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From Thúy Hằng Lê <thuyhang...@gmail.com>
Subject Re: Spark Streaming data checkpoint performance
Date Sat, 07 Nov 2015 03:10:33 GMT
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 <thuyhang612@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" <atanase@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
>>
>

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