Examples of RuleRegExp

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

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    // 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<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1",
      FilterOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getFilterProc());
    opRules.put(new RuleRegExp("R2",
      GroupByOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getGroupByProc());
    opRules.put(new RuleRegExp("R3",
      ReduceSinkOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getReduceSinkProc());
    opRules.put(new RuleRegExp("R4",
      SelectOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getSelectProc());
    opRules.put(new RuleRegExp("R5",
      CommonJoinOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R6",
      MapJoinOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getMapJoinProc());
    opRules.put(new RuleRegExp("R7",
      TableScanOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getTableScanProc());
    opRules.put(new RuleRegExp("R8",
      LateralViewJoinOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getLateralViewJoinProc());
    opRules.put(new RuleRegExp("R9",
      LateralViewForwardOperator.getOperatorName() + "%"),
      ColumnPrunerProcFactory.getLateralViewForwardProc());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(ColumnPrunerProcFactory
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    // create a the context for walking operators
    OpWalkerInfo opWalkerInfo = new OpWalkerInfo(pGraphContext);

    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1",
      FilterOperator.getOperatorName() + "%"),
      OpProcFactory.getFilterProc());
    opRules.put(new RuleRegExp("R3",
      CommonJoinOperator.getOperatorName() + "%"),
      OpProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R4",
      ReduceSinkOperator.getOperatorName() + "%"),
      OpProcFactory.getRSProc());
    opRules.put(new RuleRegExp("R5",
      TableScanOperator.getOperatorName() + "%"),
      OpProcFactory.getTSProc());
    opRules.put(new RuleRegExp("R6",
      ScriptOperator.getOperatorName() + "%"),
      OpProcFactory.getSCRProc());
    opRules.put(new RuleRegExp("R6",
      LimitOperator.getOperatorName() + "%"),
      OpProcFactory.getLIMProc());
    opRules.put(new RuleRegExp("R7",
      UDTFOperator.getOperatorName() + "%"),
      OpProcFactory.getUDTFProc());
    opRules.put(new RuleRegExp("R8",
      LateralViewForwardOperator.getOperatorName() + "%"),
      OpProcFactory.getLVFProc());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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  public ParseContext transform(ParseContext pctx) throws SemanticException {
    pGraphContext = pctx;

    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1",
      "(" + FilterOperator.getOperatorName() + "%" +
        ReduceSinkOperator.getOperatorName() + "%" +
        JoinOperator.getOperatorName() + "%)|" +
      "(" + FilterOperator.getOperatorName() + "%" +
        ReduceSinkOperator.getOperatorName() + "%" +
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    HiveConf conf = pctx.getConf();

    if (!HiveConf.getBoolVar(conf, HiveConf.ConfVars.HIVEGROUPBYSKEW)) {
      // process group-by pattern
      opRules.put(new RuleRegExp("R1",
          GroupByOperator.getOperatorName() + "%" +
              ReduceSinkOperator.getOperatorName() + "%" +
              GroupByOperator.getOperatorName() + "%"),
          getMapSortedGroupbyProc(pctx));
    } else {
      // If hive.groupby.skewindata is set to true, the operator tree is as below
      opRules.put(new RuleRegExp("R2",
          GroupByOperator.getOperatorName() + "%" +
              ReduceSinkOperator.getOperatorName() + "%" +
              GroupByOperator.getOperatorName() + "%" +
              ReduceSinkOperator.getOperatorName() + "%" +
              GroupByOperator.getOperatorName() + "%"),
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    // 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<Rule, NodeProcessor> exprRules = new LinkedHashMap<Rule, NodeProcessor>();
    exprRules.put(
        new RuleRegExp("R1", ExprNodeColumnDesc.class.getName() + "%"),
        getColumnProcessor());
    exprRules.put(
        new RuleRegExp("R2", ExprNodeFieldDesc.class.getName() + "%"),
        getFieldProcessor());
    exprRules.put(new RuleRegExp("R3", ExprNodeGenericFuncDesc.class.getName()
        + "%"), getGenericFuncProcessor());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefaultExprProcessor(),
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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// generate pruned column list for all relevant operators
    ReduceSinkDeduplicateProcCtx cppCtx = new ReduceSinkDeduplicateProcCtx(pGraphContext);

    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1",
      ReduceSinkOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      ReduceSinkDeduplicateProcFactory.getReducerReducerProc());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    BucketMapjoinOptProcCtx bucketMapJoinOptimizeCtx =
      new BucketMapjoinOptProcCtx(pctx.getConf());

    // process map joins with no reducers pattern
    opRules.put(new RuleRegExp("R1",
      MapJoinOperator.getOperatorName() + "%"),
      getBucketMapjoinProc(pctx));
    opRules.put(new RuleRegExp("R2",
      ReduceSinkOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName()),
      getBucketMapjoinRejectProc(pctx));
    opRules.put(new RuleRegExp(new String("R3"),
      UnionOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      getBucketMapjoinRejectProc(pctx));
    opRules.put(new RuleRegExp(new String("R4"),
      MapJoinOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      getBucketMapjoinRejectProc(pctx));

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    // 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<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp(new String("R1"),
      TableScanOperator.getOperatorName() + "%"),
      new GenMRTableScan1());
    opRules.put(new RuleRegExp(new String("R2"),
      TableScanOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      new GenMRRedSink1());
    opRules.put(new RuleRegExp(new String("R3"),
      ReduceSinkOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      new GenMRRedSink2());
    opRules.put(new RuleRegExp(new String("R4"),
      FileSinkOperator.getOperatorName() + "%"),
      new GenMRFileSink1());
    opRules.put(new RuleRegExp(new String("R5"),
      UnionOperator.getOperatorName() + "%"),
      new GenMRUnion1());
    opRules.put(new RuleRegExp(new String("R6"),
      UnionOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      new GenMRRedSink3());
    opRules.put(new RuleRegExp(new String("R6"),
      MapJoinOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      new GenMRRedSink4());
    opRules.put(new RuleRegExp(new String("R7"),
      TableScanOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      MapJoinFactory.getTableScanMapJoin());
    opRules.put(new RuleRegExp(new String("R8"),
      ReduceSinkOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      MapJoinFactory.getReduceSinkMapJoin());
    opRules.put(new RuleRegExp(new String("R9"),
      UnionOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      MapJoinFactory.getUnionMapJoin());
    opRules.put(new RuleRegExp(new String("R10"),
      MapJoinOperator.getOperatorName() + "%.*" + MapJoinOperator.getOperatorName() + "%"),
      MapJoinFactory.getMapJoinMapJoin());
    opRules.put(new RuleRegExp(new String("R11"),
      MapJoinOperator.getOperatorName() + "%" + SelectOperator.getOperatorName() + "%"),
      MapJoinFactory.getMapJoin());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    // Create the lineage context
    LineageCtx lCtx = new LineageCtx(pctx);

    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1", TableScanOperator.getOperatorName() + "%"),
      OpProcFactory.getTSProc());
    opRules.put(new RuleRegExp("R2", ScriptOperator.getOperatorName() + "%"),
      OpProcFactory.getTransformProc());
    opRules.put(new RuleRegExp("R3", UDTFOperator.getOperatorName() + "%"),
      OpProcFactory.getTransformProc());
    opRules.put(new RuleRegExp("R4", SelectOperator.getOperatorName() + "%"),
      OpProcFactory.getSelProc());
    opRules.put(new RuleRegExp("R5", GroupByOperator.getOperatorName() + "%"),
      OpProcFactory.getGroupByProc());
    opRules.put(new RuleRegExp("R6", UnionOperator.getOperatorName() + "%"),
      OpProcFactory.getUnionProc());
    opRules.put(new RuleRegExp("R7",
      CommonJoinOperator.getOperatorName() + "%|" + MapJoinOperator.getOperatorName() + "%"),
      OpProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R8", ReduceSinkOperator.getOperatorName() + "%"),
      OpProcFactory.getReduceSinkProc());
    opRules.put(new RuleRegExp("R9", LateralViewJoinOperator.getOperatorName() + "%"),
      OpProcFactory.getLateralViewJoinProc());

    // The dispatcher fires the processor corresponding to the closest matching rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(OpProcFactory.getDefaultProc(), opRules, lCtx);
    GraphWalker ogw = new PreOrderWalker(disp);
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Examples of org.apache.hadoop.hive.ql.lib.RuleRegExp

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    // 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<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R0",
      MapJoinOperator.getOperatorName() + "%"),
      getCurrentMapJoin());
    opRules.put(new RuleRegExp("R1",
      MapJoinOperator.getOperatorName() + "%.*" + FileSinkOperator.getOperatorName() + "%"),
      getMapJoinFS());
    opRules.put(new RuleRegExp("R2",
      MapJoinOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"),
      getMapJoinDefault());
    opRules.put(new RuleRegExp("R4",
      MapJoinOperator.getOperatorName() + "%.*" + UnionOperator.getOperatorName() + "%"),
      getMapJoinDefault());

    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
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