Examples with DynamicPartitionPruningOptimization org.apache.hadoop.hive.ql.optimizer.DynamicPartitionPruningOptimization used on opensource projects

Example 1 with DynamicPartitionPruningOptimization

use of org.apache.hadoop.hive.ql.optimizer.DynamicPartitionPruningOptimization in project hive by apache.

the class TezCompiler method runDynamicPartitionPruning.

private void runDynamicPartitionPruning(OptimizeTezProcContext procCtx, Set<ReadEntity> inputs, Set<WriteEntity> outputs) throws SemanticException {
    if (!procCtx.conf.getBoolVar(ConfVars.TEZ_DYNAMIC_PARTITION_PRUNING)) {
        return;
    }
    // Sequence of TableScan operators to be walked
    Deque<Operator<?>> deque = new LinkedList<Operator<?>>();
    deque.addAll(procCtx.parseContext.getTopOps().values());
    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp(new String("Dynamic Partition Pruning"), FilterOperator.getOperatorName() + "%"), new DynamicPartitionPruningOptimization());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(null, opRules, procCtx);
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(procCtx.parseContext.getTopOps().values());
    GraphWalker ogw = new ForwardWalker(disp);
    ogw.startWalking(topNodes, null);
}

Example 2 with DynamicPartitionPruningOptimization

use of org.apache.hadoop.hive.ql.optimizer.DynamicPartitionPruningOptimization in project hive by apache.

the class SparkCompiler method runDynamicPartitionPruning.

private void runDynamicPartitionPruning(OptimizeSparkProcContext procCtx) throws SemanticException {
    if (!conf.isSparkDPPAny()) {
        return;
    }
    ParseContext parseContext = procCtx.getParseContext();
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp(new String("Dynamic Partition Pruning"), FilterOperator.getOperatorName() + "%"), new DynamicPartitionPruningOptimization());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(null, opRules, procCtx);
    SemanticGraphWalker ogw = new ForwardWalker(disp);
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(parseContext.getTopOps().values());
    ogw.startWalking(topNodes, null);
}

Example 3 with DynamicPartitionPruningOptimization

use of org.apache.hadoop.hive.ql.optimizer.DynamicPartitionPruningOptimization in project hive by apache.

the class TezCompiler method runDynamicPartitionPruning.

private void runDynamicPartitionPruning(OptimizeTezProcContext procCtx) throws SemanticException {
    if (!procCtx.conf.getBoolVar(ConfVars.TEZ_DYNAMIC_PARTITION_PRUNING)) {
        return;
    }
    // Sequence of TableScan operators to be walked
    Deque<Operator<?>> deque = new LinkedList<Operator<?>>();
    deque.addAll(procCtx.parseContext.getTopOps().values());
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new RuleRegExp(new String("Dynamic Partition Pruning"), FilterOperator.getOperatorName() + "%"), new DynamicPartitionPruningOptimization());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(null, opRules, procCtx);
    List<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(procCtx.parseContext.getTopOps().values());
    SemanticGraphWalker ogw = new ForwardWalker(disp);
    ogw.startWalking(topNodes, null);
}