I can't reproduce the issue with my simple code:
```scala
spark.streams.addListener(new StreamingQueryListener {
override def onQueryProgress(event:
StreamingQueryListener.QueryProgressEvent): Unit = {
println(event.progress.id + " is on progress")
println(s"My accu is ${myAcc.value} on query progress")
}
...
})
def mappingFunc(key: Long, values: Iterator[String], state:
GroupState[Long]): ... = {
myAcc.add(1)
println(s">>> key: $key => state: ${state}")
...
}
val wordCounts = words
.groupByKey(v => ...)
.mapGroupsWithState(timeoutConf =
GroupStateTimeout.ProcessingTimeTimeout)(func = mappingFunc)
val query = wordCounts.writeStream
.outputMode(OutputMode.Update)
...
```
I'm wondering if there were any errors can be found from driver logs? The
micro-batch
exceptions won't terminate the streaming job running.
For the following code, we have to make sure that `StateUpdateTask` is started:
> .mapGroupsWithState(
> new
> StateUpdateTask(Long.parseLong(appConfig.getSparkStructuredStreamingConfig().STATE_TIMEOUT),
> appConfig, accumulators),
> Encoders.bean(ModelStateInfo.class),
> Encoders.bean(ModelUpdate.class),
> GroupStateTimeout.ProcessingTimeTimeout());
--
Cheers,
-z
On Thu, 28 May 2020 19:59:31 +0530
Srinivas V <srini....@gmail.com> wrote:
> Giving the code below:
> //accumulators is a class level variable in driver.
>
> sparkSession.streams().addListener(new StreamingQueryListener() {
> @Override
> public void onQueryStarted(QueryStartedEvent queryStarted) {
> logger.info("Query started: " + queryStarted.id());
> }
> @Override
> public void onQueryTerminated(QueryTerminatedEvent
> queryTerminated) {
> logger.info("Query terminated: " + queryTerminated.id());
> }
> @Override
> public void onQueryProgress(QueryProgressEvent queryProgress) {
>
> accumulators.eventsReceived(queryProgress.progress().numInputRows());
> long eventsReceived = 0;
> long eventsExpired = 0;
> long eventSentSuccess = 0;
> try {
> eventsReceived =
> accumulators.getLong(InstrumentationCounters.EVENTS_RECEIVED);
> eventsExpired =
> accumulators.getLong(InstrumentationCounters.EVENTS_STATE_EXPIRED);
> eventSentSuccess =
> accumulators.getLong(InstrumentationCounters.EVENTS_SENT);
> } catch (MissingKeyException e) {
> logger.error("Accumulator key not found due to
> Exception {}", e.getMessage());
> }
> logger.info("Events Received:{}", eventsReceived);
> logger.info("Events State Expired:{}", eventsExpired);
> logger.info("Events Sent Success:{}", eventSentSuccess);
> logger.info("Query made progress - batchId: {}
> numInputRows:{} inputRowsPerSecond:{} processedRowsPerSecond:{}
> durationMs:{}" ,
> queryProgress.progress().batchId(),
> queryProgress.progress().numInputRows(),
> queryProgress.progress().inputRowsPerSecond(),
> queryProgress.progress().processedRowsPerSecond(),
> queryProgress.progress().durationMs());
>
>
> On Thu, May 28, 2020 at 7:04 PM ZHANG Wei <wezh...@outlook.com> wrote:
>
> > May I get how the accumulator is accessed in the method
> > `onQueryProgress()`?
> >
> > AFAICT, the accumulator is incremented well. There is a way to verify that
> > in cluster like this:
> > ```
> > // Add the following while loop before invoking awaitTermination
> > while (true) {
> > println("My acc: " + myAcc.value)
> > Thread.sleep(5 * 1000)
> > }
> >
> > //query.awaitTermination()
> > ```
> >
> > And the accumulator value updated can be found from driver stdout.
> >
> > --
> > Cheers,
> > -z
> >
> > On Thu, 28 May 2020 17:12:48 +0530
> > Srinivas V <srini....@gmail.com> wrote:
> >
> > > yes, I am using stateful structured streaming. Yes similar to what you
> > do.
> > > This is in Java
> > > I do it this way:
> > > Dataset<ModelUpdate> productUpdates = watermarkedDS
> > > .groupByKey(
> > > (MapFunction<InputEventModel, String>) event ->
> > > event.getId(), Encoders.STRING())
> > > .mapGroupsWithState(
> > > new
> > >
> > StateUpdateTask(Long.parseLong(appConfig.getSparkStructuredStreamingConfig().STATE_TIMEOUT),
> > > appConfig, accumulators),
> > > Encoders.bean(ModelStateInfo.class),
> > > Encoders.bean(ModelUpdate.class),
> > > GroupStateTimeout.ProcessingTimeTimeout());
> > >
> > > StateUpdateTask contains the update method.
> > >
> > > On Thu, May 28, 2020 at 4:41 AM Something Something <
> > > mailinglist...@gmail.com> wrote:
> > >
> > > > Yes, that's exactly how I am creating them.
> > > >
> > > > Question... Are you using 'Stateful Structured Streaming' in which
> > you've
> > > > something like this?
> > > >
> > > > .mapGroupsWithState(GroupStateTimeout.ProcessingTimeTimeout())(
> > > > updateAcrossEvents
> > > > )
> > > >
> > > > And updating the Accumulator inside 'updateAcrossEvents'? We're
> > experiencing this only under 'Stateful Structured Streaming'. In other
> > streaming applications it works as expected.
> > > >
> > > >
> > > >
> > > > On Wed, May 27, 2020 at 9:01 AM Srinivas V <srini....@gmail.com>
> > wrote:
> > > >
> > > >> Yes, I am talking about Application specific Accumulators. Actually I
> > am
> > > >> getting the values printed in my driver log as well as sent to
> > Grafana. Not
> > > >> sure where and when I saw 0 before. My deploy mode is “client” on a
> > yarn
> > > >> cluster(not local Mac) where I submit from master node. It should
> > work the
> > > >> same for cluster mode as well.
> > > >> Create accumulators like this:
> > > >> AccumulatorV2 accumulator = sparkContext.longAccumulator(name);
> > > >>
> > > >>
> > > >> On Tue, May 26, 2020 at 8:42 PM Something Something <
> > > >> mailinglist...@gmail.com> wrote:
> > > >>
> > > >>> Hmm... how would they go to Graphana if they are not getting
> > computed in
> > > >>> your code? I am talking about the Application Specific Accumulators.
> > The
> > > >>> other standard counters such as 'event.progress.inputRowsPerSecond'
> > are
> > > >>> getting populated correctly!
> > > >>>
> > > >>> On Mon, May 25, 2020 at 8:39 PM Srinivas V <srini....@gmail.com>
> > wrote:
> > > >>>
> > > >>>> Hello,
> > > >>>> Even for me it comes as 0 when I print in OnQueryProgress. I use
> > > >>>> LongAccumulator as well. Yes, it prints on my local but not on
> > cluster.
> > > >>>> But one consolation is that when I send metrics to Graphana, the
> > values
> > > >>>> are coming there.
> > > >>>>
> > > >>>> On Tue, May 26, 2020 at 3:10 AM Something Something <
> > > >>>> mailinglist...@gmail.com> wrote:
> > > >>>>
> > > >>>>> No this is not working even if I use LongAccumulator.
> > > >>>>>
> > > >>>>> On Fri, May 15, 2020 at 9:54 PM ZHANG Wei <wezh...@outlook.com>
> > wrote:
> > > >>>>>
> > > >>>>>> There is a restriction in AccumulatorV2 API [1], the OUT type
> > should
> > > >>>>>> be atomic or thread safe. I'm wondering if the implementation for
> > > >>>>>> `java.util.Map[T, Long]` can meet it or not. Is there any chance
> > to replace
> > > >>>>>> CollectionLongAccumulator by CollectionAccumulator[2] or
> > LongAccumulator[3]
> > > >>>>>> and test if the StreamingListener and other codes are able to
> > work?
> > > >>>>>>
> > > >>>>>> ---
> > > >>>>>> Cheers,
> > > >>>>>> -z
> > > >>>>>> [1]
> > > >>>>>>
> > https://nam01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fspark.apache.org%2Fdocs%2Flatest%2Fapi%2Fscala%2Findex.html%23org.apache.spark.util.AccumulatorV2&data=02%7C01%7C%7C3d67f4e536ab422670f008d80313920c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637262729866357123&sdata=fY6a%2FeGVVwFvwJKMP6v8yY9S%2FEaSVuyyB89s50lpJRc%3D&reserved=0
> > > >>>>>> [2]
> > > >>>>>>
> > https://nam01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fspark.apache.org%2Fdocs%2Flatest%2Fapi%2Fscala%2Findex.html%23org.apache.spark.util.CollectionAccumulator&data=02%7C01%7C%7C3d67f4e536ab422670f008d80313920c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637262729866357123&sdata=QuFZKdKLRWRahfheHS5Zvc9GWApj2QCsBmiSEmOYsdo%3D&reserved=0
> > > >>>>>> [3]
> > > >>>>>>
> > https://nam01.safelinks.protection.outlook.com/?url=http%3A%2F%2Fspark.apache.org%2Fdocs%2Flatest%2Fapi%2Fscala%2Findex.html%23org.apache.spark.util.LongAccumulator&data=02%7C01%7C%7C3d67f4e536ab422670f008d80313920c%7C84df9e7fe9f640afb435aaaaaaaaaaaa%7C1%7C0%7C637262729866357123&sdata=3xFOiNXNSuJ8w%2FQY7th2qip16ykMjbjXFLN6NXxXGAo%3D&reserved=0
> > > >>>>>>
> > > >>>>>> ________________________________________
> > > >>>>>> From: Something Something <mailinglist...@gmail.com>
> > > >>>>>> Sent: Saturday, May 16, 2020 0:38
> > > >>>>>> To: spark-user
> > > >>>>>> Subject: Re: Using Spark Accumulators with Structured Streaming
> > > >>>>>>
> > > >>>>>> Can someone from Spark Development team tell me if this
> > functionality
> > > >>>>>> is supported and tested? I've spent a lot of time on this but
> > can't get it
> > > >>>>>> to work. Just to add more context, we've our own Accumulator
> > class that
> > > >>>>>> extends from AccumulatorV2. In this class we keep track of one or
> > more
> > > >>>>>> accumulators. Here's the definition:
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> class CollectionLongAccumulator[T]
> > > >>>>>> extends AccumulatorV2[T, java.util.Map[T, Long]]
> > > >>>>>>
> > > >>>>>> When the job begins we register an instance of this class:
> > > >>>>>>
> > > >>>>>> spark.sparkContext.register(myAccumulator, "MyAccumulator")
> > > >>>>>>
> > > >>>>>> Is this working under Structured Streaming?
> > > >>>>>>
> > > >>>>>> I will keep looking for alternate approaches but any help would be
> > > >>>>>> greatly appreciated. Thanks.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> On Thu, May 14, 2020 at 2:36 PM Something Something <
> > > >>>>>> mailinglist...@gmail.com<mailto:mailinglist...@gmail.com>> wrote:
> > > >>>>>>
> > > >>>>>> In my structured streaming job I am updating Spark Accumulators in
> > > >>>>>> the updateAcrossEvents method but they are always 0 when I try to
> > print
> > > >>>>>> them in my StreamingListener. Here's the code:
> > > >>>>>>
> > > >>>>>> .mapGroupsWithState(GroupStateTimeout.ProcessingTimeTimeout())(
> > > >>>>>> updateAcrossEvents
> > > >>>>>> )
> > > >>>>>>
> > > >>>>>>
> > > >>>>>> The accumulators get incremented in 'updateAcrossEvents'. I've a
> > > >>>>>> StreamingListener which writes values of the accumulators in
> > > >>>>>> 'onQueryProgress' method but in this method the Accumulators are
> > ALWAYS
> > > >>>>>> ZERO!
> > > >>>>>>
> > > >>>>>> When I added log statements in the updateAcrossEvents, I could see
> > > >>>>>> that these accumulators are getting incremented as expected.
> > > >>>>>>
> > > >>>>>> This only happens when I run in the 'Cluster' mode. In Local mode
> > it
> > > >>>>>> works fine which implies that the Accumulators are not getting
> > distributed
> > > >>>>>> correctly - or something like that!
> > > >>>>>>
> > > >>>>>> Note: I've seen quite a few answers on the Web that tell me to
> > > >>>>>> perform an "Action". That's not a solution here. This is a
> > 'Stateful
> > > >>>>>> Structured Streaming' job. Yes, I am also 'registering' them in
> > > >>>>>> SparkContext.
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> > > >>>>>>
> >
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