Package org.apache.flink.api.scala.operators

Source Code of org.apache.flink.api.scala.operators.ScalaAggregateOperator$AggregatingUdf

/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements.  See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership.  The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License.  You may obtain a copy of the License at
*
*     http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/

package org.apache.flink.api.scala.operators;

import java.util.ArrayList;
import java.util.Iterator;
import java.util.List;

import org.apache.commons.lang3.Validate;
import org.apache.flink.api.common.InvalidProgramException;
import org.apache.flink.api.common.functions.GroupReduceFunction;
import org.apache.flink.api.common.operators.Operator;
import org.apache.flink.api.common.operators.SingleInputSemanticProperties;
import org.apache.flink.api.common.operators.UnaryOperatorInformation;
import org.apache.flink.api.common.operators.base.GroupReduceOperatorBase;
import org.apache.flink.api.common.typeutils.TypeSerializer;
import org.apache.flink.api.common.typeutils.TypeSerializerFactory;
import org.apache.flink.api.java.aggregation.AggregationFunction;
import org.apache.flink.api.java.aggregation.AggregationFunctionFactory;
import org.apache.flink.api.java.aggregation.Aggregations;
import org.apache.flink.api.common.functions.RichGroupReduceFunction;
import org.apache.flink.api.common.functions.RichGroupReduceFunction.Combinable;
import org.apache.flink.api.java.operators.Grouping;
import org.apache.flink.api.java.operators.Keys;
import org.apache.flink.api.java.operators.SingleInputOperator;
import org.apache.flink.api.java.typeutils.TupleTypeInfoBase;
import org.apache.flink.api.java.typeutils.runtime.RuntimeStatefulSerializerFactory;
import org.apache.flink.api.java.typeutils.runtime.RuntimeStatelessSerializerFactory;
import org.apache.flink.api.java.typeutils.runtime.TupleSerializerBase;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.util.Collector;

import scala.Product;

/**
* This operator represents the application of a "aggregate" operation on a data set, and the
* result data set produced by the function.
*
* @param <IN> The type of the data set aggregated by the operator.
*/
public class ScalaAggregateOperator<IN> extends SingleInputOperator<IN, IN, ScalaAggregateOperator<IN>> {

  private final List<AggregationFunction<?>> aggregationFunctions = new ArrayList<AggregationFunction<?>>(4);

  private final List<Integer> fields = new ArrayList<Integer>(4);

  private final Grouping<IN> grouping;

  /**
   * <p>
   * Non grouped aggregation
   */
  public ScalaAggregateOperator(org.apache.flink.api.java.DataSet<IN> input, Aggregations function, int field) {
    super(Validate.notNull(input), input.getType());

    Validate.notNull(function);

    if (!input.getType().isTupleType()) {
      throw new InvalidProgramException("Aggregating on field positions is only possible on tuple data types.");
    }

    TupleTypeInfoBase<?> inType = (TupleTypeInfoBase<?>) input.getType();

    if (field < 0 || field >= inType.getArity()) {
      throw new IllegalArgumentException("Aggregation field position is out of range.");
    }

    AggregationFunctionFactory factory = function.getFactory();
    AggregationFunction<?> aggFunct = factory.createAggregationFunction(inType.getTypeAt(field).getTypeClass());

    // this is the first aggregation operator after a regular data set (non grouped aggregation)
    this.aggregationFunctions.add(aggFunct);
    this.fields.add(field);
    this.grouping = null;
  }

  /**
   *
   * Grouped aggregation
   *
   * @param input
   * @param function
   * @param field
   */
  public ScalaAggregateOperator(Grouping<IN> input, Aggregations function, int field) {
    super(Validate.notNull(input).getDataSet(), input.getDataSet().getType());

    Validate.notNull(function);

    if (!input.getDataSet().getType().isTupleType()) {
      throw new InvalidProgramException("Aggregating on field positions is only possible on tuple data types.");
    }

    TupleTypeInfoBase<?> inType = (TupleTypeInfoBase<?>) input.getDataSet().getType();

    if (field < 0 || field >= inType.getArity()) {
      throw new IllegalArgumentException("Aggregation field position is out of range.");
    }

    AggregationFunctionFactory factory = function.getFactory();
    AggregationFunction<?> aggFunct = factory.createAggregationFunction(inType.getTypeAt(field).getTypeClass());

    // set the aggregation fields
    this.aggregationFunctions.add(aggFunct);
    this.fields.add(field);
    this.grouping = input;
  }


  public ScalaAggregateOperator<IN> and(Aggregations function, int field) {
    Validate.notNull(function);

    TupleTypeInfoBase<?> inType = (TupleTypeInfoBase<?>) getType();

    if (field < 0 || field >= inType.getArity()) {
      throw new IllegalArgumentException("Aggregation field position is out of range.");
    }


    AggregationFunctionFactory factory = function.getFactory();
    AggregationFunction<?> aggFunct = factory.createAggregationFunction(inType.getTypeAt(field).getTypeClass());

    this.aggregationFunctions.add(aggFunct);
    this.fields.add(field);

    return this;
  }

  @SuppressWarnings("unchecked")
  @Override
  protected org.apache.flink.api.common.operators.base.GroupReduceOperatorBase<IN, IN, GroupReduceFunction<IN, IN>> translateToDataFlow(Operator<IN> input) {

    // sanity check
    if (this.aggregationFunctions.isEmpty() || this.aggregationFunctions.size() != this.fields.size()) {
      throw new IllegalStateException();
    }


    // construct the aggregation function
    AggregationFunction<Object>[] aggFunctions = new AggregationFunction[this.aggregationFunctions.size()];
    int[] fields = new int[this.fields.size()];
    StringBuilder genName = new StringBuilder();

    for (int i = 0; i < fields.length; i++) {
      aggFunctions[i] = (AggregationFunction<Object>) this.aggregationFunctions.get(i);
      fields[i] = this.fields.get(i);

      genName.append(aggFunctions[i].toString()).append('(').append(fields[i]).append(')').append(',');
    }
    genName.setLength(genName.length()-1);

    TypeSerializer<IN> serializer = getInputType().createSerializer();
    TypeSerializerFactory<IN> serializerFactory = null;
    if (serializer.isStateful()) {
      serializerFactory = new RuntimeStatefulSerializerFactory<IN>(
          serializer, getInputType().getTypeClass());
    } else {
      serializerFactory = new RuntimeStatelessSerializerFactory<IN>(
          serializer, getInputType().getTypeClass());
    }

    @SuppressWarnings("rawtypes")
    RichGroupReduceFunction<IN, IN> function = new AggregatingUdf(serializerFactory, aggFunctions, fields);


    String name = getName() != null ? getName() : genName.toString();

    // distinguish between grouped reduce and non-grouped reduce
    if (this.grouping == null) {
      // non grouped aggregation
      UnaryOperatorInformation<IN, IN> operatorInfo = new UnaryOperatorInformation<IN, IN>(getInputType(), getResultType());
      GroupReduceOperatorBase<IN, IN, GroupReduceFunction<IN, IN>> po =
          new GroupReduceOperatorBase<IN, IN, GroupReduceFunction<IN, IN>>(function, operatorInfo, new int[0], name);

      po.setCombinable(true);

      // set input
      po.setInput(input);
      // set dop
      po.setDegreeOfParallelism(this.getParallelism());

      return po;
    }

    if (this.grouping.getKeys() instanceof Keys.ExpressionKeys) {
      // grouped aggregation
      int[] logicalKeyPositions = this.grouping.getKeys().computeLogicalKeyPositions();
      UnaryOperatorInformation<IN, IN> operatorInfo = new UnaryOperatorInformation<IN, IN>(getInputType(), getResultType());
      GroupReduceOperatorBase<IN, IN, GroupReduceFunction<IN, IN>> po =
          new GroupReduceOperatorBase<IN, IN, GroupReduceFunction<IN, IN>>(function, operatorInfo, logicalKeyPositions, name);

      po.setCombinable(true);

      // set input
      po.setInput(input);
      // set dop
      po.setDegreeOfParallelism(this.getParallelism());

      SingleInputSemanticProperties props = new SingleInputSemanticProperties();

      for (int i = 0; i < logicalKeyPositions.length; i++) {
        int keyField = logicalKeyPositions[i];
        boolean keyFieldUsedInAgg = false;

        for (int k = 0; k < fields.length; k++) {
          int aggField = fields[k];
          if (keyField == aggField) {
            keyFieldUsedInAgg = true;
            break;
          }
        }

        if (!keyFieldUsedInAgg) {
          props.addForwardedField(keyField, keyField);
        }
      }

      po.setSemanticProperties(props);

      return po;
    }
    else if (this.grouping.getKeys() instanceof Keys.SelectorFunctionKeys) {
      throw new UnsupportedOperationException("Aggregate does not support grouping with KeySelector functions, yet.");
    }
    else {
      throw new UnsupportedOperationException("Unrecognized key type.");
    }

  }

  // --------------------------------------------------------------------------------------------

  @Combinable
  public static final class AggregatingUdf<T extends Product> extends RichGroupReduceFunction<T, T> {
    private static final long serialVersionUID = 1L;

    private final int[] fieldPositions;

    private final AggregationFunction<Object>[] aggFunctions;

    private final TypeSerializerFactory<T> serializerFactory;

    private transient TupleSerializerBase<T> serializer;

    public AggregatingUdf(TypeSerializerFactory<T> serializerFactory, AggregationFunction<Object>[] aggFunctions, int[] fieldPositions) {
      Validate.notNull(serializerFactory);
      Validate.notNull(aggFunctions);
      Validate.isTrue(aggFunctions.length == fieldPositions.length);
      Validate.isTrue(serializerFactory.getSerializer() instanceof TupleSerializerBase);

      this.serializerFactory = serializerFactory;
      this.aggFunctions = aggFunctions;
      this.fieldPositions = fieldPositions;
    }


    @Override
    public void open(Configuration parameters) throws Exception {
      for (int i = 0; i < aggFunctions.length; i++) {
        aggFunctions[i].initializeAggregate();
      }
      serializer = (TupleSerializerBase<T>)serializerFactory.getSerializer();
    }

    @Override
    public void reduce(Iterable<T> records, Collector<T> out) {
      final AggregationFunction<Object>[] aggFunctions = this.aggFunctions;
      final int[] fieldPositions = this.fieldPositions;

      // aggregators are initialized from before

      T current = null;
      final Iterator<T> values = records.iterator();
      while (values.hasNext()) {
        current = values.next();

        for (int i = 0; i < fieldPositions.length; i++) {
          Object val = current.productElement(fieldPositions[i]);
          aggFunctions[i].aggregate(val);
        }
      }

      Object[] fields = new Object[serializer.getArity()];
      int length = serializer.getArity();
      // First copy all tuple fields, then overwrite the aggregated ones
      for (int i = 0; i < length; i++) {
        fields[i] = current.productElement(i);
      }
      for (int i = 0; i < fieldPositions.length; i++) {
        Object aggVal = aggFunctions[i].getAggregate();
        fields[fieldPositions[i]] = aggVal;
        aggFunctions[i].initializeAggregate();
      }

      T result = serializer.createInstance(fields);

      out.collect(result);
    }

  }
}
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