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

Example 26 with RowSchema

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

the class SemanticAnalyzer method genGroupByPlanMapGroupByOperator.

/**
   * Generate the map-side GroupByOperator for the Query Block
   * (qb.getParseInfo().getXXX(dest)). The new GroupByOperator will be a child
   * of the inputOperatorInfo.
   *
   * @param mode
   *          The mode of the aggregation (HASH)
   * @param genericUDAFEvaluators
   *          If not null, this function will store the mapping from Aggregation
   *          StringTree to the genericUDAFEvaluator in this parameter, so it
   *          can be used in the next-stage GroupBy aggregations.
   * @return the new GroupByOperator
   */
@SuppressWarnings("nls")
private Operator genGroupByPlanMapGroupByOperator(QB qb, String dest, List<ASTNode> grpByExprs, Operator inputOperatorInfo, GroupByDesc.Mode mode, Map<String, GenericUDAFEvaluator> genericUDAFEvaluators, List<Integer> groupingSetKeys, boolean groupingSetsPresent) throws SemanticException {
    RowResolver groupByInputRowResolver = opParseCtx.get(inputOperatorInfo).getRowResolver();
    QBParseInfo parseInfo = qb.getParseInfo();
    RowResolver groupByOutputRowResolver = new RowResolver();
    groupByOutputRowResolver.setIsExprResolver(true);
    ArrayList<ExprNodeDesc> groupByKeys = new ArrayList<ExprNodeDesc>();
    ArrayList<String> outputColumnNames = new ArrayList<String>();
    ArrayList<AggregationDesc> aggregations = new ArrayList<AggregationDesc>();
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    for (int i = 0; i < grpByExprs.size(); ++i) {
        ASTNode grpbyExpr = grpByExprs.get(i);
        ExprNodeDesc grpByExprNode = genExprNodeDesc(grpbyExpr, groupByInputRowResolver);
        if ((grpByExprNode instanceof ExprNodeColumnDesc) && ExprNodeDescUtils.indexOf(grpByExprNode, groupByKeys) >= 0) {
            // Skip duplicated grouping keys, it happens when define column alias.
            grpByExprs.remove(i--);
            continue;
        }
        groupByKeys.add(grpByExprNode);
        String field = getColumnInternalName(i);
        outputColumnNames.add(field);
        groupByOutputRowResolver.putExpression(grpbyExpr, new ColumnInfo(field, grpByExprNode.getTypeInfo(), "", false));
        colExprMap.put(field, groupByKeys.get(groupByKeys.size() - 1));
    }
    // The grouping set key is present after the grouping keys, before the distinct keys
    int groupingSetsPosition = -1;
    // for the grouping set (corresponding to the rollup).
    if (groupingSetsPresent) {
        groupingSetsPosition = groupByKeys.size();
        createNewGroupingKey(groupByKeys, outputColumnNames, groupByOutputRowResolver, colExprMap);
    }
    // If there is a distinctFuncExp, add all parameters to the reduceKeys.
    if (!parseInfo.getDistinctFuncExprsForClause(dest).isEmpty()) {
        List<ASTNode> list = parseInfo.getDistinctFuncExprsForClause(dest);
        for (ASTNode value : list) {
            // 0 is function name
            for (int i = 1; i < value.getChildCount(); i++) {
                ASTNode parameter = (ASTNode) value.getChild(i);
                if (groupByOutputRowResolver.getExpression(parameter) == null) {
                    ExprNodeDesc distExprNode = genExprNodeDesc(parameter, groupByInputRowResolver);
                    groupByKeys.add(distExprNode);
                    String field = getColumnInternalName(groupByKeys.size() - 1);
                    outputColumnNames.add(field);
                    groupByOutputRowResolver.putExpression(parameter, new ColumnInfo(field, distExprNode.getTypeInfo(), "", false));
                    colExprMap.put(field, groupByKeys.get(groupByKeys.size() - 1));
                }
            }
        }
    }
    // For each aggregation
    HashMap<String, ASTNode> aggregationTrees = parseInfo.getAggregationExprsForClause(dest);
    assert (aggregationTrees != null);
    boolean containsDistinctAggr = false;
    for (Map.Entry<String, ASTNode> entry : aggregationTrees.entrySet()) {
        ASTNode value = entry.getValue();
        String aggName = unescapeIdentifier(value.getChild(0).getText());
        ArrayList<ExprNodeDesc> aggParameters = new ArrayList<ExprNodeDesc>();
        // 0 is the function name
        for (int i = 1; i < value.getChildCount(); i++) {
            ASTNode paraExpr = (ASTNode) value.getChild(i);
            ExprNodeDesc paraExprNode = genExprNodeDesc(paraExpr, groupByInputRowResolver);
            aggParameters.add(paraExprNode);
        }
        boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
        containsDistinctAggr = containsDistinctAggr || isDistinct;
        boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
        Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
        GenericUDAFEvaluator genericUDAFEvaluator = getGenericUDAFEvaluator(aggName, aggParameters, value, isDistinct, isAllColumns);
        assert (genericUDAFEvaluator != null);
        GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode, aggParameters);
        aggregations.add(new AggregationDesc(aggName.toLowerCase(), udaf.genericUDAFEvaluator, udaf.convertedParameters, isDistinct, amode));
        String field = getColumnInternalName(groupByKeys.size() + aggregations.size() - 1);
        outputColumnNames.add(field);
        if (groupByOutputRowResolver.getExpression(value) == null) {
            groupByOutputRowResolver.putExpression(value, new ColumnInfo(field, udaf.returnType, "", false));
        }
        // GroupByOperators
        if (genericUDAFEvaluators != null) {
            genericUDAFEvaluators.put(entry.getKey(), genericUDAFEvaluator);
        }
    }
    float groupByMemoryUsage = HiveConf.getFloatVar(conf, HiveConf.ConfVars.HIVEMAPAGGRHASHMEMORY);
    float memoryThreshold = HiveConf.getFloatVar(conf, HiveConf.ConfVars.HIVEMAPAGGRMEMORYTHRESHOLD);
    Operator op = putOpInsertMap(OperatorFactory.getAndMakeChild(new GroupByDesc(mode, outputColumnNames, groupByKeys, aggregations, false, groupByMemoryUsage, memoryThreshold, groupingSetKeys, groupingSetsPresent, groupingSetsPosition, containsDistinctAggr), new RowSchema(groupByOutputRowResolver.getColumnInfos()), inputOperatorInfo), groupByOutputRowResolver);
    op.setColumnExprMap(colExprMap);
    return op;
}

Example 27 with RowSchema

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

the class SemanticAnalyzer method genGroupByPlanReduceSinkOperator2MR.

/**
   * Generate the second ReduceSinkOperator for the Group By Plan
   * (parseInfo.getXXX(dest)). The new ReduceSinkOperator will be a child of
   * groupByOperatorInfo.
   *
   * The second ReduceSinkOperator will put the group by keys in the map-reduce
   * sort key, and put the partial aggregation results in the map-reduce value.
   *
   * @param numPartitionFields
   *          the number of fields in the map-reduce partition key. This should
   *          always be the same as the number of Group By keys. We should be
   *          able to remove this parameter since in this phase there is no
   *          distinct any more.
   * @return the new ReduceSinkOperator.
   * @throws SemanticException
   */
@SuppressWarnings("nls")
private Operator genGroupByPlanReduceSinkOperator2MR(QBParseInfo parseInfo, String dest, Operator groupByOperatorInfo, int numPartitionFields, int numReducers, boolean groupingSetsPresent) throws SemanticException {
    RowResolver reduceSinkInputRowResolver2 = opParseCtx.get(groupByOperatorInfo).getRowResolver();
    RowResolver reduceSinkOutputRowResolver2 = new RowResolver();
    reduceSinkOutputRowResolver2.setIsExprResolver(true);
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    ArrayList<ExprNodeDesc> reduceKeys = new ArrayList<ExprNodeDesc>();
    ArrayList<String> outputColumnNames = new ArrayList<String>();
    // Get group-by keys and store in reduceKeys
    List<ASTNode> grpByExprs = getGroupByForClause(parseInfo, dest);
    for (int i = 0; i < grpByExprs.size(); ++i) {
        ASTNode grpbyExpr = grpByExprs.get(i);
        String field = getColumnInternalName(i);
        outputColumnNames.add(field);
        TypeInfo typeInfo = reduceSinkInputRowResolver2.getExpression(grpbyExpr).getType();
        ExprNodeColumnDesc inputExpr = new ExprNodeColumnDesc(typeInfo, field, "", false);
        reduceKeys.add(inputExpr);
        ColumnInfo colInfo = new ColumnInfo(Utilities.ReduceField.KEY.toString() + "." + field, typeInfo, "", false);
        reduceSinkOutputRowResolver2.putExpression(grpbyExpr, colInfo);
        colExprMap.put(colInfo.getInternalName(), inputExpr);
    }
    // add a key for reduce sink
    if (groupingSetsPresent) {
        // Note that partitioning fields dont need to change, since it is either
        // partitioned randomly, or by all grouping keys + distinct keys
        processGroupingSetReduceSinkOperator(reduceSinkInputRowResolver2, reduceSinkOutputRowResolver2, reduceKeys, outputColumnNames, colExprMap);
    }
    // Get partial aggregation results and store in reduceValues
    ArrayList<ExprNodeDesc> reduceValues = new ArrayList<ExprNodeDesc>();
    int inputField = reduceKeys.size();
    HashMap<String, ASTNode> aggregationTrees = parseInfo.getAggregationExprsForClause(dest);
    for (Map.Entry<String, ASTNode> entry : aggregationTrees.entrySet()) {
        String field = getColumnInternalName(inputField);
        ASTNode t = entry.getValue();
        TypeInfo typeInfo = reduceSinkInputRowResolver2.getExpression(t).getType();
        ExprNodeColumnDesc exprDesc = new ExprNodeColumnDesc(typeInfo, field, "", false);
        reduceValues.add(exprDesc);
        inputField++;
        String col = getColumnInternalName(reduceValues.size() - 1);
        outputColumnNames.add(col);
        reduceSinkOutputRowResolver2.putExpression(t, new ColumnInfo(Utilities.ReduceField.VALUE.toString() + "." + col, typeInfo, "", false));
        colExprMap.put(col, exprDesc);
    }
    ReduceSinkOperator rsOp = (ReduceSinkOperator) putOpInsertMap(OperatorFactory.getAndMakeChild(PlanUtils.getReduceSinkDesc(reduceKeys, reduceValues, outputColumnNames, true, -1, numPartitionFields, numReducers, AcidUtils.Operation.NOT_ACID), new RowSchema(reduceSinkOutputRowResolver2.getColumnInfos()), groupByOperatorInfo), reduceSinkOutputRowResolver2);
    rsOp.setColumnExprMap(colExprMap);
    return rsOp;
}

Example 28 with RowSchema

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

the class SemanticAnalyzer method genGroupByPlanGroupByOperator.

/**
   * Generate the GroupByOperator for the Query Block (parseInfo.getXXX(dest)).
   * The new GroupByOperator will be a child of the reduceSinkOperatorInfo.
   *
   * @param mode
   *          The mode of the aggregation (PARTIAL1 or COMPLETE)
   * @param genericUDAFEvaluators
   *          If not null, this function will store the mapping from Aggregation
   *          StringTree to the genericUDAFEvaluator in this parameter, so it
   *          can be used in the next-stage GroupBy aggregations.
   * @return the new GroupByOperator
   */
@SuppressWarnings("nls")
private Operator genGroupByPlanGroupByOperator(QBParseInfo parseInfo, String dest, Operator input, ReduceSinkOperator rs, GroupByDesc.Mode mode, Map<String, GenericUDAFEvaluator> genericUDAFEvaluators) throws SemanticException {
    RowResolver groupByInputRowResolver = opParseCtx.get(input).getRowResolver();
    RowResolver groupByOutputRowResolver = new RowResolver();
    groupByOutputRowResolver.setIsExprResolver(true);
    ArrayList<ExprNodeDesc> groupByKeys = new ArrayList<ExprNodeDesc>();
    ArrayList<AggregationDesc> aggregations = new ArrayList<AggregationDesc>();
    ArrayList<String> outputColumnNames = new ArrayList<String>();
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    List<ASTNode> grpByExprs = getGroupByForClause(parseInfo, dest);
    for (int i = 0; i < grpByExprs.size(); ++i) {
        ASTNode grpbyExpr = grpByExprs.get(i);
        ColumnInfo exprInfo = groupByInputRowResolver.getExpression(grpbyExpr);
        if (exprInfo == null) {
            throw new SemanticException(ErrorMsg.INVALID_COLUMN.getMsg(grpbyExpr));
        }
        groupByKeys.add(new ExprNodeColumnDesc(exprInfo.getType(), exprInfo.getInternalName(), "", false));
        String field = getColumnInternalName(i);
        outputColumnNames.add(field);
        ColumnInfo oColInfo = new ColumnInfo(field, exprInfo.getType(), null, false);
        groupByOutputRowResolver.putExpression(grpbyExpr, oColInfo);
        addAlternateGByKeyMappings(grpbyExpr, oColInfo, input, groupByOutputRowResolver);
        colExprMap.put(field, groupByKeys.get(groupByKeys.size() - 1));
    }
    // For each aggregation
    HashMap<String, ASTNode> aggregationTrees = parseInfo.getAggregationExprsForClause(dest);
    assert (aggregationTrees != null);
    // get the last colName for the reduce KEY
    // it represents the column name corresponding to distinct aggr, if any
    String lastKeyColName = null;
    List<String> inputKeyCols = rs.getConf().getOutputKeyColumnNames();
    if (inputKeyCols.size() > 0) {
        lastKeyColName = inputKeyCols.get(inputKeyCols.size() - 1);
    }
    List<ExprNodeDesc> reduceValues = rs.getConf().getValueCols();
    int numDistinctUDFs = 0;
    for (Map.Entry<String, ASTNode> entry : aggregationTrees.entrySet()) {
        ASTNode value = entry.getValue();
        // This is the GenericUDAF name
        String aggName = unescapeIdentifier(value.getChild(0).getText());
        boolean isDistinct = value.getType() == HiveParser.TOK_FUNCTIONDI;
        boolean isAllColumns = value.getType() == HiveParser.TOK_FUNCTIONSTAR;
        // Convert children to aggParameters
        ArrayList<ExprNodeDesc> aggParameters = new ArrayList<ExprNodeDesc>();
        // 0 is the function name
        for (int i = 1; i < value.getChildCount(); i++) {
            ASTNode paraExpr = (ASTNode) value.getChild(i);
            ColumnInfo paraExprInfo = groupByInputRowResolver.getExpression(paraExpr);
            if (paraExprInfo == null) {
                throw new SemanticException(ErrorMsg.INVALID_COLUMN.getMsg(paraExpr));
            }
            String paraExpression = paraExprInfo.getInternalName();
            assert (paraExpression != null);
            if (isDistinct && lastKeyColName != null) {
                // if aggr is distinct, the parameter is name is constructed as
                // KEY.lastKeyColName:<tag>._colx
                paraExpression = Utilities.ReduceField.KEY.name() + "." + lastKeyColName + ":" + numDistinctUDFs + "." + getColumnInternalName(i - 1);
            }
            ExprNodeDesc expr = new ExprNodeColumnDesc(paraExprInfo.getType(), paraExpression, paraExprInfo.getTabAlias(), paraExprInfo.getIsVirtualCol());
            ExprNodeDesc reduceValue = isConstantParameterInAggregationParameters(paraExprInfo.getInternalName(), reduceValues);
            if (reduceValue != null) {
                // this parameter is a constant
                expr = reduceValue;
            }
            aggParameters.add(expr);
        }
        if (isDistinct) {
            numDistinctUDFs++;
        }
        Mode amode = groupByDescModeToUDAFMode(mode, isDistinct);
        GenericUDAFEvaluator genericUDAFEvaluator = getGenericUDAFEvaluator(aggName, aggParameters, value, isDistinct, isAllColumns);
        assert (genericUDAFEvaluator != null);
        GenericUDAFInfo udaf = getGenericUDAFInfo(genericUDAFEvaluator, amode, aggParameters);
        aggregations.add(new AggregationDesc(aggName.toLowerCase(), udaf.genericUDAFEvaluator, udaf.convertedParameters, isDistinct, amode));
        String field = getColumnInternalName(groupByKeys.size() + aggregations.size() - 1);
        outputColumnNames.add(field);
        groupByOutputRowResolver.putExpression(value, new ColumnInfo(field, udaf.returnType, "", false));
        // GroupByOperators
        if (genericUDAFEvaluators != null) {
            genericUDAFEvaluators.put(entry.getKey(), genericUDAFEvaluator);
        }
    }
    float groupByMemoryUsage = HiveConf.getFloatVar(conf, HiveConf.ConfVars.HIVEMAPAGGRHASHMEMORY);
    float memoryThreshold = HiveConf.getFloatVar(conf, HiveConf.ConfVars.HIVEMAPAGGRMEMORYTHRESHOLD);
    Operator op = putOpInsertMap(OperatorFactory.getAndMakeChild(new GroupByDesc(mode, outputColumnNames, groupByKeys, aggregations, false, groupByMemoryUsage, memoryThreshold, null, false, -1, numDistinctUDFs > 0), new RowSchema(groupByOutputRowResolver.getColumnInfos()), input), groupByOutputRowResolver);
    op.setColumnExprMap(colExprMap);
    return op;
}

Example 29 with RowSchema

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

the class SemanticAnalyzer method genNotNullFilterForJoinSourcePlan.

/*
   * for inner joins push a 'is not null predicate' to the join sources for
   * every non nullSafe predicate.
   */
private Operator genNotNullFilterForJoinSourcePlan(QB qb, Operator input, QBJoinTree joinTree, ExprNodeDesc[] joinKeys) throws SemanticException {
    if (qb == null || joinTree == null) {
        return input;
    }
    if (!joinTree.getNoOuterJoin()) {
        return input;
    }
    if (joinKeys == null || joinKeys.length == 0) {
        return input;
    }
    Map<Integer, ExprNodeDesc> hashes = new HashMap<Integer, ExprNodeDesc>();
    if (input instanceof FilterOperator) {
        ExprNodeDescUtils.getExprNodeColumnDesc(Arrays.asList(((FilterDesc) input.getConf()).getPredicate()), hashes);
    }
    ExprNodeDesc filterPred = null;
    List<Boolean> nullSafes = joinTree.getNullSafes();
    for (int i = 0; i < joinKeys.length; i++) {
        if (nullSafes.get(i) || (joinKeys[i] instanceof ExprNodeColumnDesc && ((ExprNodeColumnDesc) joinKeys[i]).getIsPartitionColOrVirtualCol())) {
            // virtual column, since those columns can never be null.
            continue;
        }
        if (null != hashes.get(joinKeys[i].hashCode())) {
            // there is already a predicate on this src.
            continue;
        }
        List<ExprNodeDesc> args = new ArrayList<ExprNodeDesc>();
        args.add(joinKeys[i]);
        ExprNodeDesc nextExpr = ExprNodeGenericFuncDesc.newInstance(FunctionRegistry.getFunctionInfo("isnotnull").getGenericUDF(), args);
        filterPred = filterPred == null ? nextExpr : ExprNodeDescUtils.mergePredicates(filterPred, nextExpr);
    }
    if (filterPred == null) {
        return input;
    }
    OpParseContext inputCtx = opParseCtx.get(input);
    RowResolver inputRR = inputCtx.getRowResolver();
    if (input instanceof FilterOperator) {
        FilterOperator f = (FilterOperator) input;
        List<ExprNodeDesc> preds = new ArrayList<ExprNodeDesc>();
        preds.add(f.getConf().getPredicate());
        preds.add(filterPred);
        f.getConf().setPredicate(ExprNodeDescUtils.mergePredicates(preds));
        return input;
    }
    FilterDesc filterDesc = new FilterDesc(filterPred, false);
    filterDesc.setGenerated(true);
    Operator output = putOpInsertMap(OperatorFactory.getAndMakeChild(filterDesc, new RowSchema(inputRR.getColumnInfos()), input), inputRR);
    if (LOG.isDebugEnabled()) {
        LOG.debug("Created Filter Plan for " + qb.getId() + " row schema: " + inputRR.toString());
    }
    return output;
}

Example 30 with RowSchema

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

the class SemanticAnalyzer method genLateralViewPlan.

private Operator genLateralViewPlan(QB qb, Operator op, ASTNode lateralViewTree) throws SemanticException {
    RowResolver lvForwardRR = new RowResolver();
    RowResolver source = opParseCtx.get(op).getRowResolver();
    Map<String, ExprNodeDesc> lvfColExprMap = new HashMap<String, ExprNodeDesc>();
    Map<String, ExprNodeDesc> selColExprMap = new HashMap<String, ExprNodeDesc>();
    List<ExprNodeDesc> colList = new ArrayList<ExprNodeDesc>();
    List<String> colNames = new ArrayList<String>();
    for (ColumnInfo col : source.getColumnInfos()) {
        String[] tabCol = source.reverseLookup(col.getInternalName());
        lvForwardRR.put(tabCol[0], tabCol[1], col);
        ExprNodeDesc colExpr = new ExprNodeColumnDesc(col);
        colList.add(colExpr);
        colNames.add(colExpr.getName());
        lvfColExprMap.put(col.getInternalName(), colExpr);
        selColExprMap.put(col.getInternalName(), colExpr.clone());
    }
    Operator lvForward = putOpInsertMap(OperatorFactory.getAndMakeChild(new LateralViewForwardDesc(), new RowSchema(lvForwardRR.getColumnInfos()), op), lvForwardRR);
    lvForward.setColumnExprMap(lvfColExprMap);
    // The order in which the two paths are added is important. The
    // lateral view join operator depends on having the select operator
    // give it the row first.
    // Get the all path by making a select(*).
    RowResolver allPathRR = opParseCtx.get(lvForward).getRowResolver();
    // Operator allPath = op;
    SelectDesc sDesc = new SelectDesc(colList, colNames, false);
    sDesc.setSelStarNoCompute(true);
    Operator allPath = putOpInsertMap(OperatorFactory.getAndMakeChild(sDesc, new RowSchema(allPathRR.getColumnInfos()), lvForward), allPathRR);
    allPath.setColumnExprMap(selColExprMap);
    int allColumns = allPathRR.getColumnInfos().size();
    // Get the UDTF Path
    QB blankQb = new QB(null, null, false);
    Operator udtfPath = genSelectPlan(null, (ASTNode) lateralViewTree.getChild(0), blankQb, lvForward, null, lateralViewTree.getType() == HiveParser.TOK_LATERAL_VIEW_OUTER);
    // add udtf aliases to QB
    for (String udtfAlias : blankQb.getAliases()) {
        qb.addAlias(udtfAlias);
    }
    RowResolver udtfPathRR = opParseCtx.get(udtfPath).getRowResolver();
    // Merge the two into the lateral view join
    // The cols of the merged result will be the combination of both the
    // cols of the UDTF path and the cols of the all path. The internal
    // names have to be changed to avoid conflicts
    RowResolver lateralViewRR = new RowResolver();
    ArrayList<String> outputInternalColNames = new ArrayList<String>();
    // For PPD, we need a column to expression map so that during the walk,
    // the processor knows how to transform the internal col names.
    // Following steps are dependant on the fact that we called
    // LVmerge.. in the above order
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    LVmergeRowResolvers(allPathRR, lateralViewRR, colExprMap, outputInternalColNames);
    LVmergeRowResolvers(udtfPathRR, lateralViewRR, colExprMap, outputInternalColNames);
    Operator lateralViewJoin = putOpInsertMap(OperatorFactory.getAndMakeChild(new LateralViewJoinDesc(allColumns, outputInternalColNames), new RowSchema(lateralViewRR.getColumnInfos()), allPath, udtfPath), lateralViewRR);
    lateralViewJoin.setColumnExprMap(colExprMap);
    return lateralViewJoin;
}