Actually, you can do partition level ingest using ForEachWriter. You just have 
to add each row to a list in the write method, and write to the data store in 
the close method

I know it’s awkward. I don’t know why  Spark doesn’t provide a 
ForEachPartitionWriter

From: Yogesh Mahajan <[email protected]>
Date: Thursday, June 21, 2018 at 3:45 PM
To: subramgr <[email protected]>
Cc: user <[email protected]>
Subject: Re: Spark 2.3.0 and Custom Sink

Since ForeachWriter works at a record level so you cannot do bulk ingest into 
KairosDB, which supports bulk inserts. This will be slow.
Instead, you can have your own Sink implementation which is a batch (DataFrame) 
level.

Thanks,
http://www.snappydata.io/blog<https://urldefense.proofpoint.com/v2/url?u=http-3A__snappydata.io&d=DwMFaQ&c=pLULRYW__RtkwsQUPxJVDGboCTdgji3AcHNJU0BpTJE&r=F2RNeGILvLdBxn7RJ4effes_QFIiEsoVM2rPi9qX1DKow5HQSjq0_WhIW109SXQ4&m=SEFEzpQgcNkmvod1F3vAjoV9R0A2scwsFxbuUwEMyJA&s=xCEVFqZ3k8jqb6oLLjPXBMcplgGBPoy5pvjGvUoA0JY&e=>

On Thu, Jun 21, 2018 at 10:54 AM, subramgr 
<[email protected]<mailto:[email protected]>> wrote:
Hi Spark Mailing list,

We are looking for pushing the output of the structured streaming query
output to KairosDB. (time series database)

What would be the recommended way of doing this? Do we implement the *Sink*
trait or do we use the *ForEachWriter*

At each trigger point if I do a *dataset.collect()* the size of the data is
not huge it should be in lower 10MBs

Any suggestions?

Thanks
Girish



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