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Date: Mon, 1 Feb 2016 17:53:39 +0000 (UTC)
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 <JIRA.12864239.1442319307856@arcas>
Subject: [jira] [Commented] (FLINK-2678) DataSet API does not support
 multi-dimensional arrays as keys
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    [ https://issues.apache.org/jira/browse/FLINK-2678?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15126635#comment-15126635 ] 

ASF GitHub Bot commented on FLINK-2678:
---------------------------------------

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

    https://github.com/apache/flink/pull/1566#discussion_r51453182
  
    --- Diff: flink-core/src/main/java/org/apache/flink/api/common/typeutils/base/GenericArrayComparator.java ---
    @@ -0,0 +1,205 @@
    +/*
    + * 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.common.typeutils.base;
    +
    +import org.apache.flink.api.common.typeutils.TypeComparator;
    +import org.apache.flink.api.common.typeutils.TypeSerializer;
    +import org.apache.flink.core.memory.DataInputView;
    +import org.apache.flink.core.memory.DataOutputView;
    +import org.apache.flink.core.memory.MemorySegment;
    +
    +import java.io.IOException;
    +import java.lang.reflect.Array;
    +import java.util.Arrays;
    +
    +public class GenericArrayComparator<T> extends TypeComparator<T[]> implements java.io.Serializable {
    +
    +	private static final long serialVersionUID = 1L;
    +
    +	private transient T[] reference;
    +
    +	protected final boolean ascendingComparison;
    +
    +	private final TypeSerializer<T[]> serializer;
    +
    +	// For use by getComparators
    +	@SuppressWarnings("rawtypes")
    +	private final TypeComparator[] comparators = new TypeComparator[] {this};
    +
    +	public GenericArrayComparator(boolean ascending, TypeSerializer<T[]> serializer) {
    +		this.ascendingComparison = ascending;
    +		this.serializer = serializer;
    +	}
    +
    +	@Override
    +	public void setReference(T[] reference) {
    +		this.reference = reference;
    +	}
    +
    +	@Override
    +	public boolean equalToReference(T[] candidate) {
    +		return compare(this.reference, candidate) == 0;
    +	}
    +
    +	@Override
    +	public int compareToReference(TypeComparator<T[]> referencedComparator) {
    +		int comp = compare(((GenericArrayComparator<T>) referencedComparator).reference, reference);
    +		return ascendingComparison ? comp : -comp;
    +	}
    +
    +	@Override
    +	public int compareSerialized(DataInputView firstSource, DataInputView secondSource) throws IOException {
    +		T[] firstArray = serializer.deserialize(firstSource);
    +		T[] secondArray = serializer.deserialize(secondSource);
    +
    +		int comp = compare(firstArray, secondArray);
    +		return ascendingComparison ? comp : -comp;
    +	}
    +
    +	@Override
    +	public int extractKeys(Object record, Object[] target, int index) {
    +		target[index] = record;
    +		return 1;
    +	}
    +
    +	@Override
    +	public TypeComparator[] getFlatComparators() {
    +		return comparators;
    +	}
    +
    +	@Override
    +	public boolean supportsNormalizedKey() {
    +		return false;
    +	}
    +
    +	@Override
    +	public boolean supportsSerializationWithKeyNormalization() {
    +		return false;
    +	}
    +
    +	@Override
    +	public int getNormalizeKeyLen() {
    +		return 0;
    +	}
    +
    +	@Override
    +	public boolean isNormalizedKeyPrefixOnly(int keyBytes) {
    +		throw new UnsupportedOperationException();
    +	}
    +
    +	@Override
    +	public void putNormalizedKey(T[] record, MemorySegment target, int offset, int numBytes) {
    +		throw new UnsupportedOperationException();
    +	}
    +
    +	@Override
    +	public void writeWithKeyNormalization(T[] record, DataOutputView target) throws IOException {
    +		throw new UnsupportedOperationException();
    +	}
    +
    +	@Override
    +	public T[] readWithKeyDenormalization(T[] reuse, DataInputView source) throws IOException {
    +		throw new UnsupportedOperationException();
    +	}
    +
    +	@Override
    +	public boolean invertNormalizedKey() {
    +		return !ascendingComparison;
    +	}
    +
    +	@Override
    +	public int hash(T[] record) {
    +		return Arrays.hashCode(record);
    +	}
    +
    +	private int compareValues(Object first, Object second) {
    --- End diff --
    
    This only works for primitive types. What about complex types?


> DataSet API does not support multi-dimensional arrays as keys
> -------------------------------------------------------------
>
>                 Key: FLINK-2678
>                 URL: https://issues.apache.org/jira/browse/FLINK-2678
>             Project: Flink
>          Issue Type: Wish
>          Components: DataSet API
>            Reporter: Till Rohrmann
>            Assignee: Subhobrata Dey
>            Priority: Minor
>
> The DataSet API does not support grouping/sorting on field which are multi-dimensional arrays. It could be helpful to also support these types.


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