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

Example 1 with TypeRule

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

the class PrunerUtils method walkExprTree.

/**
 * Walk expression tree for pruner generation.
 *
 * @param pred
 * @param ctx
 * @param colProc
 * @param fieldProc
 * @param genFuncProc
 * @param defProc
 * @return
 * @throws SemanticException
 */
public static Map<Node, Object> walkExprTree(ExprNodeDesc pred, NodeProcessorCtx ctx, SemanticNodeProcessor colProc, SemanticNodeProcessor fieldProc, SemanticNodeProcessor genFuncProc, SemanticNodeProcessor defProc) throws SemanticException {
    // 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<SemanticRule, SemanticNodeProcessor> exprRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    exprRules.put(new TypeRule(ExprNodeColumnDesc.class), colProc);
    exprRules.put(new TypeRule(ExprNodeFieldDesc.class), fieldProc);
    exprRules.put(new TypeRule(ExprNodeGenericFuncDesc.class), genFuncProc);
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(defProc, exprRules, ctx);
    SemanticGraphWalker egw = new DefaultGraphWalker(disp);
    List<Node> startNodes = new ArrayList<Node>();
    startNodes.add(pred);
    HashMap<Node, Object> outputMap = new HashMap<Node, Object>();
    egw.startWalking(startNodes, outputMap);
    return outputMap;
}

Example 2 with TypeRule

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

the class SparkCompiler method runJoinOptimizations.

private void runJoinOptimizations(OptimizeSparkProcContext procCtx) throws SemanticException {
    ParseContext pCtx = procCtx.getParseContext();
    Map<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    opRules.put(new TypeRule(JoinOperator.class), new SparkJoinOptimizer(pCtx));
    opRules.put(new TypeRule(MapJoinOperator.class), new SparkJoinHintOptimizer(pCtx));
    // 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 DefaultGraphWalker(disp);
    // Create a list of topop nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pCtx.getTopOps().values());
    ogw.startWalking(topNodes, null);
}

Example 3 with TypeRule

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

the class PrunerUtils method walkExprTree.

/**
 * Walk expression tree for pruner generation.
 *
 * @param pred
 * @param ctx
 * @param colProc
 * @param fieldProc
 * @param genFuncProc
 * @param defProc
 * @return
 * @throws SemanticException
 */
public static Map<Node, Object> walkExprTree(ExprNodeDesc pred, NodeProcessorCtx ctx, NodeProcessor colProc, NodeProcessor fieldProc, NodeProcessor genFuncProc, NodeProcessor defProc) throws SemanticException {
    // 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 TypeRule(ExprNodeColumnDesc.class), colProc);
    exprRules.put(new TypeRule(ExprNodeFieldDesc.class), fieldProc);
    exprRules.put(new TypeRule(ExprNodeGenericFuncDesc.class), genFuncProc);
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(defProc, exprRules, ctx);
    GraphWalker egw = new DefaultGraphWalker(disp);
    List<Node> startNodes = new ArrayList<Node>();
    startNodes.add(pred);
    HashMap<Node, Object> outputMap = new HashMap<Node, Object>();
    egw.startWalking(startNodes, outputMap);
    return outputMap;
}

Example 4 with TypeRule

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

the class SparkCompiler method generateTaskTreeHelper.

private void generateTaskTreeHelper(GenSparkProcContext procCtx, List<Node> topNodes) throws SemanticException {
    // 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<SemanticRule, SemanticNodeProcessor> opRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    GenSparkWork genSparkWork = new GenSparkWork(GenSparkUtils.getUtils());
    opRules.put(new RuleRegExp("Split Work - ReduceSink", ReduceSinkOperator.getOperatorName() + "%"), genSparkWork);
    opRules.put(new RuleRegExp("Split Work - SparkPartitionPruningSink", SparkPartitionPruningSinkOperator.getOperatorName() + "%"), genSparkWork);
    opRules.put(new TypeRule(MapJoinOperator.class), new SparkReduceSinkMapJoinProc());
    opRules.put(new RuleRegExp("Split Work + Move/Merge - FileSink", FileSinkOperator.getOperatorName() + "%"), new CompositeProcessor(new SparkFileSinkProcessor(), genSparkWork));
    opRules.put(new RuleRegExp("Handle Analyze Command", TableScanOperator.getOperatorName() + "%"), new SparkProcessAnalyzeTable(GenSparkUtils.getUtils()));
    opRules.put(new RuleRegExp("Remember union", UnionOperator.getOperatorName() + "%"), new SemanticNodeProcessor() {

        @Override
        public Object process(Node n, Stack<Node> s, NodeProcessorCtx procCtx, Object... os) throws SemanticException {
            GenSparkProcContext context = (GenSparkProcContext) procCtx;
            UnionOperator union = (UnionOperator) n;
            // simply need to remember that we've seen a union.
            context.currentUnionOperators.add(union);
            return null;
        }
    });
    /**
     *  SMB join case:   (Big)   (Small)  (Small)
     *                     TS       TS       TS
     *                      \       |       /
     *                       \      DS     DS
     *                         \   |    /
     *                         SMBJoinOP
     *
     * Some of the other processors are expecting only one traversal beyond SMBJoinOp.
     * We need to traverse from the big-table path only, and stop traversing on the
     * small-table path once we reach SMBJoinOp.
     * Also add some SMB join information to the context, so we can properly annotate
     * the MapWork later on.
     */
    opRules.put(new TypeRule(SMBMapJoinOperator.class), new SemanticNodeProcessor() {

        @Override
        public Object process(Node currNode, Stack<Node> stack, NodeProcessorCtx procCtx, Object... os) throws SemanticException {
            GenSparkProcContext context = (GenSparkProcContext) procCtx;
            SMBMapJoinOperator currSmbNode = (SMBMapJoinOperator) currNode;
            SparkSMBMapJoinInfo smbMapJoinCtx = context.smbMapJoinCtxMap.get(currSmbNode);
            if (smbMapJoinCtx == null) {
                smbMapJoinCtx = new SparkSMBMapJoinInfo();
                context.smbMapJoinCtxMap.put(currSmbNode, smbMapJoinCtx);
            }
            for (Node stackNode : stack) {
                if (stackNode instanceof DummyStoreOperator) {
                    // If coming from small-table side, do some book-keeping, and skip traversal.
                    smbMapJoinCtx.smallTableRootOps.add(context.currentRootOperator);
                    return true;
                }
            }
            // If coming from big-table side, do some book-keeping, and continue traversal
            smbMapJoinCtx.bigTableRootOp = context.currentRootOperator;
            return false;
        }
    });
    // 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 GenSparkWorkWalker(disp, procCtx);
    ogw.startWalking(topNodes, null);
}

Example 5 with TypeRule

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

the class ExprWalkerProcFactory method extractPushdownPreds.

/**
 * Extracts pushdown predicates from the given list of predicate expression.
 *
 * @param opContext
 *          operator context used for resolving column references
 * @param op
 *          operator of the predicates being processed
 * @param preds
 * @return The expression walker information
 * @throws SemanticException
 */
public static ExprWalkerInfo extractPushdownPreds(OpWalkerInfo opContext, Operator<? extends OperatorDesc> op, List<ExprNodeDesc> preds) throws SemanticException {
    // Create the walker, the rules dispatcher and the context.
    ExprWalkerInfo exprContext = new ExprWalkerInfo(op);
    // 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<SemanticRule, SemanticNodeProcessor> exprRules = new LinkedHashMap<SemanticRule, SemanticNodeProcessor>();
    exprRules.put(new TypeRule(ExprNodeColumnDesc.class), getColumnProcessor());
    exprRules.put(new TypeRule(ExprNodeFieldDesc.class), getFieldProcessor());
    exprRules.put(new TypeRule(ExprNodeGenericFuncDesc.class), getGenericFuncProcessor());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    SemanticDispatcher disp = new DefaultRuleDispatcher(getDefaultExprProcessor(), exprRules, exprContext);
    SemanticGraphWalker egw = new ExpressionWalker(disp);
    List<Node> startNodes = new ArrayList<Node>();
    List<ExprNodeDesc> clonedPreds = new ArrayList<ExprNodeDesc>();
    for (ExprNodeDesc node : preds) {
        ExprNodeDesc clone = node.clone();
        clonedPreds.add(clone);
        exprContext.getNewToOldExprMap().put(clone, node);
    }
    startNodes.addAll(clonedPreds);
    egw.startWalking(startNodes, null);
    HiveConf conf = opContext.getParseContext().getConf();
    // check the root expression for final candidates
    for (ExprNodeDesc pred : clonedPreds) {
        extractFinalCandidates(pred, exprContext, conf);
    }
    return exprContext;
}