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From Mich Talebzadeh <mich.talebza...@gmail.com>
Subject Re: Joining a compressed ORC table with a non compressed text table
Date Tue, 28 Jun 2016 22:02:21 GMT
Just adding that this is run in local mode with a fair bit of shuffling
going on as shown below

[image: Inline images 1]

Dr Mich Talebzadeh



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On 28 June 2016 at 22:53, Mich Talebzadeh <mich.talebzadeh@gmail.com> wrote:

> Hi,
>
>
> I have a simple join between table sales2 a compressed (snappy) ORC with
> 22 million rows and another simple table sales_staging under a million rows
> stored as a text file with no compression.
>
> The join is very simple
>
>   val s2 = HiveContext.table("sales2").select("PROD_ID")
>   val s = HiveContext.table("sales_staging").select("PROD_ID")
>
>   val rs =
> s2.join(s,"prod_id").orderBy("prod_id").sort(desc("prod_id")).take(5).foreach(println)
>
>
> Now what is happening is it is sitting on SortMergeJoin operation
> on ZippedPartitionRDD as shown in the DAG diagram below
>
>
> [image: Inline images 1]
>
>
> And at this rate  only 10% is done and will take for ever to finish :(
>
> Stage 3:==>                                                     (10 + 2) /
> 200]
>
> Ok I understand that zipped files cannot be broken into blocks and
> operations on them cannot be parallelized.
>
> Having said that what are the alternatives? Never use compression and live
> with it. I emphasise that any operation on the compressed table itself is
> pretty fast as it is a simple table scan. However, a join between two
> tables on a column as above suggests seems to be problematic?
>
> Thanks
>
> P.S. the same is happening using Hive with MR
>
> select a.prod_id from sales2 a inner join sales_staging b on a.prod_id =
> b.prod_id order by a.prod_id;
>
> Dr Mich Talebzadeh
>
>
>
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>
>
>
> http://talebzadehmich.wordpress.com
>
>
> *Disclaimer:* Use it at your own risk. Any and all responsibility for any
> loss, damage or destruction of data or any other property which may arise
> from relying on this email's technical content is explicitly disclaimed.
> The author will in no case be liable for any monetary damages arising from
> such loss, damage or destruction.
>
>
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