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

Example 6 with ReduceSinkDesc

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

the class DynamicPartitionPruningOptimization method generateSemiJoinOperatorPlan.

// Generates plan for min/max when dynamic partition pruning is ruled out.
private boolean generateSemiJoinOperatorPlan(DynamicListContext ctx, ParseContext parseContext, TableScanOperator ts, String keyBaseAlias, String internalColName, String colName, SemiJoinHint sjHint) throws SemanticException {
    // we will put a fork in the plan at the source of the reduce sink
    Operator<? extends OperatorDesc> parentOfRS = ctx.generator.getParentOperators().get(0);
    // we need the expr that generated the key of the reduce sink
    ExprNodeDesc key = ctx.getKeyCol();
    assert colName != null;
    // Fetch the TableScan Operator.
    Operator<?> op = parentOfRS;
    while (!(op == null || op instanceof TableScanOperator || op instanceof ReduceSinkOperator)) {
        op = op.getParentOperators().get(0);
    }
    Preconditions.checkNotNull(op);
    if (op instanceof TableScanOperator) {
        Table table = ((TableScanOperator) op).getConf().getTableMetadata();
        if (table.isPartitionKey(colName)) {
            // The column is partition column, skip the optimization.
            return false;
        }
    }
    // Check if there already exists a semijoin branch
    GroupByOperator gb = parseContext.getColExprToGBMap().get(key);
    if (gb != null) {
        // Already an existing semijoin branch, reuse it
        createFinalRsForSemiJoinOp(parseContext, ts, gb, key, keyBaseAlias, ctx.parent.getChildren().get(0), sjHint != null);
        // done!
        return true;
    }
    List<ExprNodeDesc> keyExprs = new ArrayList<ExprNodeDesc>();
    keyExprs.add(key);
    // group by requires "ArrayList", don't ask.
    ArrayList<String> outputNames = new ArrayList<String>();
    // project the relevant key column
    SelectDesc select = new SelectDesc(keyExprs, outputNames);
    // Create the new RowSchema for the projected column
    ColumnInfo columnInfo = parentOfRS.getSchema().getColumnInfo(internalColName);
    columnInfo = new ColumnInfo(columnInfo);
    outputNames.add(internalColName);
    ArrayList<ColumnInfo> signature = new ArrayList<ColumnInfo>();
    signature.add(columnInfo);
    RowSchema rowSchema = new RowSchema(signature);
    // Create the column expr map
    Map<String, ExprNodeDesc> colExprMap = new HashMap<String, ExprNodeDesc>();
    ExprNodeDesc exprNode = null;
    if (columnInfo == null) {
        LOG.debug("No ColumnInfo found in {} for {}", parentOfRS.getOperatorId(), internalColName);
        return false;
    }
    exprNode = new ExprNodeColumnDesc(columnInfo);
    colExprMap.put(internalColName, exprNode);
    // Create the Select Operator
    SelectOperator selectOp = (SelectOperator) OperatorFactory.getAndMakeChild(select, rowSchema, colExprMap, parentOfRS);
    // do a group by to aggregate min,max and bloom filter.
    float groupByMemoryUsage = HiveConf.getFloatVar(parseContext.getConf(), HiveConf.ConfVars.HIVEMAPAGGRHASHMEMORY);
    float memoryThreshold = HiveConf.getFloatVar(parseContext.getConf(), HiveConf.ConfVars.HIVEMAPAGGRMEMORYTHRESHOLD);
    float minReductionHashAggr = HiveConf.getFloatVar(parseContext.getConf(), ConfVars.HIVEMAPAGGRHASHMINREDUCTION);
    float minReductionHashAggrLowerBound = HiveConf.getFloatVar(parseContext.getConf(), ConfVars.HIVEMAPAGGRHASHMINREDUCTIONLOWERBOUND);
    // Add min/max and bloom filter aggregations
    List<ObjectInspector> aggFnOIs = new ArrayList<ObjectInspector>();
    aggFnOIs.add(key.getWritableObjectInspector());
    ArrayList<ExprNodeDesc> params = new ArrayList<ExprNodeDesc>();
    params.add(new ExprNodeColumnDesc(key.getTypeInfo(), outputNames.get(0), "", false));
    ArrayList<AggregationDesc> aggs = new ArrayList<AggregationDesc>();
    try {
        AggregationDesc min = new AggregationDesc("min", FunctionRegistry.getGenericUDAFEvaluator("min", aggFnOIs, false, false), params, false, Mode.PARTIAL1);
        AggregationDesc max = new AggregationDesc("max", FunctionRegistry.getGenericUDAFEvaluator("max", aggFnOIs, false, false), params, false, Mode.PARTIAL1);
        AggregationDesc bloomFilter = new AggregationDesc("bloom_filter", FunctionRegistry.getGenericUDAFEvaluator("bloom_filter", aggFnOIs, false, false), params, false, Mode.PARTIAL1);
        GenericUDAFBloomFilterEvaluator bloomFilterEval = (GenericUDAFBloomFilterEvaluator) bloomFilter.getGenericUDAFEvaluator();
        bloomFilterEval.setSourceOperator(selectOp);
        if (sjHint != null && sjHint.getNumEntries() > 0) {
            LOG.debug("Setting size for " + keyBaseAlias + " to " + sjHint.getNumEntries() + " based on the hint");
            bloomFilterEval.setHintEntries(sjHint.getNumEntries());
        }
        bloomFilterEval.setMaxEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MAX_BLOOM_FILTER_ENTRIES));
        bloomFilterEval.setMinEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MIN_BLOOM_FILTER_ENTRIES));
        bloomFilterEval.setFactor(parseContext.getConf().getFloatVar(ConfVars.TEZ_BLOOM_FILTER_FACTOR));
        bloomFilter.setGenericUDAFWritableEvaluator(bloomFilterEval);
        aggs.add(min);
        aggs.add(max);
        aggs.add(bloomFilter);
    } catch (SemanticException e) {
        LOG.error("Error creating min/max aggregations on key", e);
        throw new IllegalStateException("Error creating min/max aggregations on key", e);
    }
    // Create the Group by Operator
    ArrayList<String> gbOutputNames = new ArrayList<String>();
    gbOutputNames.add(SemanticAnalyzer.getColumnInternalName(0));
    gbOutputNames.add(SemanticAnalyzer.getColumnInternalName(1));
    gbOutputNames.add(SemanticAnalyzer.getColumnInternalName(2));
    GroupByDesc groupBy = new GroupByDesc(GroupByDesc.Mode.HASH, gbOutputNames, new ArrayList<ExprNodeDesc>(), aggs, false, groupByMemoryUsage, memoryThreshold, minReductionHashAggr, minReductionHashAggrLowerBound, null, false, -1, false);
    ArrayList<ColumnInfo> groupbyColInfos = new ArrayList<ColumnInfo>();
    groupbyColInfos.add(new ColumnInfo(gbOutputNames.get(0), key.getTypeInfo(), "", false));
    groupbyColInfos.add(new ColumnInfo(gbOutputNames.get(1), key.getTypeInfo(), "", false));
    groupbyColInfos.add(new ColumnInfo(gbOutputNames.get(2), key.getTypeInfo(), "", false));
    GroupByOperator groupByOp = (GroupByOperator) OperatorFactory.getAndMakeChild(groupBy, new RowSchema(groupbyColInfos), selectOp);
    groupByOp.setColumnExprMap(new HashMap<String, ExprNodeDesc>());
    // Get the column names of the aggregations for reduce sink
    int colPos = 0;
    ArrayList<ExprNodeDesc> rsValueCols = new ArrayList<ExprNodeDesc>();
    Map<String, ExprNodeDesc> columnExprMap = new HashMap<String, ExprNodeDesc>();
    for (int i = 0; i < aggs.size() - 1; i++) {
        ExprNodeColumnDesc colExpr = new ExprNodeColumnDesc(key.getTypeInfo(), gbOutputNames.get(colPos), "", false);
        rsValueCols.add(colExpr);
        columnExprMap.put(gbOutputNames.get(colPos), colExpr);
        colPos++;
    }
    // Bloom Filter uses binary
    ExprNodeColumnDesc colExpr = new ExprNodeColumnDesc(TypeInfoFactory.binaryTypeInfo, gbOutputNames.get(colPos), "", false);
    rsValueCols.add(colExpr);
    columnExprMap.put(gbOutputNames.get(colPos), colExpr);
    colPos++;
    // Create the reduce sink operator
    ReduceSinkDesc rsDesc = PlanUtils.getReduceSinkDesc(new ArrayList<ExprNodeDesc>(), rsValueCols, gbOutputNames, false, -1, 0, 1, Operation.NOT_ACID, NullOrdering.defaultNullOrder(parseContext.getConf()));
    ReduceSinkOperator rsOp = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(rsDesc, new RowSchema(groupByOp.getSchema()), groupByOp);
    rsOp.setColumnExprMap(columnExprMap);
    rsOp.getConf().setReducerTraits(EnumSet.of(ReduceSinkDesc.ReducerTraits.QUICKSTART));
    // Create the final Group By Operator
    ArrayList<AggregationDesc> aggsFinal = new ArrayList<AggregationDesc>();
    try {
        List<ObjectInspector> minFinalFnOIs = new ArrayList<ObjectInspector>();
        List<ObjectInspector> maxFinalFnOIs = new ArrayList<ObjectInspector>();
        List<ObjectInspector> bloomFilterFinalFnOIs = new ArrayList<ObjectInspector>();
        ArrayList<ExprNodeDesc> minFinalParams = new ArrayList<ExprNodeDesc>();
        ArrayList<ExprNodeDesc> maxFinalParams = new ArrayList<ExprNodeDesc>();
        ArrayList<ExprNodeDesc> bloomFilterFinalParams = new ArrayList<ExprNodeDesc>();
        // Use the expressions from Reduce Sink.
        minFinalFnOIs.add(rsValueCols.get(0).getWritableObjectInspector());
        maxFinalFnOIs.add(rsValueCols.get(1).getWritableObjectInspector());
        bloomFilterFinalFnOIs.add(rsValueCols.get(2).getWritableObjectInspector());
        // Coming from a ReduceSink the aggregations would be in the form VALUE._col0, VALUE._col1
        minFinalParams.add(new ExprNodeColumnDesc(rsValueCols.get(0).getTypeInfo(), Utilities.ReduceField.VALUE + "." + gbOutputNames.get(0), "", false));
        maxFinalParams.add(new ExprNodeColumnDesc(rsValueCols.get(1).getTypeInfo(), Utilities.ReduceField.VALUE + "." + gbOutputNames.get(1), "", false));
        bloomFilterFinalParams.add(new ExprNodeColumnDesc(rsValueCols.get(2).getTypeInfo(), Utilities.ReduceField.VALUE + "." + gbOutputNames.get(2), "", false));
        AggregationDesc min = new AggregationDesc("min", FunctionRegistry.getGenericUDAFEvaluator("min", minFinalFnOIs, false, false), minFinalParams, false, Mode.FINAL);
        AggregationDesc max = new AggregationDesc("max", FunctionRegistry.getGenericUDAFEvaluator("max", maxFinalFnOIs, false, false), maxFinalParams, false, Mode.FINAL);
        AggregationDesc bloomFilter = new AggregationDesc("bloom_filter", FunctionRegistry.getGenericUDAFEvaluator("bloom_filter", bloomFilterFinalFnOIs, false, false), bloomFilterFinalParams, false, Mode.FINAL);
        GenericUDAFBloomFilterEvaluator bloomFilterEval = (GenericUDAFBloomFilterEvaluator) bloomFilter.getGenericUDAFEvaluator();
        bloomFilterEval.setSourceOperator(selectOp);
        if (sjHint != null && sjHint.getNumEntries() > 0) {
            bloomFilterEval.setHintEntries(sjHint.getNumEntries());
        }
        bloomFilterEval.setMaxEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MAX_BLOOM_FILTER_ENTRIES));
        bloomFilterEval.setMinEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MIN_BLOOM_FILTER_ENTRIES));
        bloomFilterEval.setFactor(parseContext.getConf().getFloatVar(ConfVars.TEZ_BLOOM_FILTER_FACTOR));
        bloomFilter.setGenericUDAFWritableEvaluator(bloomFilterEval);
        aggsFinal.add(min);
        aggsFinal.add(max);
        aggsFinal.add(bloomFilter);
    } catch (SemanticException e) {
        LOG.error("Error creating min/max aggregations on key", e);
        throw new IllegalStateException("Error creating min/max aggregations on key", e);
    }
    GroupByDesc groupByDescFinal = new GroupByDesc(GroupByDesc.Mode.FINAL, gbOutputNames, new ArrayList<ExprNodeDesc>(), aggsFinal, false, groupByMemoryUsage, memoryThreshold, minReductionHashAggr, minReductionHashAggrLowerBound, null, false, 0, false);
    GroupByOperator groupByOpFinal = (GroupByOperator) OperatorFactory.getAndMakeChild(groupByDescFinal, new RowSchema(rsOp.getSchema()), rsOp);
    groupByOpFinal.setColumnExprMap(new HashMap<String, ExprNodeDesc>());
    createFinalRsForSemiJoinOp(parseContext, ts, groupByOpFinal, key, keyBaseAlias, ctx.parent.getChildren().get(0), sjHint != null);
    return true;
}

Example 7 with ReduceSinkDesc

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

the class GenMapRedUtils method initPlan.

/**
 * Initialize the current plan by adding it to root tasks.
 *
 * @param op
 *          the reduce sink operator encountered
 * @param opProcCtx
 *          processing context
 */
public static void initPlan(ReduceSinkOperator op, GenMRProcContext opProcCtx) throws SemanticException {
    Operator<? extends OperatorDesc> reducer = op.getChildOperators().get(0);
    Map<Operator<? extends OperatorDesc>, GenMapRedCtx> mapCurrCtx = opProcCtx.getMapCurrCtx();
    GenMapRedCtx mapredCtx = mapCurrCtx.get(op.getParentOperators().get(0));
    Task<?> currTask = mapredCtx.getCurrTask();
    MapredWork plan = (MapredWork) currTask.getWork();
    HashMap<Operator<? extends OperatorDesc>, Task<?>> opTaskMap = opProcCtx.getOpTaskMap();
    TableScanOperator currTopOp = opProcCtx.getCurrTopOp();
    opTaskMap.put(reducer, currTask);
    plan.setReduceWork(new ReduceWork());
    plan.getReduceWork().setReducer(reducer);
    ReduceSinkDesc desc = op.getConf();
    plan.getReduceWork().setNumReduceTasks(desc.getNumReducers());
    if (needsTagging(plan.getReduceWork())) {
        plan.getReduceWork().setNeedsTagging(true);
    }
    assert currTopOp != null;
    String currAliasId = opProcCtx.getCurrAliasId();
    if (!opProcCtx.isSeenOp(currTask, currTopOp)) {
        setTaskPlan(currAliasId, currTopOp, currTask, false, opProcCtx);
    }
    currTopOp = null;
    currAliasId = null;
    opProcCtx.setCurrTask(currTask);
    opProcCtx.setCurrTopOp(currTopOp);
    opProcCtx.setCurrAliasId(currAliasId);
}

Example 8 with ReduceSinkDesc

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

the class GenMapRedUtils method initUnionPlan.

/**
 * Initialize the current union plan.
 *
 * @param op
 *          the reduce sink operator encountered
 * @param opProcCtx
 *          processing context
 */
public static void initUnionPlan(ReduceSinkOperator op, UnionOperator currUnionOp, GenMRProcContext opProcCtx, Task<?> unionTask) throws SemanticException {
    Operator<? extends OperatorDesc> reducer = op.getChildOperators().get(0);
    MapredWork plan = (MapredWork) unionTask.getWork();
    HashMap<Operator<? extends OperatorDesc>, Task<?>> opTaskMap = opProcCtx.getOpTaskMap();
    opTaskMap.put(reducer, unionTask);
    plan.setReduceWork(new ReduceWork());
    plan.getReduceWork().setReducer(reducer);
    plan.getReduceWork().setReducer(reducer);
    ReduceSinkDesc desc = op.getConf();
    plan.getReduceWork().setNumReduceTasks(desc.getNumReducers());
    if (needsTagging(plan.getReduceWork())) {
        plan.getReduceWork().setNeedsTagging(true);
    }
    initUnionPlan(opProcCtx, currUnionOp, unionTask, false);
}

Example 9 with ReduceSinkDesc

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

the class GenMapRedUtils method splitPlan.

/**
 * Met cRS in pOP(parentTask with RS)-cRS-cOP(noTask) case
 * Create new child task for cRS-cOP and link two tasks by temporary file : pOP-FS / TS-cRS-cOP
 *
 * @param cRS
 *          the reduce sink operator encountered
 * @param opProcCtx
 *          processing context
 */
static void splitPlan(ReduceSinkOperator cRS, GenMRProcContext opProcCtx) throws SemanticException {
    // Generate a new task
    ParseContext parseCtx = opProcCtx.getParseCtx();
    Task<?> parentTask = opProcCtx.getCurrTask();
    MapredWork childPlan = getMapRedWork(parseCtx);
    Task<?> childTask = TaskFactory.get(childPlan);
    Operator<? extends OperatorDesc> reducer = cRS.getChildOperators().get(0);
    // Add the reducer
    ReduceWork rWork = new ReduceWork();
    childPlan.setReduceWork(rWork);
    rWork.setReducer(reducer);
    ReduceSinkDesc desc = cRS.getConf();
    childPlan.getReduceWork().setNumReduceTasks(Integer.valueOf(desc.getNumReducers()));
    opProcCtx.getOpTaskMap().put(reducer, childTask);
    splitTasks(cRS, parentTask, childTask, opProcCtx);
}

Example 10 with ReduceSinkDesc

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

the class ColumnPrunerProcFactory method getPruneReduceSinkOpRetainFlags.

private static boolean[] getPruneReduceSinkOpRetainFlags(List<String> retainedParentOpOutputCols, ReduceSinkOperator reduce) {
    ReduceSinkDesc reduceConf = reduce.getConf();
    List<ExprNodeDesc> originalValueEval = reduceConf.getValueCols();
    boolean[] flags = new boolean[originalValueEval.size()];
    for (int i = 0; i < originalValueEval.size(); i++) {
        flags[i] = false;
        List<String> current = originalValueEval.get(i).getCols();
        if (current == null || current.size() == 0) {
            flags[i] = true;
        } else {
            for (int j = 0; j < current.size(); j++) {
                if (retainedParentOpOutputCols.contains(current.get(j))) {
                    flags[i] = true;
                    break;
                }
            }
        }
    }
    return flags;
}