use of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator 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) 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.generator.getConf().getKeyCols().get(ctx.desc.getKeyIndex());
String internalColName = null;
ExprNodeDesc exprNodeDesc = key;
// Find the ExprNodeColumnDesc
while (!(exprNodeDesc instanceof ExprNodeColumnDesc) && (exprNodeDesc.getChildren() != null)) {
exprNodeDesc = exprNodeDesc.getChildren().get(0);
}
if (!(exprNodeDesc instanceof ExprNodeColumnDesc)) {
// Bail out
return false;
}
internalColName = ((ExprNodeColumnDesc) exprNodeDesc).getColumn();
if (parentOfRS instanceof SelectOperator) {
// Make sure the semijoin branch is not on partition column.
ExprNodeDesc expr = parentOfRS.getColumnExprMap().get(internalColName);
while (!(expr instanceof ExprNodeColumnDesc) && (expr.getChildren() != null)) {
expr = expr.getChildren().get(0);
}
if (!(expr instanceof ExprNodeColumnDesc)) {
// Bail out
return false;
}
ExprNodeColumnDesc colExpr = (ExprNodeColumnDesc) expr;
String colName = ExprNodeDescUtils.extractColName(colExpr);
// Fetch the TableScan Operator.
Operator<?> op = parentOfRS.getParentOperators().get(0);
while (op != null && !(op instanceof TableScanOperator)) {
op = op.getParentOperators().get(0);
}
assert op != null;
Table table = ((TableScanOperator) op).getConf().getTableMetadata();
if (table.isPartitionKey(colName)) {
// The column is partition column, skip the optimization.
return false;
}
}
List<ExprNodeDesc> keyExprs = new ArrayList<ExprNodeDesc>();
keyExprs.add(key);
// group by requires "ArrayList", don't ask.
ArrayList<String> outputNames = new ArrayList<String>();
outputNames.add(HiveConf.getColumnInternalName(0));
// 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);
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 (parentOfRS.getColumnExprMap() != null) {
exprNode = parentOfRS.getColumnExprMap().get(internalColName).clone();
} else {
exprNode = new ExprNodeColumnDesc(columnInfo);
}
if (exprNode instanceof ExprNodeColumnDesc) {
ExprNodeColumnDesc encd = (ExprNodeColumnDesc) exprNode;
encd.setColumn(internalColName);
}
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);
ArrayList<ExprNodeDesc> groupByExprs = new ArrayList<ExprNodeDesc>();
// 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);
bloomFilterEval.setMaxEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MAX_BLOOM_FILTER_ENTRIES));
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, null, false, 0, 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>();
for (int i = 0; i < aggs.size() - 1; i++) {
ExprNodeColumnDesc colExpr = new ExprNodeColumnDesc(key.getTypeInfo(), gbOutputNames.get(colPos++), "", false);
rsValueCols.add(colExpr);
}
// Bloom Filter uses binary
ExprNodeColumnDesc colExpr = new ExprNodeColumnDesc(TypeInfoFactory.binaryTypeInfo, gbOutputNames.get(colPos++), "", false);
rsValueCols.add(colExpr);
// Create the reduce sink operator
ReduceSinkDesc rsDesc = PlanUtils.getReduceSinkDesc(new ArrayList<ExprNodeDesc>(), rsValueCols, gbOutputNames, false, -1, 0, 1, Operation.NOT_ACID);
ReduceSinkOperator rsOp = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(rsDesc, new RowSchema(groupByOp.getSchema()), groupByOp);
Map<String, ExprNodeDesc> columnExprMap = new HashMap<String, ExprNodeDesc>();
rsOp.setColumnExprMap(columnExprMap);
// 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);
bloomFilterEval.setMaxEntries(parseContext.getConf().getLongVar(ConfVars.TEZ_MAX_BLOOM_FILTER_ENTRIES));
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, null, false, 0, false);
GroupByOperator groupByOpFinal = (GroupByOperator) OperatorFactory.getAndMakeChild(groupByDescFinal, new RowSchema(rsOp.getSchema()), rsOp);
groupByOpFinal.setColumnExprMap(new HashMap<String, ExprNodeDesc>());
// for explain purpose
if (parseContext.getContext().getExplainConfig() != null && parseContext.getContext().getExplainConfig().isFormatted()) {
List<String> outputOperators = new ArrayList<>();
outputOperators.add(groupByOpFinal.getOperatorId());
rsOp.getConf().setOutputOperators(outputOperators);
}
// Create the final Reduce Sink Operator
ReduceSinkDesc rsDescFinal = PlanUtils.getReduceSinkDesc(new ArrayList<ExprNodeDesc>(), rsValueCols, gbOutputNames, false, -1, 0, 1, Operation.NOT_ACID);
ReduceSinkOperator rsOpFinal = (ReduceSinkOperator) OperatorFactory.getAndMakeChild(rsDescFinal, new RowSchema(groupByOpFinal.getSchema()), groupByOpFinal);
rsOpFinal.setColumnExprMap(columnExprMap);
LOG.debug("DynamicMinMaxPushdown: Saving RS to TS mapping: " + rsOpFinal + ": " + ts);
parseContext.getRsOpToTsOpMap().put(rsOpFinal, ts);
// for explain purpose
if (parseContext.getContext().getExplainConfig() != null && parseContext.getContext().getExplainConfig().isFormatted()) {
List<String> outputOperators = new ArrayList<>();
outputOperators.add(ts.getOperatorId());
rsOpFinal.getConf().setOutputOperators(outputOperators);
}
// Save the info that is required at query time to resolve dynamic/runtime values.
RuntimeValuesInfo runtimeValuesInfo = new RuntimeValuesInfo();
TableDesc rsFinalTableDesc = PlanUtils.getReduceValueTableDesc(PlanUtils.getFieldSchemasFromColumnList(rsValueCols, "_col"));
List<String> dynamicValueIDs = new ArrayList<String>();
dynamicValueIDs.add(keyBaseAlias + "_min");
dynamicValueIDs.add(keyBaseAlias + "_max");
dynamicValueIDs.add(keyBaseAlias + "_bloom_filter");
runtimeValuesInfo.setTableDesc(rsFinalTableDesc);
runtimeValuesInfo.setDynamicValueIDs(dynamicValueIDs);
runtimeValuesInfo.setColExprs(rsValueCols);
parseContext.getRsToRuntimeValuesInfoMap().put(rsOpFinal, runtimeValuesInfo);
return true;
}
use of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator in project hive by apache.
the class VectorUDAFBloomFilter method init.
@Override
public void init(AggregationDesc desc) throws HiveException {
GenericUDAFBloomFilterEvaluator udafBloomFilter = (GenericUDAFBloomFilterEvaluator) desc.getGenericUDAFEvaluator();
expectedEntries = udafBloomFilter.getExpectedEntries();
}
use of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator in project hive by apache.
the class VectorUDAFBloomFilterMerge method init.
@Override
public void init(AggregationDesc desc) throws HiveException {
GenericUDAFBloomFilterEvaluator udafBloomFilter = (GenericUDAFBloomFilterEvaluator) desc.getGenericUDAFEvaluator();
expectedEntries = udafBloomFilter.getExpectedEntries();
}
use of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator in project hive by apache.
the class VectorUDAFBloomFilter method init.
private void init() {
GenericUDAFBloomFilterEvaluator udafBloomFilter = (GenericUDAFBloomFilterEvaluator) vecAggrDesc.getEvaluator();
expectedEntries = udafBloomFilter.getExpectedEntries();
bitSetSize = -1;
byteStream = new ByteArrayOutputStream();
// Instantiate the ValueProcessor based on the input type
ColumnVector.Type colVectorType;
try {
colVectorType = inputExpression.getOutputColumnVectorType();
} catch (HiveException e) {
throw new RuntimeException(e);
}
switch(colVectorType) {
case LONG:
case DECIMAL_64:
valueProcessor = new ValueProcessorLong();
break;
case DOUBLE:
valueProcessor = new ValueProcessorDouble();
break;
case DECIMAL:
valueProcessor = new ValueProcessorDecimal();
break;
case BYTES:
valueProcessor = new ValueProcessorBytes();
break;
case TIMESTAMP:
valueProcessor = new ValueProcessorTimestamp();
break;
default:
throw new IllegalStateException("Unsupported column vector type " + colVectorType);
}
}
use of org.apache.hadoop.hive.ql.udf.generic.GenericUDAFBloomFilter.GenericUDAFBloomFilterEvaluator 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;
}
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