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

Example 6 with TableScanOperator

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

the class Driver method getTablePartitionUsedColumns.

private static void getTablePartitionUsedColumns(HiveOperation op, BaseSemanticAnalyzer sem, Map<Table, List<String>> tab2Cols, Map<Partition, List<String>> part2Cols, Map<String, Boolean> tableUsePartLevelAuth) throws HiveException {
    // table to columns mapping (tab2Cols)
    if (op.equals(HiveOperation.CREATETABLE_AS_SELECT) || op.equals(HiveOperation.QUERY)) {
        SemanticAnalyzer querySem = (SemanticAnalyzer) sem;
        ParseContext parseCtx = querySem.getParseContext();
        for (Map.Entry<String, TableScanOperator> topOpMap : querySem.getParseContext().getTopOps().entrySet()) {
            TableScanOperator tableScanOp = topOpMap.getValue();
            if (!tableScanOp.isInsideView()) {
                Table tbl = tableScanOp.getConf().getTableMetadata();
                List<Integer> neededColumnIds = tableScanOp.getNeededColumnIDs();
                List<FieldSchema> columns = tbl.getCols();
                List<String> cols = new ArrayList<String>();
                for (int i = 0; i < neededColumnIds.size(); i++) {
                    cols.add(columns.get(neededColumnIds.get(i)).getName());
                }
                // table permission
                if (tbl.isPartitioned() && Boolean.TRUE.equals(tableUsePartLevelAuth.get(tbl.getTableName()))) {
                    String alias_id = topOpMap.getKey();
                    PrunedPartitionList partsList = PartitionPruner.prune(tableScanOp, parseCtx, alias_id);
                    Set<Partition> parts = partsList.getPartitions();
                    for (Partition part : parts) {
                        List<String> existingCols = part2Cols.get(part);
                        if (existingCols == null) {
                            existingCols = new ArrayList<String>();
                        }
                        existingCols.addAll(cols);
                        part2Cols.put(part, existingCols);
                    }
                } else {
                    List<String> existingCols = tab2Cols.get(tbl);
                    if (existingCols == null) {
                        existingCols = new ArrayList<String>();
                    }
                    existingCols.addAll(cols);
                    tab2Cols.put(tbl, existingCols);
                }
            }
        }
    }
}

Example 7 with TableScanOperator

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

the class TezCompiler method findParallelSemiJoinBranch.

private boolean findParallelSemiJoinBranch(Operator<?> mapjoin, TableScanOperator bigTableTS, ParseContext parseContext, Map<ReduceSinkOperator, TableScanOperator> semijoins) {
    boolean parallelEdges = false;
    for (Operator<?> op : mapjoin.getParentOperators()) {
        if (!(op instanceof ReduceSinkOperator)) {
            continue;
        }
        op = op.getParentOperators().get(0);
        // Follow the Reducesink operator upstream which is on small table side.
        while (!(op instanceof ReduceSinkOperator) && !(op instanceof TableScanOperator) && !(op.getChildren() != null && op.getChildren().size() > 1)) {
            if (op instanceof MapJoinOperator) {
                // ReduceSink, that is what we are looking for.
                for (Operator<?> parentOp : op.getParentOperators()) {
                    if (parentOp instanceof ReduceSinkOperator) {
                        continue;
                    }
                    // parent in current pipeline
                    op = parentOp;
                    continue;
                }
            }
            op = op.getParentOperators().get(0);
        }
        // Bail out if RS or TS is encountered.
        if (op instanceof ReduceSinkOperator || op instanceof TableScanOperator) {
            continue;
        }
        // A branch is hit.
        for (Node nd : op.getChildren()) {
            if (nd instanceof SelectOperator) {
                Operator<?> child = (Operator<?>) nd;
                while (child.getChildOperators().size() > 0) {
                    child = child.getChildOperators().get(0);
                }
                // If not ReduceSink Op, skip
                if (!(child instanceof ReduceSinkOperator)) {
                    // This still could be DPP.
                    if (child instanceof AppMasterEventOperator && ((AppMasterEventOperator) child).getConf() instanceof DynamicPruningEventDesc) {
                        // DPP indeed, Set parallel edges true
                        parallelEdges = true;
                    }
                    continue;
                }
                ReduceSinkOperator rs = (ReduceSinkOperator) child;
                SemiJoinBranchInfo sjInfo = parseContext.getRsToSemiJoinBranchInfo().get(rs);
                if (sjInfo == null) {
                    continue;
                }
                TableScanOperator ts = sjInfo.getTsOp();
                if (ts != bigTableTS) {
                    // skip, not the one we are looking for.
                    continue;
                }
                parallelEdges = true;
                if (sjInfo.getIsHint() || !sjInfo.getShouldRemove()) {
                    // Created by hint, skip it
                    continue;
                }
                // Add the semijoin branch to the map
                semijoins.put(rs, ts);
            }
        }
    }
    return parallelEdges;
}

Example 8 with TableScanOperator

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

the class TezCompiler method removeSemijoinsParallelToMapJoin.

/*
   *  The algorithm looks at all the mapjoins in the operator pipeline until
   *  it hits RS Op and for each mapjoin examines if it has paralllel semijoin
   *  edge or dynamic partition pruning.
   */
private void removeSemijoinsParallelToMapJoin(OptimizeTezProcContext procCtx) throws SemanticException {
    if (!procCtx.conf.getBoolVar(ConfVars.TEZ_DYNAMIC_SEMIJOIN_REDUCTION) || !procCtx.conf.getBoolVar(ConfVars.HIVECONVERTJOIN) || procCtx.conf.getBoolVar(ConfVars.TEZ_DYNAMIC_SEMIJOIN_REDUCTION_FOR_MAPJOIN)) {
        // are enabled for parallel mapjoins.
        return;
    }
    // Get all the TS ops.
    List<Operator<?>> topOps = new ArrayList<>();
    topOps.addAll(procCtx.parseContext.getTopOps().values());
    Map<ReduceSinkOperator, TableScanOperator> semijoins = new HashMap<>();
    for (Operator<?> parent : topOps) {
        // A TS can have multiple branches due to DPP Or Semijoin Opt.
        // USe DFS to traverse all the branches until RS is hit.
        Deque<Operator<?>> deque = new LinkedList<>();
        deque.add(parent);
        while (!deque.isEmpty()) {
            Operator<?> op = deque.pollLast();
            if (op instanceof ReduceSinkOperator) {
                // Done with this branch
                continue;
            }
            if (op instanceof MapJoinOperator) {
                // A candidate.
                if (!findParallelSemiJoinBranch(op, (TableScanOperator) parent, procCtx.parseContext, semijoins)) {
                    // no need to go down further, skip this TS operator pipeline.
                    break;
                }
            }
            deque.addAll(op.getChildOperators());
        }
    }
    if (semijoins.size() > 0) {
        for (ReduceSinkOperator rs : semijoins.keySet()) {
            if (LOG.isDebugEnabled()) {
                LOG.debug("Semijoin optimization with parallel edge to map join. Removing semijoin " + OperatorUtils.getOpNamePretty(rs) + " - " + OperatorUtils.getOpNamePretty(semijoins.get(rs)));
            }
            GenTezUtils.removeBranch(rs);
            GenTezUtils.removeSemiJoinOperator(procCtx.parseContext, rs, semijoins.get(rs));
        }
    }
}

Example 9 with TableScanOperator

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

the class HiveOpConverter method visit.

/**
 * TODO: 1. PPD needs to get pushed in to TS
 *
 * @param scanRel
 * @return
 */
OpAttr visit(HiveTableScan scanRel) {
    if (LOG.isDebugEnabled()) {
        LOG.debug("Translating operator rel#" + scanRel.getId() + ":" + scanRel.getRelTypeName() + " with row type: [" + scanRel.getRowType() + "]");
    }
    RelOptHiveTable ht = (RelOptHiveTable) scanRel.getTable();
    // 1. Setup TableScan Desc
    // 1.1 Build col details used by scan
    ArrayList<ColumnInfo> colInfos = new ArrayList<ColumnInfo>();
    List<VirtualColumn> virtualCols = new ArrayList<VirtualColumn>();
    List<Integer> neededColumnIDs = new ArrayList<Integer>();
    List<String> neededColumnNames = new ArrayList<String>();
    Set<Integer> vcolsInCalcite = new HashSet<Integer>();
    List<String> partColNames = new ArrayList<String>();
    Map<Integer, VirtualColumn> VColsMap = HiveCalciteUtil.getVColsMap(ht.getVirtualCols(), ht.getNoOfNonVirtualCols());
    Map<Integer, ColumnInfo> posToPartColInfo = ht.getPartColInfoMap();
    Map<Integer, ColumnInfo> posToNonPartColInfo = ht.getNonPartColInfoMap();
    List<Integer> neededColIndxsFrmReloptHT = scanRel.getNeededColIndxsFrmReloptHT();
    List<String> scanColNames = scanRel.getRowType().getFieldNames();
    String tableAlias = scanRel.getConcatQbIDAlias();
    String colName;
    ColumnInfo colInfo;
    VirtualColumn vc;
    for (int index = 0; index < scanRel.getRowType().getFieldList().size(); index++) {
        colName = scanColNames.get(index);
        if (VColsMap.containsKey(index)) {
            vc = VColsMap.get(index);
            virtualCols.add(vc);
            colInfo = new ColumnInfo(vc.getName(), vc.getTypeInfo(), tableAlias, true, vc.getIsHidden());
            vcolsInCalcite.add(index);
        } else if (posToPartColInfo.containsKey(index)) {
            partColNames.add(colName);
            colInfo = posToPartColInfo.get(index);
            vcolsInCalcite.add(index);
        } else {
            colInfo = posToNonPartColInfo.get(index);
        }
        colInfos.add(colInfo);
        if (neededColIndxsFrmReloptHT.contains(index)) {
            neededColumnIDs.add(index);
            neededColumnNames.add(colName);
        }
    }
    // 1.2 Create TableScanDesc
    TableScanDesc tsd = new TableScanDesc(tableAlias, virtualCols, ht.getHiveTableMD());
    // 1.3. Set Partition cols in TSDesc
    tsd.setPartColumns(partColNames);
    // 1.4. Set needed cols in TSDesc
    tsd.setNeededColumnIDs(neededColumnIDs);
    tsd.setNeededColumns(neededColumnNames);
    // 2. Setup TableScan
    TableScanOperator ts = (TableScanOperator) OperatorFactory.get(semanticAnalyzer.getOpContext(), tsd, new RowSchema(colInfos));
    // tablescan with same alias.
    if (topOps.get(tableAlias) != null) {
        tableAlias = tableAlias + this.uniqueCounter;
    }
    topOps.put(tableAlias, ts);
    if (LOG.isDebugEnabled()) {
        LOG.debug("Generated " + ts + " with row schema: [" + ts.getSchema() + "]");
    }
    return new OpAttr(tableAlias, vcolsInCalcite, ts);
}

Example 10 with TableScanOperator

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

the class GenMRSkewJoinProcessor method processSkewJoin.

/**
 * Create tasks for processing skew joins. The idea is (HIVE-964) to use
 * separated jobs and map-joins to handle skew joins.
 * <p>
 * <ul>
 * <li>
 * Number of mr jobs to handle skew keys is the number of table minus 1 (we
 * can stream the last table, so big keys in the last table will not be a
 * problem).
 * <li>
 * At runtime in Join, we output big keys in one table into one corresponding
 * directories, and all same keys in other tables into different dirs(one for
 * each table). The directories will look like:
 * <ul>
 * <li>
 * dir-T1-bigkeys(containing big keys in T1), dir-T2-keys(containing keys
 * which is big in T1),dir-T3-keys(containing keys which is big in T1), ...
 * <li>
 * dir-T1-keys(containing keys which is big in T2), dir-T2-bigkeys(containing
 * big keys in T2),dir-T3-keys(containing keys which is big in T2), ...
 * <li>
 * dir-T1-keys(containing keys which is big in T3), dir-T2-keys(containing big
 * keys in T3),dir-T3-bigkeys(containing keys which is big in T3), ... .....
 * </ul>
 * </ul>
 * For each table, we launch one mapjoin job, taking the directory containing
 * big keys in this table and corresponding dirs in other tables as input.
 * (Actally one job for one row in the above.)
 *
 * <p>
 * For more discussions, please check
 * https://issues.apache.org/jira/browse/HIVE-964.
 */
@SuppressWarnings("unchecked")
public static void processSkewJoin(JoinOperator joinOp, Task<? extends Serializable> currTask, ParseContext parseCtx) throws SemanticException {
    // now does not work with outer joins
    if (!GenMRSkewJoinProcessor.skewJoinEnabled(parseCtx.getConf(), joinOp)) {
        return;
    }
    List<Task<? extends Serializable>> children = currTask.getChildTasks();
    Path baseTmpDir = parseCtx.getContext().getMRTmpPath();
    JoinDesc joinDescriptor = joinOp.getConf();
    Map<Byte, List<ExprNodeDesc>> joinValues = joinDescriptor.getExprs();
    int numAliases = joinValues.size();
    Map<Byte, Path> bigKeysDirMap = new HashMap<Byte, Path>();
    Map<Byte, Map<Byte, Path>> smallKeysDirMap = new HashMap<Byte, Map<Byte, Path>>();
    Map<Byte, Path> skewJoinJobResultsDir = new HashMap<Byte, Path>();
    Byte[] tags = joinDescriptor.getTagOrder();
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        bigKeysDirMap.put(alias, getBigKeysDir(baseTmpDir, alias));
        Map<Byte, Path> smallKeysMap = new HashMap<Byte, Path>();
        smallKeysDirMap.put(alias, smallKeysMap);
        for (Byte src2 : tags) {
            if (!src2.equals(alias)) {
                smallKeysMap.put(src2, getSmallKeysDir(baseTmpDir, alias, src2));
            }
        }
        skewJoinJobResultsDir.put(alias, getBigKeysSkewJoinResultDir(baseTmpDir, alias));
    }
    joinDescriptor.setHandleSkewJoin(true);
    joinDescriptor.setBigKeysDirMap(bigKeysDirMap);
    joinDescriptor.setSmallKeysDirMap(smallKeysDirMap);
    joinDescriptor.setSkewKeyDefinition(HiveConf.getIntVar(parseCtx.getConf(), HiveConf.ConfVars.HIVESKEWJOINKEY));
    HashMap<Path, Task<? extends Serializable>> bigKeysDirToTaskMap = new HashMap<Path, Task<? extends Serializable>>();
    List<Serializable> listWorks = new ArrayList<Serializable>();
    List<Task<? extends Serializable>> listTasks = new ArrayList<Task<? extends Serializable>>();
    MapredWork currPlan = (MapredWork) currTask.getWork();
    TableDesc keyTblDesc = (TableDesc) currPlan.getReduceWork().getKeyDesc().clone();
    List<String> joinKeys = Utilities.getColumnNames(keyTblDesc.getProperties());
    List<String> joinKeyTypes = Utilities.getColumnTypes(keyTblDesc.getProperties());
    Map<Byte, TableDesc> tableDescList = new HashMap<Byte, TableDesc>();
    Map<Byte, RowSchema> rowSchemaList = new HashMap<Byte, RowSchema>();
    Map<Byte, List<ExprNodeDesc>> newJoinValues = new HashMap<Byte, List<ExprNodeDesc>>();
    Map<Byte, List<ExprNodeDesc>> newJoinKeys = new HashMap<Byte, List<ExprNodeDesc>>();
    // used for create mapJoinDesc, should be in order
    List<TableDesc> newJoinValueTblDesc = new ArrayList<TableDesc>();
    for (Byte tag : tags) {
        newJoinValueTblDesc.add(null);
    }
    for (int i = 0; i < numAliases; i++) {
        Byte alias = tags[i];
        List<ExprNodeDesc> valueCols = joinValues.get(alias);
        String colNames = "";
        String colTypes = "";
        int columnSize = valueCols.size();
        List<ExprNodeDesc> newValueExpr = new ArrayList<ExprNodeDesc>();
        List<ExprNodeDesc> newKeyExpr = new ArrayList<ExprNodeDesc>();
        ArrayList<ColumnInfo> columnInfos = new ArrayList<ColumnInfo>();
        boolean first = true;
        for (int k = 0; k < columnSize; k++) {
            TypeInfo type = valueCols.get(k).getTypeInfo();
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            ColumnInfo columnInfo = new ColumnInfo(newColName, type, alias.toString(), false);
            columnInfos.add(columnInfo);
            newValueExpr.add(new ExprNodeColumnDesc(columnInfo));
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + newColName;
            colTypes = colTypes + valueCols.get(k).getTypeString();
        }
        // we are putting join keys at last part of the spilled table
        for (int k = 0; k < joinKeys.size(); k++) {
            if (!first) {
                colNames = colNames + ",";
                colTypes = colTypes + ",";
            }
            first = false;
            colNames = colNames + joinKeys.get(k);
            colTypes = colTypes + joinKeyTypes.get(k);
            ColumnInfo columnInfo = new ColumnInfo(joinKeys.get(k), TypeInfoFactory.getPrimitiveTypeInfo(joinKeyTypes.get(k)), alias.toString(), false);
            columnInfos.add(columnInfo);
            newKeyExpr.add(new ExprNodeColumnDesc(columnInfo));
        }
        newJoinValues.put(alias, newValueExpr);
        newJoinKeys.put(alias, newKeyExpr);
        tableDescList.put(alias, Utilities.getTableDesc(colNames, colTypes));
        rowSchemaList.put(alias, new RowSchema(columnInfos));
        // construct value table Desc
        String valueColNames = "";
        String valueColTypes = "";
        first = true;
        for (int k = 0; k < columnSize; k++) {
            // any name, it does not matter.
            String newColName = i + "_VALUE_" + k;
            if (!first) {
                valueColNames = valueColNames + ",";
                valueColTypes = valueColTypes + ",";
            }
            valueColNames = valueColNames + newColName;
            valueColTypes = valueColTypes + valueCols.get(k).getTypeString();
            first = false;
        }
        newJoinValueTblDesc.set(Byte.valueOf((byte) i), Utilities.getTableDesc(valueColNames, valueColTypes));
    }
    joinDescriptor.setSkewKeysValuesTables(tableDescList);
    joinDescriptor.setKeyTableDesc(keyTblDesc);
    for (int i = 0; i < numAliases - 1; i++) {
        Byte src = tags[i];
        MapWork newPlan = PlanUtils.getMapRedWork().getMapWork();
        // This code has been only added for testing
        boolean mapperCannotSpanPartns = parseCtx.getConf().getBoolVar(HiveConf.ConfVars.HIVE_MAPPER_CANNOT_SPAN_MULTIPLE_PARTITIONS);
        newPlan.setMapperCannotSpanPartns(mapperCannotSpanPartns);
        MapredWork clonePlan = SerializationUtilities.clonePlan(currPlan);
        Operator<? extends OperatorDesc>[] parentOps = new TableScanOperator[tags.length];
        for (int k = 0; k < tags.length; k++) {
            Operator<? extends OperatorDesc> ts = GenMapRedUtils.createTemporaryTableScanOperator(joinOp.getCompilationOpContext(), rowSchemaList.get((byte) k));
            ((TableScanOperator) ts).setTableDescSkewJoin(tableDescList.get((byte) k));
            parentOps[k] = ts;
        }
        Operator<? extends OperatorDesc> tblScan_op = parentOps[i];
        ArrayList<String> aliases = new ArrayList<String>();
        String alias = src.toString().intern();
        aliases.add(alias);
        Path bigKeyDirPath = bigKeysDirMap.get(src);
        newPlan.addPathToAlias(bigKeyDirPath, aliases);
        newPlan.getAliasToWork().put(alias, tblScan_op);
        PartitionDesc part = new PartitionDesc(tableDescList.get(src), null);
        newPlan.addPathToPartitionInfo(bigKeyDirPath, part);
        newPlan.getAliasToPartnInfo().put(alias, part);
        Operator<? extends OperatorDesc> reducer = clonePlan.getReduceWork().getReducer();
        assert reducer instanceof JoinOperator;
        JoinOperator cloneJoinOp = (JoinOperator) reducer;
        String dumpFilePrefix = "mapfile" + PlanUtils.getCountForMapJoinDumpFilePrefix();
        MapJoinDesc mapJoinDescriptor = new MapJoinDesc(newJoinKeys, keyTblDesc, newJoinValues, newJoinValueTblDesc, newJoinValueTblDesc, joinDescriptor.getOutputColumnNames(), i, joinDescriptor.getConds(), joinDescriptor.getFilters(), joinDescriptor.getNoOuterJoin(), dumpFilePrefix, joinDescriptor.getMemoryMonitorInfo(), joinDescriptor.getInMemoryDataSize());
        mapJoinDescriptor.setTagOrder(tags);
        mapJoinDescriptor.setHandleSkewJoin(false);
        mapJoinDescriptor.setNullSafes(joinDescriptor.getNullSafes());
        mapJoinDescriptor.setColumnExprMap(joinDescriptor.getColumnExprMap());
        MapredLocalWork localPlan = new MapredLocalWork(new LinkedHashMap<String, Operator<? extends OperatorDesc>>(), new LinkedHashMap<String, FetchWork>());
        Map<Byte, Path> smallTblDirs = smallKeysDirMap.get(src);
        for (int j = 0; j < numAliases; j++) {
            if (j == i) {
                continue;
            }
            Byte small_alias = tags[j];
            Operator<? extends OperatorDesc> tblScan_op2 = parentOps[j];
            localPlan.getAliasToWork().put(small_alias.toString(), tblScan_op2);
            Path tblDir = smallTblDirs.get(small_alias);
            localPlan.getAliasToFetchWork().put(small_alias.toString(), new FetchWork(tblDir, tableDescList.get(small_alias)));
        }
        newPlan.setMapRedLocalWork(localPlan);
        // construct a map join and set it as the child operator of tblScan_op
        MapJoinOperator mapJoinOp = (MapJoinOperator) OperatorFactory.getAndMakeChild(joinOp.getCompilationOpContext(), mapJoinDescriptor, (RowSchema) null, parentOps);
        // change the children of the original join operator to point to the map
        // join operator
        List<Operator<? extends OperatorDesc>> childOps = cloneJoinOp.getChildOperators();
        for (Operator<? extends OperatorDesc> childOp : childOps) {
            childOp.replaceParent(cloneJoinOp, mapJoinOp);
        }
        mapJoinOp.setChildOperators(childOps);
        HiveConf jc = new HiveConf(parseCtx.getConf(), GenMRSkewJoinProcessor.class);
        newPlan.setNumMapTasks(HiveConf.getIntVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINNUMMAPTASK));
        newPlan.setMinSplitSize(HiveConf.getLongVar(jc, HiveConf.ConfVars.HIVESKEWJOINMAPJOINMINSPLIT));
        newPlan.setInputformat(HiveInputFormat.class.getName());
        MapredWork w = new MapredWork();
        w.setMapWork(newPlan);
        Task<? extends Serializable> skewJoinMapJoinTask = TaskFactory.get(w);
        skewJoinMapJoinTask.setFetchSource(currTask.isFetchSource());
        bigKeysDirToTaskMap.put(bigKeyDirPath, skewJoinMapJoinTask);
        listWorks.add(skewJoinMapJoinTask.getWork());
        listTasks.add(skewJoinMapJoinTask);
    }
    if (children != null) {
        for (Task<? extends Serializable> tsk : listTasks) {
            for (Task<? extends Serializable> oldChild : children) {
                tsk.addDependentTask(oldChild);
            }
        }
        currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
        for (Task<? extends Serializable> oldChild : children) {
            oldChild.getParentTasks().remove(currTask);
        }
        listTasks.addAll(children);
    }
    ConditionalResolverSkewJoinCtx context = new ConditionalResolverSkewJoinCtx(bigKeysDirToTaskMap, children);
    ConditionalWork cndWork = new ConditionalWork(listWorks);
    ConditionalTask cndTsk = (ConditionalTask) TaskFactory.get(cndWork);
    cndTsk.setListTasks(listTasks);
    cndTsk.setResolver(new ConditionalResolverSkewJoin());
    cndTsk.setResolverCtx(context);
    currTask.setChildTasks(new ArrayList<Task<? extends Serializable>>());
    currTask.addDependentTask(cndTsk);
    return;
}