Could you write your update func like this?
val updateFunc = (iterator: Iterator[(String, Seq[Int], Option[Int])])
=> {
iterator.flatMap { case (key, values, stateOption) =>
if (values.isEmpty) {
// don't access database
} else {
// update to new state and save to database
}
// return new state
}
}
and use this overload:
def updateStateByKey[S: ClassTag](
updateFunc: (Seq[V], Option[S]) => Option[S],
partitioner: Partitioner
): DStream[(K, S)]
There is a JIRA: https://issues.apache.org/jira/browse/SPARK-2629 but
doesn't have a doc now...
Best Regards,
Shixiong Zhu
2015-09-24 17:26 GMT+08:00 Bin Wang <wbi...@gmail.com>:
> Data that are not updated should be saved earlier: while the data added to
> the DStream at the first time, it should be considered as updated. So save
> the same data again is a waste.
>
> What are the community is doing? Is there any doc or discussion that I can
> look for? Thanks.
>
>
>
> Shixiong Zhu <zsxw...@gmail.com>于2015年9月24日周四 下午4:27写道：
>
>> For data that are not updated, where do you save? Or do you only want to
>> avoid accessing database for those that are not updated?
>>
>> Besides, the community is working on optimizing "updateStateBykey"'s
>> performance. Hope it will be delivered soon.
>>
>> Best Regards,
>> Shixiong Zhu
>>
>> 2015-09-24 13:45 GMT+08:00 Bin Wang <wbi...@gmail.com>:
>>
>>> I've read the source code and it seems to be impossible, but I'd like to
>>> confirm it.
>>>
>>> It is a very useful feature. For example, I need to store the state of
>>> DStream into my database, in order to recovery them from next redeploy. But
>>> I only need to save the updated ones. Save all keys into database is a lot
>>> of waste.
>>>
>>> Through the source code, I think it could be add easily: StateDStream
>>> can get prevStateRDD so that it can make a diff. Is there any chance to add
>>> this as an API of StateDStream? If so, I can work on this feature.
>>>
>>> If not possible, is there any work around or hack to do this by myself?
>>>
>>
>>
