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From "Ron Crocker (JIRA)" <j...@apache.org>
Subject [jira] [Updated] (FLINK-3697) keyBy() with nested POJO computes invalid field position indexes
Date Mon, 04 Apr 2016 20:10:25 GMT

     [ https://issues.apache.org/jira/browse/FLINK-3697?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Ron Crocker updated FLINK-3697:
-------------------------------
    Description: 
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}

  was:
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 AggregatableMetricStoragePolicy implements MetricStoragePolicy {
    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}


> 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: Minor
>              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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