Package org.apache.hadoop.hive.ql.lib

Examples of org.apache.hadoop.hive.ql.lib.DefaultGraphWalker

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        genFuncProc);

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(defProc, exprRules, ctx);
    GraphWalker egw = new DefaultGraphWalker(disp);

    List<Node> startNodes = new ArrayList<Node>();
    startNodes.add(pred);

    HashMap<Node, Object> outputMap = new HashMap<Node, Object>();
    egw.startWalking(startNodes, outputMap);
    return outputMap;
  }
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    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1", SEL + "%" + SEL + "%"), new SelectDedup());
    opRules.put(new RuleRegExp("R2", FIL + "%" + FIL + "%"), new FilterDedup());

    Dispatcher disp = new DefaultRuleDispatcher(null, opRules, null);
    GraphWalker ogw = new DefaultGraphWalker(disp);

    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
  }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules,
        samplePrunerCtx);
    GraphWalker ogw = new DefaultGraphWalker(disp);

    // Create a list of topop nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
  }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(PcrOpProcFactory.getDefaultProc(),
        opRules, opWalkerCtx);
    GraphWalker ogw = new DefaultGraphWalker(disp);

    // Create a list of topop nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);

    for (PcrOpWalkerCtx.OpToDeleteInfo entry : opToRemove) {
      entry.getParent().removeChildAndAdoptItsChildren(entry.getOperator());
    }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultExprProcessor(),
        exprRules, pprCtx);
    GraphWalker egw = new DefaultGraphWalker(disp);

    List<Node> startNodes = new ArrayList<Node>();
    startNodes.add(pred);

    HashMap<Node, Object> outputMap = new HashMap<Node, Object>();
    egw.startWalking(startNodes, outputMap);

    // Return the wrapper of the root node
    return (NodeInfoWrapper) outputMap.get(pred);
  }
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            FileSinkOperator.getOperatorName() + "%"),
        getBucketSortReduceSinkProc(pctx));

    // The dispatcher fires the processor corresponding to the closest matching rule
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, null);
    GraphWalker 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;
  }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules,
        bucketMapJoinOptimizeCtx);
    GraphWalker 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;
  }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(ReduceSinkDeduplicateProcFactory
        .getDefaultProc(), opRules, cppCtx);
    GraphWalker ogw = new DefaultGraphWalker(disp);

    // Create a list of topop nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pGraphContext.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pGraphContext;
  }
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        RewriteQueryUsingAggregateIndex.getNewQueryGroupbySchemaProc());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, this);
    GraphWalker ogw = new DefaultGraphWalker(disp);

    // Create a list of topop nodes
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.add(topOp);
    ogw.startWalking(topNodes, null);
  }
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    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1", ReduceSinkOperator.getOperatorName() + "%"),
        new CorrelationNodeProc());

    Dispatcher disp = new DefaultRuleDispatcher(getDefaultProc(), opRules, corrCtx);
    GraphWalker 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);
    // We have finished tree walking (correlation detection).
    // We will first see if we need to abort (the operator tree has not been changed).
    // If not, we will start to transform the operator tree.
    abort = corrCtx.isAbort();
    if (abort) {
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Related Classes of org.apache.hadoop.hive.ql.lib.DefaultGraphWalker

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  • org.apache.hadoop.hive.accumulo.predicate.TestAccumuloRangeGenerator
  • org.apache.hadoop.hive.ql.index.IndexPredicateAnalyzer
  • org.apache.hadoop.hive.ql.optimizer.BucketingSortingReduceSinkOptimizer
  • org.apache.hadoop.hive.ql.optimizer.BucketMapJoinOptimizer
  • org.apache.hadoop.hive.ql.optimizer.correlation.CorrelationOptimizer
  • org.apache.hadoop.hive.ql.optimizer.correlation.ReduceSinkDeDuplication
  • org.apache.hadoop.hive.ql.optimizer.DynamicPartitionPruningOptimization
  • org.apache.hadoop.hive.ql.optimizer.GroupByOptimizer
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