any issues just by sizing an app that I
> would first check memory size, cpu allocations and so on..
>
> Best,
>
> On Tue, Jul 18, 2017 at 3:30 PM, Saatvik Shah
> wrote:
>
>> Hi Riccardo,
>>
>> Yes, Thanks for suggesting I do that.
>>
sage in context: http://apache-spark-user-list.
>> 1001560.n3.nabble.com/Spark-UI-crashes-on-Large-Workloads-tp28873.html
>> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>>
>> -
>
not heard of.
Thanks and Regards,
Saatvik Shah
On Fri, Jun 30, 2017 at 10:16 AM, Jörn Franke wrote:
> In this case i do not see so many benefits of using Spark. Is the data
> volume high?
> Alternatively i recommend to convert the proprietary format into a format
> Sparks underst
egards,
Saatvik Shah
On Fri, Jun 30, 2017 at 12:50 AM, Mahesh Sawaiker <
mahesh_sawai...@persistent.com> wrote:
> Wouldn’t this work if you load the files in hdfs and let the partitions be
> equal to the amount of parallelism you want?
>
>
>
> *From:* Saatvik Shah [ma
Hey Ayan,
This isnt a typical text file - Its a proprietary data format for which a
native Spark reader is not available.
Thanks and Regards,
Saatvik Shah
On Thu, Jun 29, 2017 at 6:48 PM, ayan guha wrote:
> If your files are in same location you can use sc.wholeTextFile. If not,
> sc.te
, then after some (say 5) I
> would write to disk and reload. At that point you should call unpersist to
> free the memory as it is no longer relevant.
>
>
>
> Thanks,
>
> Assaf.
>
>
>
> *From:* Saatvik Shah [mailto:saatvikshah1...@gmail.com
ns for optimizing this process further?
>
>
>
> --
> View this message in context: http://apache-spark-user-list.
> 1001560.n3.nabble.com/Merging-multiple-Pandas-dataframes-tp28770.html
> Sent from the Apache Spark User List mailing list archive at Nabble.com.
>
> -----
elect("col1").filter("col1 in ('happy')")
>>>>> }
>>>>> override def copy(extra: ParamMap): Transformer = ???
>>>>> @DeveloperApi
>>>>> override def transformSchema(schema: StructType): StructType ={
>>
Hi Pralabh,
I want the ability to create a column such that its values be restricted to
a specific set of predefined values.
For example, suppose I have a column called EMOTION: I want to ensure each
row value is one of HAPPY,SAD,ANGRY,NEUTRAL,NA.
Thanks and Regards,
Saatvik Shah
On Fri, Jun 16
egards,
Saatvik Shah
On Fri, Jun 16, 2017 at 1:42 AM, 颜发才(Yan Facai) wrote:
> You can use some Transformers to handle categorical data,
> For example,
> StringIndexer encodes a string column of labels to a column of label
> indices:
> http://spark.apache.org/docs/latest/ml-featur
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