org.apache.hadoop.hive.ql.optimizer.SemiJoinReductionMerge Maven / Gradle / Ivy
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package org.apache.hadoop.hive.ql.optimizer;
import com.google.common.base.Preconditions;
import org.apache.hadoop.hive.conf.HiveConf;
import org.apache.hadoop.hive.ql.exec.ColumnInfo;
import org.apache.hadoop.hive.ql.exec.FilterOperator;
import org.apache.hadoop.hive.ql.exec.FunctionUtils;
import org.apache.hadoop.hive.ql.exec.GroupByOperator;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.OperatorFactory;
import org.apache.hadoop.hive.ql.exec.OperatorUtils;
import org.apache.hadoop.hive.ql.exec.ReduceSinkOperator;
import org.apache.hadoop.hive.ql.exec.RowSchema;
import org.apache.hadoop.hive.ql.exec.SelectOperator;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.io.AcidUtils;
import org.apache.hadoop.hive.ql.parse.GenTezUtils;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.RuntimeValuesInfo;
import org.apache.hadoop.hive.ql.parse.SemanticAnalyzer;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.parse.SemiJoinBranchInfo;
import org.apache.hadoop.hive.ql.plan.AggregationDesc;
import org.apache.hadoop.hive.ql.plan.DynamicValue;
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.ExprNodeDynamicValueDesc;
import org.apache.hadoop.hive.ql.plan.ExprNodeGenericFuncDesc;
import org.apache.hadoop.hive.ql.plan.FilterDesc;
import org.apache.hadoop.hive.ql.plan.GroupByDesc;
import org.apache.hadoop.hive.ql.plan.PlanUtils;
import org.apache.hadoop.hive.ql.plan.ReduceSinkDesc;
import org.apache.hadoop.hive.ql.plan.SelectDesc;
import org.apache.hadoop.hive.ql.plan.TableDesc;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFEvaluator;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFMax;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDAFMin;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFBetween;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFInBloomFilter;
import org.apache.hadoop.hive.ql.util.NullOrdering;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfo;
import org.apache.hadoop.hive.serde2.typeinfo.TypeInfoFactory;
import java.util.ArrayDeque;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.Collection;
import java.util.Collections;
import java.util.Deque;
import java.util.EnumSet;
import java.util.HashMap;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.Map.Entry;
import static com.google.common.base.Preconditions.checkState;
import static org.apache.hadoop.hive.ql.exec.FunctionRegistry.BLOOM_FILTER_FUNCTION;
import static org.apache.hadoop.hive.ql.plan.ExprNodeDescUtils.and;
/**
* A transformation that merges multiple single-column semi join reducers to one multi-column semi join reducer.
*
* Semi join reducers are comprised from two parts:
*
* - Filter creation from the source relation and broadcast: SOURCE - SEL - GB1 - RS1 - GB2 - RS2
* - Filter application on the target relation: TS - FIL[in_bloom(col)]
*
*
* An example of the transformation on three single column semi join reducers is shown below. The plan is simplified for
* presentation purposes.
*
BEFORE:
*
* / SEL[fname] - GB1 - RS1 - GB2 - RS2 \
* SOURCE - SEL[lname] - GB1 - RS1 - GB2 - RS2 -> TS[Author] - FIL[in_bloom(fname) ^ in_bloom(lname) ^ in_bloom(age)]
* \ SEL[age] - GB1 - RS1 - GB2 - RS2 /
*
* AFTER:
*
* SOURCE - SEL[fname, lname, age] - GB1 - RS1 - GB2 - RS2 -> TS[Author] - FIL[in_bloom(hash(fname,lname,age)]
*
*/
public class SemiJoinReductionMerge extends Transform {
public ParseContext transform(ParseContext parseContext) throws SemanticException {
Map allSemijoins = parseContext.getRsToSemiJoinBranchInfo();
if (allSemijoins.isEmpty()) {
return parseContext;
}
HiveConf hiveConf = parseContext.getConf();
for (Entry> sjMergeCandidate : createMergeCandidates(allSemijoins)) {
final List sjBranches = sjMergeCandidate.getValue();
if (sjBranches.size() < 2) {
continue;
}
List selOps = new ArrayList<>(sjBranches.size());
for (ReduceSinkOperator rs : sjBranches) {
selOps.add(OperatorUtils.ancestor(rs, SelectOperator.class, 0, 0, 0, 0));
}
long sjEntriesHint = extractBloomEntriesHint(sjBranches);
SelectOperator selectOp = mergeSelectOps(sjMergeCandidate.getKey().source, selOps);
GroupByOperator gbPartialOp = createGroupBy(selectOp, selectOp, GroupByDesc.Mode.HASH, sjEntriesHint, hiveConf);
ReduceSinkOperator rsPartialOp = createReduceSink(gbPartialOp, NullOrdering.defaultNullOrder(hiveConf));
rsPartialOp.getConf().setReducerTraits(EnumSet.of(ReduceSinkDesc.ReducerTraits.QUICKSTART));
GroupByOperator gbCompleteOp =
createGroupBy(selectOp, rsPartialOp, GroupByDesc.Mode.FINAL, sjEntriesHint, hiveConf);
ReduceSinkOperator rsCompleteOp = createReduceSink(gbCompleteOp, NullOrdering.defaultNullOrder(hiveConf));
final TableScanOperator sjTargetTable = sjMergeCandidate.getKey().target;
SemiJoinBranchInfo sjInfo = new SemiJoinBranchInfo(sjTargetTable, false);
parseContext.getRsToSemiJoinBranchInfo().put(rsCompleteOp, sjInfo);
// Save the info that is required at query time to resolve dynamic/runtime values.
RuntimeValuesInfo valuesInfo = createRuntimeValuesInfo(rsCompleteOp, sjBranches, parseContext);
parseContext.getRsToRuntimeValuesInfoMap().put(rsCompleteOp, valuesInfo);
ExprNodeGenericFuncDesc sjPredicate = createSemiJoinPredicate(sjBranches, valuesInfo, parseContext);
// Update filter operators with the new semi-join predicate
for (Operator op : sjTargetTable.getChildOperators()) {
if (op instanceof FilterOperator) {
FilterDesc filter = ((FilterOperator) op).getConf();
filter.setPredicate(and(filter.getPredicate(), sjPredicate));
}
}
// Update tableScan with the new semi-join predicate
sjTargetTable.getConf().setFilterExpr(and(sjTargetTable.getConf().getFilterExpr(), sjPredicate));
for (ReduceSinkOperator rs : sjBranches) {
GenTezUtils.removeSemiJoinOperator(parseContext, rs, sjTargetTable);
GenTezUtils.removeBranch(rs);
}
}
return parseContext;
}
/**
* Groups single column semijoin reducer branches together if they have the same source and target relation.
*/
private static Collection>> createMergeCandidates(
Map semijoins) {
// Predictable iteration helps to avoid small changes in the plans
LinkedHashMap> sjGroups = new LinkedHashMap<>();
for (Map.Entry smjEntry : semijoins.entrySet()) {
TableScanOperator ts = smjEntry.getValue().getTsOp();
// Semijoin optimization branch should look like -SEL-GB1-RS1-GB2-RS2
SelectOperator selOp = OperatorUtils.ancestor(smjEntry.getKey(), SelectOperator.class, 0, 0, 0, 0);
Operator source = selOp.getParentOperators().get(0);
checkState(selOp.getParentOperators().size() == 1, "Semijoin branches should not have multiple parents");
SJSourceTarget sjKey = new SJSourceTarget(source, ts);
List ops = sjGroups.computeIfAbsent(sjKey, tableScanOperator -> new ArrayList<>());
ops.add(smjEntry.getKey());
}
return sjGroups.entrySet();
}
/**
* Extracts a hint about the number of expected entries in the composite bloom filter from the hints in the specified
* (single column) semijoin branches.
*
* If none of the individual semijoin branches has hints then the method returns -1, otherwise it returns the max.
*
*/
private static long extractBloomEntriesHint(List sjBranches) {
long bloomEntries = -1;
for (ReduceSinkOperator rs : sjBranches) {
GroupByOperator gbOp = OperatorUtils.ancestor(rs, GroupByOperator.class, 0, 0, 0);
List blooms =
FunctionUtils.extractEvaluators(gbOp.getConf().getAggregators(), GenericUDAFBloomFilterEvaluator.class);
Preconditions.checkState(blooms.size() == 1);
if (blooms.get(0).hasHintEntries()) {
bloomEntries = Math.max(bloomEntries, blooms.get(0).getExpectedEntries());
}
}
return bloomEntries;
}
/**
* Creates the multi-column semi-join predicate that is applied on the target relation.
*
* Assuming that the target columns of the semi-join are fname, lname, and age, the generated predicates is:
*
* fname BETWEEN ?min_fname AND ?max_fname and
* lname BETWEEN ?min_lname AND ?max_lname and
* age BETWEEN ?min_age AND ?max_age and
* IN_BLOOM_FILTER(HASH(fname,lname,age),?bloom_filter)
*
* where the question mark (?) indicates dynamic values bound at runtime.
*/
private static ExprNodeGenericFuncDesc createSemiJoinPredicate(List sjBranches,
RuntimeValuesInfo sjValueInfo, ParseContext context) {
// Performance note: To speed-up evaluation 'BETWEEN' predicates should come before the 'IN_BLOOM_FILTER'
Deque dynamicIds = new ArrayDeque<>(sjValueInfo.getDynamicValueIDs());
List sjPredicates = new ArrayList<>();
List hashArgs = new ArrayList<>();
for (ReduceSinkOperator rs : sjBranches) {
RuntimeValuesInfo info = context.getRsToRuntimeValuesInfoMap().get(rs);
checkState(info.getTargetColumns().size() == 1, "Cannot handle multi-column semijoin branches.");
final ExprNodeDesc targetColumn = info.getTargetColumns().get(0);
TypeInfo typeInfo = targetColumn.getTypeInfo();
DynamicValue minDynamic = new DynamicValue(dynamicIds.poll(), typeInfo);
DynamicValue maxDynamic = new DynamicValue(dynamicIds.poll(), typeInfo);
List betweenArgs = Arrays.asList(
// Use false to not invert between result
new ExprNodeConstantDesc(Boolean.FALSE),
targetColumn,
new ExprNodeDynamicValueDesc(minDynamic),
new ExprNodeDynamicValueDesc(maxDynamic));
ExprNodeDesc betweenExp =
new ExprNodeGenericFuncDesc(TypeInfoFactory.booleanTypeInfo, new GenericUDFBetween(), "between", betweenArgs);
sjPredicates.add(betweenExp);
hashArgs.add(targetColumn);
}
ExprNodeDesc hashExp = ExprNodeDescUtils.murmurHash(hashArgs);
assert dynamicIds.size() == 1 : "There should be one column left untreated the one with the bloom filter";
DynamicValue bloomDynamic = new DynamicValue(dynamicIds.poll(), TypeInfoFactory.binaryTypeInfo);
sjPredicates.add(
new ExprNodeGenericFuncDesc(TypeInfoFactory.booleanTypeInfo, new GenericUDFInBloomFilter(), "in_bloom_filter",
Arrays.asList(hashExp, new ExprNodeDynamicValueDesc(bloomDynamic))));
return and(sjPredicates);
}
/**
* Creates the necessary information in order to execute the multi-column semi join and perform further optimizations.
*/
private static RuntimeValuesInfo createRuntimeValuesInfo(ReduceSinkOperator rs, List sjBranches,
ParseContext parseContext) {
List valueCols = rs.getConf().getValueCols();
RuntimeValuesInfo info = new RuntimeValuesInfo();
TableDesc rsFinalTableDesc =
PlanUtils.getReduceValueTableDesc(PlanUtils.getFieldSchemasFromColumnList(valueCols, "_col"));
List dynamicValueIDs = new ArrayList<>();
for (ExprNodeDesc rsCol : valueCols) {
dynamicValueIDs.add(rs.toString() + rsCol.getExprString());
}
info.setTableDesc(rsFinalTableDesc);
info.setDynamicValueIDs(dynamicValueIDs);
info.setColExprs(valueCols);
List targetTableExpressions = new ArrayList<>();
for (ReduceSinkOperator sjBranch : sjBranches) {
RuntimeValuesInfo sjInfo = parseContext.getRsToRuntimeValuesInfoMap().get(sjBranch);
checkState(sjInfo.getTargetColumns().size() == 1, "Cannot handle multi-column semijoin branches.");
targetTableExpressions.add(sjInfo.getTargetColumns().get(0));
}
info.setTargetColumns(targetTableExpressions);
return info;
}
/**
* Merges multiple select operators in a single one appending an additional column that is the hash of all the others.
*
*
* Input: SEL[fname], SEL[lname], SEL[age]
* Output: SEL[fname, lname, age, hash(fname, lname, age)]
*
*/
private static SelectOperator mergeSelectOps(Operator parent, List selectOperators) {
List colNames = new ArrayList<>();
List colDescs = new ArrayList<>();
List columnInfos = new ArrayList<>();
Map selectColumnExprMap = new HashMap<>();
for (SelectOperator sel : selectOperators) {
checkState(sel.getConf().getColList().size() == 1);
ExprNodeDesc col = sel.getConf().getColList().get(0);
String colName = HiveConf.getColumnInternalName(colDescs.size());
colNames.add(colName);
columnInfos.add(new ColumnInfo(colName, col.getTypeInfo(), "", false));
colDescs.add(col);
selectColumnExprMap.put(colName, col);
}
ExprNodeDesc hashExp = ExprNodeDescUtils.murmurHash(colDescs);
String hashName = HiveConf.getColumnInternalName(colDescs.size() + 1);
colNames.add(hashName);
columnInfos.add(new ColumnInfo(hashName, hashExp.getTypeInfo(), "", false));
// The n-1 columns in selDescs are used as parameters to min/max aggregations
List selDescs = new ArrayList<>(colDescs);
// The nth column in selDescs is used as parameter to the bloom_filter aggregation
selDescs.add(hashExp);
SelectDesc select = new SelectDesc(selDescs, colNames);
SelectOperator selectOp =
(SelectOperator) OperatorFactory.getAndMakeChild(select, new RowSchema(columnInfos), parent);
selectOp.setColumnExprMap(selectColumnExprMap);
return selectOp;
}
/**
* Creates a reduce sink operator that emits all columns of the parent as values.
*/
private static ReduceSinkOperator createReduceSink(Operator parentOp, NullOrdering nullOrder)
throws SemanticException {
List valueCols = new ArrayList<>();
RowSchema parentSchema = parentOp.getSchema();
List outColNames = new ArrayList<>();
for (int i = 0; i < parentSchema.getSignature().size(); i++) {
ColumnInfo colInfo = parentSchema.getSignature().get(i);
ExprNodeColumnDesc colExpr = new ExprNodeColumnDesc(colInfo.getType(), colInfo.getInternalName(), "", false);
valueCols.add(colExpr);
outColNames.add(SemanticAnalyzer.getColumnInternalName(i));
}
ReduceSinkDesc rsDesc = PlanUtils
.getReduceSinkDesc(Collections.emptyList(), valueCols, outColNames, false, -1, 0, 1,
AcidUtils.Operation.NOT_ACID, nullOrder);
rsDesc.setColumnExprMap(Collections.emptyMap());
return (ReduceSinkOperator) OperatorFactory.getAndMakeChild(rsDesc, new RowSchema(parentSchema), parentOp);
}
/**
* Creates a group by operator with min, max, and bloomFilter aggregations for every column of the parent.
*
* The method generates two kind of group by operators for intermediate and final aggregations respectively.
* Intermediate aggregations require the parent operator to be a select operator while final aggregations assume that
* the parent is a reduce sink operator.
*
*
* Intermediate group by example.
*
* Input: SEL[fname, lname, age, hash(fname,lname,age)]
* Output: GBY[min(fname),max(fname),min(lname),max(lname),min(age),max(age),bloom(hash)]
*
*
*
* Final group by example.
*
* Input: RS[fname_min,fname_max,lname_min,lname_max,age_min,age_max, hash_bloom]
* Output: GBY[min(fname_min),max(fname_max),min(lname_min),max(lname_max),min(age_min),max(age_max),bloom(hash_bloom)]
*
*
*/
private static GroupByOperator createGroupBy(SelectOperator selectOp, Operator parentOp, GroupByDesc.Mode gbMode,
long bloomEntriesHint, HiveConf hiveConf) {
final List params;
final GenericUDAFEvaluator.Mode udafMode = SemanticAnalyzer.groupByDescModeToUDAFMode(gbMode, false);
switch (gbMode) {
case FINAL:
params = createGroupByAggregationParameters((ReduceSinkOperator) parentOp);
break;
case HASH:
params = createGroupByAggregationParameters(selectOp);
break;
default:
throw new AssertionError(gbMode.toString() + " is not supported");
}
List gbAggs = new ArrayList<>();
Deque paramsCopy = new ArrayDeque<>(params);
while (paramsCopy.size() > 1) {
gbAggs.add(minAggregation(udafMode, paramsCopy.poll()));
gbAggs.add(maxAggregation(udafMode, paramsCopy.poll()));
}
gbAggs.add(bloomFilterAggregation(udafMode, paramsCopy.poll(), selectOp, bloomEntriesHint, hiveConf));
assert paramsCopy.size() == 0;
List gbOutputNames = new ArrayList<>(gbAggs.size());
List gbColInfos = new ArrayList<>(gbAggs.size());
for (int i = 0; i < params.size(); i++) {
String colName = HiveConf.getColumnInternalName(i);
gbOutputNames.add(colName);
final TypeInfo colType;
if (i == params.size() - 1) {
colType = TypeInfoFactory.binaryTypeInfo; // Bloom type
} else {
colType = params.get(i).getTypeInfo(); // Min/Max type
}
gbColInfos.add(new ColumnInfo(colName, colType, "", false));
}
float groupByMemoryUsage = HiveConf.getFloatVar(hiveConf, HiveConf.ConfVars.HIVEMAPAGGRHASHMEMORY);
float memoryThreshold = HiveConf.getFloatVar(hiveConf, HiveConf.ConfVars.HIVEMAPAGGRMEMORYTHRESHOLD);
float minReductionHashAggr = HiveConf.getFloatVar(hiveConf, HiveConf.ConfVars.HIVEMAPAGGRHASHMINREDUCTION);
float minReductionHashAggrLowerBound = HiveConf.getFloatVar(hiveConf, HiveConf.ConfVars.HIVEMAPAGGRHASHMINREDUCTIONLOWERBOUND);
GroupByDesc groupBy =
new GroupByDesc(gbMode, gbOutputNames, Collections.emptyList(), gbAggs, false, groupByMemoryUsage,
memoryThreshold, minReductionHashAggr, minReductionHashAggrLowerBound, null, false, -1, false);
groupBy.setColumnExprMap(Collections.emptyMap());
return (GroupByOperator) OperatorFactory.getAndMakeChild(groupBy, new RowSchema(gbColInfos), parentOp);
}
private static List createGroupByAggregationParameters(SelectOperator selectOp) {
List params = new ArrayList<>();
// The first n-1 cols are used as parameters for min & max so we need two expressions
for (ColumnInfo c : selectOp.getSchema().getSignature()) {
String name = c.getInternalName();
ExprNodeColumnDesc p = new ExprNodeColumnDesc(new ColumnInfo(name, c.getType(), "", false));
params.add(p);
params.add(p);
}
// The last col is used as parameter for bloom so we need only one expression
params.remove(params.size() - 1);
return params;
}
private static List createGroupByAggregationParameters(ReduceSinkOperator reduceOp) {
List params = new ArrayList<>();
// There is a 1-1 mapping between columns and parameters for the aggregation functions min, max, bloom
for (ColumnInfo c : reduceOp.getSchema().getSignature()) {
String name = Utilities.ReduceField.VALUE + "." + c.getInternalName();
params.add(new ExprNodeColumnDesc(new ColumnInfo(name, c.getType(), "", false)));
}
return params;
}
private static AggregationDesc minAggregation(GenericUDAFEvaluator.Mode mode, ExprNodeDesc col) {
List p = Collections.singletonList(col);
return new AggregationDesc("min", new GenericUDAFMin.GenericUDAFMinEvaluator(), p, false, mode);
}
private static AggregationDesc maxAggregation(GenericUDAFEvaluator.Mode mode, ExprNodeDesc col) {
List p = Collections.singletonList(col);
return new AggregationDesc("max", new GenericUDAFMax.GenericUDAFMaxEvaluator(), p, false, mode);
}
private static AggregationDesc bloomFilterAggregation(GenericUDAFEvaluator.Mode mode, ExprNodeDesc col,
SelectOperator source, long numEntriesHint, HiveConf conf) {
GenericUDAFBloomFilterEvaluator bloomFilterEval = new GenericUDAFBloomFilterEvaluator();
bloomFilterEval.setSourceOperator(source);
bloomFilterEval.setMaxEntries(conf.getLongVar(HiveConf.ConfVars.TEZ_MAX_BLOOM_FILTER_ENTRIES));
bloomFilterEval.setMinEntries(conf.getLongVar(HiveConf.ConfVars.TEZ_MIN_BLOOM_FILTER_ENTRIES));
bloomFilterEval.setFactor(conf.getFloatVar(HiveConf.ConfVars.TEZ_BLOOM_FILTER_FACTOR));
bloomFilterEval.setHintEntries(numEntriesHint);
List params;
// numThreads is available only for VectorUDAFBloomFilterMerge, which only supports
// these two modes, don't add numThreads otherwise
switch(mode) {
case PARTIAL2:
case FINAL:
int numThreads = conf.getIntVar(HiveConf.ConfVars.TEZ_BLOOM_FILTER_MERGE_THREADS);
TypeInfo intTypeInfo = TypeInfoFactory.getPrimitiveTypeInfoFromJavaPrimitive(Integer.TYPE);
params = Arrays.asList(col, new ExprNodeConstantDesc(intTypeInfo, numThreads));
break;
default:
params = Collections.singletonList(col);
break;
}
AggregationDesc bloom = new AggregationDesc(BLOOM_FILTER_FUNCTION, bloomFilterEval, params, false, mode);
// It is necessary to set the bloom filter evaluator otherwise there are runtime failures see HIVE-24018
bloom.setGenericUDAFWritableEvaluator(bloomFilterEval);
return bloom;
}
/**
* An object that represents the source and target of a semi-join reducer.
*
* The objects are meant to be used as keys in maps so it is required to implement hashCode and equals methods.
*/
private static final class SJSourceTarget {
private final Operator source;
private final TableScanOperator target;
public SJSourceTarget(Operator source, TableScanOperator target) {
this.source = source;
this.target = target;
}
@Override public boolean equals(Object o) {
if (this == o) {
return true;
}
if (o == null || getClass() != o.getClass()) {
return false;
}
SJSourceTarget that = (SJSourceTarget) o;
if (!source.equals(that.source)) {
return false;
}
return target.equals(that.target);
}
@Override public int hashCode() {
int result = source.hashCode();
result = 31 * result + target.hashCode();
return result;
}
}
}