Examples with ReduceSinkOperator org.apache.hadoop.hive.ql.exec.ReduceSinkOperator used on opensource projects

Example 11 with ReduceSinkOperator

use of org.apache.hadoop.hive.ql.exec.ReduceSinkOperator in project hive by apache.

the class HiveOpConverter method translateJoin.

private OpAttr translateJoin(RelNode joinRel) throws SemanticException {
    // 0. Additional data structures needed for the join optimization
    // through Hive
    String[] baseSrc = new String[joinRel.getInputs().size()];
    String tabAlias = getHiveDerivedTableAlias();
    // 1. Convert inputs
    OpAttr[] inputs = new OpAttr[joinRel.getInputs().size()];
    List<Operator<?>> children = new ArrayList<Operator<?>>(joinRel.getInputs().size());
    for (int i = 0; i < inputs.length; i++) {
        inputs[i] = dispatch(joinRel.getInput(i));
        children.add(inputs[i].inputs.get(0));
        baseSrc[i] = inputs[i].tabAlias;
    }
    // 2. Generate tags
    for (int tag = 0; tag < children.size(); tag++) {
        ReduceSinkOperator reduceSinkOp = (ReduceSinkOperator) children.get(tag);
        reduceSinkOp.getConf().setTag(tag);
    }
    // 3. Virtual columns
    Set<Integer> newVcolsInCalcite = new HashSet<Integer>();
    newVcolsInCalcite.addAll(inputs[0].vcolsInCalcite);
    if (joinRel instanceof HiveMultiJoin || !(joinRel instanceof SemiJoin)) {
        int shift = inputs[0].inputs.get(0).getSchema().getSignature().size();
        for (int i = 1; i < inputs.length; i++) {
            newVcolsInCalcite.addAll(HiveCalciteUtil.shiftVColsSet(inputs[i].vcolsInCalcite, shift));
            shift += inputs[i].inputs.get(0).getSchema().getSignature().size();
        }
    }
    if (LOG.isDebugEnabled()) {
        LOG.debug("Translating operator rel#" + joinRel.getId() + ":" + joinRel.getRelTypeName() + " with row type: [" + joinRel.getRowType() + "]");
    }
    // 4. Extract join key expressions from HiveSortExchange
    ExprNodeDesc[][] joinExpressions = new ExprNodeDesc[inputs.length][];
    for (int i = 0; i < inputs.length; i++) {
        joinExpressions[i] = ((HiveSortExchange) joinRel.getInput(i)).getJoinExpressions();
    }
    // 5. Extract rest of join predicate info. We infer the rest of join condition
    //    that will be added to the filters (join conditions that are not part of
    //    the join key)
    List<RexNode> joinFilters;
    if (joinRel instanceof HiveJoin) {
        joinFilters = ImmutableList.of(((HiveJoin) joinRel).getJoinFilter());
    } else if (joinRel instanceof HiveMultiJoin) {
        joinFilters = ((HiveMultiJoin) joinRel).getJoinFilters();
    } else if (joinRel instanceof HiveSemiJoin) {
        joinFilters = ImmutableList.of(((HiveSemiJoin) joinRel).getJoinFilter());
    } else {
        throw new SemanticException("Can't handle join type: " + joinRel.getClass().getName());
    }
    List<List<ExprNodeDesc>> filterExpressions = Lists.newArrayList();
    for (int i = 0; i < joinFilters.size(); i++) {
        List<ExprNodeDesc> filterExpressionsForInput = new ArrayList<ExprNodeDesc>();
        if (joinFilters.get(i) != null) {
            for (RexNode conj : RelOptUtil.conjunctions(joinFilters.get(i))) {
                ExprNodeDesc expr = convertToExprNode(conj, joinRel, null, newVcolsInCalcite);
                filterExpressionsForInput.add(expr);
            }
        }
        filterExpressions.add(filterExpressionsForInput);
    }
    // 6. Generate Join operator
    JoinOperator joinOp = genJoin(joinRel, joinExpressions, filterExpressions, children, baseSrc, tabAlias);
    // 7. Return result
    return new OpAttr(tabAlias, newVcolsInCalcite, joinOp);
}

Example 12 with ReduceSinkOperator

use of org.apache.hadoop.hive.ql.exec.ReduceSinkOperator in project hive by apache.

the class HiveOpConverter method visit.

OpAttr visit(HiveSortExchange exchangeRel) throws SemanticException {
    OpAttr inputOpAf = dispatch(exchangeRel.getInput());
    String tabAlias = inputOpAf.tabAlias;
    if (tabAlias == null || tabAlias.length() == 0) {
        tabAlias = getHiveDerivedTableAlias();
    }
    if (LOG.isDebugEnabled()) {
        LOG.debug("Translating operator rel#" + exchangeRel.getId() + ":" + exchangeRel.getRelTypeName() + " with row type: [" + exchangeRel.getRowType() + "]");
    }
    RelDistribution distribution = exchangeRel.getDistribution();
    if (distribution.getType() != Type.HASH_DISTRIBUTED) {
        throw new SemanticException("Only hash distribution supported for LogicalExchange");
    }
    ExprNodeDesc[] expressions = new ExprNodeDesc[exchangeRel.getJoinKeys().size()];
    for (int index = 0; index < exchangeRel.getJoinKeys().size(); index++) {
        expressions[index] = convertToExprNode(exchangeRel.getJoinKeys().get(index), exchangeRel.getInput(), inputOpAf.tabAlias, inputOpAf);
    }
    exchangeRel.setJoinExpressions(expressions);
    ReduceSinkOperator rsOp = genReduceSink(inputOpAf.inputs.get(0), tabAlias, expressions, -1, -1, Operation.NOT_ACID, hiveConf);
    return new OpAttr(tabAlias, inputOpAf.vcolsInCalcite, rsOp);
}

Example 13 with ReduceSinkOperator

use of org.apache.hadoop.hive.ql.exec.ReduceSinkOperator in project hive by apache.

the class HiveGBOpConvUtil method genReduceGBRS.

private static OpAttr genReduceGBRS(OpAttr inputOpAf, GBInfo gbInfo) throws SemanticException {
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    ArrayList<String> outputColumnNames = new ArrayList<String>();
    ArrayList<ColumnInfo> colInfoLst = new ArrayList<ColumnInfo>();
    GroupByOperator reduceSideGB1 = (GroupByOperator) inputOpAf.inputs.get(0);
    List<ColumnInfo> gb1ColInfoLst = reduceSideGB1.getSchema().getSignature();
    ArrayList<ExprNodeDesc> reduceKeys = getReduceKeysForRS(reduceSideGB1, 0, gbInfo.gbKeys.size() - 1, outputColumnNames, false, colInfoLst, colExprMap, true, true);
    if (inclGrpSetInReduceSide(gbInfo)) {
        addGrpSetCol(false, gb1ColInfoLst.get(reduceKeys.size()).getInternalName(), true, reduceKeys, outputColumnNames, colInfoLst, colExprMap);
    }
    ArrayList<ExprNodeDesc> reduceValues = getValueKeysForRS(reduceSideGB1, reduceSideGB1.getConf().getKeys().size(), outputColumnNames, colInfoLst, colExprMap, true, true);
    ReduceSinkOperator rsOp = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(PlanUtils.getReduceSinkDesc(reduceKeys, reduceValues, outputColumnNames, true, -1, getNumPartFieldsForReduceSideRS(gbInfo), getParallelismForReduceSideRS(gbInfo), AcidUtils.Operation.NOT_ACID), new RowSchema(colInfoLst), reduceSideGB1);
    rsOp.setColumnExprMap(colExprMap);
    return new OpAttr("", new HashSet<Integer>(), rsOp);
}

Example 14 with ReduceSinkOperator

use of org.apache.hadoop.hive.ql.exec.ReduceSinkOperator in project hive by apache.

the class GenTezWork method process.

@Override
public Object process(Node nd, Stack<Node> stack, NodeProcessorCtx procContext, Object... nodeOutputs) throws SemanticException {
    GenTezProcContext context = (GenTezProcContext) procContext;
    assert context != null && context.currentTask != null && context.currentRootOperator != null;
    // Operator is a file sink or reduce sink. Something that forces
    // a new vertex.
    Operator<?> operator = (Operator<?>) nd;
    // root is the start of the operator pipeline we're currently
    // packing into a vertex, typically a table scan, union or join
    Operator<?> root = context.currentRootOperator;
    LOG.debug("Root operator: " + root);
    LOG.debug("Leaf operator: " + operator);
    if (context.clonedReduceSinks.contains(operator)) {
        // just skip and keep going
        return null;
    }
    TezWork tezWork = context.currentTask.getWork();
    // Right now the work graph is pretty simple. If there is no
    // Preceding work we have a root and will generate a map
    // vertex. If there is a preceding work we will generate
    // a reduce vertex
    BaseWork work;
    if (context.rootToWorkMap.containsKey(root)) {
        // will result into a vertex with multiple FS or RS operators.
        if (context.childToWorkMap.containsKey(operator)) {
            // if we've seen both root and child, we can bail.
            // clear out the mapjoin set. we don't need it anymore.
            context.currentMapJoinOperators.clear();
            // clear out the union set. we don't need it anymore.
            context.currentUnionOperators.clear();
            return null;
        } else {
            // At this point we don't have to do anything special. Just
            // run through the regular paces w/o creating a new task.
            work = context.rootToWorkMap.get(root);
        }
    } else {
        // create a new vertex
        if (context.preceedingWork == null) {
            work = utils.createMapWork(context, root, tezWork, null);
        } else {
            work = GenTezUtils.createReduceWork(context, root, tezWork);
        }
        context.rootToWorkMap.put(root, work);
    }
    // this is where we set the sort columns that we will be using for KeyValueInputMerge
    if (operator instanceof DummyStoreOperator) {
        work.addSortCols(root.getOpTraits().getSortCols().get(0));
    }
    if (!context.childToWorkMap.containsKey(operator)) {
        List<BaseWork> workItems = new LinkedList<BaseWork>();
        workItems.add(work);
        context.childToWorkMap.put(operator, workItems);
    } else {
        context.childToWorkMap.get(operator).add(work);
    }
    // which can affect the working of all downstream transformations.
    if (context.currentMergeJoinOperator != null) {
        // we are currently walking the big table side of the merge join. we need to create or hook up
        // merge join work.
        MergeJoinWork mergeJoinWork = null;
        if (context.opMergeJoinWorkMap.containsKey(context.currentMergeJoinOperator)) {
            // we have found a merge work corresponding to this closing operator. Hook up this work.
            mergeJoinWork = context.opMergeJoinWorkMap.get(context.currentMergeJoinOperator);
        } else {
            // we need to create the merge join work
            mergeJoinWork = new MergeJoinWork();
            mergeJoinWork.setMergeJoinOperator(context.currentMergeJoinOperator);
            tezWork.add(mergeJoinWork);
            context.opMergeJoinWorkMap.put(context.currentMergeJoinOperator, mergeJoinWork);
        }
        // connect the work correctly.
        work.addSortCols(root.getOpTraits().getSortCols().get(0));
        mergeJoinWork.addMergedWork(work, null, context.leafOperatorToFollowingWork);
        Operator<? extends OperatorDesc> parentOp = getParentFromStack(context.currentMergeJoinOperator, stack);
        // Set the big table position. Both the reduce work and merge join operator
        // should be set with the same value.
        //      int pos = context.currentMergeJoinOperator.getTagForOperator(parentOp);
        int pos = context.currentMergeJoinOperator.getConf().getBigTablePosition();
        work.setTag(pos);
        context.currentMergeJoinOperator.getConf().setBigTablePosition(pos);
        tezWork.setVertexType(work, VertexType.MULTI_INPUT_UNINITIALIZED_EDGES);
        for (BaseWork parentWork : tezWork.getParents(work)) {
            TezEdgeProperty edgeProp = tezWork.getEdgeProperty(parentWork, work);
            tezWork.disconnect(parentWork, work);
            tezWork.connect(parentWork, mergeJoinWork, edgeProp);
        }
        for (BaseWork childWork : tezWork.getChildren(work)) {
            TezEdgeProperty edgeProp = tezWork.getEdgeProperty(work, childWork);
            tezWork.disconnect(work, childWork);
            tezWork.connect(mergeJoinWork, childWork, edgeProp);
        }
        tezWork.remove(work);
        context.rootToWorkMap.put(root, mergeJoinWork);
        context.childToWorkMap.get(operator).remove(work);
        context.childToWorkMap.get(operator).add(mergeJoinWork);
        work = mergeJoinWork;
        context.currentMergeJoinOperator = null;
    }
    // remember which mapjoin operator links with which work
    if (!context.currentMapJoinOperators.isEmpty()) {
        for (MapJoinOperator mj : context.currentMapJoinOperators) {
            // so we can later run the same logic that is run in ReduceSinkMapJoinProc.
            if (mj.getConf().isDynamicPartitionHashJoin()) {
                // Since this is a dynamic partitioned hash join, the work for this join should be a ReduceWork
                ReduceWork reduceWork = (ReduceWork) work;
                int bigTablePosition = mj.getConf().getPosBigTable();
                reduceWork.setTag(bigTablePosition);
                // Use context.mapJoinParentMap to get the original RS parents, because
                // the MapJoin's parents may have been replaced by dummy operator.
                List<Operator<?>> mapJoinOriginalParents = context.mapJoinParentMap.get(mj);
                if (mapJoinOriginalParents == null) {
                    throw new SemanticException("Unexpected error - context.mapJoinParentMap did not have an entry for " + mj);
                }
                for (int pos = 0; pos < mapJoinOriginalParents.size(); ++pos) {
                    // This processing only needs to happen for the small tables
                    if (pos == bigTablePosition) {
                        continue;
                    }
                    Operator<?> parentOp = mapJoinOriginalParents.get(pos);
                    context.smallTableParentToMapJoinMap.put(parentOp, mj);
                    ReduceSinkOperator parentRS = (ReduceSinkOperator) parentOp;
                    // TableDesc needed for dynamic partitioned hash join
                    GenMapRedUtils.setKeyAndValueDesc(reduceWork, parentRS);
                    // has its ReduceSink parent removed.
                    if (!context.mapJoinToUnprocessedSmallTableReduceSinks.get(mj).contains(parentRS)) {
                        // This reduce sink has been processed already, so the work for the parentRS exists
                        BaseWork parentWork = ReduceSinkMapJoinProc.getMapJoinParentWork(context, parentRS);
                        int tag = parentRS.getConf().getTag();
                        tag = (tag == -1 ? 0 : tag);
                        reduceWork.getTagToInput().put(tag, parentWork.getName());
                    }
                }
            }
            LOG.debug("Processing map join: " + mj);
            // mapjoin later
            if (!context.mapJoinWorkMap.containsKey(mj)) {
                List<BaseWork> workItems = new LinkedList<BaseWork>();
                workItems.add(work);
                context.mapJoinWorkMap.put(mj, workItems);
            } else {
                context.mapJoinWorkMap.get(mj).add(work);
            }
            /*
         * this happens in case of map join operations.
         * The tree looks like this:
         *
         *        RS <--- we are here perhaps
         *        |
         *     MapJoin
         *     /     \
         *   RS       TS
         *  /
         * TS
         *
         * If we are at the RS pointed above, and we may have already visited the
         * RS following the TS, we have already generated work for the TS-RS.
         * We need to hook the current work to this generated work.
         */
            if (context.linkOpWithWorkMap.containsKey(mj)) {
                Map<BaseWork, TezEdgeProperty> linkWorkMap = context.linkOpWithWorkMap.get(mj);
                if (linkWorkMap != null) {
                    // Note: it's not quite clear why this is done inside this if. Seems like it should be on the top level.
                    if (context.linkChildOpWithDummyOp.containsKey(mj)) {
                        if (LOG.isDebugEnabled()) {
                            LOG.debug("Adding dummy ops to work: " + work.getName() + ": " + context.linkChildOpWithDummyOp.get(mj));
                        }
                        for (Operator<?> dummy : context.linkChildOpWithDummyOp.get(mj)) {
                            work.addDummyOp((HashTableDummyOperator) dummy);
                        }
                    }
                    for (Entry<BaseWork, TezEdgeProperty> parentWorkMap : linkWorkMap.entrySet()) {
                        BaseWork parentWork = parentWorkMap.getKey();
                        LOG.debug("connecting " + parentWork.getName() + " with " + work.getName());
                        TezEdgeProperty edgeProp = parentWorkMap.getValue();
                        tezWork.connect(parentWork, work, edgeProp);
                        if (edgeProp.getEdgeType() == EdgeType.CUSTOM_EDGE) {
                            tezWork.setVertexType(work, VertexType.INITIALIZED_EDGES);
                        }
                        // of the downstream work
                        for (ReduceSinkOperator r : context.linkWorkWithReduceSinkMap.get(parentWork)) {
                            if (r.getConf().getOutputName() != null) {
                                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(r.getCompilationOpContext(), (ReduceSinkDesc) r.getConf().clone(), new RowSchema(r.getSchema()), r.getParentOperators());
                                context.clonedReduceSinks.add(r);
                            }
                            r.getConf().setOutputName(work.getName());
                            context.connectedReduceSinks.add(r);
                        }
                    }
                }
            }
        }
        // clear out the set. we don't need it anymore.
        context.currentMapJoinOperators.clear();
    }
    // we might have to connect parent work with this work later.
    for (Operator<?> parent : new ArrayList<Operator<?>>(root.getParentOperators())) {
        if (LOG.isDebugEnabled()) {
            LOG.debug("Removing " + parent + " as parent from " + root);
        }
        context.leafOperatorToFollowingWork.remove(parent);
        context.leafOperatorToFollowingWork.put(parent, work);
        root.removeParent(parent);
    }
    if (!context.currentUnionOperators.isEmpty()) {
        // if there are union all operators, it means that the walking context contains union all operators.
        // please see more details of context.currentUnionOperator in GenTezWorkWalker
        UnionWork unionWork;
        if (context.unionWorkMap.containsKey(operator)) {
            // since we've passed this operator before.
            assert operator.getChildOperators().isEmpty();
            unionWork = (UnionWork) context.unionWorkMap.get(operator);
            // finally connect the union work with work
            connectUnionWorkWithWork(unionWork, work, tezWork, context);
        } else {
            // we've not seen this terminal before. we need to check
            // rootUnionWorkMap which contains the information of mapping the root
            // operator of a union work to a union work
            unionWork = context.rootUnionWorkMap.get(root);
            if (unionWork == null) {
                // if unionWork is null, it means it is the first time. we need to
                // create a union work object and add this work to it. Subsequent
                // work should reference the union and not the actual work.
                unionWork = GenTezUtils.createUnionWork(context, root, operator, tezWork);
                // finally connect the union work with work
                connectUnionWorkWithWork(unionWork, work, tezWork, context);
            }
        }
        context.currentUnionOperators.clear();
        work = unionWork;
    }
    // reasons. Roots are data sources, leaves are data sinks. I know.
    if (context.leafOperatorToFollowingWork.containsKey(operator)) {
        BaseWork followingWork = context.leafOperatorToFollowingWork.get(operator);
        long bytesPerReducer = context.conf.getLongVar(HiveConf.ConfVars.BYTESPERREDUCER);
        LOG.debug("Second pass. Leaf operator: " + operator + " has common downstream work:" + followingWork);
        if (operator instanceof DummyStoreOperator) {
            // this is the small table side.
            assert (followingWork instanceof MergeJoinWork);
            MergeJoinWork mergeJoinWork = (MergeJoinWork) followingWork;
            CommonMergeJoinOperator mergeJoinOp = mergeJoinWork.getMergeJoinOperator();
            work.setTag(mergeJoinOp.getTagForOperator(operator));
            mergeJoinWork.addMergedWork(null, work, context.leafOperatorToFollowingWork);
            tezWork.setVertexType(mergeJoinWork, VertexType.MULTI_INPUT_UNINITIALIZED_EDGES);
            for (BaseWork parentWork : tezWork.getParents(work)) {
                TezEdgeProperty edgeProp = tezWork.getEdgeProperty(parentWork, work);
                tezWork.disconnect(parentWork, work);
                tezWork.connect(parentWork, mergeJoinWork, edgeProp);
            }
            work = mergeJoinWork;
        } else {
            // need to add this branch to the key + value info
            assert operator instanceof ReduceSinkOperator && ((followingWork instanceof ReduceWork) || (followingWork instanceof MergeJoinWork) || followingWork instanceof UnionWork);
            ReduceSinkOperator rs = (ReduceSinkOperator) operator;
            ReduceWork rWork = null;
            if (followingWork instanceof MergeJoinWork) {
                MergeJoinWork mergeJoinWork = (MergeJoinWork) followingWork;
                rWork = (ReduceWork) mergeJoinWork.getMainWork();
            } else if (followingWork instanceof UnionWork) {
                // this can only be possible if there is merge work followed by the union
                UnionWork unionWork = (UnionWork) followingWork;
                int index = getFollowingWorkIndex(tezWork, unionWork, rs);
                BaseWork baseWork = tezWork.getChildren(unionWork).get(index);
                if (baseWork instanceof MergeJoinWork) {
                    MergeJoinWork mergeJoinWork = (MergeJoinWork) baseWork;
                    // disconnect the connection to union work and connect to merge work
                    followingWork = mergeJoinWork;
                    rWork = (ReduceWork) mergeJoinWork.getMainWork();
                } else {
                    rWork = (ReduceWork) baseWork;
                }
            } else {
                rWork = (ReduceWork) followingWork;
            }
            GenMapRedUtils.setKeyAndValueDesc(rWork, rs);
            // remember which parent belongs to which tag
            int tag = rs.getConf().getTag();
            rWork.getTagToInput().put(tag == -1 ? 0 : tag, work.getName());
            // remember the output name of the reduce sink
            rs.getConf().setOutputName(rWork.getName());
            // For dynamic partitioned hash join, run the ReduceSinkMapJoinProc logic for any
            // ReduceSink parents that we missed.
            MapJoinOperator mj = context.smallTableParentToMapJoinMap.get(rs);
            if (mj != null) {
                // Only need to run the logic for tables we missed
                if (context.mapJoinToUnprocessedSmallTableReduceSinks.get(mj).contains(rs)) {
                    // ReduceSinkMapJoinProc logic does not work unless the ReduceSink is connected as
                    // a parent of the MapJoin, but at this point we have already removed all of the
                    // parents from the MapJoin.
                    // Try temporarily adding the RS as a parent
                    ArrayList<Operator<?>> tempMJParents = new ArrayList<Operator<?>>();
                    tempMJParents.add(rs);
                    mj.setParentOperators(tempMJParents);
                    // ReduceSink also needs MapJoin as child
                    List<Operator<?>> rsChildren = rs.getChildOperators();
                    rsChildren.add(mj);
                    // Since the MapJoin has had all of its other parents removed at this point,
                    // it would be bad here if processReduceSinkToHashJoin() tries to do anything
                    // with the RS parent based on its position in the list of parents.
                    ReduceSinkMapJoinProc.processReduceSinkToHashJoin(rs, mj, context);
                    // Remove any parents from MapJoin again
                    mj.removeParents();
                // TODO: do we also need to remove the MapJoin from the list of RS's children?
                }
            }
            if (!context.connectedReduceSinks.contains(rs)) {
                // add dependency between the two work items
                TezEdgeProperty edgeProp;
                EdgeType edgeType = GenTezUtils.determineEdgeType(work, followingWork, rs);
                if (rWork.isAutoReduceParallelism()) {
                    edgeProp = new TezEdgeProperty(context.conf, edgeType, true, rWork.getMinReduceTasks(), rWork.getMaxReduceTasks(), bytesPerReducer);
                } else {
                    edgeProp = new TezEdgeProperty(edgeType);
                }
                tezWork.connect(work, followingWork, edgeProp);
                context.connectedReduceSinks.add(rs);
            }
        }
    } else {
        LOG.debug("First pass. Leaf operator: " + operator);
    }
    // the next item will be a new root.
    if (!operator.getChildOperators().isEmpty()) {
        assert operator.getChildOperators().size() == 1;
        context.parentOfRoot = operator;
        context.currentRootOperator = operator.getChildOperators().get(0);
        context.preceedingWork = work;
    }
    return null;
}

Example 15 with ReduceSinkOperator

use of org.apache.hadoop.hive.ql.exec.ReduceSinkOperator in project hive by apache.

the class GenSparkUtils method createReduceWork.

public ReduceWork createReduceWork(GenSparkProcContext context, Operator<?> root, SparkWork sparkWork) throws SemanticException {
    Preconditions.checkArgument(!root.getParentOperators().isEmpty(), "AssertionError: expected root.getParentOperators() to be non-empty");
    ReduceWork reduceWork = new ReduceWork("Reducer " + (++sequenceNumber));
    LOG.debug("Adding reduce work (" + reduceWork.getName() + ") for " + root);
    reduceWork.setReducer(root);
    reduceWork.setNeedsTagging(GenMapRedUtils.needsTagging(reduceWork));
    // Pick the maximum # reducers across all parents as the # of reduce tasks.
    int maxExecutors = -1;
    for (Operator<? extends OperatorDesc> parentOfRoot : root.getParentOperators()) {
        Preconditions.checkArgument(parentOfRoot instanceof ReduceSinkOperator, "AssertionError: expected parentOfRoot to be an " + "instance of ReduceSinkOperator, but was " + parentOfRoot.getClass().getName());
        ReduceSinkOperator reduceSink = (ReduceSinkOperator) parentOfRoot;
        maxExecutors = Math.max(maxExecutors, reduceSink.getConf().getNumReducers());
    }
    reduceWork.setNumReduceTasks(maxExecutors);
    ReduceSinkOperator reduceSink = (ReduceSinkOperator) context.parentOfRoot;
    setupReduceSink(context, reduceWork, reduceSink);
    sparkWork.add(reduceWork);
    SparkEdgeProperty edgeProp = getEdgeProperty(reduceSink, reduceWork);
    sparkWork.connect(context.preceedingWork, reduceWork, edgeProp);
    return reduceWork;
}