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From hernan saab <hernan_javier_s...@yahoo.com>
Subject Re: hive on spark - version question
Date Fri, 17 Mar 2017 21:25:18 GMT
Stephan,
Thanks for the response.
The one thing that I don't appreciate from those who promote and DOCUMENT spark on hive is
that, seemingly, there is absolutely no evidence seen that says that hive on spark WORKS. As
a matter of fact, after a lot of pain, I noticed it is not supported by just about anybody.
If someone dares to document Hive on Spark (see link https://cwiki.apache.org/confluence/display/Hive/Hive+on+Spark%3A+Getting+Started)
 why can't they have the decency to mention what specific combo of Hadoop/Spark/Hive versions
used that works? Have a git repo included in a doc with all the right versions and libraries.
Why not? We can start from there and progressively use newer libraries in case the doc becomes
stale. I am not really asking much, I just want to know what the documenter used to claim
that Hive on Spark works, that's it.
Clearly, for most cases, this setup is broken and it misleads people to waste time on a broken
setup.
I love this tech. But I do notice that there is some mean spirited or very negligent actions
made by the apache development community. Documenting hive on spark while knowing it won't
work for most cases means apache developers don't give a crap about the time wasted by people
like us.

 

    On Friday, March 17, 2017 1:14 PM, Edward Capriolo <edlinuxguru@gmail.com> wrote:
 

 

On Fri, Mar 17, 2017 at 2:56 PM, hernan saab <hernan_javier_saab@yahoo.com> wrote:

I have been in a similar world of pain. Basically, I tried to use an external Hive to have
user access controls with a spark engine.At the end, I realized that it was a better idea
to use apache tez instead of a spark engine for my particular case.
But the journey is what I want to share with you.The big data apache tools and libraries such
as Hive, Tez, Spark, Hadoop , Parquet etc etc are not interchangeable as we would like to
think. There are very limited combinations for very specific versions. This is why tools like
Ambari can be useful. Ambari sets a path of combos of versions known to work and the dirty
work is done under the UI. 
More often than not, when you try a version that few people tried, you will get error messages
that will derailed you and cause you to waste a lot of time.
In addition, this group, as well as many other apache big data user groups,  provides extremely
poor support for users. The answers you usually get are not even hints to a solution. Their
answers usually translate to "there is nothing I am willing to do about your problem. If I
did, I should get paid" in many cryptic ways.
If you ask your question to the Spark group they will take you to the Hive group and viceversa
(I can almost guarantee it based on previous experiences)
But in hindsight, people who work on this kinds of things typically make more money that the
average developers. If you make more $$s it makes sense learning this stuff is supposed to
be harder.
Conclusion, don't try it. Or try using Tez/Hive instead of Spark/Hive  if you are querying
large files.
 

    On Friday, March 17, 2017 11:33 AM, Stephen Sprague <spragues@gmail.com> wrote:
 

 :(  gettin' no love on this one.   any SME's know if Spark 2.1.0 will work with Hive 2.1.0
?  That JavaSparkListener class looks like a deal breaker to me, alas.

thanks in advance.

Cheers,
Stephen.

On Mon, Mar 13, 2017 at 10:32 PM, Stephen Sprague <spragues@gmail.com> wrote:

hi guys,
wondering where we stand with Hive On Spark these days?

i'm trying to run Spark 2.1.0 with Hive 2.1.0 (purely coincidental versions) and running up
against this class not found:

java.lang. NoClassDefFoundError: org/apache/spark/ JavaSparkListener


searching the Cyber i find this:
    1. http://stackoverflow.com/ questions/41953688/setting- spark-as-default-execution-
engine-for-hive

    which pretty much describes my situation too and it references this:


    2. https://issues.apache.org/ jira/browse/SPARK-17563

    which indicates a "won't fix" - but does reference this:


    3. https://issues.apache.org/ jira/browse/HIVE-14029

    which looks to be fixed in hive 2.2 - which is not released yet.


so if i want to use spark 2.1.0 with hive am i out of luck - until hive 2.2?

thanks,
Stephen.





   

Stephan,  
I understand some of your frustration.  Remember that many in open source are volunteering
their time. This is why if you pay a vendor for support of some software you might pay 50K
a year or $200.00 an hour. If I was your vendor/consultant I would have started the clock
10 minutes ago just to answer this email :). The only "pay" I ever got from Hive is that I
can use it as a resume bullet point, and I wrote a book which pays me royalties.
As it relates specifically to your problem, when you see the trends you are seeing it probably
means you are in a minority of the user base. Either your doing something no one else is doing,
you are too cutting edge, or no one has an easy solution. Hive is making the move from the
classic MapReduce, two other execution engines have been made Tez and HiveOnSpark. Because
we are open source we allow people to "scratch an itch" that is the Apache way. From time
to time in means something that was added stops being viable because of lack of support.
I agree with your final assessment which is Tez is the most viable engine for Hive. This is
by no means a put down of the HiveOnSpark work and it does not mean it will never the most
viable. By the same token if the versions fall out of sync and all that exists is complains
the viability speaks for itself. 
Remember that keeping two fast moving things together is no easy chore. I used to run Hive
+ cassandra. Seems easy, crap two versions of common CLI, shade one version everything works,
crap new hive release has different versions of thrift, shade + patch, crap now one of the
other dependencies is incompatible fork + shade + patch. At some point you have to say to
yourself if I can not make critical mass of this solution such that I am the only one doing/patching
it then I give up and find some other way to do it.


   
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