Spark streaming automatically takes care of unpersisting any RDDs generated
by DStream. You can set the StreamingContext.remember() to set the minimum
persistence duration. Any persisted RDD older than that will be
automatically unpersisted
On Thu, Nov 5, 2015 at 9:12 AM, swetha kasireddy <swethakasire...@gmail.com>
wrote:
> Its just in the same thread for a particular RDD, I need to uncache it
> every 2 minutes to clear out the data that is present in a Map inside that.
>
> On Wed, Nov 4, 2015 at 11:54 PM, Saisai Shao <sai.sai.s...@gmail.com>
> wrote:
>
>> Hi Swetha,
>>
>> Would you mind elaborating your usage scenario of DStream unpersisting?
>>
>> From my understanding:
>>
>> 1. Spark Streaming will automatically unpersist outdated data (you
>> already mentioned about the configurations).
>> 2. If streaming job is started, I think you may lose the control of the
>> job, when do you call this unpersist, how to call this unpersist (from
>> another thread)?
>>
>> Thanks
>> Saisai
>>
>>
>> On Thu, Nov 5, 2015 at 3:13 PM, swetha kasireddy <
>> swethakasire...@gmail.com> wrote:
>>
>>> Other than setting the following.
>>>
>>> sparkConf.set("spark.streaming.unpersist", "true")
>>> sparkConf.set("spark.cleaner.ttl", "7200s")
>>>
>>>
>>> On Wed, Nov 4, 2015 at 5:03 PM, swetha <swethakasire...@gmail.com>
>>> wrote:
>>>
>>>> Hi,
>>>>
>>>> How to unpersist a DStream in Spark Streaming? I know that we can
>>>> persist
>>>> using dStream.persist() or dStream.cache. But, I don't see any method to
>>>> unPersist.
>>>>
>>>> Thanks,
>>>> Swetha
>>>>
>>>>
>>>>
>>>> --
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>>>
>>
>
