Hi Fabian,

Switching the solution set join to a co-group indeed fixed the issue. Thank you!

Joshua

On Oct 25, 2017, at 11:00 AM, Fabian Hueske 
<fhue...@gmail.com<mailto:fhue...@gmail.com>> wrote:

Hi Joshua,

with the unmanaged solution set, the records are not serialized but they need 
to be copied to avoid them from being mutated by the user-code JoinFunction.
The stacktrace hints that the NPE is caused by copying a null record. This 
would happen if the solution set would not contain the key.

I was not sure if there is a restriction of the delta iteration that all keys 
must be present in the initial solution set. I tried to find this in the 
documentation but didn't see information on that.
So I checked and was able to reproduce the problem.
It is only possible to join the solution set with keys that are actually 
contained in the solution set.

It's a bit surprising that this limitation is not documented and no proper 
exception is thrown. In fact it would be possible to avoid the exception by 
either:
- not calling the join function (this would be inner join semantics) or
- calling the join function with a null value (similar to an outer join).

If created a JIRA issue [1] to track the problem.

Best, Fabian

[1] 
https://issues.apache.org/jira/browse/FLINK-7919<https://na01.safelinks.protection.outlook.com/?url=https%3A%2F%2Fissues.apache.org%2Fjira%2Fbrowse%2FFLINK-7919&data=02%7C01%7CJGriffith%40campuslabs.com%7Ce68181b40c7649df3ab808d51bc1a3b6%7C809fd6c8b87647a9abe28be2888f4a55%7C0%7C0%7C636445440850807259&sdata=88tdKjTu8QbisJdVdQdFlJmegNpHPdUSVEOF8EBeNx0%3D&reserved=0>

2017-10-25 16:58 GMT+02:00 Joshua Griffith 
<jgriff...@campuslabs.com<mailto:jgriff...@campuslabs.com>>:
Hello Fabian,

Thank you for your response. I tried setting the solution set to unmanaged and 
got a different error:

2017-10-24 20:46:11.473 [Join (join solution trees) (1/8)] ERROR 
org.apache.flink.runtime.operators.BatchTask  - Error in task code:  Join (join 
solution trees) (1/8)
java.lang.NullPointerException: null
at 
org.apache.flink.api.java.typeutils.runtime.TupleSerializer.copy(TupleSerializer.java:104)
at 
org.apache.flink.api.java.typeutils.runtime.TupleSerializer.copy(TupleSerializer.java:30)
at 
org.apache.flink.runtime.operators.JoinWithSolutionSetSecondDriver.run(JoinWithSolutionSetSecondDriver.java:207)
at org.apache.flink.runtime.operators.BatchTask.run(BatchTask.java:490)
at 
org.apache.flink.runtime.iterative.task.AbstractIterativeTask.run(AbstractIterativeTask.java:146)
at 
org.apache.flink.runtime.iterative.task.IterationIntermediateTask.run(IterationIntermediateTask.java:92)
at org.apache.flink.runtime.operators.BatchTask.invoke(BatchTask.java:355)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
at java.lang.Thread.run(Thread.java:748)

I initially thought this was due to a null being present in the solution set 
tuple so I added assertions to ensure that tuple values were never null. 
However, I’m still getting the above error. Did changing it to unmanaged cause 
the tuples to be serialized? Is there another reason aside from null values 
that this error might be thrown?

Thank you,

Joshua

On Oct 25, 2017, at 3:12 AM, Fabian Hueske 
<fhue...@gmail.com<mailto:fhue...@gmail.com>> wrote:

Hi Joshua,

that is correct. Delta iterations cannot spill to disk. The solution set is 
managed in an in-memory hash table.
Spilling that hash table to disk would have a significant impact on the 
performance.

By default the hash table is organized in Flink's managed memory.
You can try to increase the managed memory size (tweaking managed memory vs. 
heap memory, increasing heap memory, ...) or add more resources and increase 
the parallelism.
Alternatively, it is possible to store the solution set in a Java HashMap on 
the heap by setting the solution set to unManaged 
(DeltaIteration.setSolutionSetUnManaged(true)).

Best, Fabian


2017-10-24 21:09 GMT+02:00 Joshua Griffith 
<jgriff...@campuslabs.com<mailto:jgriff...@campuslabs.com>>:
I’m currently using a delta iteration within a batch job and received the 
following error:

java.lang.RuntimeException: Memory ran out. Compaction failed. numPartitions: 
32 minPartition: 11 maxPartition: 24 number of overflow segments: 0 bucketSize: 
125 Overall memory: 23232512 Partition memory: 18350080 Message: null
at 
org.apache.flink.runtime.operators.hash.CompactingHashTable.insertRecordIntoPartition(CompactingHashTable.java:457)
at 
org.apache.flink.runtime.operators.hash.CompactingHashTable.insertOrReplaceRecord(CompactingHashTable.java:392)
at 
org.apache.flink.runtime.iterative.io<https://na01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fiterative.io&data=02%7C01%7CJGriffith%40campuslabs.com%7Cd8ec77de6d934f7200a708d51b80337a%7C809fd6c8b87647a9abe28be2888f4a55%7C0%7C0%7C636445159803224851&sdata=g0iK%2BZymCRuy4fEyHJ55bvhanT%2FLe7QzoURYLBhnlos%3D&reserved=0>.SolutionSetUpdateOutputCollector.collect(SolutionSetUpdateOutputCollector.java:54)
at 
org.apache.flink.runtime.operators.util.metrics.CountingCollector.collect(CountingCollector.java:35)
at org.apache.flink.runtime.operators.NoOpDriver.run(NoOpDriver.java:96)
at org.apache.flink.runtime.operators.BatchTask.run(BatchTask.java:490)
at 
org.apache.flink.runtime.iterative.task.AbstractIterativeTask.run(AbstractIterativeTask.java:146)
at 
org.apache.flink.runtime.iterative.task.IterationTailTask.run(IterationTailTask.java:107)
at org.apache.flink.runtime.operators.BatchTask.invoke(BatchTask.java:355)
at org.apache.flink.runtime.taskmanager.Task.run(Task.java:702)
at java.lang.Thread.run(Thread.java:748)

It looks like the job ran out of Flink managed memory. Can delta iterations not 
spill to disk?

Thanks,

Joshua




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