use of org.apache.hadoop.hive.ql.exec.mr.ExecDriver in project hive by apache.
the class BucketingSortingInferenceOptimizer method inferBucketingSorting.
/**
* 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<ExecDriver> mapRedTasks) throws SemanticException {
for (ExecDriver mapRedTask : mapRedTasks) {
// of the outputs of intermediate map reduce jobs.
if (!mapRedTask.getWork().isFinalMapRed()) {
continue;
}
if (mapRedTask.getWork().getReduceWork() == null) {
continue;
}
Operator<? extends OperatorDesc> 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<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
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", new String[] { GroupByOperator.getOperatorName() }), BucketingSortingOpProcFactory.getGroupByProc());
// Matches only JoinOperators which are reducers, rather than map joins, SMB map joins, etc.
opRules.put(new RuleExactMatch("R3", new String[] { 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", new String[] { 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<Node> topNodes = new ArrayList<Node>();
topNodes.add(reducer);
ogw.startWalking(topNodes, null);
mapRedTask.getWork().getMapWork().getBucketedColsByDirectory().putAll(bCtx.getBucketedColsByDirectory());
mapRedTask.getWork().getMapWork().getSortedColsByDirectory().putAll(bCtx.getSortedColsByDirectory());
}
}
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