org.apache.hadoop.hive.ql.optimizer.physical.BucketingSortingInferenceOptimizer Maven / Gradle / Ivy
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*
* http://www.apache.org/licenses/LICENSE-2.0
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package org.apache.hadoop.hive.ql.optimizer.physical;
import java.util.ArrayList;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import org.apache.hadoop.hive.ql.exec.FileSinkOperator;
import org.apache.hadoop.hive.ql.exec.FilterOperator;
import org.apache.hadoop.hive.ql.exec.ForwardOperator;
import org.apache.hadoop.hive.ql.exec.GroupByOperator;
import org.apache.hadoop.hive.ql.exec.JoinOperator;
import org.apache.hadoop.hive.ql.exec.LateralViewForwardOperator;
import org.apache.hadoop.hive.ql.exec.LateralViewJoinOperator;
import org.apache.hadoop.hive.ql.exec.LimitOperator;
import org.apache.hadoop.hive.ql.exec.Operator;
import org.apache.hadoop.hive.ql.exec.SelectOperator;
import org.apache.hadoop.hive.ql.exec.Utilities;
import org.apache.hadoop.hive.ql.exec.mr.ExecDriver;
import org.apache.hadoop.hive.ql.lib.DefaultRuleDispatcher;
import org.apache.hadoop.hive.ql.lib.Dispatcher;
import org.apache.hadoop.hive.ql.lib.GraphWalker;
import org.apache.hadoop.hive.ql.lib.Node;
import org.apache.hadoop.hive.ql.lib.NodeProcessor;
import org.apache.hadoop.hive.ql.lib.PreOrderWalker;
import org.apache.hadoop.hive.ql.lib.Rule;
import org.apache.hadoop.hive.ql.lib.RuleExactMatch;
import org.apache.hadoop.hive.ql.lib.RuleRegExp;
import org.apache.hadoop.hive.ql.parse.SemanticException;
import org.apache.hadoop.hive.ql.plan.OperatorDesc;
/**
*
* BucketingSortingInferenceOptimizer.
*
* For each map reduce task, attmepts to infer bucketing and sorting metadata for the outputs.
*
* Currently only map reduce tasks which produce final output have there output metadata inferred,
* but it can be extended to intermediate tasks as well.
*
* This should be run as the last physical optimizer, as other physical optimizers may invalidate
* the inferences made. If a physical optimizer depends on the results and is designed to
* carefully maintain these inferences, it may follow this one.
*/
public class BucketingSortingInferenceOptimizer implements PhysicalPlanResolver {
@Override
public PhysicalContext resolve(PhysicalContext pctx) throws SemanticException {
inferBucketingSorting(Utilities.getMRTasks(pctx.rootTasks));
return pctx;
}
/**
* For each map reduce task, if it has a reducer, infer whether or not the final output of the
* reducer is bucketed and/or sorted
*
* @param mapRedTasks
* @throws SemanticException
*/
private void inferBucketingSorting(List mapRedTasks) throws SemanticException {
for (ExecDriver mapRedTask : mapRedTasks) {
// For now this only is used to determine the bucketing/sorting of outputs, in the future
// this can be removed to optimize the query plan based on the bucketing/sorting properties
// of the outputs of intermediate map reduce jobs.
if (!mapRedTask.getWork().isFinalMapRed()) {
continue;
}
if (mapRedTask.getWork().getReduceWork() == null) {
continue;
}
Operator reducer = mapRedTask.getWork().getReduceWork().getReducer();
// uses sampling, which means it's not bucketed
boolean disableBucketing = mapRedTask.getWork().getMapWork().getSamplingType() > 0;
BucketingSortingCtx bCtx = new BucketingSortingCtx(disableBucketing);
// RuleRegExp rules are used to match operators anywhere in the tree
// RuleExactMatch rules are used to specify exactly what the tree should look like
// In particular, this guarantees that the first operator is the reducer
// (and its parent(s) are ReduceSinkOperators) since it begins walking the tree from
// the reducer.
Map opRules = new LinkedHashMap();
opRules.put(new RuleRegExp("R1", SelectOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getSelProc());
// Matches only GroupByOperators which are reducers, rather than map group by operators,
// or multi group by optimization specific operators
opRules.put(new RuleExactMatch("R2", GroupByOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getGroupByProc());
// Matches only JoinOperators which are reducers, rather than map joins, SMB map joins, etc.
opRules.put(new RuleExactMatch("R3", JoinOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getJoinProc());
opRules.put(new RuleRegExp("R5", FileSinkOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getFileSinkProc());
opRules.put(new RuleRegExp("R7", FilterOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getFilterProc());
opRules.put(new RuleRegExp("R8", LimitOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getLimitProc());
opRules.put(new RuleRegExp("R9", LateralViewForwardOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getLateralViewForwardProc());
opRules.put(new RuleRegExp("R10", LateralViewJoinOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getLateralViewJoinProc());
// Matches only ForwardOperators which are preceded by some other operator in the tree,
// in particular it can't be a reducer (and hence cannot be one of the ForwardOperators
// added by the multi group by optimization)
opRules.put(new RuleRegExp("R11", ".+" + ForwardOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getForwardProc());
// Matches only ForwardOperators which are reducers and are followed by GroupByOperators
// (specific to the multi group by optimization)
opRules.put(new RuleExactMatch("R12", ForwardOperator.getOperatorName() + "%" +
GroupByOperator.getOperatorName() + "%"),
BucketingSortingOpProcFactory.getMultiGroupByProc());
// The dispatcher fires the processor corresponding to the closest matching rule and passes
// the context along
Dispatcher disp = new DefaultRuleDispatcher(BucketingSortingOpProcFactory.getDefaultProc(),
opRules, bCtx);
GraphWalker ogw = new PreOrderWalker(disp);
// Create a list of topop nodes
ArrayList topNodes = new ArrayList();
topNodes.add(reducer);
ogw.startWalking(topNodes, null);
mapRedTask.getWork().getMapWork().getBucketedColsByDirectory().putAll(bCtx.getBucketedColsByDirectory());
mapRedTask.getWork().getMapWork().getSortedColsByDirectory().putAll(bCtx.getSortedColsByDirectory());
}
}
}