Examples with MapJoinDesc org.apache.hadoop.hive.ql.plan.MapJoinDesc used on opensource projects

Example 6 with MapJoinDesc

use of org.apache.hadoop.hive.ql.plan.MapJoinDesc in project hive by apache.

the class ConvertJoinMapJoin method convertJoinSMBJoin.

// replaces the join operator with a new CommonJoinOperator, removes the
// parent reduce sinks
private void convertJoinSMBJoin(JoinOperator joinOp, OptimizeTezProcContext context, int mapJoinConversionPos, int numBuckets, boolean adjustParentsChildren) throws SemanticException {
    MapJoinDesc mapJoinDesc = null;
    if (adjustParentsChildren) {
        mapJoinDesc = MapJoinProcessor.getMapJoinDesc(context.conf, joinOp, joinOp.getConf().isLeftInputJoin(), joinOp.getConf().getBaseSrc(), joinOp.getConf().getMapAliases(), mapJoinConversionPos, true);
    } else {
        JoinDesc joinDesc = joinOp.getConf();
        // retain the original join desc in the map join.
        mapJoinDesc = new MapJoinDesc(MapJoinProcessor.getKeys(joinOp.getConf().isLeftInputJoin(), joinOp.getConf().getBaseSrc(), joinOp).getSecond(), null, joinDesc.getExprs(), null, null, joinDesc.getOutputColumnNames(), mapJoinConversionPos, joinDesc.getConds(), joinDesc.getFilters(), joinDesc.getNoOuterJoin(), null);
        mapJoinDesc.setNullSafes(joinDesc.getNullSafes());
        mapJoinDesc.setFilterMap(joinDesc.getFilterMap());
        mapJoinDesc.setResidualFilterExprs(joinDesc.getResidualFilterExprs());
        mapJoinDesc.resetOrder();
    }
    CommonMergeJoinOperator mergeJoinOp = (CommonMergeJoinOperator) OperatorFactory.get(joinOp.getCompilationOpContext(), new CommonMergeJoinDesc(numBuckets, mapJoinConversionPos, mapJoinDesc), joinOp.getSchema());
    int numReduceSinks = joinOp.getOpTraits().getNumReduceSinks();
    OpTraits opTraits = new OpTraits(joinOp.getOpTraits().getBucketColNames(), numBuckets, joinOp.getOpTraits().getSortCols(), numReduceSinks);
    mergeJoinOp.setOpTraits(opTraits);
    mergeJoinOp.setStatistics(joinOp.getStatistics());
    for (Operator<? extends OperatorDesc> parentOp : joinOp.getParentOperators()) {
        int pos = parentOp.getChildOperators().indexOf(joinOp);
        parentOp.getChildOperators().remove(pos);
        parentOp.getChildOperators().add(pos, mergeJoinOp);
    }
    for (Operator<? extends OperatorDesc> childOp : joinOp.getChildOperators()) {
        int pos = childOp.getParentOperators().indexOf(joinOp);
        childOp.getParentOperators().remove(pos);
        childOp.getParentOperators().add(pos, mergeJoinOp);
    }
    List<Operator<? extends OperatorDesc>> childOperators = mergeJoinOp.getChildOperators();
    List<Operator<? extends OperatorDesc>> parentOperators = mergeJoinOp.getParentOperators();
    childOperators.clear();
    parentOperators.clear();
    childOperators.addAll(joinOp.getChildOperators());
    parentOperators.addAll(joinOp.getParentOperators());
    mergeJoinOp.getConf().setGenJoinKeys(false);
    if (adjustParentsChildren) {
        mergeJoinOp.getConf().setGenJoinKeys(true);
        List<Operator<? extends OperatorDesc>> newParentOpList = new ArrayList<Operator<? extends OperatorDesc>>();
        for (Operator<? extends OperatorDesc> parentOp : mergeJoinOp.getParentOperators()) {
            for (Operator<? extends OperatorDesc> grandParentOp : parentOp.getParentOperators()) {
                grandParentOp.getChildOperators().remove(parentOp);
                grandParentOp.getChildOperators().add(mergeJoinOp);
                newParentOpList.add(grandParentOp);
            }
        }
        mergeJoinOp.getParentOperators().clear();
        mergeJoinOp.getParentOperators().addAll(newParentOpList);
        List<Operator<? extends OperatorDesc>> parentOps = new ArrayList<Operator<? extends OperatorDesc>>(mergeJoinOp.getParentOperators());
        for (Operator<? extends OperatorDesc> parentOp : parentOps) {
            int parentIndex = mergeJoinOp.getParentOperators().indexOf(parentOp);
            if (parentIndex == mapJoinConversionPos) {
                continue;
            }
            // insert the dummy store operator here
            DummyStoreOperator dummyStoreOp = new TezDummyStoreOperator(mergeJoinOp.getCompilationOpContext());
            dummyStoreOp.setParentOperators(new ArrayList<Operator<? extends OperatorDesc>>());
            dummyStoreOp.setChildOperators(new ArrayList<Operator<? extends OperatorDesc>>());
            dummyStoreOp.getChildOperators().add(mergeJoinOp);
            int index = parentOp.getChildOperators().indexOf(mergeJoinOp);
            parentOp.getChildOperators().remove(index);
            parentOp.getChildOperators().add(index, dummyStoreOp);
            dummyStoreOp.getParentOperators().add(parentOp);
            mergeJoinOp.getParentOperators().remove(parentIndex);
            mergeJoinOp.getParentOperators().add(parentIndex, dummyStoreOp);
        }
    }
    mergeJoinOp.cloneOriginalParentsList(mergeJoinOp.getParentOperators());
}

Example 7 with MapJoinDesc

use of org.apache.hadoop.hive.ql.plan.MapJoinDesc in project hive by apache.

the class ConvertJoinMapJoin method convertJoinBucketMapJoin.

private boolean convertJoinBucketMapJoin(JoinOperator joinOp, OptimizeTezProcContext context, int bigTablePosition, TezBucketJoinProcCtx tezBucketJoinProcCtx) throws SemanticException {
    if (!checkConvertJoinBucketMapJoin(joinOp, context, bigTablePosition, tezBucketJoinProcCtx)) {
        LOG.info("Check conversion to bucket map join failed.");
        return false;
    }
    MapJoinOperator mapJoinOp = convertJoinMapJoin(joinOp, context, bigTablePosition, true);
    if (mapJoinOp == null) {
        LOG.debug("Conversion to bucket map join failed.");
        return false;
    }
    MapJoinDesc joinDesc = mapJoinOp.getConf();
    joinDesc.setBucketMapJoin(true);
    // we can set the traits for this join operator
    OpTraits opTraits = new OpTraits(joinOp.getOpTraits().getBucketColNames(), tezBucketJoinProcCtx.getNumBuckets(), null, joinOp.getOpTraits().getNumReduceSinks());
    mapJoinOp.setOpTraits(opTraits);
    mapJoinOp.setStatistics(joinOp.getStatistics());
    setNumberOfBucketsOnChildren(mapJoinOp);
    // Once the conversion is done, we can set the partitioner to bucket cols on the small table
    Map<String, Integer> bigTableBucketNumMapping = new HashMap<String, Integer>();
    bigTableBucketNumMapping.put(joinDesc.getBigTableAlias(), tezBucketJoinProcCtx.getNumBuckets());
    joinDesc.setBigTableBucketNumMapping(bigTableBucketNumMapping);
    return true;
}

Example 8 with MapJoinDesc

use of org.apache.hadoop.hive.ql.plan.MapJoinDesc in project hive by apache.

the class ReduceSinkMapJoinProc method processReduceSinkToHashJoin.

public static Object processReduceSinkToHashJoin(ReduceSinkOperator parentRS, MapJoinOperator mapJoinOp, GenTezProcContext context) throws SemanticException {
    // remove the tag for in-memory side of mapjoin
    parentRS.getConf().setSkipTag(true);
    parentRS.setSkipTag(true);
    // Mark this small table as being processed
    if (mapJoinOp.getConf().isDynamicPartitionHashJoin()) {
        context.mapJoinToUnprocessedSmallTableReduceSinks.get(mapJoinOp).remove(parentRS);
    }
    List<BaseWork> mapJoinWork = null;
    /*
     *  if there was a pre-existing work generated for the big-table mapjoin side,
     *  we need to hook the work generated for the RS (associated with the RS-MJ pattern)
     *  with the pre-existing work.
     *
     *  Otherwise, we need to associate that the mapjoin op
     *  to be linked to the RS work (associated with the RS-MJ pattern).
     *
     */
    mapJoinWork = context.mapJoinWorkMap.get(mapJoinOp);
    BaseWork parentWork = getMapJoinParentWork(context, parentRS);
    // set the link between mapjoin and parent vertex
    int pos = context.mapJoinParentMap.get(mapJoinOp).indexOf(parentRS);
    if (pos == -1) {
        throw new SemanticException("Cannot find position of parent in mapjoin");
    }
    MapJoinDesc joinConf = mapJoinOp.getConf();
    long keyCount = Long.MAX_VALUE, rowCount = Long.MAX_VALUE, bucketCount = 1;
    long tableSize = Long.MAX_VALUE;
    Statistics stats = parentRS.getStatistics();
    if (stats != null) {
        keyCount = rowCount = stats.getNumRows();
        if (keyCount <= 0) {
            keyCount = rowCount = Long.MAX_VALUE;
        }
        tableSize = stats.getDataSize();
        ArrayList<String> keyCols = parentRS.getConf().getOutputKeyColumnNames();
        if (keyCols != null && !keyCols.isEmpty()) {
            // See if we can arrive at a smaller number using distinct stats from key columns.
            long maxKeyCount = 1;
            String prefix = Utilities.ReduceField.KEY.toString();
            for (String keyCol : keyCols) {
                ExprNodeDesc realCol = parentRS.getColumnExprMap().get(prefix + "." + keyCol);
                ColStatistics cs = StatsUtils.getColStatisticsFromExpression(context.conf, stats, realCol);
                if (cs == null || cs.getCountDistint() <= 0) {
                    maxKeyCount = Long.MAX_VALUE;
                    break;
                }
                maxKeyCount *= cs.getCountDistint();
                if (maxKeyCount >= keyCount) {
                    break;
                }
            }
            keyCount = Math.min(maxKeyCount, keyCount);
        }
        if (joinConf.isBucketMapJoin()) {
            OpTraits opTraits = mapJoinOp.getOpTraits();
            bucketCount = (opTraits == null) ? -1 : opTraits.getNumBuckets();
            if (bucketCount > 0) {
                // We cannot obtain a better estimate without CustomPartitionVertex providing it
                // to us somehow; in which case using statistics would be completely unnecessary.
                keyCount /= bucketCount;
                tableSize /= bucketCount;
            }
        } else if (joinConf.isDynamicPartitionHashJoin()) {
            // For dynamic partitioned hash join, assuming table is split evenly among the reduce tasks.
            bucketCount = parentRS.getConf().getNumReducers();
            keyCount /= bucketCount;
            tableSize /= bucketCount;
        }
    }
    if (keyCount == 0) {
        keyCount = 1;
    }
    if (tableSize == 0) {
        tableSize = 1;
    }
    LOG.info("Mapjoin " + mapJoinOp + "(bucket map join = )" + joinConf.isBucketMapJoin() + ", pos: " + pos + " --> " + parentWork.getName() + " (" + keyCount + " keys estimated from " + rowCount + " rows, " + bucketCount + " buckets)");
    joinConf.getParentToInput().put(pos, parentWork.getName());
    if (keyCount != Long.MAX_VALUE) {
        joinConf.getParentKeyCounts().put(pos, keyCount);
    }
    joinConf.getParentDataSizes().put(pos, tableSize);
    int numBuckets = -1;
    EdgeType edgeType = EdgeType.BROADCAST_EDGE;
    if (joinConf.isBucketMapJoin()) {
        numBuckets = (Integer) joinConf.getBigTableBucketNumMapping().values().toArray()[0];
        /*
       * Here, we can be in one of 4 states.
       *
       * 1. If map join work is null implies that we have not yet traversed the big table side. We
       * just need to see if we can find a reduce sink operator in the big table side. This would
       * imply a reduce side operation.
       *
       * 2. If we don't find a reducesink in 1 it has to be the case that it is a map side operation.
       *
       * 3. If we have already created a work item for the big table side, we need to see if we can
       * find a table scan operator in the big table side. This would imply a map side operation.
       *
       * 4. If we don't find a table scan operator, it has to be a reduce side operation.
       */
        if (mapJoinWork == null) {
            Operator<?> rootOp = OperatorUtils.findSingleOperatorUpstreamJoinAccounted(mapJoinOp.getParentOperators().get(joinConf.getPosBigTable()), ReduceSinkOperator.class);
            if (rootOp == null) {
                // likely we found a table scan operator
                edgeType = EdgeType.CUSTOM_EDGE;
            } else {
                // we have found a reduce sink
                edgeType = EdgeType.CUSTOM_SIMPLE_EDGE;
            }
        } else {
            Operator<?> rootOp = OperatorUtils.findSingleOperatorUpstreamJoinAccounted(mapJoinOp.getParentOperators().get(joinConf.getPosBigTable()), TableScanOperator.class);
            if (rootOp != null) {
                // likely we found a table scan operator
                edgeType = EdgeType.CUSTOM_EDGE;
            } else {
                // we have found a reduce sink
                edgeType = EdgeType.CUSTOM_SIMPLE_EDGE;
            }
        }
    } else if (mapJoinOp.getConf().isDynamicPartitionHashJoin()) {
        edgeType = EdgeType.CUSTOM_SIMPLE_EDGE;
    }
    if (edgeType == EdgeType.CUSTOM_EDGE) {
        // disable auto parallelism for bucket map joins
        parentRS.getConf().setReducerTraits(EnumSet.of(FIXED));
    }
    TezEdgeProperty edgeProp = new TezEdgeProperty(null, edgeType, numBuckets);
    if (mapJoinWork != null) {
        for (BaseWork myWork : mapJoinWork) {
            // link the work with the work associated with the reduce sink that triggered this rule
            TezWork tezWork = context.currentTask.getWork();
            LOG.debug("connecting " + parentWork.getName() + " with " + myWork.getName());
            tezWork.connect(parentWork, myWork, edgeProp);
            if (edgeType == EdgeType.CUSTOM_EDGE) {
                tezWork.setVertexType(myWork, VertexType.INITIALIZED_EDGES);
            }
            ReduceSinkOperator r = null;
            if (context.connectedReduceSinks.contains(parentRS)) {
                LOG.debug("Cloning reduce sink for multi-child broadcast edge");
                // we've already set this one up. Need to clone for the next work.
                r = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(parentRS.getCompilationOpContext(), (ReduceSinkDesc) parentRS.getConf().clone(), new RowSchema(parentRS.getSchema()), parentRS.getParentOperators());
                context.clonedReduceSinks.add(r);
            } else {
                r = parentRS;
            }
            // remember the output name of the reduce sink
            r.getConf().setOutputName(myWork.getName());
            context.connectedReduceSinks.add(r);
        }
    }
    // remember in case we need to connect additional work later
    Map<BaseWork, TezEdgeProperty> linkWorkMap = null;
    if (context.linkOpWithWorkMap.containsKey(mapJoinOp)) {
        linkWorkMap = context.linkOpWithWorkMap.get(mapJoinOp);
    } else {
        linkWorkMap = new HashMap<BaseWork, TezEdgeProperty>();
    }
    linkWorkMap.put(parentWork, edgeProp);
    context.linkOpWithWorkMap.put(mapJoinOp, linkWorkMap);
    List<ReduceSinkOperator> reduceSinks = context.linkWorkWithReduceSinkMap.get(parentWork);
    if (reduceSinks == null) {
        reduceSinks = new ArrayList<ReduceSinkOperator>();
    }
    reduceSinks.add(parentRS);
    context.linkWorkWithReduceSinkMap.put(parentWork, reduceSinks);
    // create the dummy operators
    List<Operator<?>> dummyOperators = new ArrayList<Operator<?>>();
    // create an new operator: HashTableDummyOperator, which share the table desc
    HashTableDummyDesc desc = new HashTableDummyDesc();
    @SuppressWarnings("unchecked") HashTableDummyOperator dummyOp = (HashTableDummyOperator) OperatorFactory.get(parentRS.getCompilationOpContext(), desc);
    TableDesc tbl;
    // need to create the correct table descriptor for key/value
    RowSchema rowSchema = parentRS.getParentOperators().get(0).getSchema();
    tbl = PlanUtils.getReduceValueTableDesc(PlanUtils.getFieldSchemasFromRowSchema(rowSchema, ""));
    dummyOp.getConf().setTbl(tbl);
    Map<Byte, List<ExprNodeDesc>> keyExprMap = mapJoinOp.getConf().getKeys();
    List<ExprNodeDesc> keyCols = keyExprMap.get(Byte.valueOf((byte) 0));
    StringBuilder keyOrder = new StringBuilder();
    StringBuilder keyNullOrder = new StringBuilder();
    for (ExprNodeDesc k : keyCols) {
        keyOrder.append("+");
        keyNullOrder.append("a");
    }
    TableDesc keyTableDesc = PlanUtils.getReduceKeyTableDesc(PlanUtils.getFieldSchemasFromColumnList(keyCols, "mapjoinkey"), keyOrder.toString(), keyNullOrder.toString());
    mapJoinOp.getConf().setKeyTableDesc(keyTableDesc);
    // let the dummy op be the parent of mapjoin op
    mapJoinOp.replaceParent(parentRS, dummyOp);
    List<Operator<? extends OperatorDesc>> dummyChildren = new ArrayList<Operator<? extends OperatorDesc>>();
    dummyChildren.add(mapJoinOp);
    dummyOp.setChildOperators(dummyChildren);
    dummyOperators.add(dummyOp);
    // cut the operator tree so as to not retain connections from the parent RS downstream
    List<Operator<? extends OperatorDesc>> childOperators = parentRS.getChildOperators();
    int childIndex = childOperators.indexOf(mapJoinOp);
    childOperators.remove(childIndex);
    // at task startup
    if (mapJoinWork != null) {
        for (BaseWork myWork : mapJoinWork) {
            LOG.debug("adding dummy op to work " + myWork.getName() + " from MJ work: " + dummyOp);
            myWork.addDummyOp(dummyOp);
        }
    }
    if (context.linkChildOpWithDummyOp.containsKey(mapJoinOp)) {
        for (Operator<?> op : context.linkChildOpWithDummyOp.get(mapJoinOp)) {
            dummyOperators.add(op);
        }
    }
    context.linkChildOpWithDummyOp.put(mapJoinOp, dummyOperators);
    return true;
}

Example 9 with MapJoinDesc

use of org.apache.hadoop.hive.ql.plan.MapJoinDesc in project hive by apache.

the class ColumnPrunerProcFactory method pruneJoinOperator.

private static void pruneJoinOperator(NodeProcessorCtx ctx, CommonJoinOperator op, JoinDesc conf, Map<String, ExprNodeDesc> columnExprMap, Map<Byte, List<Integer>> retainMap, boolean mapJoin) throws SemanticException {
    ColumnPrunerProcCtx cppCtx = (ColumnPrunerProcCtx) ctx;
    List<Operator<? extends OperatorDesc>> childOperators = op.getChildOperators();
    LOG.info("JOIN " + op.getIdentifier() + " oldExprs: " + conf.getExprs());
    if (cppCtx.genColLists(op) == null) {
        return;
    }
    List<FieldNode> neededColList = new ArrayList<>(cppCtx.genColLists(op));
    Map<Byte, List<FieldNode>> prunedColLists = new HashMap<>();
    for (byte tag : conf.getTagOrder()) {
        prunedColLists.put(tag, new ArrayList<FieldNode>());
    }
    //add the columns in join filters
    Set<Map.Entry<Byte, List<ExprNodeDesc>>> filters = conf.getFilters().entrySet();
    Iterator<Map.Entry<Byte, List<ExprNodeDesc>>> iter = filters.iterator();
    while (iter.hasNext()) {
        Map.Entry<Byte, List<ExprNodeDesc>> entry = iter.next();
        Byte tag = entry.getKey();
        for (ExprNodeDesc desc : entry.getValue()) {
            List<FieldNode> cols = prunedColLists.get(tag);
            cols = mergeFieldNodesWithDesc(cols, desc);
            prunedColLists.put(tag, cols);
        }
    }
    //add the columns in residual filters
    if (conf.getResidualFilterExprs() != null) {
        for (ExprNodeDesc desc : conf.getResidualFilterExprs()) {
            neededColList = mergeFieldNodesWithDesc(neededColList, desc);
        }
    }
    RowSchema joinRS = op.getSchema();
    ArrayList<String> outputCols = new ArrayList<String>();
    ArrayList<ColumnInfo> rs = new ArrayList<ColumnInfo>();
    Map<String, ExprNodeDesc> newColExprMap = new HashMap<String, ExprNodeDesc>();
    for (int i = 0; i < conf.getOutputColumnNames().size(); i++) {
        String internalName = conf.getOutputColumnNames().get(i);
        ExprNodeDesc desc = columnExprMap.get(internalName);
        Byte tag = conf.getReversedExprs().get(internalName);
        if (lookupColumn(neededColList, internalName) == null) {
            int index = conf.getExprs().get(tag).indexOf(desc);
            if (index < 0) {
                continue;
            }
            conf.getExprs().get(tag).remove(desc);
            if (retainMap != null) {
                retainMap.get(tag).remove(index);
            }
        } else {
            List<FieldNode> prunedRSList = prunedColLists.get(tag);
            if (prunedRSList == null) {
                prunedRSList = new ArrayList<>();
                prunedColLists.put(tag, prunedRSList);
            }
            prunedColLists.put(tag, mergeFieldNodesWithDesc(prunedRSList, desc));
            outputCols.add(internalName);
            newColExprMap.put(internalName, desc);
        }
    }
    if (mapJoin) {
        // regenerate the valueTableDesc
        List<TableDesc> valueTableDescs = new ArrayList<TableDesc>();
        for (int pos = 0; pos < op.getParentOperators().size(); pos++) {
            List<ExprNodeDesc> valueCols = conf.getExprs().get(Byte.valueOf((byte) pos));
            StringBuilder keyOrder = new StringBuilder();
            for (int i = 0; i < valueCols.size(); i++) {
                keyOrder.append("+");
            }
            TableDesc valueTableDesc = PlanUtils.getMapJoinValueTableDesc(PlanUtils.getFieldSchemasFromColumnList(valueCols, "mapjoinvalue"));
            valueTableDescs.add(valueTableDesc);
        }
        ((MapJoinDesc) conf).setValueTblDescs(valueTableDescs);
        Set<Map.Entry<Byte, List<ExprNodeDesc>>> exprs = ((MapJoinDesc) conf).getKeys().entrySet();
        Iterator<Map.Entry<Byte, List<ExprNodeDesc>>> iters = exprs.iterator();
        while (iters.hasNext()) {
            Map.Entry<Byte, List<ExprNodeDesc>> entry = iters.next();
            List<ExprNodeDesc> lists = entry.getValue();
            for (int j = 0; j < lists.size(); j++) {
                ExprNodeDesc desc = lists.get(j);
                Byte tag = entry.getKey();
                List<FieldNode> cols = prunedColLists.get(tag);
                cols = mergeFieldNodesWithDesc(cols, desc);
                prunedColLists.put(tag, cols);
            }
        }
    }
    for (Operator<? extends OperatorDesc> child : childOperators) {
        if (child instanceof ReduceSinkOperator) {
            boolean[] flags = getPruneReduceSinkOpRetainFlags(toColumnNames(neededColList), (ReduceSinkOperator) child);
            pruneReduceSinkOperator(flags, (ReduceSinkOperator) child, cppCtx);
        }
    }
    for (int i = 0; i < outputCols.size(); i++) {
        String internalName = outputCols.get(i);
        ColumnInfo col = joinRS.getColumnInfo(internalName);
        rs.add(col);
    }
    LOG.info("JOIN " + op.getIdentifier() + " newExprs: " + conf.getExprs());
    op.setColumnExprMap(newColExprMap);
    conf.setOutputColumnNames(outputCols);
    op.getSchema().setSignature(rs);
    cppCtx.getJoinPrunedColLists().put(op, prunedColLists);
}

Example 10 with MapJoinDesc

use of org.apache.hadoop.hive.ql.plan.MapJoinDesc in project hive by apache.

the class MapJoinProcessor method convertJoinOpMapJoinOp.

public static MapJoinOperator convertJoinOpMapJoinOp(HiveConf hconf, JoinOperator op, boolean leftInputJoin, String[] baseSrc, List<String> mapAliases, int mapJoinPos, boolean noCheckOuterJoin, boolean adjustParentsChildren) throws SemanticException {
    MapJoinDesc mapJoinDescriptor = getMapJoinDesc(hconf, op, leftInputJoin, baseSrc, mapAliases, mapJoinPos, noCheckOuterJoin, adjustParentsChildren);
    // reduce sink row resolver used to generate map join op
    RowSchema outputRS = op.getSchema();
    MapJoinOperator mapJoinOp = (MapJoinOperator) OperatorFactory.getAndMakeChild(op.getCompilationOpContext(), mapJoinDescriptor, new RowSchema(outputRS.getSignature()), op.getParentOperators());
    mapJoinOp.getConf().setReversedExprs(op.getConf().getReversedExprs());
    Map<String, ExprNodeDesc> colExprMap = op.getColumnExprMap();
    mapJoinOp.setColumnExprMap(colExprMap);
    List<Operator<? extends OperatorDesc>> childOps = op.getChildOperators();
    for (Operator<? extends OperatorDesc> childOp : childOps) {
        childOp.replaceParent(op, mapJoinOp);
    }
    mapJoinOp.setPosToAliasMap(op.getPosToAliasMap());
    mapJoinOp.setChildOperators(childOps);
    op.setChildOperators(null);
    op.setParentOperators(null);
    return mapJoinOp;
}