Examples with AggregateCall org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall used on opensource projects

Example 61 with AggregateCall

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall in project beam by apache.

the class AggregateScanConverter method convertAggCall.

private AggregateCall convertAggCall(ResolvedComputedColumn computedColumn, int columnRefOff, int groupCount, RelNode input) {
    ResolvedAggregateFunctionCall aggregateFunctionCall = (ResolvedAggregateFunctionCall) computedColumn.getExpr();
    // Reject AVG(INT64)
    if (aggregateFunctionCall.getFunction().getName().equals("avg")) {
        FunctionSignature signature = aggregateFunctionCall.getSignature();
        if (signature.getFunctionArgumentList().get(0).getType().getKind().equals(TypeKind.TYPE_INT64)) {
            throw new UnsupportedOperationException(AVG_ILLEGAL_LONG_INPUT_TYPE);
        }
    }
    // Reject aggregation DISTINCT
    if (aggregateFunctionCall.getDistinct()) {
        throw new UnsupportedOperationException("Does not support " + aggregateFunctionCall.getFunction().getSqlName() + " DISTINCT. 'SELECT DISTINCT' syntax could be used to deduplicate before" + " aggregation.");
    }
    final SqlAggFunction sqlAggFunction;
    if (aggregateFunctionCall.getFunction().getGroup().equals(BeamZetaSqlCatalog.USER_DEFINED_JAVA_AGGREGATE_FUNCTIONS)) {
        // Create a new operator for user-defined functions.
        SqlReturnTypeInference typeInference = x -> ZetaSqlCalciteTranslationUtils.toCalciteType(aggregateFunctionCall.getFunction().getSignatureList().get(0).getResultType().getType(), // TODO(BEAM-9514) set nullable=true
        false, getCluster().getRexBuilder());
        UdafImpl<?, ?, ?> impl = new UdafImpl<>(getExpressionConverter().userFunctionDefinitions.javaAggregateFunctions().get(aggregateFunctionCall.getFunction().getNamePath()));
        sqlAggFunction = SqlOperators.createUdafOperator(aggregateFunctionCall.getFunction().getName(), typeInference, impl);
    } else {
        // Look up builtin functions in SqlOperatorMappingTable.
        sqlAggFunction = (SqlAggFunction) SqlOperatorMappingTable.create(aggregateFunctionCall);
        if (sqlAggFunction == null) {
            throw new UnsupportedOperationException("Does not support ZetaSQL aggregate function: " + aggregateFunctionCall.getFunction().getName());
        }
    }
    List<Integer> argList = new ArrayList<>();
    ResolvedAggregateFunctionCall expr = ((ResolvedAggregateFunctionCall) computedColumn.getExpr());
    List<ZetaSQLResolvedNodeKind.ResolvedNodeKind> resolvedNodeKinds = Arrays.asList(RESOLVED_CAST, RESOLVED_COLUMN_REF, RESOLVED_GET_STRUCT_FIELD);
    for (int i = 0; i < expr.getArgumentList().size(); i++) {
        // Throw an error if aggregate function's input isn't either a ColumnRef or a cast(ColumnRef).
        // TODO: is there a general way to handle aggregation calls conversion?
        ZetaSQLResolvedNodeKind.ResolvedNodeKind resolvedNodeKind = expr.getArgumentList().get(i).nodeKind();
        if (i == 0 && resolvedNodeKinds.contains(resolvedNodeKind)) {
            argList.add(columnRefOff);
        } else if (i > 0 && resolvedNodeKind == RESOLVED_LITERAL) {
            continue;
        } else {
            throw new UnsupportedOperationException("Aggregate function only accepts Column Reference or CAST(Column Reference) as the first argument and " + "Literals as subsequent arguments as its inputs");
        }
    }
    String aggName = getTrait().resolveAlias(computedColumn.getColumn());
    return AggregateCall.create(sqlAggFunction, false, false, false, argList, -1, null, RelCollations.EMPTY, groupCount, input, // When we pass null as the return type, Calcite infers it for us.
    null, aggName);
}

Example 62 with AggregateCall

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall in project druid by druid-io.

the class ArrayConcatSqlAggregator method toDruidAggregation.

@Nullable
@Override
public Aggregation toDruidAggregation(PlannerContext plannerContext, RowSignature rowSignature, VirtualColumnRegistry virtualColumnRegistry, RexBuilder rexBuilder, String name, AggregateCall aggregateCall, Project project, List<Aggregation> existingAggregations, boolean finalizeAggregations) {
    final List<RexNode> arguments = aggregateCall.getArgList().stream().map(i -> Expressions.fromFieldAccess(rowSignature, project, i)).collect(Collectors.toList());
    Integer maxSizeBytes = null;
    if (arguments.size() > 1) {
        RexNode maxBytes = arguments.get(1);
        if (!maxBytes.isA(SqlKind.LITERAL)) {
            // maxBytes must be a literal
            return null;
        }
        maxSizeBytes = ((Number) RexLiteral.value(maxBytes)).intValue();
    }
    final DruidExpression arg = Expressions.toDruidExpression(plannerContext, rowSignature, arguments.get(0));
    final ExprMacroTable macroTable = plannerContext.getExprMacroTable();
    final String fieldName;
    final ColumnType druidType = Calcites.getValueTypeForRelDataTypeFull(aggregateCall.getType());
    if (druidType == null || !druidType.isArray()) {
        // must be an array
        return null;
    }
    final String initialvalue = ExpressionType.fromColumnTypeStrict(druidType).asTypeString() + "[]";
    if (arg.isDirectColumnAccess()) {
        fieldName = arg.getDirectColumn();
    } else {
        VirtualColumn vc = virtualColumnRegistry.getOrCreateVirtualColumnForExpression(plannerContext, arg, druidType);
        fieldName = vc.getOutputName();
    }
    if (aggregateCall.isDistinct()) {
        return Aggregation.create(new ExpressionLambdaAggregatorFactory(name, ImmutableSet.of(fieldName), null, initialvalue, null, true, false, false, StringUtils.format("array_set_add_all(\"__acc\", \"%s\")", fieldName), StringUtils.format("array_set_add_all(\"__acc\", \"%s\")", name), null, null, maxSizeBytes != null ? new HumanReadableBytes(maxSizeBytes) : null, macroTable));
    } else {
        return Aggregation.create(new ExpressionLambdaAggregatorFactory(name, ImmutableSet.of(fieldName), null, initialvalue, null, true, false, false, StringUtils.format("array_concat(\"__acc\", \"%s\")", fieldName), StringUtils.format("array_concat(\"__acc\", \"%s\")", name), null, null, maxSizeBytes != null ? new HumanReadableBytes(maxSizeBytes) : null, macroTable));
    }
}

Example 63 with AggregateCall

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall in project hazelcast by hazelcast.

the class AggregateAbstractPhysicalRule method aggregateOperation.

protected static AggregateOperation<?, JetSqlRow> aggregateOperation(RelDataType inputType, ImmutableBitSet groupSet, List<AggregateCall> aggregateCalls) {
    List<QueryDataType> operandTypes = OptUtils.schema(inputType).getTypes();
    List<SupplierEx<SqlAggregation>> aggregationProviders = new ArrayList<>();
    List<FunctionEx<JetSqlRow, Object>> valueProviders = new ArrayList<>();
    for (Integer groupIndex : groupSet.toList()) {
        aggregationProviders.add(ValueSqlAggregation::new);
        // getMaybeSerialized is safe for ValueAggr because it only passes the value on
        valueProviders.add(new RowGetMaybeSerializedFn(groupIndex));
    }
    for (AggregateCall aggregateCall : aggregateCalls) {
        boolean distinct = aggregateCall.isDistinct();
        List<Integer> aggregateCallArguments = aggregateCall.getArgList();
        SqlKind kind = aggregateCall.getAggregation().getKind();
        switch(kind) {
            case COUNT:
                if (distinct) {
                    int countIndex = aggregateCallArguments.get(0);
                    aggregationProviders.add(new AggregateCountSupplier(true, true));
                    // getMaybeSerialized is safe for COUNT because the aggregation only looks whether it is null or not
                    valueProviders.add(new RowGetMaybeSerializedFn(countIndex));
                } else if (aggregateCallArguments.size() == 1) {
                    int countIndex = aggregateCallArguments.get(0);
                    aggregationProviders.add(new AggregateCountSupplier(true, false));
                    valueProviders.add(new RowGetMaybeSerializedFn(countIndex));
                } else {
                    aggregationProviders.add(new AggregateCountSupplier(false, false));
                    valueProviders.add(NullFunction.INSTANCE);
                }
                break;
            case MIN:
                int minIndex = aggregateCallArguments.get(0);
                aggregationProviders.add(MinSqlAggregation::new);
                valueProviders.add(new RowGetFn(minIndex));
                break;
            case MAX:
                int maxIndex = aggregateCallArguments.get(0);
                aggregationProviders.add(MaxSqlAggregation::new);
                valueProviders.add(new RowGetFn(maxIndex));
                break;
            case SUM:
                int sumIndex = aggregateCallArguments.get(0);
                QueryDataType sumOperandType = operandTypes.get(sumIndex);
                aggregationProviders.add(new AggregateSumSupplier(distinct, sumOperandType));
                valueProviders.add(new RowGetFn(sumIndex));
                break;
            case AVG:
                int avgIndex = aggregateCallArguments.get(0);
                QueryDataType avgOperandType = operandTypes.get(avgIndex);
                aggregationProviders.add(new AggregateAvgSupplier(distinct, avgOperandType));
                valueProviders.add(new RowGetFn(avgIndex));
                break;
            default:
                throw QueryException.error("Unsupported aggregation function: " + kind);
        }
    }
    return AggregateOperation.withCreate(new AggregateCreateSupplier(aggregationProviders)).andAccumulate(new AggregateAccumulateFunction(valueProviders)).andCombine(AggregateCombineFunction.INSTANCE).andExportFinish(AggregateExportFinishFunction.INSTANCE);
}

Example 64 with AggregateCall

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall in project druid by druid-io.

the class QuantileSqlAggregator method toDruidAggregation.

@Nullable
@Override
public Aggregation toDruidAggregation(final PlannerContext plannerContext, final RowSignature rowSignature, final VirtualColumnRegistry virtualColumnRegistry, final RexBuilder rexBuilder, final String name, final AggregateCall aggregateCall, final Project project, final List<Aggregation> existingAggregations, final boolean finalizeAggregations) {
    final DruidExpression input = Aggregations.toDruidExpressionForNumericAggregator(plannerContext, rowSignature, Expressions.fromFieldAccess(rowSignature, project, aggregateCall.getArgList().get(0)));
    if (input == null) {
        return null;
    }
    final AggregatorFactory aggregatorFactory;
    final String histogramName = StringUtils.format("%s:agg", name);
    final RexNode probabilityArg = Expressions.fromFieldAccess(rowSignature, project, aggregateCall.getArgList().get(1));
    if (!probabilityArg.isA(SqlKind.LITERAL)) {
        // Probability must be a literal in order to plan.
        return null;
    }
    final float probability = ((Number) RexLiteral.value(probabilityArg)).floatValue();
    final int resolution;
    if (aggregateCall.getArgList().size() >= 3) {
        final RexNode resolutionArg = Expressions.fromFieldAccess(rowSignature, project, aggregateCall.getArgList().get(2));
        if (!resolutionArg.isA(SqlKind.LITERAL)) {
            // Resolution must be a literal in order to plan.
            return null;
        }
        resolution = ((Number) RexLiteral.value(resolutionArg)).intValue();
    } else {
        resolution = ApproximateHistogram.DEFAULT_HISTOGRAM_SIZE;
    }
    final int numBuckets = ApproximateHistogram.DEFAULT_BUCKET_SIZE;
    final float lowerLimit = Float.NEGATIVE_INFINITY;
    final float upperLimit = Float.POSITIVE_INFINITY;
    // Look for existing matching aggregatorFactory.
    for (final Aggregation existing : existingAggregations) {
        for (AggregatorFactory factory : existing.getAggregatorFactories()) {
            if (factory instanceof ApproximateHistogramAggregatorFactory) {
                final ApproximateHistogramAggregatorFactory theFactory = (ApproximateHistogramAggregatorFactory) factory;
                // Check input for equivalence.
                final boolean inputMatches;
                final DruidExpression virtualInput = virtualColumnRegistry.findVirtualColumnExpressions(theFactory.requiredFields()).stream().findFirst().orElse(null);
                if (virtualInput == null) {
                    inputMatches = input.isDirectColumnAccess() && input.getDirectColumn().equals(theFactory.getFieldName());
                } else {
                    inputMatches = virtualInput.equals(input);
                }
                final boolean matches = inputMatches && theFactory.getResolution() == resolution && theFactory.getNumBuckets() == numBuckets && theFactory.getLowerLimit() == lowerLimit && theFactory.getUpperLimit() == upperLimit;
                if (matches) {
                    // Found existing one. Use this.
                    return Aggregation.create(ImmutableList.of(), new QuantilePostAggregator(name, factory.getName(), probability));
                }
            }
        }
    }
    // No existing match found. Create a new one.
    if (input.isDirectColumnAccess()) {
        if (rowSignature.getColumnType(input.getDirectColumn()).map(type -> type.is(ValueType.COMPLEX)).orElse(false)) {
            aggregatorFactory = new ApproximateHistogramFoldingAggregatorFactory(histogramName, input.getDirectColumn(), resolution, numBuckets, lowerLimit, upperLimit, false);
        } else {
            aggregatorFactory = new ApproximateHistogramAggregatorFactory(histogramName, input.getDirectColumn(), resolution, numBuckets, lowerLimit, upperLimit, false);
        }
    } else {
        final String virtualColumnName = virtualColumnRegistry.getOrCreateVirtualColumnForExpression(input, ColumnType.FLOAT);
        aggregatorFactory = new ApproximateHistogramAggregatorFactory(histogramName, virtualColumnName, resolution, numBuckets, lowerLimit, upperLimit, false);
    }
    return Aggregation.create(ImmutableList.of(aggregatorFactory), new QuantilePostAggregator(name, histogramName, probability));
}

Example 65 with AggregateCall

use of org.apache.beam.vendor.calcite.v1_28_0.org.apache.calcite.rel.core.AggregateCall in project hive by apache.

the class HiveRelOptUtil method createSingleValueAggRel.

/**
 * Creates a LogicalAggregate that removes all duplicates from the result of
 * an underlying relational expression.
 *
 * @param rel underlying rel
 * @return rel implementing SingleValueAgg
 */
public static RelNode createSingleValueAggRel(RelOptCluster cluster, RelNode rel, RelFactories.AggregateFactory aggregateFactory) {
    // assert (rel.getRowType().getFieldCount() == 1);
    final int aggCallCnt = rel.getRowType().getFieldCount();
    final List<AggregateCall> aggCalls = new ArrayList<>();
    for (int i = 0; i < aggCallCnt; i++) {
        aggCalls.add(AggregateCall.create(SqlStdOperatorTable.SINGLE_VALUE, false, false, ImmutableList.of(i), -1, 0, rel, null, null));
    }
    return aggregateFactory.createAggregate(rel, Collections.emptyList(), ImmutableBitSet.of(), null, aggCalls);
}