HI Talebzadeh,
sorry I forget to answer last part of your question:
At O/S level you should see many CoarseGrainedExecutorBackend through jps
each corresponding to one executor. Are they doing anything?
There is one worker with one executor bussy and the rest is almost idle:
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
9305 spark 20 0 30.489g 5.075g 22256 S * 0.3 18.5* 0:36.25 java
The only one - bussy one is running all 8cores machine
PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND
9580 zdata 20 0 29.664g 0.021t 6836 S* 676.7 79.4* 40:08.61 java
Thanks
Jakub
On 14 July 2016 at 19:22, Jakub Stransky <stransky...@gmail.com> wrote:
> HI Talebzadeh,
>
> we are using 6 worker machines - running.
>
> We are reading the data through sqlContext (data frame) as it is suggested
> in the documentation over the JdbcRdd
>
> prop just specifies name, password, and driver class.
>
> Right after this data load we register it as a temp table
>
> val df_init = sqlContext.read
> .jdbc(
> url = Configuration.dbUrl,
> table = Configuration.dbTable,
> prop
> )
>
> df_init.registerTempTable("df_init")
>
> Afterwords we do some data filtering, column selection and filtering some
> rows with sqlContext.sql ("select statement here")
>
> and after this selection we try to repartition the data in order to get
> them distributed across the cluster and that seems it is not working. And
> then we persist that filtered and selected dataFrame.
>
> And the desired state should be filtered dataframe should be distributed
> accross the nodes in the cluster.
>
> Jakub
>
>
>
> On 14 July 2016 at 19:03, Mich Talebzadeh <mich.talebza...@gmail.com>
> wrote:
>
>> Hi Jakub,
>>
>> Sounds like one executor. Can you point out:
>>
>>
>> 1. The number of slaves/workers you are running
>> 2. Are you using JDBC to read data in?
>> 3. Do you register DF as temp table and if so have you cached temp
>> table
>>
>> Sounds like only one executor is active and the rest are sitting idele.
>>
>> At O/S level you should see many CoarseGrainedExecutorBackend through jps
>> each corresponding to one executor. Are they doing anything?
>>
>> HTH
>>
>> Dr Mich Talebzadeh
>>
>>
>>
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>>
>>
>>
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>>
>>
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>>
>> On 14 July 2016 at 17:18, Jakub Stransky <stransky...@gmail.com> wrote:
>>
>>> Hello,
>>>
>>> I have a spark cluster running in a single mode, master + 6 executors.
>>>
>>> My application is reading a data from database via DataFrame.read then
>>> there is a filtering of rows. After that I re-partition data and I wonder
>>> why on the executors page of the driver UI I see RDD blocks all allocated
>>> still on single executor machine
>>>
>>> [image: Inline images 1]
>>> As highlighted on the picture above. I did expect that after
>>> re-partition the data will be shuffled across cluster but that is obviously
>>> not happening here.
>>>
>>> I can understand that database read is happening in non-parallel fashion
>>> but re-partition should fix it as far as I understand.
>>>
>>> Could someone experienced clarify that?
>>>
>>> Thanks
>>>
>>
>>
>
>
> --
> Jakub Stransky
> cz.linkedin.com/in/jakubstransky
>
>
--
Jakub Stransky
cz.linkedin.com/in/jakubstransky
