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From Дмитрий Павлов <dm.pav...@inbox.ru>
Subject Re[2]: How to load kudu RDD with correct partitioner
Date Thu, 15 Nov 2018 09:02:51 GMT

Hi Grant

I really appreciate for your reply

Let me explain my case with Kudu and Spark.  We a using Kudu with Spark in production to
aggregate current and historical records.
 
So i have 2 tables:

Table A - which have following partition  schema:
HASH (record_id) PARTITIONS N,
RANGE (meet_date) (
    PARTITION 2018-11-15T00:00:00.000000Z <= VALUES < 2018-11-16T00:00:00.000000Z,
    PARTITION 2018-11-16T00:00:00.000000Z <= VALUES < 2018-11-17T00:00:00.000000Z,
    PARTITION 2018-11-17T00:00:00.000000Z <= VALUES < 2018-11-18T00:00:00.000000Z
) Table B 
HASH (record_id) PARTITIONS N,
RANGE (record_id) (
    PARTITION UNBOUNDED
) Table B contains historical information and Table contains current information flow splited
by days. History table is big enough (~ 4 000 000 000 records)  

So i expect that records with same record_id from Table A and Table B will be stored on same
kudu nodes.  (May be this expectation is unreasonable) Please correct me if i'm wrong.

Next i try to do following

RDDA = kuduRDD(Table A)
RDDB = kuduRDD(Table B)

RDDA join RDDB by record_id 

And here i do not expect any shuffling but it does. Spark knows about partition locality
(getPrefferedLocation returns correct list of kudu locations). 
but looks like it does not know about original Kudu partitioning. So i have to add rdd.partitionBy(new
HashPartitioner(N)) before join operation
and it leads to shuffling  
Regards, Dmitry

>Среда, 14 ноября 2018, 18:58 +03:00 от Grant Henke <ghenke@cloudera.com>:
>
>Unfortunately, I am not sure of a simple way to provide the partitioner information with
the existing implementation. Currently the KuduRDD does not override the  RDD partitioner
, though it probably could as an improvement. 
>
>Would you like to file a Kudu jira to track the work? Would you be interested in contributing
the improvement? 
>
>I am curious to know, how are you planning to use the knowledge of the original Kudu partitioning
and how is it useful to your Spark workflow?
>
>Thanks,
>Grant
>
>
>
>On Wed, Nov 14, 2018 at 2:41 AM Dmitry Pavlov < dm.pavlov@inbox.ru > wrote:
>>Hi guys
>>
>>I have a question about Kudu with Spark.
>>
>>For example there is a table in kudu with field record_id and following partitioning:
>>HASH (record_id) PARTITIONS N
>>
>>Is it possible to load records from such table in key value fashion with correct partitioner
information in RDD? For example RDD[(record_id, row)]
>>Because when i try to use kuduRDD in spark the partitioner has None value so im losing
information about original (kudu) partitioning.
>>
>>Thanks
>
>-- 
>Grant Henke 
>Software Engineer | Cloudera
>grant@cloudera.com |  twitter.com/gchenke |  linkedin.com/in/granthenke

-- 
Дмитрий Павлов
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