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From "Robert Metzger (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-3697) keyBy() with nested POJO computes invalid field position indexes
Date Tue, 05 Apr 2016 12:52:25 GMT

    [ https://issues.apache.org/jira/browse/FLINK-3697?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15226188#comment-15226188
] 

Robert Metzger commented on FLINK-3697:
---------------------------------------

[~rcrocker@newrelic.com] are you okay with using the code you've provided for my test case?

> keyBy() with nested POJO computes invalid field position indexes
> ----------------------------------------------------------------
>
>                 Key: FLINK-3697
>                 URL: https://issues.apache.org/jira/browse/FLINK-3697
>             Project: Flink
>          Issue Type: Bug
>          Components: DataStream API
>    Affects Versions: 1.0.0
>         Environment: MacOS X 10.10
>            Reporter: Ron Crocker
>            Priority: Critical
>              Labels: pojo
>
> Using named keys in keyBy() for nested POJO types results in failure. The iindexes for
named key fields are used inconsistently with nested POJO types. In particular, {{PojoTypeInfo.getFlatFields()}}
returns the field's position after (apparently) flattening the structure but is referenced
in the unflattened version of the POJO type by {{PojoTypeInfo.getTypeAt()}}.
> In the example below, getFlatFields() returns positions 0, 1, and 14. These positions
appear correct in the flattened structure of the Data class. However, in {{KeySelector<X,
Tuple> getSelectorForKeys(Keys<X> keys, TypeInformation<X> typeInfo, ExecutionConfig
executionConfig)}}, a call to {{compositeType.getTypeAt(logicalKeyPositions[i])}} for the
third key results {{PojoTypeInfo.getTypeAt()}} declaring it out of range, as it compares the
length of the directly named fields of the object vs the length of flattened version of that
type.
> Concrete Example:
> Consider this graph:
> {code}
> DataStream<TimesliceData> dataStream = see.addSource(new FlinkKafkaConsumer08<>(timesliceConstants.topic,
new DataDeserialzer(), kafkaConsumerProperties));
> dataStream
>       .flatMap(new DataMapper())
>       .keyBy("aaa", "abc", "wxyz")
> {code}
> {{DataDeserialzer}} returns a "NativeDataFormat" object; {{DataMapper}} takes this NativeDataFormat
object and extracts individual Data objects: {code}
> public class Data {
>     public int aaa;
>     public int abc;
>     public long wxyz;
>     public int t1;
>     public int t2;
>     public Policy policy;
>     public Stats stats;
>     public Data() {}
> {code}
> A {{Policy}} object is an instance of this class:
> {code}
> public class Policy {
>     public short a;
>     public short b;
>     public boolean c;
>     public boolean d;
>     public Policy() {}
> }
> {code}
> A {{Stats}} object is an instance of this class:
> {code}
> public class Stats {
>     public long count;
>     public float a;
>     public float b;
>     public float c;
>     public float d;
>     public float e;
>     public Stats() {}
> }
> {code}



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