Hi,
I think we might have a slight misunderstanding here. In most situations you do
in fact have to configure two directories:
- the directory where the metadata for externalised checkpoints is stored,
this would be "state.checkpoints.dir"
- the directory where the actual checkpoint data shoul
Hi Aviad,
sorry for the late reply.
You can configure the checkpoint directory (which is also used for
externalized checkpoints) when you create the state backend:
env.setStateBackend(new RocksDBStateBackend("hdfs:///checkpoints-data/");
This configures the checkpoint directory to be hdfs:///che
Hi,
thanks for the answer.
I can use the first option (REST API).
for some reason it is undocumented in flink documentation
(https://ci.apache.org/projects/flink/flink-docs-release-1.3/monitoring/rest_api.html)
regarding the second option, configure each job with an externalized
checkpoint direct
Hi Aviad,
I had a similar situation and my solution was to use the flink
monitoring rest api (/jobs/{jobid}/checkpoints) to get the mapping
between job and checkpoint file.
Wrap this in a script and run periodically( in my case, it was 30 sec).
You can also configure each job with an external
Hi Jared,
I just wanted to follow up on this problem that you reported. Are there any new
insights about this problem from your debugging efforts and does it still
exists for you?
Best,
Stefan
> Am 09.07.2017 um 18:37 schrieb Jared Stehler
> :
>
> We are using the rocksDB state backend. We h
We are using the rocksDB state backend. We had not activated incremental
checkpointing, but in the course of debugging this, we ended up doing so, and
also moving back to S3 from EFS as it appeared that EFS was introducing large
latencies. I will attempt to provide some profiler data as we are a
On Mon, Jul 3, 2017 at 12:02 PM, Stefan Richter
wrote:
> Another thing that could be really helpful, if possible, can you attach a
> profiler/sampling to your job manager and figure out the hotspot methods
> where most time is spend? This would be very helpful as a starting point
> where the probl
Hi,
I have two quick questions about this problem report:
1) Which state backend are you using?
2) In case you are using RocksDB, did you also activate incremental
checkpointing when moving to Flink 1.3.
Another thing that could be really helpful, if possible, can you attach a
profiler/samplin
