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https://issues.apache.org/jira/browse/FLINK-3779?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15388116#comment-15388116
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ASF GitHub Bot commented on FLINK-3779:
---------------------------------------
Github user soniclavier commented on the issue:
https://github.com/apache/flink/pull/2051
Thanks Ufuk & Stephen for the reply,
I tried the serializers suggested by you
```
val typeHint = new TypeHint[Tuple2[Long,String]](){}
val serializer = TypeInformation.of(typeHint).createSerializer(null)
//also tried this
val fieldSerializers = Array[TypeSerializer[_]](StringSerializer.INSTANCE,
LongSerializer.INSTANCE)
val serializer2 = new
TupleSerializer(classOf[Tuple2[Long,String]].asInstanceOf[Class[_]].asInstanceOf[Class[Tuple2[String,
Long]]], fieldSerializers)
```
But both gives me compilation error at
```
val serializedKey = KvStateRequestSerializer.serializeKeyAndNamespace(
key,
serializer2,
VoidNamespace.INSTANCE,
VoidNamespaceSerializer.INSTANCE)
```
the compilation error is:
```
Error:(43, 7) type mismatch;
found :
org.apache.flink.api.common.typeutils.TypeSerializer[org.apache.flink.api.java.tuple.Tuple2[Long,String]]
required:
org.apache.flink.api.common.typeutils.TypeSerializer[java.io.Serializable]
Note: org.apache.flink.api.java.tuple.Tuple2[Long,String] <:
java.io.Serializable, but Java-defined class TypeSerializer is invariant in
type T.
You may wish to investigate a wildcard type such as `_ <:
java.io.Serializable`. (SLS 3.2.10)
serializer,
^
```
I had seen this before when I tried to set the serializer from
`queryableState.getKeySerializer`
Note : It works fine when I use the longer version of serializer that I
created.
> Add support for queryable state
> -------------------------------
>
> Key: FLINK-3779
> URL: https://issues.apache.org/jira/browse/FLINK-3779
> Project: Flink
> Issue Type: Improvement
> Components: Distributed Coordination
> Reporter: Ufuk Celebi
> Assignee: Ufuk Celebi
>
> Flink offers state abstractions for user functions in order to guarantee
> fault-tolerant processing of streams. Users can work with both
> non-partitioned (Checkpointed interface) and partitioned state
> (getRuntimeContext().getState(ValueStateDescriptor) and other variants).
> The partitioned state interface provides access to different types of state
> that are all scoped to the key of the current input element. This type of
> state can only be used on a KeyedStream, which is created via stream.keyBy().
> Currently, all of this state is internal to Flink and used in order to
> provide processing guarantees in failure cases (e.g. exactly-once processing).
> The goal of Queryable State is to expose this state outside of Flink by
> supporting queries against the partitioned key value state.
> This will help to eliminate the need for distributed operations/transactions
> with external systems such as key-value stores which are often the bottleneck
> in practice. Exposing the local state to the outside moves a good part of the
> database work into the stream processor, allowing both high throughput
> queries and immediate access to the computed state.
> This is the initial design doc for the feature:
> https://docs.google.com/document/d/1NkQuhIKYmcprIU5Vjp04db1HgmYSsZtCMxgDi_iTN-g.
> Feel free to comment.
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