final TableScan scan = new HiveTableScan(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
optTable, null == tableAlias ? tabMetaData.getTableName() : tableAlias,
getAliasId(tableAlias, qb), HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP), qb.isInsideView()
|| qb.getAliasInsideView().contains(tableAlias.toLowerCase()));
tableRel = DruidQuery.create(cluster, cluster.traitSetOf(BindableConvention.INSTANCE),
optTable, druidTable, ImmutableList.of(scan), DruidSqlOperatorConverter.getDefaultMap());
} else if (tableType == TableType.JDBC) {
RelOptHiveTable optTable = new RelOptHiveTable(relOptSchema, fullyQualifiedTabName,
rowType, tabMetaData, nonPartitionColumns, partitionColumns, virtualCols, conf,
partitionCache, colStatsCache, noColsMissingStats);
final HiveTableScan hts = new HiveTableScan(cluster,
cluster.traitSetOf(HiveRelNode.CONVENTION), optTable,
null == tableAlias ? tabMetaData.getTableName() : tableAlias,
getAliasId(tableAlias, qb),
HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP),
qb.isInsideView() || qb.getAliasInsideView().contains(tableAlias.toLowerCase()));
LOG.debug("JDBC is running");
final String dataBaseType = tabMetaData.getProperty("hive.sql.database.type");
final String url = tabMetaData.getProperty("hive.sql.jdbc.url");
final String driver = tabMetaData.getProperty("hive.sql.jdbc.driver");
final String user = tabMetaData.getProperty("hive.sql.dbcp.username");
final String pswd = tabMetaData.getProperty("hive.sql.dbcp.password");
//final String query = tabMetaData.getProperty("hive.sql.query");
final String tableName = tabMetaData.getProperty("hive.sql.table");
final DataSource ds = JdbcSchema.dataSource(url, driver, user, pswd);
SqlDialect jdbcDialect = JdbcSchema.createDialect(SqlDialectFactoryImpl.INSTANCE, ds);
JdbcConvention jc = JdbcConvention.of(jdbcDialect, null, dataBaseType);
JdbcSchema schema = new JdbcSchema(ds, jc.dialect, jc, null/*catalog */, null/*schema */);
JdbcTable jt = (JdbcTable) schema.getTable(tableName);
if (jt == null) {
throw new SemanticException("Table " + tableName + " was not found in the database");
}
JdbcHiveTableScan jdbcTableRel = new JdbcHiveTableScan(cluster, optTable, jt, jc, hts);
tableRel = new HiveJdbcConverter(cluster, jdbcTableRel.getTraitSet().replace(HiveRelNode.CONVENTION),
jdbcTableRel, jc);
}
} else {
// Build row type from field
RelDataType rowType = inferNotNullableColumns(tabMetaData, TypeConverter.getType(cluster, rr, null));
// Build RelOptAbstractTable
String fullyQualifiedTabName = tabMetaData.getDbName();
if (fullyQualifiedTabName != null && !fullyQualifiedTabName.isEmpty()) {
fullyQualifiedTabName = fullyQualifiedTabName + "." + tabMetaData.getTableName();
}
else {
fullyQualifiedTabName = tabMetaData.getTableName();
}
RelOptHiveTable optTable = new RelOptHiveTable(relOptSchema, fullyQualifiedTabName,
rowType, tabMetaData, nonPartitionColumns, partitionColumns, virtualCols, conf,
partitionCache, colStatsCache, noColsMissingStats);
// Build Hive Table Scan Rel
tableRel = new HiveTableScan(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION), optTable,
null == tableAlias ? tabMetaData.getTableName() : tableAlias,
getAliasId(tableAlias, qb), HiveConf.getBoolVar(conf,
HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP), qb.isInsideView()
|| qb.getAliasInsideView().contains(tableAlias.toLowerCase()));
}
// 6. Add Schema(RR) to RelNode-Schema map
ImmutableMap hiveToCalciteColMap = buildHiveToCalciteColumnMap(rr,
tableRel);
relToHiveRR.put(tableRel, rr);
relToHiveColNameCalcitePosMap.put(tableRel, hiveToCalciteColMap);
} catch (Exception e) {
if (e instanceof SemanticException) {
throw (SemanticException) e;
} else {
throw (new RuntimeException(e));
}
}
return tableRel;
}
private RelDataType inferNotNullableColumns(Table tabMetaData, RelDataType rowType)
throws HiveException {
// Retrieve not null constraints
final NotNullConstraint nnc = Hive.get().getReliableNotNullConstraints(
tabMetaData.getDbName(), tabMetaData.getTableName());
// Retrieve primary key constraints (cannot be null)
final PrimaryKeyInfo pkc = Hive.get().getReliablePrimaryKeys(
tabMetaData.getDbName(), tabMetaData.getTableName());
if (nnc.getNotNullConstraints().isEmpty() && pkc.getColNames().isEmpty()) {
return rowType;
}
// Build the bitset with not null columns
ImmutableBitSet.Builder builder = ImmutableBitSet.builder();
for (String nnCol : nnc.getNotNullConstraints().values()) {
int nnPos = -1;
for (int i = 0; i < rowType.getFieldNames().size(); i++) {
if (rowType.getFieldNames().get(i).equals(nnCol)) {
nnPos = i;
break;
}
}
if (nnPos == -1) {
LOG.error("Column for not null constraint definition " + nnCol + " not found");
return rowType;
}
builder.set(nnPos);
}
for (String pkCol : pkc.getColNames().values()) {
int pkPos = -1;
for (int i = 0; i < rowType.getFieldNames().size(); i++) {
if (rowType.getFieldNames().get(i).equals(pkCol)) {
pkPos = i;
break;
}
}
if (pkPos == -1) {
LOG.error("Column for not null constraint definition " + pkCol + " not found");
return rowType;
}
builder.set(pkPos);
}
ImmutableBitSet bitSet = builder.build();
RexBuilder rexBuilder = cluster.getRexBuilder();
RelDataTypeFactory dtFactory = rexBuilder.getTypeFactory();
List fieldTypes = new LinkedList();
List fieldNames = new LinkedList();
for (RelDataTypeField rdtf : rowType.getFieldList()) {
if (bitSet.indexOf(rdtf.getIndex()) != -1) {
fieldTypes.add(dtFactory.createTypeWithNullability(rdtf.getType(), false));
} else {
fieldTypes.add(rdtf.getType());
}
fieldNames.add(rdtf.getName());
}
return dtFactory.createStructType(fieldTypes, fieldNames);
}
private TableType obtainTableType(Table tabMetaData) {
if (tabMetaData.getStorageHandler() != null) {
final String storageHandlerStr = tabMetaData.getStorageHandler().toString();
if (storageHandlerStr
.equals(Constants.DRUID_HIVE_STORAGE_HANDLER_ID)) {
return TableType.DRUID;
}
if (storageHandlerStr
.equals(Constants.JDBC_HIVE_STORAGE_HANDLER_ID)) {
return TableType.JDBC;
}
}
return TableType.NATIVE;
}
private RelNode genFilterRelNode(ASTNode filterExpr, RelNode srcRel,
ImmutableMap outerNameToPosMap, RowResolver outerRR,
boolean useCaching) throws SemanticException {
ExprNodeDesc filterCondn = genExprNodeDesc(filterExpr, relToHiveRR.get(srcRel),
outerRR, null, useCaching);
if (filterCondn instanceof ExprNodeConstantDesc
&& !filterCondn.getTypeString().equals(serdeConstants.BOOLEAN_TYPE_NAME)) {
// queries like select * from t1 where 'foo';
// Calcite's rule PushFilterThroughProject chokes on it. Arguably, we
// can insert a cast to
// boolean in such cases, but since Postgres, Oracle and MS SQL server
// fail on compile time
// for such queries, its an arcane corner case, not worth of adding that
// complexity.
throw new CalciteSemanticException("Filter expression with non-boolean return type.",
UnsupportedFeature.Filter_expression_with_non_boolean_return_type);
}
ImmutableMap hiveColNameCalcitePosMap = this.relToHiveColNameCalcitePosMap
.get(srcRel);
RexNode convertedFilterExpr = new RexNodeConverter(cluster, srcRel.getRowType(),
outerNameToPosMap, hiveColNameCalcitePosMap, relToHiveRR.get(srcRel), outerRR,
0, true, subqueryId).convert(filterCondn);
RexNode factoredFilterExpr = RexUtil
.pullFactors(cluster.getRexBuilder(), convertedFilterExpr);
RelNode filterRel = new HiveFilter(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
srcRel, factoredFilterExpr);
this.relToHiveColNameCalcitePosMap.put(filterRel, hiveColNameCalcitePosMap);
relToHiveRR.put(filterRel, relToHiveRR.get(srcRel));
relToHiveColNameCalcitePosMap.put(filterRel, hiveColNameCalcitePosMap);
return filterRel;
}
private void subqueryRestrictionCheck(QB qb, ASTNode searchCond, RelNode srcRel,
boolean forHavingClause, Set corrScalarQueries,
Set scalarQueriesWithAggNoWinNoGby) throws SemanticException {
List subQueriesInOriginalTree = SubQueryUtils.findSubQueries(searchCond);
ASTNode clonedSearchCond = (ASTNode) SubQueryUtils.adaptor.dupTree(searchCond);
List subQueries = SubQueryUtils.findSubQueries(clonedSearchCond);
for(int i=0; i subqInfo = new ObjectPair(false, 0);
ASTNode outerQueryExpr = (ASTNode) subQueryAST.getChild(2);
if (outerQueryExpr != null && outerQueryExpr.getType() == HiveParser.TOK_SUBQUERY_EXPR) {
throw new CalciteSubquerySemanticException(
ErrorMsg.UNSUPPORTED_SUBQUERY_EXPRESSION.getMsg(
outerQueryExpr, "IN/NOT IN subqueries are not allowed in LHS"));
}
QBSubQuery subQuery = SubQueryUtils.buildSubQuery(qb.getId(), sqIdx, subQueryAST,
originalSubQueryAST, ctx);
RowResolver inputRR = relToHiveRR.get(srcRel);
String havingInputAlias = null;
boolean [] subqueryConfig = {false, false};
subQuery.subqueryRestrictionsCheck(inputRR, forHavingClause,
havingInputAlias, subqueryConfig);
if(subqueryConfig[0]) {
corrScalarQueries.add(originalSubQueryAST);
}
if(subqueryConfig[1]) {
scalarQueriesWithAggNoWinNoGby.add(originalSubQueryAST);
}
}
}
private RelNode genLateralViewPlans(ASTNode lateralView, Map aliasToRel)
throws SemanticException {
final RexBuilder rexBuilder = this.cluster.getRexBuilder();
final RelDataTypeFactory dtFactory = this.cluster.getTypeFactory();
final String inlineFunctionName =
GenericUDTFInline.class.getAnnotation(Description.class).name();
int numChildren = lateralView.getChildCount();
assert (numChildren == 2);
// 1) Obtain input and all related data structures
ASTNode next = (ASTNode) lateralView.getChild(1);
RelNode inputRel = null;
switch (next.getToken().getType()) {
case HiveParser.TOK_TABREF:
case HiveParser.TOK_SUBQUERY:
case HiveParser.TOK_PTBLFUNCTION:
String inputTableName = SemanticAnalyzer.getUnescapedUnqualifiedTableName(
(ASTNode) next.getChild(0)).toLowerCase();
String inputTableAlias;
if (next.getToken().getType() == HiveParser.TOK_PTBLFUNCTION) {
// ptf node form is: ^(TOK_PTBLFUNCTION $name $alias?
// partitionTableFunctionSource partitioningSpec? expression*)
// ptf node guaranteed to have an alias here
inputTableAlias = SemanticAnalyzer.unescapeIdentifier(next.getChild(1).getText().toLowerCase());
} else {
inputTableAlias = next.getChildCount() == 1 ? inputTableName :
SemanticAnalyzer.unescapeIdentifier(next.getChild(next.getChildCount() - 1).getText().toLowerCase());
}
inputRel = aliasToRel.get(inputTableAlias);
break;
case HiveParser.TOK_LATERAL_VIEW:
inputRel = genLateralViewPlans(next, aliasToRel);
break;
default:
throw new SemanticException(ErrorMsg.LATERAL_VIEW_INVALID_CHILD.getMsg(lateralView));
}
// Input row resolver
RowResolver inputRR = this.relToHiveRR.get(inputRel);
// Extract input refs. They will serve as input for the function invocation
List inputRefs = Lists.transform(inputRel.getRowType().getFieldList(),
input -> new RexInputRef(input.getIndex(), input.getType()));
// Extract type for the arguments
List inputRefsTypes = new ArrayList<>();
for (int i = 0; i < inputRefs.size(); i++) {
inputRefsTypes.add(inputRefs.get(i).getType());
}
// Input name to position map
ImmutableMap inputPosMap = this.relToHiveColNameCalcitePosMap.get(inputRel);
// 2) Generate HiveTableFunctionScan RelNode for lateral view
// TODO: Support different functions (not only INLINE) with LATERAL VIEW JOIN
// ^(TOK_LATERAL_VIEW ^(TOK_SELECT ^(TOK_SELEXPR ^(TOK_FUNCTION Identifier["inline"] valuesClause) identifier* tableAlias)))
final ASTNode selExprClause =
(ASTNode) lateralView.getChild(0).getChild(0);
final ASTNode functionCall =
(ASTNode) selExprClause.getChild(0);
if (functionCall.getChild(0).getText().compareToIgnoreCase(inlineFunctionName) != 0) {
throw new SemanticException("CBO only supports inline LVJ");
}
final ASTNode valuesClause =
(ASTNode) functionCall.getChild(1);
// Output types. They will be the concatenation of the input refs types and
// the types of the expressions for the lateral view generated rows
List outputFieldTypes = new ArrayList<>(inputRefsTypes);
List outputFieldNames = new ArrayList<>(inputRel.getRowType().getFieldNames());
// Generate all expressions from lateral view
ExprNodeDesc valuesExpr = genExprNodeDesc(valuesClause, inputRR, false);
RexCall convertedOriginalValuesExpr = (RexCall) new RexNodeConverter(this.cluster, inputRel.getRowType(),
inputPosMap, 0, false).convert(valuesExpr);
RelDataType valuesRowType = ((ArraySqlType) convertedOriginalValuesExpr.getType()).getComponentType();
List newStructExprs = new ArrayList<>();
for (RexNode structExpr : convertedOriginalValuesExpr.getOperands()) {
RexCall structCall = (RexCall) structExpr;
List exprs = new ArrayList<>(inputRefs);
exprs.addAll(structCall.getOperands());
newStructExprs.add(rexBuilder.makeCall(structCall.op, exprs));
}
RexNode convertedFinalValuesExpr =
rexBuilder.makeCall(convertedOriginalValuesExpr.op, newStructExprs);
// The return type will be the concatenation of input type and original values type
RelDataType retType = SqlValidatorUtil.deriveJoinRowType(inputRel.getRowType(),
valuesRowType, JoinRelType.INNER, dtFactory, null, ImmutableList.of());
// Create inline SQL operator
FunctionInfo inlineFunctionInfo = FunctionRegistry.getFunctionInfo(inlineFunctionName);
SqlOperator calciteOp = SqlFunctionConverter.getCalciteOperator(
inlineFunctionName, inlineFunctionInfo.getGenericUDTF(),
ImmutableList.copyOf(inputRefsTypes), retType);
RelNode htfsRel = HiveTableFunctionScan.create(cluster, TraitsUtil.getDefaultTraitSet(cluster),
ImmutableList.of(inputRel), rexBuilder.makeCall(calciteOp, convertedFinalValuesExpr),
null, retType, null);
// 3) Keep track of colname-to-posmap && RR for new op
RowResolver outputRR = new RowResolver();
// Add all input columns
if (!RowResolver.add(outputRR, inputRR)) {
LOG.warn("Duplicates detected when adding columns to RR: see previous message");
}
// Add all columns from lateral view
// First we extract the information that the query provides
String tableAlias = null;
List columnAliases = new ArrayList<>();
Set uniqueNames = new HashSet<>();
for (int i = 1; i < selExprClause.getChildren().size(); i++) {
ASTNode child = (ASTNode) selExprClause.getChild(i);
switch (child.getToken().getType()) {
case HiveParser.TOK_TABALIAS:
tableAlias = unescapeIdentifier(child.getChild(0).getText());
break;
default:
String colAlias = unescapeIdentifier(child.getText());
if (uniqueNames.contains(colAlias)) {
// Column aliases defined by query for lateral view output are duplicated
throw new SemanticException(ErrorMsg.COLUMN_ALIAS_ALREADY_EXISTS.getMsg(colAlias));
}
columnAliases.add(colAlias);
uniqueNames.add(colAlias);
}
}
if (tableAlias == null) {
// Parser enforces that table alias is added, but check again
throw new SemanticException("Alias should be specified LVJ");
}
if (!columnAliases.isEmpty() &&
columnAliases.size() != valuesRowType.getFieldCount()) {
// Number of columns in the aliases does not match with number of columns
// generated by the lateral view
throw new SemanticException(ErrorMsg.UDTF_ALIAS_MISMATCH.getMsg());
}
if (columnAliases.isEmpty()) {
// Auto-generate column aliases
for (int i = 0; i < valuesRowType.getFieldCount(); i++) {
columnAliases.add(SemanticAnalyzer.getColumnInternalName(i));
}
}
int numInputExprs = inputRR.getColumnInfos().size();
ListTypeInfo listTypeInfo = (ListTypeInfo) valuesExpr.getTypeInfo(); // Array should have ListTypeInfo
StructTypeInfo typeInfos = (StructTypeInfo) listTypeInfo.getListElementTypeInfo(); // Within the list, we extract types
for (int i = 0, j = 0; i < columnAliases.size(); i++) {
String internalColName;
do {
internalColName = SemanticAnalyzer.getColumnInternalName(j++);
} while (inputRR.getPosition(internalColName) != -1);
outputRR.put(tableAlias, columnAliases.get(i),
new ColumnInfo(internalColName, typeInfos.getAllStructFieldTypeInfos().get(i),
tableAlias, false));
}
this.relToHiveColNameCalcitePosMap
.put(htfsRel, buildHiveToCalciteColumnMap(outputRR, htfsRel));
this.relToHiveRR.put(htfsRel, outputRR);
// 4) Return new operator
return htfsRel;
}
private boolean genSubQueryRelNode(QB qb, ASTNode node, RelNode srcRel, boolean forHavingClause,
Map subQueryToRelNode) throws SemanticException {
Set corrScalarQueriesWithAgg = new HashSet();
Set scalarQueriesWithAggNoWinNoGby= new HashSet();
//disallow subqueries which HIVE doesn't currently support
subqueryRestrictionCheck(qb, node, srcRel, forHavingClause, corrScalarQueriesWithAgg,
scalarQueriesWithAggNoWinNoGby);
Deque stack = new ArrayDeque();
stack.push(node);
boolean isSubQuery = false;
while (!stack.isEmpty()) {
ASTNode next = stack.pop();
switch(next.getType()) {
case HiveParser.TOK_SUBQUERY_EXPR:
/*
* Restriction 2.h Subquery isnot allowed in LHS
*/
if(next.getChildren().size() == 3
&& next.getChild(2).getType() == HiveParser.TOK_SUBQUERY_EXPR){
throw new CalciteSemanticException(ErrorMsg.UNSUPPORTED_SUBQUERY_EXPRESSION.getMsg(
next.getChild(2),
"SubQuery in LHS expressions are not supported."));
}
String sbQueryAlias = "sq_" + qb.incrNumSubQueryPredicates();
QB qbSQ = new QB(qb.getId(), sbQueryAlias, true);
Phase1Ctx ctx1 = initPhase1Ctx();
doPhase1((ASTNode)next.getChild(1), qbSQ, ctx1, null);
getMetaData(qbSQ);
this.subqueryId++;
RelNode subQueryRelNode = genLogicalPlan(qbSQ, false,
relToHiveColNameCalcitePosMap.get(srcRel), relToHiveRR.get(srcRel));
subQueryToRelNode.put(next, subQueryRelNode);
//keep track of subqueries which are scalar, correlated and contains aggregate
// subquery expression. This will later be special cased in Subquery remove rule
// for correlated scalar queries with aggregate we have take care of the case where
// inner aggregate happens on empty result
if(corrScalarQueriesWithAgg.contains(next)) {
corrScalarRexSQWithAgg.add(subQueryRelNode);
}
if(scalarQueriesWithAggNoWinNoGby.contains(next)) {
scalarAggNoGbyNoWin.add(subQueryRelNode);
}
isSubQuery = true;
break;
default:
int childCount = next.getChildCount();
for(int i = childCount - 1; i >= 0; i--) {
stack.push((ASTNode) next.getChild(i));
}
}
}
return isSubQuery;
}
private RelNode genFilterRelNode(QB qb, ASTNode searchCond, RelNode srcRel,
Map aliasToRel, ImmutableMap outerNameToPosMap,
RowResolver outerRR, boolean forHavingClause) throws SemanticException {
Map subQueryToRelNode = new HashMap<>();
boolean isSubQuery = genSubQueryRelNode(qb, searchCond, srcRel, forHavingClause,
subQueryToRelNode);
if(isSubQuery) {
ExprNodeDesc subQueryExpr = genExprNodeDesc(searchCond, relToHiveRR.get(srcRel),
outerRR, subQueryToRelNode, forHavingClause);
ImmutableMap hiveColNameCalcitePosMap = this.relToHiveColNameCalcitePosMap
.get(srcRel);
RexNode convertedFilterLHS = new RexNodeConverter(cluster, srcRel.getRowType(),
outerNameToPosMap, hiveColNameCalcitePosMap, relToHiveRR.get(srcRel),
outerRR, 0, true, subqueryId).convert(subQueryExpr);
RelNode filterRel = new HiveFilter(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
srcRel, convertedFilterLHS);
this.relToHiveColNameCalcitePosMap.put(filterRel, this.relToHiveColNameCalcitePosMap
.get(srcRel));
relToHiveRR.put(filterRel, relToHiveRR.get(srcRel));
return filterRel;
} else {
return genFilterRelNode(searchCond, srcRel, outerNameToPosMap, outerRR, forHavingClause);
}
}
private RelNode projectLeftOuterSide(RelNode srcRel, int numColumns) throws SemanticException {
RowResolver iRR = relToHiveRR.get(srcRel);
RowResolver oRR = new RowResolver();
RowResolver.add(oRR, iRR, numColumns);
List calciteColLst = new ArrayList();
List oFieldNames = new ArrayList();
RelDataType iType = srcRel.getRowType();
for (int i = 0; i < iType.getFieldCount(); i++) {
RelDataTypeField fType = iType.getFieldList().get(i);
String fName = iType.getFieldNames().get(i);
calciteColLst.add(cluster.getRexBuilder().makeInputRef(fType.getType(), i));
oFieldNames.add(fName);
}
HiveRelNode selRel = HiveProject.create(srcRel, calciteColLst, oFieldNames);
this.relToHiveColNameCalcitePosMap.put(selRel, buildHiveToCalciteColumnMap(oRR, selRel));
this.relToHiveRR.put(selRel, oRR);
return selRel;
}
private RelNode genFilterLogicalPlan(QB qb, RelNode srcRel, Map aliasToRel,
ImmutableMap outerNameToPosMap, RowResolver outerRR,
boolean forHavingClause) throws SemanticException {
RelNode filterRel = null;
Iterator whereClauseIterator = getQBParseInfo(qb).getDestToWhereExpr().values()
.iterator();
if (whereClauseIterator.hasNext()) {
filterRel = genFilterRelNode(qb, (ASTNode) whereClauseIterator.next().getChild(0), srcRel,
aliasToRel, outerNameToPosMap, outerRR, forHavingClause);
}
return filterRel;
}
/**
* Class to store GenericUDAF related information.
*/
private class AggInfo {
private final List m_aggParams;
private final TypeInfo m_returnType;
private final String m_udfName;
private final boolean m_distinct;
private AggInfo(List aggParams, TypeInfo returnType, String udfName,
boolean isDistinct) {
m_aggParams = aggParams;
m_returnType = returnType;
m_udfName = udfName;
m_distinct = isDistinct;
}
}
private AggregateCall convertGBAgg(AggInfo agg, RelNode input, List gbChildProjLst,
RexNodeConverter converter, HashMap rexNodeToPosMap,
Integer childProjLstIndx) throws SemanticException {
// 1. Get agg fn ret type in Calcite
RelDataType aggFnRetType = TypeConverter.convert(agg.m_returnType,
this.cluster.getTypeFactory());
// 2. Convert Agg Fn args and type of args to Calcite
// TODO: Does HQL allows expressions as aggregate args or can it only be
// projections from child?
Integer inputIndx;
List argList = new ArrayList();
RexNode rexNd = null;
RelDataTypeFactory dtFactory = this.cluster.getTypeFactory();
ImmutableList.Builder aggArgRelDTBldr = new ImmutableList.Builder();
for (ExprNodeDesc expr : agg.m_aggParams) {
rexNd = converter.convert(expr);
inputIndx = rexNodeToPosMap.get(rexNd.toString());
if (inputIndx == null) {
gbChildProjLst.add(rexNd);
rexNodeToPosMap.put(rexNd.toString(), childProjLstIndx);
inputIndx = childProjLstIndx;
childProjLstIndx++;
}
argList.add(inputIndx);
// TODO: does arg need type cast?
aggArgRelDTBldr.add(TypeConverter.convert(expr.getTypeInfo(), dtFactory));
}
// 3. Get Aggregation FN from Calcite given name, ret type and input arg
// type
final SqlAggFunction aggregation = SqlFunctionConverter.getCalciteAggFn(agg.m_udfName, agg.m_distinct,
aggArgRelDTBldr.build(), aggFnRetType);
return new AggregateCall(aggregation, agg.m_distinct, argList, aggFnRetType, null);
}
private RelNode genGBRelNode(List gbExprs, List aggInfoLst,
List groupSets, RelNode srcRel) throws SemanticException {
ImmutableMap posMap = this.relToHiveColNameCalcitePosMap.get(srcRel);
RexNodeConverter converter = new RexNodeConverter(this.cluster, srcRel.getRowType(), posMap,
0, false);
final boolean hasGroupSets = groupSets != null && !groupSets.isEmpty();
final List gbChildProjLst = Lists.newArrayList();
final HashMap rexNodeToPosMap = new HashMap();
final List groupSetPositions = Lists.newArrayList();
Integer gbIndx = 0;
RexNode rnd;
for (ExprNodeDesc key : gbExprs) {
rnd = converter.convert(key);
gbChildProjLst.add(rnd);
groupSetPositions.add(gbIndx);
rexNodeToPosMap.put(rnd.toString(), gbIndx);
gbIndx++;
}
final ImmutableBitSet groupSet = ImmutableBitSet.of(groupSetPositions);
// Grouping sets: we need to transform them into ImmutableBitSet
// objects for Calcite
List transformedGroupSets = null;
if(hasGroupSets) {
Set setTransformedGroupSets =
new HashSet(groupSets.size());
for(long val: groupSets) {
setTransformedGroupSets.add(convert(val, groupSet.cardinality()));
}
// Calcite expects the grouping sets sorted and without duplicates
transformedGroupSets = new ArrayList(setTransformedGroupSets);
Collections.sort(transformedGroupSets, ImmutableBitSet.COMPARATOR);
}
List aggregateCalls = Lists.newArrayList();
for (AggInfo agg : aggInfoLst) {
aggregateCalls.add(convertGBAgg(agg, srcRel, gbChildProjLst, converter, rexNodeToPosMap,
gbChildProjLst.size()));
}
if (hasGroupSets) {
// Create GroupingID column
AggregateCall aggCall = AggregateCall.create(HiveGroupingID.INSTANCE,
false, new ImmutableList.Builder().build(), -1,
this.cluster.getTypeFactory().createSqlType(SqlTypeName.BIGINT),
HiveGroupingID.INSTANCE.getName());
aggregateCalls.add(aggCall);
}
if (gbChildProjLst.isEmpty()) {
// This will happen for count(*), in such cases we arbitarily pick
// first element from srcRel
gbChildProjLst.add(this.cluster.getRexBuilder().makeInputRef(srcRel, 0));
}
RelNode gbInputRel = HiveProject.create(srcRel, gbChildProjLst, null);
HiveRelNode aggregateRel = new HiveAggregate(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
gbInputRel, groupSet, transformedGroupSets, aggregateCalls);
return aggregateRel;
}
/* This method returns the flip big-endian representation of value */
private ImmutableBitSet convert(long value, int length) {
BitSet bits = new BitSet();
for (int index = length - 1; index >= 0; index--) {
if (value % 2 != 0) {
bits.set(index);
}
value = value >>> 1;
}
// We flip the bits because Calcite considers that '1'
// means that the column participates in the GroupBy
// and '0' does not, as opposed to grouping_id.
bits.flip(0, length);
return ImmutableBitSet.FROM_BIT_SET.apply(bits);
}
private void addAlternateGByKeyMappings(ASTNode gByExpr, ColumnInfo colInfo,
RowResolver gByInputRR, RowResolver gByRR) {
if (gByExpr.getType() == HiveParser.DOT
&& gByExpr.getChild(0).getType() == HiveParser.TOK_TABLE_OR_COL) {
String tab_alias = BaseSemanticAnalyzer.unescapeIdentifier(gByExpr.getChild(0).getChild(0)
.getText().toLowerCase());
String col_alias = BaseSemanticAnalyzer.unescapeIdentifier(gByExpr.getChild(1).getText().toLowerCase());
gByRR.put(tab_alias, col_alias, colInfo);
} else if (gByExpr.getType() == HiveParser.TOK_TABLE_OR_COL) {
String col_alias = BaseSemanticAnalyzer.unescapeIdentifier(gByExpr.getChild(0).getText().toLowerCase());
String tab_alias = null;
/*
* If the input to the GBy has a tab alias for the column, then add an
* entry based on that tab_alias. For e.g. this query: select b.x,
* count(*) from t1 b group by x needs (tab_alias=b, col_alias=x) in the
* GBy RR. tab_alias=b comes from looking at the RowResolver that is the
* ancestor before any GBy/ReduceSinks added for the GBY operation.
*/
try {
ColumnInfo pColInfo = gByInputRR.get(tab_alias, col_alias);
tab_alias = pColInfo == null ? null : pColInfo.getTabAlias();
} catch (SemanticException se) {
}
gByRR.put(tab_alias, col_alias, colInfo);
}
}
private void addToGBExpr(RowResolver groupByOutputRowResolver,
RowResolver groupByInputRowResolver, ASTNode grpbyExpr, ExprNodeDesc grpbyExprNDesc,
List gbExprNDescLst, List outputColumnNames) {
// TODO: Should we use grpbyExprNDesc.getTypeInfo()? what if expr is
// UDF
int i = gbExprNDescLst.size();
String field = SemanticAnalyzer.getColumnInternalName(i);
outputColumnNames.add(field);
gbExprNDescLst.add(grpbyExprNDesc);
ColumnInfo oColInfo = new ColumnInfo(field, grpbyExprNDesc.getTypeInfo(), null, false);
groupByOutputRowResolver.putExpression(grpbyExpr, oColInfo);
addAlternateGByKeyMappings(grpbyExpr, oColInfo, groupByInputRowResolver,
groupByOutputRowResolver);
}
private AggInfo getHiveAggInfo(ASTNode aggAst, int aggFnLstArgIndx, RowResolver inputRR)
throws SemanticException {
AggInfo aInfo = null;
// 1 Convert UDAF Params to ExprNodeDesc
ArrayList aggParameters = new ArrayList();
for (int i = 1; i <= aggFnLstArgIndx; i++) {
ASTNode paraExpr = (ASTNode) aggAst.getChild(i);
ExprNodeDesc paraExprNode = genExprNodeDesc(paraExpr, inputRR);
aggParameters.add(paraExprNode);
}
// 2. Is this distinct UDAF
boolean isDistinct = aggAst.getType() == HiveParser.TOK_FUNCTIONDI;
// 3. Determine type of UDAF
TypeInfo udafRetType = null;
// 3.1 Obtain UDAF name
String aggName = SemanticAnalyzer.unescapeIdentifier(aggAst.getChild(0).getText());
// 3.2 Rank functions type is 'int'/'double'
if (FunctionRegistry.isRankingFunction(aggName)) {
if (aggName.equalsIgnoreCase("percent_rank"))
udafRetType = TypeInfoFactory.doubleTypeInfo;
else
udafRetType = TypeInfoFactory.intTypeInfo;
} else {
// 3.3 Try obtaining UDAF evaluators to determine the ret type
try {
boolean isAllColumns = aggAst.getType() == HiveParser.TOK_FUNCTIONSTAR;
// 3.3.1 Get UDAF Evaluator
Mode amode = SemanticAnalyzer.groupByDescModeToUDAFMode(GroupByDesc.Mode.COMPLETE,
isDistinct);
GenericUDAFEvaluator genericUDAFEvaluator = null;
if (aggName.toLowerCase().equals(FunctionRegistry.LEAD_FUNC_NAME)
|| aggName.toLowerCase().equals(FunctionRegistry.LAG_FUNC_NAME)) {
ArrayList originalParameterTypeInfos = SemanticAnalyzer
.getWritableObjectInspector(aggParameters);
genericUDAFEvaluator = FunctionRegistry.getGenericWindowingEvaluator(aggName,
originalParameterTypeInfos, isDistinct, isAllColumns);
GenericUDAFInfo udaf = SemanticAnalyzer.getGenericUDAFInfo(genericUDAFEvaluator, amode,
aggParameters);
udafRetType = ((ListTypeInfo) udaf.returnType).getListElementTypeInfo();
} else {
genericUDAFEvaluator = SemanticAnalyzer.getGenericUDAFEvaluator(aggName, aggParameters,
aggAst, isDistinct, isAllColumns);
assert (genericUDAFEvaluator != null);
// 3.3.2 Get UDAF Info using UDAF Evaluator
GenericUDAFInfo udaf = SemanticAnalyzer.getGenericUDAFInfo(genericUDAFEvaluator, amode,
aggParameters);
if (FunctionRegistry.pivotResult(aggName)) {
udafRetType = ((ListTypeInfo)udaf.returnType).getListElementTypeInfo();
} else {
udafRetType = udaf.returnType;
}
}
} catch (Exception e) {
LOG.debug("CBO: Couldn't Obtain UDAF evaluators for " + aggName
+ ", trying to translate to GenericUDF");
}
// 3.4 Try GenericUDF translation
if (udafRetType == null) {
TypeCheckCtx tcCtx = new TypeCheckCtx(inputRR);
// We allow stateful functions in the SELECT list (but nowhere else)
tcCtx.setAllowStatefulFunctions(true);
tcCtx.setAllowDistinctFunctions(false);
ExprNodeDesc exp = genExprNodeDesc((ASTNode) aggAst.getChild(0), inputRR, tcCtx);
udafRetType = exp.getTypeInfo();
}
}
// 4. Construct AggInfo
aInfo = new AggInfo(aggParameters, udafRetType, aggName, isDistinct);
return aInfo;
}
/**
* Generate GB plan.
*
* @param qb
* @param srcRel
* @return TODO: 1. Grouping Sets (roll up..)
* @throws SemanticException
*/
private RelNode genGBLogicalPlan(QB qb, RelNode srcRel) throws SemanticException {
RelNode gbRel = null;
QBParseInfo qbp = getQBParseInfo(qb);
// 1. Gather GB Expressions (AST) (GB + Aggregations)
// NOTE: Multi Insert is not supported
String detsClauseName = qbp.getClauseNames().iterator().next();
// Check and transform group by *. This will only happen for select distinct *.
// Here the "genSelectPlan" is being leveraged.
// The main benefits are (1) remove virtual columns that should
// not be included in the group by; (2) add the fully qualified column names to unParseTranslator
// so that view is supported. The drawback is that an additional SEL op is added. If it is
// not necessary, it will be removed by NonBlockingOpDeDupProc Optimizer because it will match
// SEL%SEL% rule.
ASTNode selExprList = qb.getParseInfo().getSelForClause(detsClauseName);
SubQueryUtils.checkForTopLevelSubqueries(selExprList);
if (selExprList.getToken().getType() == HiveParser.TOK_SELECTDI
&& selExprList.getChildCount() == 1 && selExprList.getChild(0).getChildCount() == 1) {
ASTNode node = (ASTNode) selExprList.getChild(0).getChild(0);
if (node.getToken().getType() == HiveParser.TOK_ALLCOLREF) {
// As we said before, here we use genSelectLogicalPlan to rewrite AllColRef
srcRel = genSelectLogicalPlan(qb, srcRel, srcRel, null, null, true).getKey();
RowResolver rr = this.relToHiveRR.get(srcRel);
qbp.setSelExprForClause(detsClauseName, SemanticAnalyzer.genSelectDIAST(rr));
}
}
// Select DISTINCT + windowing; GBy handled by genSelectForWindowing
if (selExprList.getToken().getType() == HiveParser.TOK_SELECTDI &&
!qb.getAllWindowingSpecs().isEmpty()) {
return null;
}
List grpByAstExprs = getGroupByForClause(qbp, detsClauseName);
HashMap aggregationTrees = qbp.getAggregationExprsForClause(detsClauseName);
boolean hasGrpByAstExprs = (grpByAstExprs != null && !grpByAstExprs.isEmpty()) ? true : false;
boolean hasAggregationTrees = (aggregationTrees != null && !aggregationTrees.isEmpty()) ? true
: false;
final boolean cubeRollupGrpSetPresent = (!qbp.getDestRollups().isEmpty()
|| !qbp.getDestGroupingSets().isEmpty() || !qbp.getDestCubes().isEmpty());
// 2. Sanity check
if (conf.getBoolVar(HiveConf.ConfVars.HIVEGROUPBYSKEW)
&& qbp.getDistinctFuncExprsForClause(detsClauseName).size() > 1) {
throw new SemanticException(ErrorMsg.UNSUPPORTED_MULTIPLE_DISTINCTS.getMsg());
}
if (cubeRollupGrpSetPresent) {
if (!HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVEMAPSIDEAGGREGATE)) {
throw new SemanticException(ErrorMsg.HIVE_GROUPING_SETS_AGGR_NOMAPAGGR.getMsg());
}
if (conf.getBoolVar(HiveConf.ConfVars.HIVEGROUPBYSKEW)) {
checkExpressionsForGroupingSet(grpByAstExprs, qb.getParseInfo()
.getDistinctFuncExprsForClause(detsClauseName), aggregationTrees,
this.relToHiveRR.get(srcRel));
if (qbp.getDestGroupingSets().size() > conf
.getIntVar(HiveConf.ConfVars.HIVE_NEW_JOB_GROUPING_SET_CARDINALITY)) {
String errorMsg = "The number of rows per input row due to grouping sets is "
+ qbp.getDestGroupingSets().size();
throw new SemanticException(
ErrorMsg.HIVE_GROUPING_SETS_THRESHOLD_NOT_ALLOWED_WITH_SKEW.getMsg(errorMsg));
}
}
}
if (hasGrpByAstExprs || hasAggregationTrees) {
ArrayList gbExprNDescLst = new ArrayList();
ArrayList outputColumnNames = new ArrayList();
// 3. Input, Output Row Resolvers
RowResolver groupByInputRowResolver = this.relToHiveRR.get(srcRel);
RowResolver groupByOutputRowResolver = new RowResolver();
groupByOutputRowResolver.setIsExprResolver(true);
if (hasGrpByAstExprs) {
// 4. Construct GB Keys (ExprNode)
for (int i = 0; i < grpByAstExprs.size(); ++i) {
ASTNode grpbyExpr = grpByAstExprs.get(i);
Map astToExprNDescMap = genAllExprNodeDesc(grpbyExpr, groupByInputRowResolver);
ExprNodeDesc grpbyExprNDesc = astToExprNDescMap.get(grpbyExpr);
if (grpbyExprNDesc == null)
throw new CalciteSemanticException("Invalid Column Reference: " + grpbyExpr.dump(),
UnsupportedFeature.Invalid_column_reference);
addToGBExpr(groupByOutputRowResolver, groupByInputRowResolver, grpbyExpr,
grpbyExprNDesc, gbExprNDescLst, outputColumnNames);
}
}
// 5. GroupingSets, Cube, Rollup
int groupingColsSize = gbExprNDescLst.size();
List groupingSets = null;
if (cubeRollupGrpSetPresent) {
groupingSets = getGroupByGroupingSetsForClause(qbp, detsClauseName).getSecond();
}
// 6. Construct aggregation function Info
ArrayList aggregations = new ArrayList();
if (hasAggregationTrees) {
assert (aggregationTrees != null);
for (ASTNode value : aggregationTrees.values()) {
// 6.1 Determine type of UDAF
// This is the GenericUDAF name
String aggName = SemanticAnalyzer.unescapeIdentifier(value.getChild(0).getText());
boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
// 6.2 Convert UDAF Params to ExprNodeDesc
ArrayList aggParameters = new ArrayList();
for (int i = 1; i < value.getChildCount(); i++) {
ASTNode paraExpr = (ASTNode) value.getChild(i);
ExprNodeDesc paraExprNode = genExprNodeDesc(paraExpr, groupByInputRowResolver);
aggParameters.add(paraExprNode);
}
Mode amode = SemanticAnalyzer.groupByDescModeToUDAFMode(GroupByDesc.Mode.COMPLETE,
isDistinct);
GenericUDAFEvaluator genericUDAFEvaluator = SemanticAnalyzer.getGenericUDAFEvaluator(
aggName, aggParameters, value, isDistinct, isAllColumns);
assert (genericUDAFEvaluator != null);
GenericUDAFInfo udaf = SemanticAnalyzer.getGenericUDAFInfo(genericUDAFEvaluator, amode,
aggParameters);
AggInfo aInfo = new AggInfo(aggParameters, udaf.returnType, aggName, isDistinct);
aggregations.add(aInfo);
String field = getColumnInternalName(groupingColsSize + aggregations.size() - 1);
outputColumnNames.add(field);
groupByOutputRowResolver.putExpression(value, new ColumnInfo(field, aInfo.m_returnType,
"", false));
}
}
// 7. If GroupingSets, Cube, Rollup were used, we account grouping__id
if(groupingSets != null && !groupingSets.isEmpty()) {
String field = getColumnInternalName(groupingColsSize + aggregations.size());
outputColumnNames.add(field);
groupByOutputRowResolver.put(null, VirtualColumn.GROUPINGID.getName(),
new ColumnInfo(
field,
VirtualColumn.GROUPINGID.getTypeInfo(),
null,
true));
}
// 8. We create the group_by operator
gbRel = genGBRelNode(gbExprNDescLst, aggregations, groupingSets, srcRel);
relToHiveColNameCalcitePosMap.put(gbRel,
buildHiveToCalciteColumnMap(groupByOutputRowResolver, gbRel));
this.relToHiveRR.put(gbRel, groupByOutputRowResolver);
}
return gbRel;
}
/**
* Generate OB RelNode and input Select RelNode that should be used to
* introduce top constraining Project. If Input select RelNode is not
* present then don't introduce top constraining select.
*
* @param qb
* @param selPair
* @param outermostOB
* @return RelNode OB RelNode
* @throws SemanticException
*/
private RelNode genOBLogicalPlan(QB qb, Pair selPair,
boolean outermostOB) throws SemanticException {
// selPair.getKey() is the operator right before OB
// selPair.getValue() is RR which only contains columns needed in result
// set. Extra columns needed by order by will be absent from it.
RelNode srcRel = selPair.getKey();
RowResolver selectOutputRR = selPair.getValue();
RelNode sortRel = null;
RelNode returnRel = null;
QBParseInfo qbp = getQBParseInfo(qb);
String dest = qbp.getClauseNames().iterator().next();
ASTNode obAST = qbp.getOrderByForClause(dest);
if (obAST != null) {
// 1. OB Expr sanity test
// in strict mode, in the presence of order by, limit must be
// specified
Integer limit = qb.getParseInfo().getDestLimit(dest);
if (limit == null) {
String error = StrictChecks.checkNoLimit(conf);
if (error != null) {
throw new SemanticException(SemanticAnalyzer.generateErrorMessage(obAST, error));
}
}
// 2. Walk through OB exprs and extract field collations and additional
// virtual columns needed
final List newVCLst = new ArrayList();
final List fieldCollations = Lists.newArrayList();
int fieldIndex = 0;
List obASTExprLst = obAST.getChildren();
ASTNode obASTExpr;
ASTNode nullObASTExpr;
List> vcASTTypePairs = new ArrayList>();
RowResolver inputRR = relToHiveRR.get(srcRel);
RowResolver outputRR = new RowResolver();
RexNode rnd;
RexNodeConverter converter = new RexNodeConverter(cluster, srcRel.getRowType(),
relToHiveColNameCalcitePosMap.get(srcRel), 0, false);
int srcRelRecordSz = srcRel.getRowType().getFieldCount();
for (int i = 0; i < obASTExprLst.size(); i++) {
// 2.1 Convert AST Expr to ExprNode
obASTExpr = (ASTNode) obASTExprLst.get(i);
nullObASTExpr = (ASTNode) obASTExpr.getChild(0);
ASTNode ref = (ASTNode) nullObASTExpr.getChild(0);
Map astToExprNDescMap = null;
ExprNodeDesc obExprNDesc = null;
boolean isBothByPos = HiveConf.getBoolVar(conf, ConfVars.HIVE_GROUPBY_ORDERBY_POSITION_ALIAS);
boolean isObyByPos = isBothByPos
|| HiveConf.getBoolVar(conf, ConfVars.HIVE_ORDERBY_POSITION_ALIAS);
// replace each of the position alias in ORDERBY with the actual column
if (ref != null && ref.getToken().getType() == HiveParser.Number) {
if (isObyByPos) {
int pos = Integer.parseInt(ref.getText());
if (pos > 0 && pos <= selectOutputRR.getColumnInfos().size()) {
// fieldIndex becomes so simple
// Note that pos starts from 1 while fieldIndex starts from 0;
fieldIndex = pos - 1;
} else {
throw new SemanticException(
ErrorMsg.INVALID_POSITION_ALIAS_IN_ORDERBY.getMsg("Position alias: " + pos
+ " does not exist\n" + "The Select List is indexed from 1 to "
+ selectOutputRR.getColumnInfos().size()));
}
} else { // if not using position alias and it is a number.
LOG.warn("Using constant number "
+ ref.getText()
+ " in order by. If you try to use position alias when hive.orderby.position.alias is false, the position alias will be ignored.");
}
} else {
// first try to get it from select
// in case of udtf, selectOutputRR may be null.
if (selectOutputRR != null) {
try {
astToExprNDescMap = genAllExprNodeDesc(ref, selectOutputRR);
obExprNDesc = astToExprNDescMap.get(ref);
} catch (SemanticException ex) {
// we can tolerate this as this is the previous behavior
LOG.debug("Can not find column in " + ref.getText() + ". The error msg is "
+ ex.getMessage());
}
}
// then try to get it from all
if (obExprNDesc == null) {
astToExprNDescMap = genAllExprNodeDesc(ref, inputRR);
obExprNDesc = astToExprNDescMap.get(ref);
}
if (obExprNDesc == null) {
throw new SemanticException("Invalid order by expression: " + obASTExpr.toString());
}
// 2.2 Convert ExprNode to RexNode
rnd = converter.convert(obExprNDesc);
// 2.3 Determine the index of ob expr in child schema
// NOTE: Calcite can not take compound exprs in OB without it being
// present in the child (& hence we add a child Project Rel)
if (rnd instanceof RexInputRef) {
fieldIndex = ((RexInputRef) rnd).getIndex();
} else {
fieldIndex = srcRelRecordSz + newVCLst.size();
newVCLst.add(rnd);
vcASTTypePairs.add(new Pair(ref, obExprNDesc.getTypeInfo()));
}
}
// 2.4 Determine the Direction of order by
RelFieldCollation.Direction order = RelFieldCollation.Direction.DESCENDING;
if (obASTExpr.getType() == HiveParser.TOK_TABSORTCOLNAMEASC) {
order = RelFieldCollation.Direction.ASCENDING;
}
RelFieldCollation.NullDirection nullOrder;
if (nullObASTExpr.getType() == HiveParser.TOK_NULLS_FIRST) {
nullOrder = RelFieldCollation.NullDirection.FIRST;
} else if (nullObASTExpr.getType() == HiveParser.TOK_NULLS_LAST) {
nullOrder = RelFieldCollation.NullDirection.LAST;
} else {
throw new SemanticException("Unexpected null ordering option: "
+ nullObASTExpr.getType());
}
// 2.5 Add to field collations
fieldCollations.add(new RelFieldCollation(fieldIndex, order, nullOrder));
}
// 3. Add Child Project Rel if needed, Generate Output RR, input Sel Rel
// for top constraining Sel
RelNode obInputRel = srcRel;
if (!newVCLst.isEmpty()) {
List originalInputRefs = Lists.transform(srcRel.getRowType().getFieldList(),
new Function() {
@Override
public RexNode apply(RelDataTypeField input) {
return new RexInputRef(input.getIndex(), input.getType());
}
});
RowResolver obSyntheticProjectRR = new RowResolver();
if (!RowResolver.add(obSyntheticProjectRR, inputRR)) {
throw new CalciteSemanticException(
"Duplicates detected when adding columns to RR: see previous message",
UnsupportedFeature.Duplicates_in_RR);
}
int vcolPos = inputRR.getRowSchema().getSignature().size();
for (Pair astTypePair : vcASTTypePairs) {
obSyntheticProjectRR.putExpression(astTypePair.getKey(), new ColumnInfo(
SemanticAnalyzer.getColumnInternalName(vcolPos), astTypePair.getValue(), null,
false));
vcolPos++;
}
obInputRel = genSelectRelNode(CompositeList.of(originalInputRefs, newVCLst),
obSyntheticProjectRR, srcRel);
if (outermostOB) {
if (!RowResolver.add(outputRR, inputRR)) {
throw new CalciteSemanticException(
"Duplicates detected when adding columns to RR: see previous message",
UnsupportedFeature.Duplicates_in_RR);
}
} else {
if (!RowResolver.add(outputRR, obSyntheticProjectRR)) {
throw new CalciteSemanticException(
"Duplicates detected when adding columns to RR: see previous message",
UnsupportedFeature.Duplicates_in_RR);
}
}
} else {
if (!RowResolver.add(outputRR, inputRR)) {
throw new CalciteSemanticException(
"Duplicates detected when adding columns to RR: see previous message",
UnsupportedFeature.Duplicates_in_RR);
}
}
// 4. Construct SortRel
RelTraitSet traitSet = cluster.traitSetOf(HiveRelNode.CONVENTION);
RelCollation canonizedCollation = traitSet.canonize(RelCollationImpl.of(fieldCollations));
sortRel = new HiveSortLimit(cluster, traitSet, obInputRel, canonizedCollation, null, null);
// 5. Update the maps
// NOTE: Output RR for SortRel is considered same as its input; we may
// end up not using VC that is present in sort rel. Also note that
// rowtype of sortrel is the type of it child; if child happens to be
// synthetic project that we introduced then that projectrel would
// contain the vc.
ImmutableMap hiveColNameCalcitePosMap = buildHiveToCalciteColumnMap(
outputRR, sortRel);
relToHiveRR.put(sortRel, outputRR);
relToHiveColNameCalcitePosMap.put(sortRel, hiveColNameCalcitePosMap);
if (selectOutputRR != null) {
List originalInputRefs = Lists.transform(srcRel.getRowType().getFieldList(),
new Function() {
@Override
public RexNode apply(RelDataTypeField input) {
return new RexInputRef(input.getIndex(), input.getType());
}
});
List selectedRefs = Lists.newArrayList();
for (int index = 0; index < selectOutputRR.getColumnInfos().size(); index++) {
selectedRefs.add(originalInputRefs.get(index));
}
// We need to add select since order by schema may have more columns than result schema.
returnRel = genSelectRelNode(selectedRefs, selectOutputRR, sortRel);
} else {
returnRel = sortRel;
}
}
return returnRel;
}
private RelNode genLimitLogicalPlan(QB qb, RelNode srcRel) throws SemanticException {
HiveRelNode sortRel = null;
QBParseInfo qbp = getQBParseInfo(qb);
SimpleEntry entry =
qbp.getDestToLimit().get(qbp.getClauseNames().iterator().next());
Integer offset = (entry == null) ? 0 : entry.getKey();
Integer fetch = (entry == null) ? null : entry.getValue();
if (fetch != null) {
RexNode offsetRN = cluster.getRexBuilder().makeExactLiteral(BigDecimal.valueOf(offset));
RexNode fetchRN = cluster.getRexBuilder().makeExactLiteral(BigDecimal.valueOf(fetch));
RelTraitSet traitSet = cluster.traitSetOf(HiveRelNode.CONVENTION);
RelCollation canonizedCollation = traitSet.canonize(RelCollations.EMPTY);
sortRel = new HiveSortLimit(cluster, traitSet, srcRel, canonizedCollation, offsetRN, fetchRN);
RowResolver outputRR = new RowResolver();
if (!RowResolver.add(outputRR, relToHiveRR.get(srcRel))) {
throw new CalciteSemanticException(
"Duplicates detected when adding columns to RR: see previous message",
UnsupportedFeature.Duplicates_in_RR);
}
ImmutableMap hiveColNameCalcitePosMap = buildHiveToCalciteColumnMap(
outputRR, sortRel);
relToHiveRR.put(sortRel, outputRR);
relToHiveColNameCalcitePosMap.put(sortRel, hiveColNameCalcitePosMap);
}
return sortRel;
}
private List getPartitionKeys(PartitionSpec ps, RexNodeConverter converter,
RowResolver inputRR) throws SemanticException {
List pKeys = new ArrayList();
if (ps != null) {
List pExprs = ps.getExpressions();
for (PartitionExpression pExpr : pExprs) {
TypeCheckCtx tcCtx = new TypeCheckCtx(inputRR);
tcCtx.setAllowStatefulFunctions(true);
ExprNodeDesc exp = genExprNodeDesc(pExpr.getExpression(), inputRR, tcCtx);
pKeys.add(converter.convert(exp));
}
}
return pKeys;
}
private List getOrderKeys(OrderSpec os, RexNodeConverter converter,
RowResolver inputRR) throws SemanticException {
List oKeys = new ArrayList();
if (os != null) {
List oExprs = os.getExpressions();
for (OrderExpression oExpr : oExprs) {
TypeCheckCtx tcCtx = new TypeCheckCtx(inputRR);
tcCtx.setAllowStatefulFunctions(true);
ExprNodeDesc exp = genExprNodeDesc(oExpr.getExpression(), inputRR, tcCtx);
RexNode ordExp = converter.convert(exp);
Set flags = new HashSet();
if (oExpr.getOrder() == org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.Order.DESC) {
flags.add(SqlKind.DESCENDING);
}
if (oExpr.getNullOrder() == org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.NullOrder.NULLS_FIRST) {
flags.add(SqlKind.NULLS_FIRST);
} else if (oExpr.getNullOrder() == org.apache.hadoop.hive.ql.parse.PTFInvocationSpec.NullOrder.NULLS_LAST) {
flags.add(SqlKind.NULLS_LAST);
} else {
throw new SemanticException(
"Unexpected null ordering option: " + oExpr.getNullOrder());
}
oKeys.add(new RexFieldCollation(ordExp, flags));
}
}
return oKeys;
}
private RexWindowBound getBound(BoundarySpec bs, RexNodeConverter converter) {
RexWindowBound rwb = null;
if (bs != null) {
SqlParserPos pos = new SqlParserPos(1, 1);
SqlNode amt = bs.getAmt() == 0 ? null : SqlLiteral.createExactNumeric(
String.valueOf(bs.getAmt()), new SqlParserPos(2, 2));
RexNode amtLiteral = null;
SqlCall sc = null;
if (amt != null)
amtLiteral = cluster.getRexBuilder().makeLiteral(new Integer(bs.getAmt()),
cluster.getTypeFactory().createSqlType(SqlTypeName.INTEGER), true);
switch (bs.getDirection()) {
case PRECEDING:
if (amt == null) {
rwb = RexWindowBound.create(SqlWindow.createUnboundedPreceding(pos), null);
} else {
sc = (SqlCall) SqlWindow.createPreceding(amt, pos);
rwb = RexWindowBound.create(sc,
cluster.getRexBuilder().makeCall(sc.getOperator(), amtLiteral));
}
break;
case CURRENT:
rwb = RexWindowBound.create(SqlWindow.createCurrentRow(new SqlParserPos(1, 1)), null);
break;
case FOLLOWING:
if (amt == null) {
rwb = RexWindowBound.create(SqlWindow.createUnboundedFollowing(new SqlParserPos(1, 1)),
null);
} else {
sc = (SqlCall) SqlWindow.createFollowing(amt, pos);
rwb = RexWindowBound.create(sc,
cluster.getRexBuilder().makeCall(sc.getOperator(), amtLiteral));
}
break;
}
}
return rwb;
}
private int getWindowSpecIndx(ASTNode wndAST) {
int wi = wndAST.getChildCount() - 1;
if (wi <= 0 || (wndAST.getChild(wi).getType() != HiveParser.TOK_WINDOWSPEC)) {
wi = -1;
}
return wi;
}
private Pair genWindowingProj(QB qb, WindowExpressionSpec wExpSpec,
RelNode srcRel) throws SemanticException {
RexNode w = null;
TypeInfo wHiveRetType = null;
if (wExpSpec instanceof WindowFunctionSpec) {
WindowFunctionSpec wFnSpec = (WindowFunctionSpec) wExpSpec;
ASTNode windowProjAst = wFnSpec.getExpression();
// TODO: do we need to get to child?
int wndSpecASTIndx = getWindowSpecIndx(windowProjAst);
// 2. Get Hive Aggregate Info
AggInfo hiveAggInfo = getHiveAggInfo(windowProjAst, wndSpecASTIndx - 1,
this.relToHiveRR.get(srcRel));
// 3. Get Calcite Return type for Agg Fn
wHiveRetType = hiveAggInfo.m_returnType;
RelDataType calciteAggFnRetType = TypeConverter.convert(hiveAggInfo.m_returnType,
this.cluster.getTypeFactory());
// 4. Convert Agg Fn args to Calcite
ImmutableMap posMap = this.relToHiveColNameCalcitePosMap.get(srcRel);
RexNodeConverter converter = new RexNodeConverter(this.cluster, srcRel.getRowType(),
posMap, 0, false);
Builder calciteAggFnArgsBldr = ImmutableList. builder();
Builder calciteAggFnArgsTypeBldr = ImmutableList. builder();
for (int i = 0; i < hiveAggInfo.m_aggParams.size(); i++) {
calciteAggFnArgsBldr.add(converter.convert(hiveAggInfo.m_aggParams.get(i)));
calciteAggFnArgsTypeBldr.add(TypeConverter.convert(hiveAggInfo.m_aggParams.get(i)
.getTypeInfo(), this.cluster.getTypeFactory()));
}
ImmutableList calciteAggFnArgs = calciteAggFnArgsBldr.build();
ImmutableList calciteAggFnArgsType = calciteAggFnArgsTypeBldr.build();
// 5. Get Calcite Agg Fn
final SqlAggFunction calciteAggFn = SqlFunctionConverter.getCalciteAggFn(
hiveAggInfo.m_udfName, hiveAggInfo.m_distinct, calciteAggFnArgsType, calciteAggFnRetType);
// 6. Translate Window spec
RowResolver inputRR = relToHiveRR.get(srcRel);
WindowSpec wndSpec = ((WindowFunctionSpec) wExpSpec).getWindowSpec();
List partitionKeys = getPartitionKeys(wndSpec.getPartition(), converter, inputRR);
List orderKeys = getOrderKeys(wndSpec.getOrder(), converter, inputRR);
RexWindowBound upperBound = getBound(wndSpec.getWindowFrame().getStart(), converter);
RexWindowBound lowerBound = getBound(wndSpec.getWindowFrame().getEnd(), converter);
boolean isRows = wndSpec.getWindowFrame().getWindowType() == WindowType.ROWS;
w = cluster.getRexBuilder().makeOver(calciteAggFnRetType, calciteAggFn, calciteAggFnArgs,
partitionKeys, ImmutableList. copyOf(orderKeys), lowerBound,
upperBound, isRows, true, false, hiveAggInfo.m_distinct);
} else {
// TODO: Convert to Semantic Exception
throw new RuntimeException("Unsupported window Spec");
}
return new Pair(w, wHiveRetType);
}
private RelNode genSelectForWindowing(QB qb, RelNode srcRel, HashSet newColumns)
throws SemanticException {
getQBParseInfo(qb);
WindowingSpec wSpec = (!qb.getAllWindowingSpecs().isEmpty()) ? qb.getAllWindowingSpecs()
.values().iterator().next() : null;
if (wSpec == null)
return null;
// 1. Get valid Window Function Spec
wSpec.validateAndMakeEffective();
List windowExpressions = wSpec.getWindowExpressions();
if (windowExpressions == null || windowExpressions.isEmpty())
return null;
RowResolver inputRR = this.relToHiveRR.get(srcRel);
// 2. Get RexNodes for original Projections from below
List projsForWindowSelOp = new ArrayList(
HiveCalciteUtil.getProjsFromBelowAsInputRef(srcRel));
// 3. Construct new Row Resolver with everything from below.
RowResolver out_rwsch = new RowResolver();
if (!RowResolver.add(out_rwsch, inputRR)) {
LOG.warn("Duplicates detected when adding columns to RR: see previous message");
}
// 4. Walk through Window Expressions & Construct RexNodes for those,
// Update out_rwsch
final QBParseInfo qbp = getQBParseInfo(qb);
final String selClauseName = qbp.getClauseNames().iterator().next();
final boolean cubeRollupGrpSetPresent = (!qbp.getDestRollups().isEmpty()
|| !qbp.getDestGroupingSets().isEmpty() || !qbp.getDestCubes().isEmpty());
for (WindowExpressionSpec wExprSpec : windowExpressions) {
if (!qbp.getDestToGroupBy().isEmpty()) {
// Special handling of grouping function
wExprSpec.setExpression(rewriteGroupingFunctionAST(
getGroupByForClause(qbp, selClauseName), wExprSpec.getExpression(),
!cubeRollupGrpSetPresent));
}
if (out_rwsch.getExpression(wExprSpec.getExpression()) == null) {
Pair wtp = genWindowingProj(qb, wExprSpec, srcRel);
projsForWindowSelOp.add(wtp.getKey());
// 6.2.2 Update Output Row Schema
ColumnInfo oColInfo = new ColumnInfo(
SemanticAnalyzer.getColumnInternalName(projsForWindowSelOp.size()), wtp.getValue(),
null, false);
out_rwsch.putExpression(wExprSpec.getExpression(), oColInfo);
newColumns.add(oColInfo);
}
}
return genSelectRelNode(projsForWindowSelOp, out_rwsch, srcRel, windowExpressions);
}
private RelNode genSelectRelNode(List calciteColLst, RowResolver out_rwsch,
RelNode srcRel) throws CalciteSemanticException {
return genSelectRelNode(calciteColLst, out_rwsch, srcRel, null);
}
private RelNode genSelectRelNode(List calciteColLst, RowResolver out_rwsch,
RelNode srcRel, List windowExpressions) throws CalciteSemanticException {
// 1. Build Column Names
Set colNamesSet = new HashSet();
List cInfoLst = out_rwsch.getRowSchema().getSignature();
ArrayList columnNames = new ArrayList();
Map windowToAlias = null;
if (windowExpressions != null ) {
windowToAlias = new HashMap();
for (WindowExpressionSpec wes : windowExpressions) {
windowToAlias.put(wes.getExpression().toStringTree().toLowerCase(), wes.getAlias());
}
}
String[] qualifiedColNames;
String tmpColAlias;
for (int i = 0; i < calciteColLst.size(); i++) {
ColumnInfo cInfo = cInfoLst.get(i);
qualifiedColNames = out_rwsch.reverseLookup(cInfo.getInternalName());
/*
* if (qualifiedColNames[0] != null && !qualifiedColNames[0].isEmpty())
* tmpColAlias = qualifiedColNames[0] + "." + qualifiedColNames[1]; else
*/
tmpColAlias = qualifiedColNames[1];
if (tmpColAlias.contains(".") || tmpColAlias.contains(":")) {
tmpColAlias = cInfo.getInternalName();
}
// Prepend column names with '_o_' if it starts with '_c'
/*
* Hive treats names that start with '_c' as internalNames; so change
* the names so we don't run into this issue when converting back to
* Hive AST.
*/
if (tmpColAlias.startsWith("_c")) {
tmpColAlias = "_o_" + tmpColAlias;
} else if (windowToAlias != null && windowToAlias.containsKey(tmpColAlias)) {
tmpColAlias = windowToAlias.get(tmpColAlias);
}
int suffix = 1;
while (colNamesSet.contains(tmpColAlias)) {
tmpColAlias = qualifiedColNames[1] + suffix;
suffix++;
}
colNamesSet.add(tmpColAlias);
columnNames.add(tmpColAlias);
}
// 3 Build Calcite Rel Node for project using converted projections & col
// names
HiveRelNode selRel = HiveProject.create(srcRel, calciteColLst, columnNames);
// 4. Keep track of colname-to-posmap && RR for new select
this.relToHiveColNameCalcitePosMap
.put(selRel, buildHiveToCalciteColumnMap(out_rwsch, selRel));
this.relToHiveRR.put(selRel, out_rwsch);
return selRel;
}
private void setQueryHints(QB qb) throws SemanticException {
QBParseInfo qbp = getQBParseInfo(qb);
String selClauseName = qbp.getClauseNames().iterator().next();
Tree selExpr0 = qbp.getSelForClause(selClauseName).getChild(0);
if (selExpr0.getType() != HiveParser.QUERY_HINT) return;
String hint = ctx.getTokenRewriteStream().toString(
selExpr0.getTokenStartIndex(), selExpr0.getTokenStopIndex());
LOG.debug("Handling query hints: " + hint);
ParseDriver pd = new ParseDriver();
try {
ASTNode hintNode = pd.parseHint(hint);
qbp.setHints(hintNode);
} catch (ParseException e) {
throw new SemanticException("failed to parse query hint: "+e.getMessage(), e);
}
}
/**
* NOTE: there can only be one select caluse since we don't handle multi
* destination insert.
*
* @throws SemanticException
*/
/**
* @param qb
* @param srcRel
* @param starSrcRel
* @param outerNameToPosMap
* @param outerRR
* @param isAllColRefRewrite
* when it is true, it means that it is called from group by *, where we use
* genSelectLogicalPlan to rewrite *
* @return RelNode: the select relnode RowResolver: i.e., originalRR, the RR after select when there is an order by.
* @throws SemanticException
*/
private Pair genSelectLogicalPlan(QB qb, RelNode srcRel, RelNode starSrcRel,
ImmutableMap outerNameToPosMap, RowResolver outerRR, boolean isAllColRefRewrite)
throws SemanticException {
// 0. Generate a Select Node for Windowing
// Exclude the newly-generated select columns from */etc. resolution.
HashSet excludedColumns = new HashSet();
RelNode selForWindow = genSelectForWindowing(qb, srcRel, excludedColumns);
srcRel = (selForWindow == null) ? srcRel : selForWindow;
ArrayList col_list = new ArrayList();
// 1. Get Select Expression List
QBParseInfo qbp = getQBParseInfo(qb);
String selClauseName = qbp.getClauseNames().iterator().next();
ASTNode selExprList = qbp.getSelForClause(selClauseName);
// make sure if there is subquery it is top level expression
SubQueryUtils.checkForTopLevelSubqueries(selExprList);
final boolean cubeRollupGrpSetPresent = (!qbp.getDestRollups().isEmpty()
|| !qbp.getDestGroupingSets().isEmpty() || !qbp.getDestCubes().isEmpty());
// 2.Row resolvers for input, output
RowResolver out_rwsch = new RowResolver();
Integer pos = Integer.valueOf(0);
// TODO: will this also fix windowing? try
RowResolver inputRR = this.relToHiveRR.get(srcRel), starRR = inputRR;
if (starSrcRel != null) {
starRR = this.relToHiveRR.get(starSrcRel);
}
// 3. Query Hints
// TODO: Handle Query Hints; currently we ignore them
boolean selectStar = false;
int posn = 0;
boolean hintPresent = (selExprList.getChild(0).getType() == HiveParser.QUERY_HINT);
if (hintPresent) {
posn++;
}
// 4. Bailout if select involves Transform
boolean isInTransform = (selExprList.getChild(posn).getChild(0).getType() == HiveParser.TOK_TRANSFORM);
if (isInTransform) {
String msg = String.format("SELECT TRANSFORM is currently not supported in CBO,"
+ " turn off cbo to use TRANSFORM.");
LOG.debug(msg);
throw new CalciteSemanticException(msg, UnsupportedFeature.Select_transform);
}
// 5. Check if select involves UDTF
String udtfTableAlias = null;
GenericUDTF genericUDTF = null;
String genericUDTFName = null;
ArrayList udtfColAliases = new ArrayList();
ASTNode expr = (ASTNode) selExprList.getChild(posn).getChild(0);
int exprType = expr.getType();
if (exprType == HiveParser.TOK_FUNCTION || exprType == HiveParser.TOK_FUNCTIONSTAR) {
String funcName = TypeCheckProcFactory.DefaultExprProcessor.getFunctionText(expr, true);
FunctionInfo fi = FunctionRegistry.getFunctionInfo(funcName);
if (fi != null && fi.getGenericUDTF() != null) {
LOG.debug("Find UDTF " + funcName);
genericUDTF = fi.getGenericUDTF();
genericUDTFName = funcName;
if (!fi.isNative()) {
unparseTranslator.addIdentifierTranslation((ASTNode) expr.getChild(0));
}
if (genericUDTF != null && (selectStar = exprType == HiveParser.TOK_FUNCTIONSTAR)) {
genColListRegex(".*", null, (ASTNode) expr.getChild(0),
col_list, null, inputRR, starRR, pos, out_rwsch, qb.getAliases(), false);
}
}
}
if (genericUDTF != null) {
// Only support a single expression when it's a UDTF
if (selExprList.getChildCount() > 1) {
throw new SemanticException(generateErrorMessage(
(ASTNode) selExprList.getChild(1),
ErrorMsg.UDTF_MULTIPLE_EXPR.getMsg()));
}
ASTNode selExpr = (ASTNode) selExprList.getChild(posn);
// Get the column / table aliases from the expression. Start from 1 as
// 0 is the TOK_FUNCTION
// column names also can be inferred from result of UDTF
for (int i = 1; i < selExpr.getChildCount(); i++) {
ASTNode selExprChild = (ASTNode) selExpr.getChild(i);
switch (selExprChild.getType()) {
case HiveParser.Identifier:
udtfColAliases.add(unescapeIdentifier(selExprChild.getText().toLowerCase()));
unparseTranslator.addIdentifierTranslation(selExprChild);
break;
case HiveParser.TOK_TABALIAS:
assert (selExprChild.getChildCount() == 1);
udtfTableAlias = unescapeIdentifier(selExprChild.getChild(0)
.getText());
qb.addAlias(udtfTableAlias);
unparseTranslator.addIdentifierTranslation((ASTNode) selExprChild
.getChild(0));
break;
default:
throw new SemanticException("Find invalid token type " + selExprChild.getType()
+ " in UDTF.");
}
}
LOG.debug("UDTF table alias is " + udtfTableAlias);
LOG.debug("UDTF col aliases are " + udtfColAliases);
}
// 6. Iterate over all expression (after SELECT)
ASTNode exprList;
if (genericUDTF != null) {
exprList = expr;
} else {
exprList = selExprList;
}
// For UDTF's, skip the function name to get the expressions
int startPosn = genericUDTF != null ? posn + 1 : posn;
for (int i = startPosn; i < exprList.getChildCount(); ++i) {
// 6.1 child can be EXPR AS ALIAS, or EXPR.
ASTNode child = (ASTNode) exprList.getChild(i);
boolean hasAsClause = (!isInTransform) && (child.getChildCount() == 2);
// 6.2 EXPR AS (ALIAS,...) parses, but is only allowed for UDTF's
// This check is not needed and invalid when there is a transform b/c
// the
// AST's are slightly different.
if (genericUDTF == null && child.getChildCount() > 2) {
throw new SemanticException(SemanticAnalyzer.generateErrorMessage(
(ASTNode) child.getChild(2), ErrorMsg.INVALID_AS.getMsg()));
}
String tabAlias;
String colAlias;
if (genericUDTF != null) {
tabAlias = null;
colAlias = getAutogenColAliasPrfxLbl() + i;
expr = child;
} else {
// 6.3 Get rid of TOK_SELEXPR
expr = (ASTNode) child.getChild(0);
String[] colRef = SemanticAnalyzer.getColAlias(child, getAutogenColAliasPrfxLbl(),
inputRR, autogenColAliasPrfxIncludeFuncName(), i);
tabAlias = colRef[0];
colAlias = colRef[1];
if (hasAsClause) {
unparseTranslator.addIdentifierTranslation((ASTNode) child
.getChild(1));
}
}
Map subQueryToRelNode = new HashMap<>();
boolean isSubQuery = genSubQueryRelNode(qb, expr, srcRel, false,
subQueryToRelNode);
if(isSubQuery) {
ExprNodeDesc subQueryExpr = genExprNodeDesc(expr, relToHiveRR.get(srcRel),
outerRR, subQueryToRelNode, true);
col_list.add(subQueryExpr);
ColumnInfo colInfo = new ColumnInfo(SemanticAnalyzer.getColumnInternalName(pos),
subQueryExpr.getWritableObjectInspector(), tabAlias, false);
if (!out_rwsch.putWithCheck(tabAlias, colAlias, null, colInfo)) {
throw new CalciteSemanticException("Cannot add column to RR: " + tabAlias + "."
+ colAlias + " => " + colInfo + " due to duplication, see previous warnings",
UnsupportedFeature.Duplicates_in_RR);
}
pos = Integer.valueOf(pos.intValue() + 1);
} else {
// 6.4 Build ExprNode corresponding to colums
if (expr.getType() == HiveParser.TOK_ALLCOLREF) {
pos = genColListRegex(".*", expr.getChildCount() == 0 ? null : SemanticAnalyzer
.getUnescapedName((ASTNode) expr.getChild(0)).toLowerCase(), expr, col_list,
excludedColumns, inputRR, starRR, pos, out_rwsch, qb.getAliases(), true);
selectStar = true;
} else if (expr.getType() == HiveParser.TOK_TABLE_OR_COL
&& !hasAsClause
&& !inputRR.getIsExprResolver()
&& SemanticAnalyzer.isRegex(
SemanticAnalyzer.unescapeIdentifier(expr.getChild(0).getText()), conf)) {
// In case the expression is a regex COL.
// This can only happen without AS clause
// We don't allow this for ExprResolver - the Group By case
pos = genColListRegex(SemanticAnalyzer.unescapeIdentifier(expr.getChild(0).getText()),
null, expr, col_list, excludedColumns, inputRR, starRR, pos, out_rwsch,
qb.getAliases(), true);
} else if (expr.getType() == HiveParser.DOT
&& expr.getChild(0).getType() == HiveParser.TOK_TABLE_OR_COL
&& inputRR.hasTableAlias(SemanticAnalyzer.unescapeIdentifier(expr.getChild(0)
.getChild(0).getText().toLowerCase()))
&& !hasAsClause
&& !inputRR.getIsExprResolver()
&& SemanticAnalyzer.isRegex(
SemanticAnalyzer.unescapeIdentifier(expr.getChild(1).getText()), conf)) {
// In case the expression is TABLE.COL (col can be regex).
// This can only happen without AS clause
// We don't allow this for ExprResolver - the Group By case
pos = genColListRegex(
SemanticAnalyzer.unescapeIdentifier(expr.getChild(1).getText()),
SemanticAnalyzer.unescapeIdentifier(expr.getChild(0).getChild(0).getText()
.toLowerCase()), expr, col_list, excludedColumns, inputRR, starRR, pos,
out_rwsch, qb.getAliases(), true);
} else if (ParseUtils.containsTokenOfType(expr, HiveParser.TOK_FUNCTIONDI)
&& !(srcRel instanceof HiveAggregate)) {
// Likely a malformed query eg, select hash(distinct c1) from t1;
throw new CalciteSemanticException("Distinct without an aggregation.",
UnsupportedFeature.Distinct_without_an_aggreggation);
} else {
// Case when this is an expression
TypeCheckCtx tcCtx = new TypeCheckCtx(inputRR);
// We allow stateful functions in the SELECT list (but nowhere else)
tcCtx.setAllowStatefulFunctions(true);
if (!qbp.getDestToGroupBy().isEmpty()) {
// Special handling of grouping function
expr = rewriteGroupingFunctionAST(getGroupByForClause(qbp, selClauseName), expr,
!cubeRollupGrpSetPresent);
}
ExprNodeDesc exp = genExprNodeDesc(expr, inputRR, tcCtx);
String recommended = recommendName(exp, colAlias);
if (recommended != null && out_rwsch.get(null, recommended) == null) {
colAlias = recommended;
}
col_list.add(exp);
ColumnInfo colInfo = new ColumnInfo(SemanticAnalyzer.getColumnInternalName(pos),
exp.getWritableObjectInspector(), tabAlias, false);
colInfo.setSkewedCol((exp instanceof ExprNodeColumnDesc) ? ((ExprNodeColumnDesc) exp)
.isSkewedCol() : false);
if (!out_rwsch.putWithCheck(tabAlias, colAlias, null, colInfo)) {
throw new CalciteSemanticException("Cannot add column to RR: " + tabAlias + "."
+ colAlias + " => " + colInfo + " due to duplication, see previous warnings",
UnsupportedFeature.Duplicates_in_RR);
}
pos = Integer.valueOf(pos.intValue() + 1);
}
}
}
selectStar = selectStar && exprList.getChildCount() == posn + 1;
// 7. Convert Hive projections to Calcite
List calciteColLst = new ArrayList();
RexNodeConverter rexNodeConv = new RexNodeConverter(cluster, srcRel.getRowType(),
outerNameToPosMap, buildHiveColNameToInputPosMap(col_list, inputRR), relToHiveRR.get(srcRel),
outerRR, 0, false, subqueryId);
for (ExprNodeDesc colExpr : col_list) {
calciteColLst.add(rexNodeConv.convert(colExpr));
}
// 8. Build Calcite Rel
RelNode outputRel = null;
if (genericUDTF != null) {
// The basic idea for CBO support of UDTF is to treat UDTF as a special
// project.
// In AST return path, as we just need to generate a SEL_EXPR, we just
// need to remember the expressions and the alias.
// In OP return path, we need to generate a SEL and then a UDTF
// following old semantic analyzer.
outputRel = genUDTFPlan(genericUDTF, genericUDTFName, udtfTableAlias, udtfColAliases, qb,
calciteColLst, out_rwsch, srcRel);
} else {
String dest = qbp.getClauseNames().iterator().next();
ASTNode obAST = qbp.getOrderByForClause(dest);
RowResolver originalRR = null;
// We only support limited unselected column following by order by.
// TODO: support unselected columns in genericUDTF and windowing functions.
// We examine the order by in this query block and adds in column needed
// by order by in select list.
if (obAST != null && !(selForWindow != null && selExprList.getToken().getType() == HiveParser.TOK_SELECTDI) && !isAllColRefRewrite) {
// 1. OB Expr sanity test
// in strict mode, in the presence of order by, limit must be
// specified
Integer limit = qb.getParseInfo().getDestLimit(dest);
if (limit == null) {
String error = StrictChecks.checkNoLimit(conf);
if (error != null) {
throw new SemanticException(SemanticAnalyzer.generateErrorMessage(obAST, error));
}
}
List originalInputRefs = Lists.transform(srcRel.getRowType().getFieldList(),
new Function() {
@Override
public RexNode apply(RelDataTypeField input) {
return new RexInputRef(input.getIndex(), input.getType());
}
});
originalRR = out_rwsch.duplicate();
for (int i = 0; i < inputRR.getColumnInfos().size(); i++) {
ColumnInfo colInfo = new ColumnInfo(inputRR.getColumnInfos().get(i));
String internalName = SemanticAnalyzer.getColumnInternalName(out_rwsch.getColumnInfos()
.size() + i);
colInfo.setInternalName(internalName);
// if there is any confict, then we do not generate it in the new select
// otherwise, we add it into the calciteColLst and generate the new select
if (!out_rwsch.putWithCheck(colInfo.getTabAlias(), colInfo.getAlias(), internalName,
colInfo)) {
LOG.trace("Column already present in RR. skipping.");
} else {
calciteColLst.add(originalInputRefs.get(i));
}
}
outputRel = genSelectRelNode(calciteColLst, out_rwsch, srcRel);
// outputRel is the generated augmented select with extra unselected
// columns, and originalRR is the original generated select
return new Pair(outputRel, originalRR);
} else {
outputRel = genSelectRelNode(calciteColLst, out_rwsch, srcRel);
}
}
// 9. Handle select distinct as GBY if there exist windowing functions
if (selForWindow != null && selExprList.getToken().getType() == HiveParser.TOK_SELECTDI) {
ImmutableBitSet groupSet = ImmutableBitSet.range(outputRel.getRowType().getFieldList().size());
outputRel = new HiveAggregate(cluster, cluster.traitSetOf(HiveRelNode.CONVENTION),
outputRel, groupSet, null, new ArrayList());
RowResolver groupByOutputRowResolver = new RowResolver();
for (int i = 0; i < out_rwsch.getColumnInfos().size(); i++) {
ColumnInfo colInfo = out_rwsch.getColumnInfos().get(i);
ColumnInfo newColInfo = new ColumnInfo(colInfo.getInternalName(),
colInfo.getType(), colInfo.getTabAlias(), colInfo.getIsVirtualCol());
groupByOutputRowResolver.put(colInfo.getTabAlias(), colInfo.getAlias(), newColInfo);
}
relToHiveColNameCalcitePosMap.put(outputRel,
buildHiveToCalciteColumnMap(groupByOutputRowResolver, outputRel));
this.relToHiveRR.put(outputRel, groupByOutputRowResolver);
}
return new Pair(outputRel, null);
}
private RelNode genUDTFPlan(GenericUDTF genericUDTF, String genericUDTFName, String outputTableAlias,
ArrayList 