Package org.apache.hadoop.hive.ql.optimizer.unionproc

Examples of org.apache.hadoop.hive.ql.optimizer.unionproc.UnionProcContext$UnionParseContext

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  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx opProcCtx, Object... nodeOutputs) throws SemanticException {
    ReduceSinkOperator op = (ReduceSinkOperator)nd;
    GenMRProcContext ctx = (GenMRProcContext)opProcCtx;

    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // union was map only - no special processing needed
    if (uCtx.isMapOnlySubq())
      return (new GenMRRedSink1()).process(nd, stack, opProcCtx, nodeOutputs);

    // union consisted on a bunch of map-reduce jobs, and it has been split at the union
    Operator<? extends Serializable> reducer = op.getChildOperators().get(0);
    Map<Operator<? extends Serializable>, GenMapRedCtx> mapCurrCtx = ctx.getMapCurrCtx();
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   */
  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx opProcCtx, Object... nodeOutputs) throws SemanticException {
    UnionOperator union = (UnionOperator)nd;
    GenMRProcContext ctx = (GenMRProcContext)opProcCtx;
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // Map-only subqueries can be optimized in future to not write to a file in future
    Map<Operator<? extends Serializable>, GenMapRedCtx> mapCurrCtx = ctx.getMapCurrCtx();

    // The plan needs to be broken only if one of the sub-queries involve a map-reduce job
    if (uCtx.isMapOnlySubq()) {
      mapCurrCtx.put((Operator<? extends Serializable>)nd, new GenMapRedCtx(ctx.getCurrTask(), ctx.getCurrTopOp(), ctx.getCurrAliasId()));
      return null;
    }

    ctx.setCurrUnionOp(union);

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);
    assert uPrsCtx != null;

    Task<? extends Serializable> currTask = ctx.getCurrTask();
    int pos = UnionProcFactory.getPositionParent(union, stack);

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      Object... nodeOutputs) throws SemanticException {
    ReduceSinkOperator op = (ReduceSinkOperator) nd;
    GenMRProcContext ctx = (GenMRProcContext) opProcCtx;

    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // union was map only - no special processing needed
    if (uCtx.isMapOnlySubq()) {
      return (new GenMRRedSink1()).process(nd, stack, opProcCtx, nodeOutputs);
    }

    // union consisted on a bunch of map-reduce jobs, and it has been split at
    // the union
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  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx opProcCtx,
      Object... nodeOutputs) throws SemanticException {
    UnionOperator union = (UnionOperator) nd;
    GenMRProcContext ctx = (GenMRProcContext) opProcCtx;
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // Map-only subqueries can be optimized in future to not write to a file in
    // future
    Map<Operator<? extends Serializable>, GenMapRedCtx> mapCurrCtx = ctx
        .getMapCurrCtx();

    // The plan needs to be broken only if one of the sub-queries involve a
    // map-reduce job
    if (uCtx.isMapOnlySubq()) {
      // merge currTask from multiple topOps
      HashMap<Operator<? extends Serializable>, Task<? extends Serializable>> opTaskMap = ctx
          .getOpTaskMap();
      if (opTaskMap != null && opTaskMap.size() > 0) {
        Task<? extends Serializable> tsk = opTaskMap.get(null);
        if (tsk != null) {
          ctx.setCurrTask(tsk);
        }
      }

      UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);
      if ((uPrsCtx != null) && (uPrsCtx.getMapJoinQuery())) {
        GenMapRedUtils.mergeMapJoinUnion(union, ctx, UnionProcFactory
            .getPositionParent(union, stack));
      } else {
        mapCurrCtx.put((Operator<? extends Serializable>) nd, new GenMapRedCtx(
            ctx.getCurrTask(), ctx.getCurrTopOp(), ctx.getCurrAliasId()));
      }
      return null;
    }

    ctx.setCurrUnionOp(union);

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);
    assert uPrsCtx != null;

    Task<? extends Serializable> currTask = ctx.getCurrTask();
    int pos = UnionProcFactory.getPositionParent(union, stack);
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    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procCtx,
        Object... nodeOutputs) throws SemanticException {
      GenMRProcContext ctx = (GenMRProcContext) procCtx;

      ParseContext parseCtx = ctx.getParseCtx();
      UnionProcContext uCtx = parseCtx.getUCtx();

      // union was map only - no special processing needed
      if (uCtx.isMapOnlySubq()) {
        return (new TableScanMapJoin())
            .process(nd, stack, procCtx, nodeOutputs);
      }

      UnionOperator currUnion = ctx.getCurrUnionOp();
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  }

  public static void mergeMapJoinUnion(UnionOperator union,
      GenMRProcContext ctx, int pos) throws SemanticException {
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);
    assert uPrsCtx != null;

    Task<? extends Serializable> currTask = ctx.getCurrTask();

    GenMRUnionCtx uCtxTask = ctx.getUnionTask(union);
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  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx opProcCtx,
      Object... nodeOutputs) throws SemanticException {
    UnionOperator union = (UnionOperator) nd;
    GenMRProcContext ctx = (GenMRProcContext) opProcCtx;
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // Map-only subqueries can be optimized in future to not write to a file in
    // future
    Map<Operator<? extends Serializable>, GenMapRedCtx> mapCurrCtx = ctx.getMapCurrCtx();

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);

    ctx.setCurrUnionOp(union);
    // The plan needs to be broken only if one of the sub-queries involve a
    // map-reduce job
    if (uPrsCtx.allMapOnlySubQ()) {
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  }

  public static void mergeMapJoinUnion(UnionOperator union,
      GenMRProcContext ctx, int pos) throws SemanticException {
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);
    assert uPrsCtx != null;

    Task<? extends Serializable> currTask = ctx.getCurrTask();

    GenMRUnionCtx uCtxTask = ctx.getUnionTask(union);
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  public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx opProcCtx,
      Object... nodeOutputs) throws SemanticException {
    UnionOperator union = (UnionOperator) nd;
    GenMRProcContext ctx = (GenMRProcContext) opProcCtx;
    ParseContext parseCtx = ctx.getParseCtx();
    UnionProcContext uCtx = parseCtx.getUCtx();

    // Map-only subqueries can be optimized in future to not write to a file in
    // future
    Map<Operator<? extends OperatorDesc>, GenMapRedCtx> mapCurrCtx = ctx.getMapCurrCtx();

    if (union.getConf().isAllInputsInSameReducer()) {
      // All inputs of this UnionOperator are in the same Reducer.
      // We do not need to break the operator tree.
      mapCurrCtx.put((Operator<? extends OperatorDesc>) nd,
        new GenMapRedCtx(ctx.getCurrTask(),ctx.getCurrAliasId()));
      return null;
    }

    UnionParseContext uPrsCtx = uCtx.getUnionParseContext(union);

    ctx.setCurrUnionOp(union);
    // The plan needs to be broken only if one of the sub-queries involve a
    // map-reduce job
    if (uPrsCtx.allMapOnlySubQ()) {
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    public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procCtx,
        Object... nodeOutputs) throws SemanticException {
      GenMRProcContext ctx = (GenMRProcContext) procCtx;

      ParseContext parseCtx = ctx.getParseCtx();
      UnionProcContext uCtx = parseCtx.getUCtx();

      // union was map only - no special processing needed
      if (uCtx.isMapOnlySubq()) {
        return (new TableScanMapJoin())
            .process(nd, stack, procCtx, nodeOutputs);
      }

      UnionOperator currUnion = ctx.getCurrUnionOp();
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Related Classes of org.apache.hadoop.hive.ql.optimizer.unionproc.UnionProcContext$UnionParseContext

  • org.apache.hadoop.hive.ql.optimizer.GenMapRedUtils
  • org.apache.hadoop.hive.ql.optimizer.GenMRRedSink3
  • org.apache.hadoop.hive.ql.optimizer.GenMRUnion1
  • org.apache.hadoop.hive.ql.optimizer.MapJoinFactory$UnionMapJoin
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