Small correction to what I said: Sources have to implement
ParallelSourceFunction in order to be run with a higher parallelism.
The javadocs for the RichSourceFunction are /somewhat /incorrect, but in
a sense also correct.
This is because you can have a RichSourceFunction that also implements
ParallelSourceFunction, which would then be functionally equivalent to
RichParallelSourceFunction.
Ultimately there's little difference between a RichSourceFunction and a
RichParallelSourceFunction; it's just that the latter also implements
ParallelSourceFunction.
ParallelSourceFunction also is really just an interface for tagging;
there's nothing functional in there.
So whenever you look at the javadocs for a method you end up in the
RichSourceFunction interface; so there's some value in ignoring this
slight difference for practical purposes.
But to wrap up, generally speaking, yes, you'd always want to extend
RichParallelSourceFunction for a parallel data source; not out of
necessity, but simplicity.
On 07/06/2020 17:43, Ken Krugler wrote:
Hi Chesnay,
On Jun 19, 2019, at 6:05 AM, Chesnay Schepler <ches...@apache.org
<mailto:ches...@apache.org>> wrote:
A (Rich)SourceFunction that does not implement
RichParallelSourceFunction is always run with a parallelism of 1.
RichSourceFunction
<https://ci.apache.org/projects/flink/flink-docs-stable/api/java/index.html?org/apache/flink/streaming/api/functions/source/RichSourceFunction.html> says "Base
class for implementing a *parallel* data source…” and also talks about
(in a similar, but not identical way as RichParallelSourceFunction
<https://ci.apache.org/projects/flink/flink-docs-stable/api/java/index.html?org/apache/flink/streaming/api/functions/source/RichSourceFunction.html>)
use of getRuntimeContext() to determine the sub-task index.
But you’d always want to extend RichParallelSourceFunction to create a
parallel data source, yes?
Seems confusing.
Thanks,
— Ken
On 19/06/2019 14:36, Flavio Pompermaier wrote:
My sourcefunction is intrinsically single-thread. Is there a way to
force this aspect?
I can't find a real difference between a RichParallelSourceFunction
and a RichSourceFunction.
Is this last (RichSourceFunction) implicitly using parallelism = 1?
On Wed, Jun 19, 2019 at 2:25 PM Chesnay Schepler <ches...@apache.org
<mailto:ches...@apache.org>> wrote:
It returns a list of states so that state can be re-distributed
if the parallelism changes.
If you hard-code the interface to return a single value then
you're implicitly locking the parallelism.
When you reduce the parallelism you'd no longer be able to
restore all state, since you have less instances than stored state.
On 19/06/2019 14:19, Flavio Pompermaier wrote:
It's not clear to me why the source checkpoint returns a list
of object...when it could be useful to use a list instead of a
single value?
The documentation says The returned list should contain one
entry for redistributable unit of state" but this is not very
clear to me..
Best,
Flavio
On Wed, Jun 19, 2019 at 12:40 PM Chesnay Schepler
<ches...@apache.org <mailto:ches...@apache.org>> wrote:
This looks fine to me.
What exactly were you worried about?
On 19/06/2019 12:33, Flavio Pompermaier wrote:
> Hi to all,
> in my use case I have to ingest data from a rest service,
where I
> periodically poll the data (of course a queue would be a
better choice
> but this doesn't depend on me).
>
> So I wrote a RichSourceFunction that starts a thread that
poll for new
> data.
> However, I'd like to restart from the last "from" value
(in the case
> the job is stopped).
>
> My initial thought was to write somewhere the last used
date and, on
> job restart, read that date (from a file for example).
However, Flink
> stateful source should be a better choice here...am I
wrong? So I
> made my source function implementing
ListCheckpointed<String>:
>
> @Override
> public List<String> snapshotState(long checkpointId, long
timestamp)
> throws Exception {
> return
Collections.singletonList(pollingThread.getDateFromAsString());
> }
> @Override
> public void restoreState(List<String> state) throws
Exception {
> for (String dateFrom : state) {
> startDateStr = dateFrom;
> }
> }
>
> @Override
> public void run(SourceContext<MyEvent> ctx) throws
Exception {
> final Object lock = ctx.getCheckpointLock();
> Client httpClient = getHttpClient();
> try {
> pollingThread = new
MyPollingThread.Builder(baseUrl,
> httpClient)//
> .setStartDate(startDateStr, datePatternStr)//
> .build();
> // start the polling thread
> new Thread(pr).start();
> .... (etc)
> }
>
> Is this the correct approach or did I misunderstood how
stateful
> source functions work?
>
> Best,
> Flavio
--------------------------
Ken Krugler
http://www.scaleunlimited.com
custom big data solutions & training
Hadoop, Cascading, Cassandra & Solr
