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https://issues.apache.org/jira/browse/FLINK-6791?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Nico Kruber closed FLINK-6791.
------------------------------
Resolution: Invalid
unfortunately, I forgot to post the error message I saw back then and probably
mixed it up since now, I only receive messages similar to
{code}
2017-06-12 14:20:25,133 ERROR akka.remote.EndpointWriter
- Transient association error (association remains live)
akka.remote.OversizedPayloadException: Discarding oversized payload sent to
Actor[akka.tcp://flink@localhost:6123/user/jobmanager#454802553]: max allowed
size 10485760 bytes, actual size of encoded class
org.apache.flink.runtime.messages.checkpoint.AcknowledgeCheckpoint was 13052581
bytes.
{code}
After an {{akka.remote.OversizedPayloadException}}, Flink shows the symptoms
described in this issue, and not due to the {{MemoryStateBackend}}'s max size.
> Using MemoryStateBackend as checkpoint stream back-end may block
> checkpoint/savepoint creation
> ----------------------------------------------------------------------------------------------
>
> Key: FLINK-6791
> URL: https://issues.apache.org/jira/browse/FLINK-6791
> Project: Flink
> Issue Type: Bug
> Components: State Backends, Checkpointing
> Affects Versions: 1.3.0, 1.2.1, 1.4.0
> Reporter: Nico Kruber
>
> If the `MemoryStateBackend` is used as the checkpoint stream back-end in e.g.
> RocksDBStateBackend, it will block further checkpoint/savepoint creation if
> the checkpoint data reaches the back-end's max state size. In that case, an
> error message is logged at the task manager but the save-/checkpoint never
> completes and although the job continues, no further checkpoints will be made.
> Please see the following example that should be reproducible:
> {code:java}
> env.setStateBackend(new RocksDBStateBackend(new MemoryStateBackend(1000 *
> 1024 * 1024, false), false));
> env.enableCheckpointing(100L);
> final long numKeys = 100_000L;
> DataStreamSource<Tuple1<Long>> source1 =
> env.addSource(new RichParallelSourceFunction<Tuple1<Long>>() {
> private volatile boolean running = true;
> @Override
> public void run(SourceContext<Tuple1<Long>> ctx) throws
> Exception {
> long counter = 0;
> while (running) {
> synchronized (ctx.getCheckpointLock()) {
> ctx.collect(Tuple1.of(counter %
> numKeys));
> counter++;
> }
> Thread.yield();
> }
> }
> @Override
> public void cancel() {
> running = false;
> }
> });
> source1.keyBy(0)
> .map(new RichMapFunction<Tuple1<Long>, Tuple1<Long>>() {
> private transient ValueState<List<Long>> val;
> @Override
> public Tuple1<Long> map(Tuple1<Long> value)
> throws Exception {
> val.update(Collections.nCopies(100, value.f0));
> return value;
> }
> @Override
> public void open(final Configuration parameters) throws
> Exception {
> ValueStateDescriptor<List<Long>> descriptor =
> new ValueStateDescriptor<>(
> "data", // the
> state name
>
> TypeInformation.of(new TypeHint<List<Long>>() {
> }) // type
> information
> );
> val = getRuntimeContext().getState(descriptor);
> }
> }).uid("identity-map-with-state")
> .addSink(new DiscardingSink<Tuple1<Long>>());
> env.execute("failingsnapshots");
> {code}
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