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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-1293) Add support for out-of-place aggregations
Date Mon, 01 Dec 2014 13:20:13 GMT

    [ https://issues.apache.org/jira/browse/FLINK-1293?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14229773#comment-14229773
] 

ASF GitHub Bot commented on FLINK-1293:
---------------------------------------

Github user fhueske commented on a diff in the pull request:

    https://github.com/apache/incubator-flink/pull/243#discussion_r21087628
  
    --- Diff: flink-java/src/main/java/org/apache/flink/api/java/aggregation/AggregationOperatorFactory.java
---
    @@ -0,0 +1,297 @@
    +/*
    + * 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.java.aggregation;
    +
    +import static java.lang.String.format;
    +import static java.util.Arrays.asList;
    +import static org.apache.flink.api.java.aggregation.Aggregations.key;
    +
    +import java.util.ArrayList;
    +import java.util.List;
    +import java.util.Vector;
    +
    +import org.apache.commons.lang3.ArrayUtils;
    +import org.apache.commons.lang3.Validate;
    +import org.apache.flink.api.common.typeinfo.BasicTypeInfo;
    +import org.apache.flink.api.common.typeinfo.TypeInformation;
    +import org.apache.flink.api.java.DataSet;
    +import org.apache.flink.api.java.aggregation.AggregationFunction.ResultTypeBehavior;
    +import org.apache.flink.api.java.operators.AggregationOperator;
    +import org.apache.flink.api.java.operators.UnsortedGrouping;
    +import org.apache.flink.api.java.tuple.Tuple;
    +import org.apache.flink.api.java.typeutils.TupleTypeInfo;
    +import org.apache.flink.api.java.typeutils.TupleTypeInfoBase;
    +
    +import com.google.common.primitives.Ints;
    +
    +/**
    + * Factory method container to construct an
    + * {@link AggregationOperator} from a {@link DataSet} or
    + * {@link UnsortedGrouping}.
    + * 
    + * <p>The factory performs the following tasks:
    + * 
    + * <ol>
    + *  <li>Decompose composite aggregation functions into intermediates.
    + *  <li>Insert missing key aggregation function for any group keys. 
    + *  <li>Set intermediate, and output position for each aggregation function.
    + *  <li>Map any group keys to their position in the intermediate tuple.
    + *  <li>Compute the types of intermediate tuple and aggregation result.
    + *  <li>Create the aggregation operator.
    + * </ol>
    + *
    + * <p>Note: Tasks are implemented in a member class in order to
    + * facilitate testing. 
    + */
    +public class AggregationOperatorFactory {
    +	
    +	private static final AggregationOperatorFactory INSTANCE = new AggregationOperatorFactory();
    +	private AggregationFunctionPreprocessor aggregationFunctionPreprocessor = new AggregationFunctionPreprocessor();
    +	private ResultTypeFactory resultTypeFactory = new ResultTypeFactory();
    +	
    +	
    +	/**
    +	 * Construct an {@link AggregationOperator} that implements the
    +	 * aggregation functions listed in {@code functions} on the
    +	 * (ungrouped) DataSet {@code input}. 
    +	 * @param input	An (ungrouped) DataSet.
    +	 * @param functions The aggregation functions that should be computed.
    +	 * @return An AggregationOperator representing the specified aggregations.
    +	 */
    +	public <T, R extends Tuple> AggregationOperator<T, R> aggregate(DataSet<T>
input, AggregationFunction<?, ?>[] functions) {
    +		AggregationOperator<T, R> op = createAggregationOperator(input, new int[0], functions);
    +		return op;
    +	}
    +
    +	/**
    +	 * Construct an {@link AggregationOperator} that implements the
    +	 * aggregation functions listed in {@code functions} on the grouped
    +	 * DataSet {@code input}.
    +	 * 
    +	 * <p>If there are no {@link Aggregations.keys} specified in
    +	 * {@code functions} then a {@code key()} aggregation function is
    +	 * inserted for each group key.
    +	 *  
    +	 * @param input	An grouped DataSet.
    +	 * @param functions The aggregation functions that should be computed.
    +	 * @return An AggregationOperator representing the specified aggregations.
    +	 */
    +	public <T, R extends Tuple> AggregationOperator<T, R> aggregate(UnsortedGrouping<T>
grouping, AggregationFunction<?, ?>[] functions) {
    +		DataSet<T> input = grouping.getDataSet();
    +		int[] groupKeys = grouping.getKeys().computeLogicalKeyPositions();
    +		AggregationOperator<T, R> op = createAggregationOperator(input, groupKeys, functions);
    +		return op;
    +	}
    +	
    +	// TODO if sum and/or count are present, use these to compute average
    +	<T, R extends Tuple> AggregationOperator<T, R> createAggregationOperator(DataSet<T>
input, int[] groupKeys, AggregationFunction<?, ?>[] functions) {
    +		AggregationFunction<?, ?>[] functionsWithExpandedKeys = aggregationFunctionPreprocessor.expandKeys(functions,
groupKeys);
    +		AggregationFunction<?, ?>[] intermediateFunctions = aggregationFunctionPreprocessor.createIntermediateFunctions(functionsWithExpandedKeys,
groupKeys);
    +		int[] intermediateGroupKeys = aggregationFunctionPreprocessor.createIntermediateGroupKeys(intermediateFunctions);
    +		TypeInformation<R> resultType = resultTypeFactory.createAggregationResultType(input.getType(),
functionsWithExpandedKeys);
    +		TypeInformation<Tuple> intermediateType = resultTypeFactory.createAggregationResultType(input.getType(),
intermediateFunctions);
    +		AggregationOperator<T, R> op = new AggregationOperator<T, R>(input, resultType,
intermediateType, intermediateGroupKeys, functionsWithExpandedKeys, intermediateFunctions);
    +		return op;
    +	}
    +
    +	static class AggregationFunctionPreprocessor {
    +
    +		public AggregationFunction<?, ?>[] expandKeys(AggregationFunction<?, ?>[]
functions, int[] groupKeys) {
    +			Vector<AggregationFunction<?, ?>> expanded = new Vector<AggregationFunction<?,?>>();
    +
    +			// test where keys should be included and save keys defined by user
    +			int insertionPosition = -1;
    +			int currentPosition = 0;
    +			List<Integer> definedByUser = new ArrayList<Integer>();
    +			for (AggregationFunction<?, ?> function : functions) {
    +				if (function instanceof KeySelectionAggregationFunction) {
    +					if (function == KeySelectionAggregationFunction.INCLUDE_ALL_KEYS_FUNCTION) {
    +						if (insertionPosition == -1) {
    +							insertionPosition = currentPosition;
    +						}
    +						continue;
    +					} else {
    +						int field = function.getInputPosition();
    +						Validate.isTrue(ArrayUtils.contains(groupKeys, field),
    +								format("The key %d is not in the grouping %s", 
    +										field, asList(groupKeys)));
    +						definedByUser.add(field);
    +					}
    +				}
    +				expanded.add(function);
    +				currentPosition += 1;
    +			}
    +
    +			// insert missing keys if requested
    +			AggregationFunction<?, ?>[] result = null;
    +			if (insertionPosition != -1) {
    +				for (int groupKey : groupKeys) {
    +					if ( ! definedByUser.contains(groupKey) ) {
    +						AggregationFunction<?, ?> key = key(groupKey);
    +						expanded.insertElementAt(key, insertionPosition);
    +						insertionPosition += 1;
    +					}
    +				}
    +				result = new AggregationFunction<?, ?>[expanded.size()];
    +				expanded.toArray(result);
    +			} else {
    +				result = functions;
    +			}
    +			return result;
    +		}
    +
    +		public AggregationFunction<?, ?>[] createIntermediateFunctions(AggregationFunction<?,
?>[] functions, int[] groupKeys) {
    +			List<AggregationFunction<?, ?>> intermediates = new ArrayList<AggregationFunction<?,?>>();
    +			List<CompositeAggregationFunction<?, ?>> composites = new ArrayList<CompositeAggregationFunction<?,
?>>();
    +			int outputPosition = 0;
    +			for (AggregationFunction<?, ?> function : functions) {
    +
    +				// set output position according to the order specified by the user
    +				function.setOutputPosition(outputPosition);
    +				outputPosition += 1;
    +
    +				// check if key() is used without groupBy
    +				if (groupKeys.length == 0
    +						&& function instanceof KeySelectionAggregationFunction) {
    +					throw new IllegalArgumentException("Key selection aggregation function can only
be used on grouped DataSets.");
    +				}
    +
    +				// separate composites
    +				if (function instanceof CompositeAggregationFunction) {
    +					composites.add((CompositeAggregationFunction<?, ?>) function);
    --- End diff --
    
    Couldn't you decompose composite functions right here, without putting them in the list?


> Add support for out-of-place aggregations
> -----------------------------------------
>
>                 Key: FLINK-1293
>                 URL: https://issues.apache.org/jira/browse/FLINK-1293
>             Project: Flink
>          Issue Type: Improvement
>          Components: Java API, Scala API
>    Affects Versions: 0.7.0-incubating
>            Reporter: Viktor Rosenfeld
>            Assignee: Viktor Rosenfeld
>            Priority: Minor
>
> Currently, the output of an aggregation is of the same type as the input. This restriction
has to major drawbacks:
> 1. Every tuple field can only be used in one aggregation because the aggregations result
is stored in the field.
> 2. Aggregations having a return type that is different from the input type, e.g., count
or average, cannot be implemented.
> It would be nice to have the aggregation return any kind of tuple as a result, so the
restrictions above no longer apply.
> See also:
> - https://github.com/stratosphere/stratosphere/wiki/Design-of-Aggregate-Operator
> - http://apache-flink-incubator-mailing-list-archive.1008284.n3.nabble.com/Hi-Aggregation-support-td2311.html



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