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

Example 46 with RuleRegExp

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

the class ColumnPruner method transform.

/**
 * Transform the query tree. For each table under consideration, check if all
 * columns are needed. If not, only select the operators needed at the
 * beginning and proceed.
 *
 * @param pactx
 *          the current parse context
 */
@Override
public ParseContext transform(ParseContext pactx) throws SemanticException {
    pGraphContext = pactx;
    // generate pruned column list for all relevant operators
    ColumnPrunerProcCtx cppCtx = new ColumnPrunerProcCtx(pactx);
    // 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> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1", FilterOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getFilterProc());
    opRules.put(new RuleRegExp("R2", GroupByOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getGroupByProc());
    opRules.put(new RuleRegExp("R3", ReduceSinkOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getReduceSinkProc());
    opRules.put(new RuleRegExp("R4", SelectOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getSelectProc());
    opRules.put(new RuleRegExp("R5", CommonJoinOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getJoinProc());
    opRules.put(new RuleRegExp("R6", MapJoinOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getMapJoinProc());
    opRules.put(new RuleRegExp("R7", TableScanOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getTableScanProc());
    opRules.put(new RuleRegExp("R8", LateralViewJoinOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getLateralViewJoinProc());
    opRules.put(new RuleRegExp("R9", LateralViewForwardOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getLateralViewForwardProc());
    opRules.put(new RuleRegExp("R10", PTFOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getPTFProc());
    opRules.put(new RuleRegExp("R11", ScriptOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getScriptProc());
    opRules.put(new RuleRegExp("R12", LimitOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getLimitProc());
    opRules.put(new RuleRegExp("R13", UnionOperator.getOperatorName() + "%"), ColumnPrunerProcFactory.getUnionProc());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(ColumnPrunerProcFactory.getDefaultProc(), opRules, cppCtx);
    GraphWalker ogw = new ColumnPrunerWalker(disp);
    // Create a list of topop nodes
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pGraphContext.getTopOps().values());
    ogw.startWalking(topNodes, null);
    // set it back so that column pruner in the optimizer will not do the
    // view column authorization again even if it is triggered again.
    pGraphContext.setNeedViewColumnAuthorization(false);
    return pGraphContext;
}

Example 47 with RuleRegExp

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

the class IdentityProjectRemover method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    // 0. We check the conditions to apply this transformation,
    // if we do not meet them we bail out
    final boolean cboEnabled = HiveConf.getBoolVar(pctx.getConf(), HiveConf.ConfVars.HIVE_CBO_ENABLED);
    final boolean returnPathEnabled = HiveConf.getBoolVar(pctx.getConf(), HiveConf.ConfVars.HIVE_CBO_RETPATH_HIVEOP);
    final boolean cboSucceeded = pctx.getContext().isCboSucceeded();
    if (cboEnabled && returnPathEnabled && cboSucceeded) {
        return pctx;
    }
    // 1. We apply the transformation
    Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R1", "(" + SelectOperator.getOperatorName() + "%)"), new ProjectRemover());
    GraphWalker ogw = new DefaultGraphWalker(new DefaultRuleDispatcher(null, opRules, null));
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(pctx.getTopOps().values());
    ogw.startWalking(topNodes, null);
    return pctx;
}

Example 48 with RuleRegExp

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

the class MapJoinProcessor method transform.

/**
 * Transform the query tree. For each join, check if it is a map-side join (user specified). If
 * yes, convert it to a map-side join.
 *
 * @param pactx
 *          current parse context
 */
@Override
public ParseContext transform(ParseContext pactx) throws SemanticException {
    List<MapJoinOperator> listMapJoinOps = new ArrayList<MapJoinOperator>();
    // traverse all the joins and convert them if necessary
    if (pactx.getJoinOps() != null) {
        Set<JoinOperator> joinMap = new HashSet<JoinOperator>();
        Set<MapJoinOperator> mapJoinMap = pactx.getMapJoinOps();
        if (mapJoinMap == null) {
            mapJoinMap = new HashSet<MapJoinOperator>();
            pactx.setMapJoinOps(mapJoinMap);
        }
        Iterator<JoinOperator> joinCtxIter = pactx.getJoinOps().iterator();
        while (joinCtxIter.hasNext()) {
            JoinOperator joinOp = joinCtxIter.next();
            int mapJoinPos = mapSideJoin(joinOp);
            if (mapJoinPos >= 0) {
                MapJoinOperator mapJoinOp = generateMapJoinOperator(pactx, joinOp, mapJoinPos);
                listMapJoinOps.add(mapJoinOp);
                mapJoinOp.getConf().setQBJoinTreeProps(joinOp.getConf());
                mapJoinMap.add(mapJoinOp);
            } else {
                joinOp.getConf().setQBJoinTreeProps(joinOp.getConf());
                joinMap.add(joinOp);
            }
        }
        // store the new joinContext
        pactx.setJoinOps(joinMap);
    }
    // Go over the list and find if a reducer is not needed
    List<AbstractMapJoinOperator<? extends MapJoinDesc>> listMapJoinOpsNoRed = new ArrayList<AbstractMapJoinOperator<? extends MapJoinDesc>>();
    // 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> opRules = new LinkedHashMap<Rule, NodeProcessor>();
    opRules.put(new RuleRegExp("R0", MapJoinOperator.getOperatorName() + "%"), getCurrentMapJoin());
    opRules.put(new RuleRegExp("R1", MapJoinOperator.getOperatorName() + "%.*" + FileSinkOperator.getOperatorName() + "%"), getMapJoinFS());
    opRules.put(new RuleRegExp("R2", MapJoinOperator.getOperatorName() + "%.*" + ReduceSinkOperator.getOperatorName() + "%"), getMapJoinDefault());
    opRules.put(new RuleRegExp("R4", MapJoinOperator.getOperatorName() + "%.*" + UnionOperator.getOperatorName() + "%"), getMapJoinDefault());
    // The dispatcher fires the processor corresponding to the closest matching
    // rule and passes the context along
    Dispatcher disp = new DefaultRuleDispatcher(getDefault(), opRules, new MapJoinWalkerCtx(listMapJoinOpsNoRed, pactx));
    GraphWalker ogw = new GenMapRedWalker(disp);
    ArrayList<Node> topNodes = new ArrayList<Node>();
    topNodes.addAll(listMapJoinOps);
    ogw.startWalking(topNodes, null);
    pactx.setListMapJoinOpsNoReducer(listMapJoinOpsNoRed);
    return pactx;
}

Example 49 with RuleRegExp

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

the class RedundantDynamicPruningConditionsRemoval method transform.

/**
 * Transform the query tree.
 *
 * @param pctx the current parse context
 */
@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    // Make sure semijoin is not enabled. If it is, then do not remove the dynamic partition pruning predicates.
    if (!pctx.getConf().getBoolVar(HiveConf.ConfVars.TEZ_DYNAMIC_SEMIJOIN_REDUCTION)) {
        Map<Rule, NodeProcessor> opRules = new LinkedHashMap<Rule, NodeProcessor>();
        opRules.put(new RuleRegExp("R1", TableScanOperator.getOperatorName() + "%" + FilterOperator.getOperatorName() + "%"), new FilterTransformer());
        Dispatcher disp = new DefaultRuleDispatcher(null, opRules, null);
        GraphWalker ogw = new DefaultGraphWalker(disp);
        List<Node> topNodes = new ArrayList<Node>();
        topNodes.addAll(pctx.getTopOps().values());
        ogw.startWalking(topNodes, null);
    }
    return pctx;
}

Example 50 with RuleRegExp

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

the class TablePropertyEnrichmentOptimizer method transform.

@Override
public ParseContext transform(ParseContext pctx) throws SemanticException {
    LOG.info("TablePropertyEnrichmentOptimizer::transform().");
    Map<Rule, NodeProcessor> opRules = Maps.newLinkedHashMap();
    opRules.put(new RuleRegExp("R1", TableScanOperator.getOperatorName() + "%"), new Processor());
    WalkerCtx context = new WalkerCtx(pctx.getConf());
    Dispatcher disp = new DefaultRuleDispatcher(null, opRules, context);
    List<Node> topNodes = Lists.newArrayList();
    topNodes.addAll(pctx.getTopOps().values());
    GraphWalker walker = new PreOrderWalker(disp);
    walker.startWalking(topNodes, null);
    LOG.info("TablePropertyEnrichmentOptimizer::transform() complete!");
    return pctx;
}