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From Scott Carey <sc...@richrelevance.com>
Subject Re: PIG and Hive
Date Thu, 07 May 2009 18:08:07 GMT
The work was done 3 months ago, and the exact query I used may not have been the below - it
was functionally the same - two sources,  arithmetic aggregation on each inner-joined by a
small set of values.  We wrote a hand-coded map reduce, a Pig script, and Hive against the
same data and performance tested.

At that time, even "SELECT count(a.z) FROM a group by a.z" took 3 phases (not sure how many
were fetch versus M/R).  Since then, we abandoned Hive for reassessment at a later date. 
All releases of Hive since then http://hadoop.apache.org/hive/docs/r0.3.0/changes.html don't
have anything under "optimizations" and few of the enhancements listed suggest that there
has been much change on the performance front (yet).

Can Hive not yet detect an implicit inner join in a WHERE clause?

Our use case would have less optimization-savvy people querying data ad-hoc, so being able
to detect implicit joins and collapse subselects, etc is a requirement.  I'm not going to
go sitting over the shoulder of everyone who wants to do some ad-hoc data analysis and tell
them how to re-write their queries to perform better.
That is a big weakness of SQL that affects everything that uses it - there are so many equivalent
or near-equivalent forms of expression that often lead to implementation specific performance

I'm sure Hive will get over that hump but it takes time.  I'm certainly interested in it and
will have a deeper look again in the second half of this year.

On 5/7/09 10:12 AM, "Namit Jain" <njain@facebook.com> wrote:

SELECT count(a.z), count(b.z), x, y from a, b where a.x = b.x and a.y = b.y
group by x, y.

If you do a explain on the above query, you will see that you are performing a Cartesian product
followed by the filter.

It would be better to rewrite the query as:

SELECT count(a.z), count(b.z), a.x, a.y from a JOIN b ON( a.x = b.x and a.y = b.y)
group by a.x, a.y;

The explain should have 2 map-reduce jobs and a fetch task (which is not a map-reduce job).
Can you send me the exact Hive query that you are trying along with the schema of tables 'a'
and 'b'.

In order to see the plan, you can do:



------ Forwarded Message
From: Ricky Ho <rho@adobe.com>
Reply-To: <core-user@hadoop.apache.org>
Date: Wed, 6 May 2009 21:11:43 -0700
To: <core-user@hadoop.apache.org>
Subject: RE: PIG and Hive

Thanks for Olga example and Scott's comment.

My goal is to pick a higher level parallel programming language (as a algorithm design / prototyping
tool) to express my parallel algorithms in a concise way.  The deeper I look into these, I
have a stronger feeling that PIG and HIVE are competitors rather than complementing each other.
 I think a large set of problems can be done in either way, without much difference in terms
of skillset requirements.

At this moment, I am focus in the richness of the language model rather than the implementation
optimization.  Supporting "collection" as well as the flatten operation in the language model
seems to make PIG more powerful.  Yes, you can achieve the same thing in Hive but then it
starts to look odd.  Am I missing something Hive folks ?


-----Original Message-----
From: Scott Carey [mailto:scott@richrelevance.com]
Sent: Wednesday, May 06, 2009 7:48 PM
To: core-user@hadoop.apache.org
Subject: Re: PIG and Hive

Pig currently also compiles similar operations (like the below) into many
fewer map reduce passes and is several times faster in general.

This will change as the optimizer and available optimizations converge and
in the future they won't differ much.  But for now, Pig optimizes much

I ran a test that boiled down to SQL like this:

SELECT count(a.z), count(b.z), x, y from a, b where a.x = b.x and a.y = b.y
group by x, y.

(and equivalent, but more verbose Pig)

Pig did it in one map reduce pass in about 2 minutes and Hive did it in 5
map reduce passes in 10 minutes.

There is nothing keeping Hive from applying the optimizations necessary to
make that one pass, but those sort of performance optimizations aren't there
yet.  That is expected, it is a younger project.

It would be useful if more of these higher level tools shared work on the
various optimizations.  Pig and Hive (and perhaps CloudBase and Cascading?)
could benefit from a shared map-reduce compiler.

On 5/6/09 5:32 PM, "Olga Natkovich" <olgan@yahoo-inc.com> wrote:

> Hi Ricky,
> This is how the code will look in Pig.
> A = load 'textdoc' using TextLoader() as (sentence: chararray);
> B = foreach A generate flatten(TOKENIZE(sentence)) as word;
> C = group B by word;
> D = foreach C generate group, COUNT(B);
> store D into 'wordcount';
> Pig training (http://www.cloudera.com/hadoop-training-pig-tutorial)
> explains how the example above works.
> Let me know if you have further questions.
> Olga
>> -----Original Message-----
>> From: Ricky Ho [mailto:rho@adobe.com]
>> Sent: Wednesday, May 06, 2009 3:56 PM
>> To: core-user@hadoop.apache.org
>> Subject: RE: PIG and Hive
>> Thanks Amr,
>> Without knowing the details of Hive, one constraint of SQL
>> model is you can never generate more than one records from a
>> single record.  I don't know how this is done in Hive.
>> Another question is whether the Hive script can take in
>> user-defined functions ?
>> Using the following word count as an example.  Can you show
>> me how the Pig script and Hive script looks like ?
>> Map:
>>   Input: a line (a collection of words)
>>   Output: multiple [word, 1]
>> Reduce:
>>   Input: [word, [1, 1, 1, ...]]
>>   Output: [word, count]
>> Rgds,
>> Ricky
>> -----Original Message-----
>> From: Amr Awadallah [mailto:aaa@cloudera.com]
>> Sent: Wednesday, May 06, 2009 3:14 PM
>> To: core-user@hadoop.apache.org
>> Subject: Re: PIG and Hive
>>> The difference between PIG and Hive seems to be pretty
>> insignificant.
>> Difference between Pig and Hive is significant, specifically:
>> (1) Pig doesn't require underlying structure to the data,
>> Hive does imply structure via a metastore. This has it pros
>> and cons. It allows Pig to be more suitable for ETL kind
>> tasks where the input data is still a mish-mash and you want
>> to convert it to be structured. On the other hand, Hive's
>> metastore provides a dictionary that lets you easily see what
>> columns exist in which tables which can be very handy.
>> (2) Pig is a new language, easy to learn if you know
>> languages similar to Perl. Hive is a sub-set of SQL with very
>> simple variations to enable map-reduce like computation. So,
>> if you come from a SQL background you will find Hive QL
>> extremely easy to pickup (many of your SQL queries will run
>> as is), while if you come from a procedural programming
>> background (w/o SQL knowledge) then Pig will be much more
>> suitable for you. Furthermore, Hive is a bit easier to
>> integrate with other systems and tools since it speaks the
>> language they already speak (i.e. SQL).
>> You're right that HBase is a completely different game, HBase
>> is not about being a high level language that compiles to
>> map-reduce, HBase is about allowing Hadoop to support
>> lookups/transactions on key/value pairs. HBase allows you to
>> (1) do quick random lookups, versus scan all of data
>> sequentially, (2) do insert/update/delete from middle, not
>> just add/append.
>> -- amr
>> Ricky Ho wrote:
>>> Jeff,
>>> Thanks for the pointer.
>>> It is pretty clear that Hive and PIG are the same kind and
>> HBase is a different kind.
>>> The difference between PIG and Hive seems to be pretty
>> insignificant.  Layer a tool on top of them can completely
>> hide their difference.
>>> I am viewing your PIG and Hive tutorial and hopefully can
>> extract some technical details there.
>>> Rgds,
>>> Ricky
>>> -----Original Message-----
>>> From: Jeff Hammerbacher [mailto:hammer@cloudera.com]
>>> Sent: Wednesday, May 06, 2009 1:38 PM
>>> To: core-user@hadoop.apache.org
>>> Subject: Re: PIG and Hive
>>> Here's a permalink for the thread on MarkMail:
>>> http://markmail.org/thread/ee4hpcji74higqvk
>>> On Wed, May 6, 2009 at 4:55 AM, Sharad Agarwal
>> <sharadag@yahoo-inc.com>wrote<sharadag@yahoo-inc.com%3ewrote>:
>>>> see core-user mail thread with subject "HBase, Hive, Pig and other
>>>> Hadoop based technologies"
>>>> - Sharad
>>>> Ricky Ho wrote:
>>>>> Are they competing technologies of providing a higher
>> level language
>>>>> for
>>>> Map/Reduce programming ?
>>>>> Or are they complementary ?
>>>>> Any comparison between them ?
>>>>> Rgds,
>>>>> Ricky

------ End of Forwarded Message


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