If you leave enable.auto.commit set to true, it will commit offsets to
kafka, but you will get undefined delivery semantics.
If you just want to restart from a fresh state, the easiest thing to
do is use a new consumer group name.
But if that keeps happening, you should look into why your retention
is not sufficient.
On Tue, Sep 6, 2016 at 9:39 AM, Srikanth <srikanth...@gmail.com> wrote:
> You are right. I got confused as its all part of same log when running from
> IDE.
> I was looking for a good guide to read to understand the this integ.
>
> I'm not managing offset on my own. I've not enabled checkpoint for my tests.
> I assumed offsets will be stored in kafka by default.
>
> KafkaUtils.createDirectStream[Array[Byte], Array[Byte]] (
> ssc, PreferConsistent, SubscribePattern[Array[Byte],
> Array[Byte]](pattern, kafkaParams) )
>
> * @param offsets: offsets to begin at on initial startup. If no offset
> is given for a
> * TopicPartition, the committed offset (if applicable) or kafka param
> * auto.offset.reset will be used.
>
> 16/09/02 13:11:11 INFO ConsumerConfig: ConsumerConfig values:
> enable.auto.commit = true
> auto.offset.reset = latest
>
> Srikanth
>
> On Sat, Sep 3, 2016 at 8:59 AM, Cody Koeninger <c...@koeninger.org> wrote:
>>
>> Seems like you're confused about the purpose of that line of code, it
>> applies to executors, not the driver. The driver is responsible for
>> determining offsets.
>>
>> Where are you storing offsets, in Kafka, checkpoints, or your own store?
>> Auto offset reset won't be used if there are stored offsets.
>>
>>
>> On Sep 2, 2016 14:58, "Srikanth" <srikanth...@gmail.com> wrote:
>>>
>>> Hi,
>>>
>>> Upon restarting my Spark Streaming app it is failing with error
>>>
>>> Exception in thread "main" org.apache.spark.SparkException: Job aborted
>>> due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent
>>> failure: Lost task 0.0 in stage 1.0 (TID 6, localhost):
>>> org.apache.kafka.clients.consumer.OffsetOutOfRangeException: Offsets out of
>>> range with no configured reset policy for partitions: {mt-event-2=1710706}
>>>
>>> It is correct that the last read offset was deleted by kafka due to
>>> retention period expiry.
>>> I've set auto.offset.reset in my app but it is getting reset here
>>>
>>> https://github.com/apache/spark/blob/master/external/kafka-0-10/src/main/scala/org/apache/spark/streaming/kafka010/KafkaUtils.scala#L160
>>>
>>> How to force it to restart in this case (fully aware of potential data
>>> loss)?
>>>
>>> Srikanth
>
>
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