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

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

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        RewriteCanApplyProcFactory.canApplyOnSelectOperator());

    // 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 PreOrderWalker(disp);

    // Create a list of topop nodes
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.add(topOp);

    try {
      ogw.startWalking(topNodes, null);
    } catch (SemanticException e) {
      LOG.error("Exception in walking operator tree. Rewrite variables not populated");
      LOG.error(org.apache.hadoop.util.StringUtils.stringifyException(e));
      throw new SemanticException(e.getMessage(), e);
    }
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      opRules.put(new RuleRegExp("R2", "GBY%.*FS%"), new FileSinkProcessor());

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

      // Create a list of topOp nodes
      ArrayList<Node> topNodes = new ArrayList<Node>();
      // Get the top Nodes for this map-reduce task
      for (Operator<? extends Serializable>
           workOperator : topOperators) {
        if (parseContext.getTopOps().values().contains(workOperator)) {
          topNodes.add(workOperator);
        }
      }

      if (task.getReducer() != null) {
        topNodes.add(task.getReducer());
      }
     
      ogw.startWalking(topNodes, null);

      LOG.info(String.format("Found %d metadata only table scans",
          walkerCtx.getMetadataOnlyTableScans().size()));
      Iterator<TableScanOperator> iterator
        = walkerCtx.getMetadataOnlyTableScans().iterator();
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      opRules.put(new RuleRegExp("R2", "GBY%.*FS%"), new FileSinkProcessor());

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

      // Create a list of topOp nodes
      ArrayList<Node> topNodes = new ArrayList<Node>();
      // Get the top Nodes for this map-reduce task
      for (Operator<? extends Serializable>
           workOperator : topOperators) {
        if (parseContext.getTopOps().values().contains(workOperator)) {
          topNodes.add(workOperator);
        }
      }

      if (task.getReducer() != null) {
        topNodes.add(task.getReducer());
      }

      ogw.startWalking(topNodes, null);

      LOG.info(String.format("Found %d metadata only table scans",
          walkerCtx.getMetadataOnlyTableScans().size()));
      Iterator<TableScanOperator> iterator
        = walkerCtx.getMetadataOnlyTableScans().iterator();
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    // The dispatcher fires the processor for the matching rule and passes the
    // context along
    UnionProcContext uCtx = new UnionProcContext();
    Dispatcher disp = new DefaultRuleDispatcher(UnionProcFactory.getNoUnion(),
        opRules, uCtx);
    GraphWalker ogw = new PreOrderWalker(disp);

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

    return pCtx;
  }
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    TransitiveContext context = new TransitiveContext();
    Dispatcher disp = new DefaultRuleDispatcher(null, opRules, context);
    GraphWalker ogw = new PreOrderWalker(disp);

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

    Map<ReduceSinkOperator, List<ExprNodeDesc>> newFilters = context.getNewfilters();

    // insert new filter between RS and parent of RS
    for (Map.Entry<ReduceSinkOperator, List<ExprNodeDesc>> entry : newFilters.entrySet()) {
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    if(!isNoArgumentMacro) {
      /*
       * Walk down expression to see which arguments are actually used.
       */
      Node expression = (Node) ast.getChild(2);
      PreOrderWalker walker = new PreOrderWalker(new Dispatcher() {
        @Override
        public Object dispatch(Node nd, Stack<Node> stack, Object... nodeOutputs)
            throws SemanticException {
          if(nd instanceof ASTNode) {
            ASTNode node = (ASTNode)nd;
            if(node.getType() == HiveParser.TOK_TABLE_OR_COL) {
              actualColumnNames.add(node.getChild(0).getText());
            }
          }
          return null;
        }
      });
      walker.startWalking(Collections.singletonList(expression), null);
    }
    for (FieldSchema argument : arguments) {
      TypeInfo colType =
          TypeInfoUtils.getTypeInfoFromTypeString(argument.getType());
      rowResolver.put("", argument.getName(),
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    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(StatsRulesProcFactory.getDefaultRule(), opRules,
        aspCtx);
    GraphWalker ogw = new PreOrderWalker(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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    opRules.put(new RuleRegExp("R10", PTFOperator.getOperatorName() + "%"),
        OpProcFactory.getTransformProc());

    // 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);

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

    // Transfer the index from the lineage context to the session state.
    if (SessionState.get() != null) {
      SessionState.get().getLineageState().setIndex(lCtx.getIndex());
    }
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      opRules.put(new RuleRegExp("R1", TableScanOperator.getOperatorName() + ".*" +
          ReduceSinkOperator.getOperatorName()), vnp);
      opRules.put(new RuleRegExp("R2", TableScanOperator.getOperatorName() + ".*"
          + FileSinkOperator.getOperatorName()), vnp);
      Dispatcher disp = new DefaultRuleDispatcher(vnp, opRules, null);
      GraphWalker ogw = new PreOrderWalker(disp);
      // iterator the mapper operator tree
      ArrayList<Node> topNodes = new ArrayList<Node>();
      topNodes.addAll(mapWork.getAliasToWork().values());
      HashMap<Node, Object> nodeOutput = new HashMap<Node, Object>();
      ogw.startWalking(topNodes, nodeOutput);

      Map<String, Map<Integer, String>> columnVectorTypes = vnp.getScratchColumnVectorTypes();
      mapWork.setScratchColumnVectorTypes(columnVectorTypes);
      Map<String, Map<String, Integer>> columnMap = vnp.getScratchColumnMap();
      mapWork.setScratchColumnMap(columnMap);
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      // 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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Related Classes of org.apache.hadoop.hive.ql.lib.PreOrderWalker

  • org.apache.hadoop.hive.ql.optimizer.index.RewriteCanApplyCtx
  • org.apache.hadoop.hive.ql.optimizer.lineage.Generator
  • org.apache.hadoop.hive.ql.optimizer.metainfo.annotation.AnnotateWithOpTraits
  • org.apache.hadoop.hive.ql.optimizer.physical.BucketingSortingInferenceOptimizer
  • org.apache.hadoop.hive.ql.optimizer.physical.MetadataOnlyOptimizer$MetadataOnlyTaskDispatcher
  • org.apache.hadoop.hive.ql.optimizer.physical.NullScanTaskDispatcher
  • org.apache.hadoop.hive.ql.optimizer.physical.Vectorizer$VectorizationDispatcher
  • org.apache.hadoop.hive.ql.optimizer.SortedDynPartitionOptimizer
  • org.apache.hadoop.hive.ql.optimizer.stats.annotation.AnnotateWithStatistics
  • org.apache.hadoop.hive.ql.optimizer.unionproc.UnionProcessor
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