Can you try storing the state (word count) in an external key value store?
On Sat, Nov 7, 2015, 8:40 AM Thúy Hằng Lê <thuyhang...@gmail.com> wrote:
> Hi all,
>
> Anyone could help me on this. It's a bit urgent for me on this.
> I'm very confused and curious about Spark data checkpoint performance? Is
> there any detail implementation of checkpoint I can look into?
> Spark Streaming only take sub-second to process 20K messages/sec, however
> it take 25 seconds for checkpoint. Now my application have average 30
> seconds latency and keep increasingly.
>
>
> 2015-11-06 11:11 GMT+07:00 Thúy Hằng Lê <thuyhang...@gmail.com>:
>
>> Thankd all, it would be great to have this feature soon.
>> Do you know what's the release plan for 1.6?
>>
>> In addition to this, I still have checkpoint performance problem
>>
>> My code is just simple like this:
>> JavaStreamingContext jssc = new
>> JavaStreamingContext(sparkConf,Durations.seconds(2));
>> jssc.checkpoint("spark-data/checkpoint");
>> JavaPairInputDStream<String, String> messages =
>> KafkaUtils.createDirectStream(...);
>> JavaPairDStream<String, List<Double>> stats =
>> messages.mapToPair(parseJson)
>> .reduceByKey(REDUCE_STATS)
>> .updateStateByKey(RUNNING_STATS);
>>
>> stats.print()
>>
>> Now I need to maintain about 800k keys, the stats here is only count
>> number of occurence for key.
>> While running the cache dir is very small (about 50M), my question is:
>>
>> 1/ For regular micro-batch it takes about 800ms to finish, but every 10
>> seconds when data checkpoint is running
>> It took me 5 seconds to finish the same size micro-batch, why it's too
>> high? what's kind of job in checkpoint?
>> why it's keep increasing?
>>
>> 2/ When I changes the data checkpoint interval like using:
>> stats.checkpoint(Durations.seconds(100)); //change to 100, defaults
>> is 10
>>
>> The checkpoint is keep increasing significantly first checkpoint is
>> 10s, second is 30s, third is 70s ... and keep increasing :)
>> Why it's too high when increasing checkpoint interval?
>>
>> It seems that default interval works more stable.
>>
>> On Nov 4, 2015 9:08 PM, "Adrian Tanase" <atan...@adobe.com> wrote:
>>
>>> Nice! Thanks for sharing, I wasn’t aware of the new API.
>>>
>>> Left some comments on the JIRA and design doc.
>>>
>>> -adrian
>>>
>>> From: Shixiong Zhu
>>> Date: Tuesday, November 3, 2015 at 3:32 AM
>>> To: Thúy Hằng Lê
>>> Cc: Adrian Tanase, "user@spark.apache.org"
>>> Subject: Re: Spark Streaming data checkpoint performance
>>>
>>> "trackStateByKey" is about to be added in 1.6 to resolve the
>>> performance issue of "updateStateByKey". You can take a look at
>>> https://issues.apache.org/jira/browse/SPARK-2629 and
>>> https://github.com/apache/spark/pull/9256
>>>
>>
>
