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https://issues.apache.org/jira/browse/CRUNCH-485?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14267428#comment-14267428
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Tycho Lamerigts commented on CRUNCH-485:
----------------------------------------
I did indeed try requireSortedKeys() but it merely sorts the results *after*
grouping. In other words, the grouping is not affected and is still incorrect.
Note that this is not about sorting per se, the groupByKey needs to determine
if key objects are _equal_ and Avro objects use sort order to determine
equality too. See example below. Crunch-on-MapReduce takes this into account,
whereas Crunch-on-Spark doesn't. I do not know if the difference is
intentional, but it definitely is inconsistent and I would argue that
Crunch-on-MapReduce behavior is the desired behavior.
{code}
package example;
import com.google.common.collect.Lists;
import org.apache.avro.Schema;
import org.apache.avro.Schema.Field;
import org.apache.avro.Schema.Field.Order;
import org.apache.avro.Schema.Type;
import org.apache.avro.generic.GenericData.Record;
import org.apache.avro.generic.GenericRecordBuilder;
import org.codehaus.jackson.node.JsonNodeFactory;
import org.junit.Test;
import static org.junit.Assert.assertEquals;
public class AvroEqualsTest {
@Test
public void fieldsWithIgnoredSortOrderAreNotUsedInEquals() {
Schema mySchema = Schema.createRecord(Lists.newArrayList(new
Field("field1",
Schema.create(Type.STRING),
null,
JsonNodeFactory.instance.textNode(""),
Order.ASCENDING), new Field("field2",
Schema.create(Type.STRING),
null,
JsonNodeFactory.instance.textNode(""),
Order.IGNORE)));
GenericRecordBuilder myGRB = new GenericRecordBuilder(mySchema);
Record myRecord1 = myGRB.set("field1", "hello").set("field2",
"world").build();
Record myRecord2 = myGRB.set("field1", "hello").set("field2",
"there").build();
assertEquals(myRecord1, myRecord2);
}
}
{code}
> groupByKey on Spark incorrect if key is Avro record with defined sort order
> ---------------------------------------------------------------------------
>
> Key: CRUNCH-485
> URL: https://issues.apache.org/jira/browse/CRUNCH-485
> Project: Crunch
> Issue Type: Bug
> Components: Core
> Affects Versions: 0.11.0
> Reporter: Tycho Lamerigts
> Assignee: Josh Wills
>
> GroupByKey on Spark is incorrect if the key type is an Avro record with
> defined sort order (http://avro.apache.org/docs/1.7.7/spec.html#order).
> Instead, it serializes the entire avro record to a binary blob (byte array)
> and groups identical blobs. This is wrong. By contrast, groupByKey on
> MapReduce works as expected, so it does take Avro's sort order into account.
> The culprit is probably the following code from
> org.apache.crunch.impl.spark.collect.PGroupedTableImpl#getJavaRDDLikeInternal
> {code}
> groupedRDD = parentRDD.map(new PairMapFunction(ptype.getOutputMapFn(),
> runtime.getRuntimeContext()))
> .mapToPair(new MapOutputFunction(keySerde, valueSerde))
> .groupByKey(numPartitions);
> {code}
> where MapOutputFunction simply converts the entire key object to a binary
> blob, without taking sort order into account.
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