Examples with SemanticRule org.apache.hadoop.hive.ql.lib.SemanticRule used on opensource projects

Example 1 with SemanticRule

use of org.apache.hadoop.hive.ql.lib.SemanticRule in project hive by apache.

the class DagUtils method collectFileSinkUris.

private void collectFileSinkUris(List<Node> topNodes, Set<URI> uris, Set<TableDesc> tableDescs) {
    CollectFileSinkUrisNodeProcessor np = new CollectFileSinkUrisNodeProcessor(uris, tableDescs);
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    addCollectFileSinkUrisRules(opRules, np);
    SemanticDispatcher disp = new DefaultRuleDispatcher(np, opRules, null);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    try {
        ogw.startWalking(topNodes, null);
    } catch (SemanticException e) {
        throw new RuntimeException(e);
    }
}

Example 2 with SemanticRule

use of org.apache.hadoop.hive.ql.lib.SemanticRule in project hive by apache.

the class ConstantPropagate method transform.

/**
 * Transform the query tree.
 *
 * @param pactx
 *        the current parse context
 */
@Override
public ParseContext transform(ParseContext pactx) throws SemanticException {
    pGraphContext = pactx;
    // generate pruned column list for all relevant operators
    ConstantPropagateProcCtx cppCtx = new ConstantPropagateProcCtx(constantPropagateOption);
    // create a walker which walks the tree in a DFS manner while maintaining
    // the operator stack. The dispatcher
    // generates the plan from the operator tree
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp("R1", FilterOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getFilterProc());
    opRules.put(new RuleRegExp("R2", GroupByOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getGroupByProc());
    opRules.put(new RuleRegExp("R3", SelectOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getSelectProc());
    opRules.put(new RuleRegExp("R4", FileSinkOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getFileSinkProc());
    opRules.put(new RuleRegExp("R5", ReduceSinkOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getReduceSinkProc());
    opRules.put(new RuleRegExp("R6", JoinOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R7", TableScanOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getTableScanProc());
    opRules.put(new RuleRegExp("R8", ScriptOperator.getOperatorName() + "%"), ConstantPropagateProcFactory.getStopProc());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(ConstantPropagateProcFactory.getDefaultProc(), opRules, cppCtx);
    SemanticGraphWalker ogw = new ConstantPropagateWalker(disp);
    // Create a list of operator nodes to start the walking.
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pGraphContext.getTopOps().values());
    ogw.startWalking(topNodes, null);
    for (Operator<? extends Serializable> opToDelete : cppCtx.getOpToDelete()) {
        if (opToDelete.getParentOperators() == null || opToDelete.getParentOperators().size() != 1) {
            throw new RuntimeException("Error pruning operator " + opToDelete + ". It should have only 1 parent.");
        }
        opToDelete.getParentOperators().get(0).removeChildAndAdoptItsChildren(opToDelete);
    }
    cppCtx.getOpToDelete().clear();
    return pGraphContext;
}

Example 3 with SemanticRule

use of org.apache.hadoop.hive.ql.lib.SemanticRule in project hive by apache.

the class CountDistinctRewriteProc method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    // process group-by pattern
    opRules.put(new RuleRegExp("R1", GroupByOperator.getOperatorName() + "%" + ReduceSinkOperator.getOperatorName() + "%" + GroupByOperator.getOperatorName() + "%"), getCountDistinctProc(pctx));
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, null);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    // Create a list of topop nodes
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
}

Example 4 with SemanticRule

use of org.apache.hadoop.hive.ql.lib.SemanticRule in project hive by apache.

the class BucketingSortingReduceSinkOptimizer method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    // process reduce sink added by hive.enforce.bucketing or hive.enforce.sorting
    opRules.put(new RuleRegExp("R1", ReduceSinkOperator.getOperatorName() + "%" + SelectOperator.getOperatorName() + "%" + FileSinkOperator.getOperatorName() + "%"), getBucketSortReduceSinkProc(pctx));
    // The dispatcher fires the processor corresponding to the closest matching rule
    SemanticDispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, null);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    // Create a list of top nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
}

Example 5 with SemanticRule

use of org.apache.hadoop.hive.ql.lib.SemanticRule in project hive by apache.

the class BucketMapJoinOptimizer method transform.

public ParseContext transform(ParseContext pctx) throws SemanticException {
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    BucketJoinProcCtx bucketMapJoinOptimizeCtx = new BucketJoinProcCtx(pctx.getConf());
    // process map joins with no reducers pattern
    opRules.put(new RuleRegExp("R1", MapJoinOperator.getOperatorName() + "%"), getBucketMapjoinProc(pctx));
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, bucketMapJoinOptimizeCtx);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    // Create a list of topop nodes
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
}