org.apache.hadoop.hive.ql.optimizer.GenMRRedSink3 Maven / Gradle / Ivy
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* Licensed to the Apache Software Foundation (ASF) under one
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* 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,
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* See the License for the specific language governing permissions and
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*/
package org.apache.hadoop.hive.ql.optimizer;
import java.io.Serializable;
import java.util.HashMap;
import java.util.Map;
import java.util.Stack;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.ReduceSinkOperator;
import org.apache.hadoop.hive.ql.exec.Task;
import org.apache.hadoop.hive.ql.exec.UnionOperator;
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.lib.Utils;
import org.apache.hadoop.hive.ql.optimizer.GenMRProcContext.GenMapRedCtx;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.MapredWork;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
/**
* Processor for the rule - union followed by reduce sink.
*/
public class GenMRRedSink3 implements NodeProcessor {
public GenMRRedSink3() {
}
/**
* Reduce Scan encountered.
*
* @param nd
* the reduce sink operator encountered
* @param opProcCtx
* context
*/
public Object process(Node nd, Stack stack, NodeProcessorCtx opProcCtx,
Object... nodeOutputs) throws SemanticException {
ReduceSinkOperator op = (ReduceSinkOperator) nd;
GenMRProcContext ctx = (GenMRProcContext) opProcCtx;
// union consisted on a bunch of map-reduce jobs, and it has been split at
// the union
Operator extends OperatorDesc> reducer = op.getChildOperators().get(0);
UnionOperator union = Utils.findNode(stack, UnionOperator.class);
assert union != null;
Map, GenMapRedCtx> mapCurrCtx = ctx
.getMapCurrCtx();
GenMapRedCtx mapredCtx = mapCurrCtx.get(union);
Task extends Serializable> unionTask = null;
if(mapredCtx != null) {
unionTask = mapredCtx.getCurrTask();
} else {
unionTask = ctx.getCurrTask();
}
MapredWork plan = (MapredWork) unionTask.getWork();
HashMap, Task extends Serializable>> opTaskMap = ctx
.getOpTaskMap();
Task extends Serializable> reducerTask = opTaskMap.get(reducer);
ctx.setCurrTask(unionTask);
// If the plan for this reducer does not exist, initialize the plan
if (reducerTask == null) {
// When the reducer is encountered for the first time
if (plan.getReduceWork() == null) {
GenMapRedUtils.initUnionPlan(op, union, ctx, unionTask);
// When union is followed by a multi-table insert
} else {
GenMapRedUtils.splitPlan(op, ctx);
}
} else if (plan.getReduceWork() != null && plan.getReduceWork().getReducer() == reducer) {
// The union is already initialized. However, the union is walked from
// another input
// initUnionPlan is idempotent
GenMapRedUtils.initUnionPlan(op, union, ctx, unionTask);
} else {
GenMapRedUtils.joinUnionPlan(ctx, union, unionTask, reducerTask, false);
ctx.setCurrTask(reducerTask);
}
mapCurrCtx.put(op, new GenMapRedCtx(ctx.getCurrTask(),
ctx.getCurrAliasId()));
// the union operator has been processed
ctx.setCurrUnionOp(null);
return true;
}
}