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

Example 16 with SemanticDispatcher

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

the class SparkSkewJoinResolver method resolve.

@Override
public PhysicalContext resolve(PhysicalContext pctx) throws SemanticException {
    SparkSkewJoinProcFactory.getVisitedJoinOp().clear();
    SemanticDispatcher disp = new SparkSkewJoinTaskDispatcher(pctx);
    // since we may split current task, use a pre-order walker
    SemanticGraphWalker ogw = new PreOrderWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getRootTasks());
    ogw.startWalking(topNodes, null);
    return pctx;
}

Example 17 with SemanticDispatcher

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

the class SkewJoinResolver method resolve.

@Override
public PhysicalContext resolve(PhysicalContext pctx) throws SemanticException {
    SemanticDispatcher disp = new SkewJoinTaskDispatcher(pctx);
    SemanticGraphWalker ogw = new DefaultGraphWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getRootTasks());
    ogw.startWalking(topNodes, null);
    return pctx;
}

Example 18 with SemanticDispatcher

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

the class PredicatePushDown method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    pGraphContext = pctx;
    // create a the context for walking operators
    OpWalkerInfo opWalkerInfo = new OpWalkerInfo(pGraphContext);
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp("R1", FilterOperator.getOperatorName() + "%"), OpProcFactory.getFilterProc());
    opRules.put(new RuleRegExp("R2", PTFOperator.getOperatorName() + "%"), OpProcFactory.getPTFProc());
    opRules.put(new RuleRegExp("R3", CommonJoinOperator.getOperatorName() + "%"), OpProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R4", TableScanOperator.getOperatorName() + "%"), OpProcFactory.getTSProc());
    opRules.put(new RuleRegExp("R5", 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());
    opRules.put(new RuleRegExp("R9", LateralViewJoinOperator.getOperatorName() + "%"), OpProcFactory.getLVJProc());
    opRules.put(new RuleRegExp("R10", ReduceSinkOperator.getOperatorName() + "%"), OpProcFactory.getRSProc());
    opRules.put(new RuleRegExp("R11", GroupByOperator.getOperatorName() + "%"), OpProcFactory.getGBYProc());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(OpProcFactory.getDefaultProc(), opRules, opWalkerInfo);
    SemanticGraphWalker 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);
    if (LOG.isDebugEnabled()) {
        LOG.debug("After PPD:\n" + Operator.toString(pctx.getTopOps().values()));
    }
    return pGraphContext;
}

Example 19 with SemanticDispatcher

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

the class SimplePredicatePushDown method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    pGraphContext = pctx;
    // create a the context for walking operators
    OpWalkerInfo opWalkerInfo = new OpWalkerInfo(pGraphContext);
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp("R1", FilterOperator.getOperatorName() + "%"), OpProcFactory.getFilterSyntheticJoinPredicateProc());
    opRules.put(new RuleRegExp("R2", PTFOperator.getOperatorName() + "%"), OpProcFactory.getPTFProc());
    opRules.put(new RuleRegExp("R3", CommonJoinOperator.getOperatorName() + "%"), OpProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R4", TableScanOperator.getOperatorName() + "%"), OpProcFactory.getTSProc());
    opRules.put(new RuleRegExp("R5", 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());
    opRules.put(new RuleRegExp("R9", LateralViewJoinOperator.getOperatorName() + "%"), OpProcFactory.getLVJProc());
    opRules.put(new RuleRegExp("R10", ReduceSinkOperator.getOperatorName() + "%"), OpProcFactory.getRSProc());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(OpProcFactory.getDefaultProc(), opRules, opWalkerInfo);
    SemanticGraphWalker 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);
    if (LOG.isDebugEnabled()) {
        LOG.debug("After PPD:\n" + Operator.toString(pctx.getTopOps().values()));
    }
    return pGraphContext;
}

Example 20 with SemanticDispatcher

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

the class PredicateTransitivePropagate method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    pGraphContext = pctx;
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp("R1", "(" + FilterOperator.getOperatorName() + "%" + ReduceSinkOperator.getOperatorName() + "%" + JoinOperator.getOperatorName() + "%)"), new JoinTransitive());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    TransitiveContext context = new TransitiveContext();
    SemanticDispatcher disp = new DefaultRuleDispatcher(null, opRules, context);
    SemanticGraphWalker ogw = new LevelOrderWalker(disp, 2);
    // 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()) {
        ReduceSinkOperator reducer = entry.getKey();
        Operator<?> parent = reducer.getParentOperators().get(0);
        List<ExprNodeDesc> exprs = entry.getValue();
        if (parent instanceof FilterOperator) {
            exprs = ExprNodeDescUtils.split(((FilterOperator) parent).getConf().getPredicate(), exprs);
            ExprNodeDesc merged = ExprNodeDescUtils.mergePredicates(exprs);
            ((FilterOperator) parent).getConf().setPredicate(merged);
        } else {
            ExprNodeDesc merged = ExprNodeDescUtils.mergePredicates(exprs);
            RowSchema parentRS = parent.getSchema();
            Operator<FilterDesc> newFilter = createFilter(reducer, parent, parentRS, merged);
        }
    }
    return pGraphContext;
}