Tathagata,
In our logs I see the batch duration millis being set first to 10 then to
20 seconds. I don't see the 20 being reflected later during ingestion.
In the Spark UI under Streaming I see the below output, notice the *10
second* Batch interval. Can you think of a reason why it's stuck at 10?
It used to be 1 second by the way, then somehow over the course of a few
restarts we managed to get it to be 10 seconds. Now it won't get reset to
20 seconds. Any ideas?
Streaming
- *Started at: *Thu Sep 03 10:59:03 EDT 2015
- *Time since start: *1 day 8 hours 44 minutes
- *Network receivers: *0
- *Batch interval: *10 seconds
- *Processed batches: *11790
- *Waiting batches: *0
- *Received records: *0
- *Processed records: *0
Statistics over last 100 processed batchesReceiver Statistics
No receivers
Batch Processing Statistics
MetricLast batchMinimum25th percentileMedian75th percentileMaximumProcessing
Time23 ms7 ms10 ms11 ms14 ms172 msScheduling Delay1 ms0 ms0 ms0 ms1 ms2
msTotal Delay24 ms8 ms10 ms12 ms14 ms173 ms
On Fri, Sep 4, 2015 at 3:50 PM, Tathagata Das <t...@databricks.com> wrote:
> Could you see what the streaming tab in the Spark UI says? It should show
> the underlying batch duration of the StreamingContext, the details of when
> the batch starts, etc.
>
> BTW, it seems that the 5.6 or 6.8 seconds delay is present only when data
> is present (that is, * Documents processed: > 0)*
>
> On Fri, Sep 4, 2015 at 3:38 AM, Dmitry Goldenberg <
> dgoldenberg...@gmail.com> wrote:
>
>> Tathagata,
>>
>> Checkpointing is turned on but we were not recovering. I'm looking at the
>> logs now, feeding fresh content hours after the restart. Here's a snippet:
>>
>> 2015-09-04 06:11:20,013 ... Documents processed: 0.
>> 2015-09-04 06:11:30,014 ... Documents processed: 0.
>> 2015-09-04 06:11:40,011 ... Documents processed: 0.
>> 2015-09-04 06:11:50,012 ... Documents processed: 0.
>> 2015-09-04 06:12:00,010 ... Documents processed: 0.
>> 2015-09-04 06:12:10,047 ... Documents processed: 0.
>> 2015-09-04 06:12:20,012 ... Documents processed: 0.
>> 2015-09-04 06:12:30,011 ... Documents processed: 0.
>> 2015-09-04 06:12:40,012 ... Documents processed: 0.
>> *2015-09-04 06:12:55,629 ... Documents processed: 4.*
>> 2015-09-04 06:13:00,018 ... Documents processed: 0.
>> 2015-09-04 06:13:10,012 ... Documents processed: 0.
>> 2015-09-04 06:13:20,019 ... Documents processed: 0.
>> 2015-09-04 06:13:30,014 ... Documents processed: 0.
>> 2015-09-04 06:13:40,041 ... Documents processed: 0.
>> 2015-09-04 06:13:50,009 ... Documents processed: 0.
>> ...
>> 2015-09-04 06:17:30,019 ... Documents processed: 0.
>> *2015-09-04 06:17:46,832 ... Documents processed: 40.*
>>
>> Interestingly, the fresh content (4 documents) is fed about 5.6 seconds
>> after the previous batch, not 10 seconds. The second fresh batch comes in
>> 6.8 seconds after the previous empty one.
>>
>> Granted, the log message is printed after iterating over the messages
>> which may account for some time differences. But generally, looking at the
>> log messages being printed before we iterate, it's still 10 seconds each
>> time, not 20 which is what batchdurationmillis is currently set to.
>>
>> Code:
>>
>> JavaPairInputDStream<String, String> messages =
>> KafkaUtils.createDirectStream(....);
>> messages.checkpoint(Durations.milliseconds(checkpointMillis));
>>
>>
>> JavaDStream<String> messageBodies = messages.map(new
>> Function<Tuple2<String,
>> String>, String>() {
>> @Override
>> public String call(Tuple2<String, String> tuple2) {
>> return tuple2._2();
>> }
>> });
>>
>> messageBodies.foreachRDD(new Function<JavaRDD<String>, Void>() {
>> @Override
>> public Void call(JavaRDD<String> rdd) throws Exception {
>> ProcessPartitionFunction func = new ProcessPartitionFunction(...);
>> rdd.foreachPartition(func);
>> return null;
>> }
>> });
>>
>> The log message comes from ProcessPartitionFunction:
>>
>> public void call(Iterator<String> messageIterator) throws Exception {
>> log.info("Starting data partition processing. AppName={},
>> topic={}.)...", appName, topic);
>> // ... iterate ...
>> log.info("Finished data partition processing (appName={}, topic={}).
>> Documents processed: {}.", appName, topic, docCount);
>> }
>>
>> Any ideas? Thanks.
>>
>> - Dmitry
>>
>> On Thu, Sep 3, 2015 at 10:45 PM, Tathagata Das <t...@databricks.com>
>> wrote:
>>
>>> Are you accidentally recovering from checkpoint files which has 10
>>> second as the batch interval?
>>>
>>>
>>> On Thu, Sep 3, 2015 at 7:34 AM, Dmitry Goldenberg <
>>> dgoldenberg...@gmail.com> wrote:
>>>
>>>> I'm seeing an oddity where I initially set the batchdurationmillis to 1
>>>> second and it works fine:
>>>>
>>>> JavaStreamingContext jssc = new JavaStreamingContext(sparkConf,
>>>> Durations.milliseconds(batchDurationMillis));
>>>>
>>>> Then I tried changing the value to 10 seconds. The change didn't seem
>>>> to take. I've bounced the Spark workers and the consumers and now I'm
>>>> seeing RDD's coming in once around 10 seconds (not always 10 seconds
>>>> according to the logs).
>>>>
>>>> However, now I'm trying to change the value to 20 seconds and it's just
>>>> not taking. I've bounced Spark master, workers, and consumers and the value
>>>> seems "stuck" at 10 seconds.
>>>>
>>>> Any ideas? We're running Spark 1.3.0 built for Hadoop 2.4.
>>>>
>>>> Thanks.
>>>>
>>>> - Dmitry
>>>>
>>>>
>>>
>>
>
