I am using the compiled version of spark-sql. But the API seems to have changed 
and the storage handler is not receiving the pushdown predicate as it did on 
hive 0.11 on shark 0.9.2.  We’ve only written our own storage handler.

Specifically, the FILTER_EXPR_CONF-like parameters are not being set in the 
jobconf.  Either that changed, or there’s a bug and nobody noticed and we were 
the only people using ;)  As mentioned, there very well could be an API change 
that I missed, or spark-sql doesn’t populate that when running HIVECONTEXT.  I 
don’t know which, hopefully someone here does!

   Thanks,

~ Shawn M Lavelle

PS I had asked this question months ago, but I think the spam filter prevented 
me from seeing anything about it. I got our IT department to white list the 
alias.  I thank you for your patience if my issue was already discussed.

From: Jörn Franke [mailto:[email protected]]
Sent: Tuesday, July 19, 2016 10:58 AM
To: [email protected]
Subject: Re: Hive External Storage Handlers

The main reason is that if you compile it yourself then nobody can understand 
what you did. Hence any distribution can be downloaded and people can follow 
what you did. As far as I recall you had described several problems that the 
distributions did not have (eg you could not compile tez, spark only in an 
outdated version etc). Furthermore the distributions have a clear baseline for 
configuration of several complex pieces of software.

Hence even for production use a self-compiled version of something complex such 
as the Hadoop, hive, spark toolkit is clearly a no go.

On 19 Jul 2016, at 08:25, Mich Talebzadeh 
<[email protected]<mailto:[email protected]>> wrote:


"So not use a self-compiled hive or Spark version, but only the ones supplied 
by distributions (cloudera, Hortonworks, Bigtop...) You will face performance 
problems, strange errors etc when building and testing your code using 
self-compiled versions."

This comment does not make sense and is meaningless without any evidence. 
Either you provide evidence that you have done this work and you encountered 
errors or better not mention it. Sounds like scaremongering.









Dr Mich Talebzadeh



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On 19 July 2016 at 06:51, Jörn Franke 
<[email protected]<mailto:[email protected]>> wrote:
So not use a self-compiled hive or Spark version, but only the ones supplied by 
distributions (cloudera, Hortonworks, Bigtop...) You will face performance 
problems, strange errors etc when building and testing your code using 
self-compiled versions.

If you use the Hive APIs then the engine should not be relevant for your 
storage handler. Nevertheless, the APIs of the storage handler might have 
changed.

However, I wonder why a 1-1 mapping does not work for you.

On 18 Jul 2016, at 22:46, Mich Talebzadeh 
<[email protected]<mailto:[email protected]>> wrote:
Hi,

You can move up to Hive 2 that works fine and pretty stable. You can opt for 
Hive 1.2.1 if yoy wish.

If you want to use Spark (the replacement for Shark) as the execution engine 
for Hive then the version that works (that I have managed to make it work with 
Hive is Spark 1.3.1) that you will need to build from source.

It works and it is table.

Otherwise you may decide to use Spark Thrift Server (STS) that allows JDBC 
access to Spark SQL (through beeline, Squirrel , Zeppelin) that has Hive SQL 
context built into it as if you were using Hive Thrift Server (HSS)

HTH



Dr Mich Talebzadeh



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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.



On 18 July 2016 at 21:38, Lavelle, Shawn 
<[email protected]<mailto:[email protected]>> wrote:
Hello,

    I am working with an external storage handler written for Hive 0.11 and run 
on a Shark execution engine.  I’d like to move forward and upgrade to hive 
1.2.1 on spark 1.6 or even 2.0.

   This storage has a need to run queries across tables existing in different 
databases in the external data store, so existing drivers that map hive to 
external storage in 1 to 1 mappings are insufficient. I have attempted this 
upgrade already, but found out that predicate pushdown was not occurring.  Was 
this changed in 1.2?

   Can I update and use the same storage handler in Hive or has this concept 
been replaced by the RDDs and DataFrame API?

   Are these questions better for the Spark list?

   Thank you,

~ Shawn M Lavelle



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