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/*
* 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.optimizer;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.Stack;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.TableScanOperator;
import org.apache.hadoop.hive.ql.exec.Task;
import org.apache.hadoop.hive.ql.exec.TaskFactory;
import org.apache.hadoop.hive.ql.exec.mr.MapRedTask;
import org.apache.hadoop.hive.ql.io.orc.OrcInputFormat;
import org.apache.hadoop.hive.ql.io.parquet.MapredParquetInputFormat;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.lib.NodeProcessor;
import org.apache.hadoop.hive.ql.lib.NodeProcessorCtx;
import org.apache.hadoop.hive.ql.metadata.Partition;
import org.apache.hadoop.hive.ql.metadata.Table;
import org.apache.hadoop.hive.ql.optimizer.GenMRProcContext.GenMapRedCtx;
import org.apache.hadoop.hive.ql.parse.ParseContext;
import org.apache.hadoop.hive.ql.parse.PrunedPartitionList;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.StatsWork;
import org.apache.hadoop.hive.ql.plan.BasicStatsWork;
import org.apache.hadoop.hive.ql.plan.MapredWork;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
import org.apache.hadoop.mapred.InputFormat;
/**
* Processor for the rule - table scan.
*/
public class GenMRTableScan1 implements NodeProcessor {
public GenMRTableScan1() {
}
/**
* Table Sink encountered.
* @param nd
* the table sink operator encountered
* @param opProcCtx
* context
*/
@Override
public Object process(Node nd, Stack stack, NodeProcessorCtx opProcCtx,
Object... nodeOutputs) throws SemanticException {
TableScanOperator op = (TableScanOperator) nd;
GenMRProcContext ctx = (GenMRProcContext) opProcCtx;
ParseContext parseCtx = ctx.getParseCtx();
Table table = op.getConf().getTableMetadata();
Class inputFormat = table.getInputFormatClass();
Map, GenMapRedCtx> mapCurrCtx = ctx.getMapCurrCtx();
// create a dummy MapReduce task
MapredWork currWork = GenMapRedUtils.getMapRedWork(parseCtx);
MapRedTask currTask = (MapRedTask) TaskFactory.get(currWork);
ctx.setCurrTask(currTask);
ctx.setCurrTopOp(op);
for (String alias : parseCtx.getTopOps().keySet()) {
Operator currOp = parseCtx.getTopOps().get(alias);
if (currOp == op) {
String currAliasId = alias;
ctx.setCurrAliasId(currAliasId);
mapCurrCtx.put(op, new GenMapRedCtx(currTask, currAliasId));
if (parseCtx.getQueryProperties().isAnalyzeCommand()) {
boolean noScan = parseCtx.getQueryProperties().isNoScanAnalyzeCommand();
if (OrcInputFormat.class.isAssignableFrom(inputFormat) ||
MapredParquetInputFormat.class.isAssignableFrom(inputFormat)) {
// For ORC and Parquet, all the following statements are the same
// ANALYZE TABLE T [PARTITION (...)] COMPUTE STATISTICS
// ANALYZE TABLE T [PARTITION (...)] COMPUTE STATISTICS noscan;
// There will not be any MR or Tez job above this task
StatsWork statWork = new StatsWork(table, parseCtx.getConf());
statWork.setFooterScan();
// If partition is specified, get pruned partition list
Set confirmedParts = GenMapRedUtils.getConfirmedPartitionsForScan(op);
if (confirmedParts.size() > 0) {
List partCols = GenMapRedUtils.getPartitionColumns(op);
PrunedPartitionList partList = new PrunedPartitionList(table, confirmedParts, partCols, false);
statWork.addInputPartitions(partList.getPartitions());
}
Task snjTask = TaskFactory.get(statWork);
ctx.setCurrTask(snjTask);
ctx.setCurrTopOp(null);
ctx.getRootTasks().clear();
ctx.getRootTasks().add(snjTask);
} else {
// ANALYZE TABLE T [PARTITION (...)] COMPUTE STATISTICS;
// The plan consists of a simple MapRedTask followed by a StatsTask.
// The MR task is just a simple TableScanOperator
BasicStatsWork statsWork = new BasicStatsWork(table.getTableSpec());
statsWork.setIsExplicitAnalyze(true);
statsWork.setNoScanAnalyzeCommand(noScan);
StatsWork columnStatsWork = new StatsWork(table, statsWork, parseCtx.getConf());
columnStatsWork.collectStatsFromAggregator(op.getConf());
columnStatsWork.setSourceTask(currTask);
Task columnStatsTask = TaskFactory.get(columnStatsWork);
currTask.addDependentTask(columnStatsTask);
if (!ctx.getRootTasks().contains(currTask)) {
ctx.getRootTasks().add(currTask);
}
// ANALYZE TABLE T [PARTITION (...)] COMPUTE STATISTICS noscan;
// The plan consists of a StatsTask only.
if (noScan) {
columnStatsTask.setParentTasks(null);
ctx.getRootTasks().remove(currTask);
ctx.getRootTasks().add(columnStatsTask);
}
currWork.getMapWork().setGatheringStats(true);
if (currWork.getReduceWork() != null) {
currWork.getReduceWork().setGatheringStats(true);
}
// NOTE: here we should use the new partition predicate pushdown API to get a list of
// pruned list,
// and pass it to setTaskPlan as the last parameter
Set confirmedPartns = GenMapRedUtils
.getConfirmedPartitionsForScan(op);
if (confirmedPartns.size() > 0) {
List partCols = GenMapRedUtils.getPartitionColumns(op);
PrunedPartitionList partList = new PrunedPartitionList(table, confirmedPartns, partCols, false);
GenMapRedUtils.setTaskPlan(currAliasId, op, currTask, false, ctx, partList);
} else { // non-partitioned table
GenMapRedUtils.setTaskPlan(currAliasId, op, currTask, false, ctx);
}
}
}
return true;
}
}
assert false;
return null;
}
}
