Great ! Glad to see things are merging ... At that point, PIG and Hive are even more competitive to each other.
Rgds, Ricky -----Original Message----- From: Ashish Thusoo [mailto:athu...@facebook.com] Sent: Thursday, May 07, 2009 11:11 AM To: core-user@hadoop.apache.org Subject: RE: PIG and Hive Scott, Namit is actually correct. If you do a explain on the query that he sent out, you actually get only 2 map/reduce jobs and not 5 with Hive. We have verified that and that is consistent with what we should expect in this case. We would be very interested to know the exact query that you used as 5 map/reduce jobs is somewhat of a surprise to us. Ricky, Without SQL - at least PIG does not have that now, it is really not usable for people like data analysts at this time - people who have been brought up on SQL and do not necessarily have the skill set of learning another imperative programing language. PIG appeals more to the engineering users - our approach has been different though even in this respect. We have followed a philosophy of allowing even engineering users to write their custom code in an imperative programming language of their choice and be able to plugin that customized logic in different parts of the data flow. Again, this idea may appeal to some and may not appeal to others and it is really a subjective call when it comes to engineering users when you think from the language perspective. Regarding collect and flatten, these have been in Hive roadmap for quite sometime (just as SQL has been on the pig roadmap :)) and we will put those into the language at some future release. Ashish -----Original Message----- From: Namit Jain [mailto:nj...@facebook.com] Sent: Thursday, May 07, 2009 10:12 AM To: core-user@hadoop.apache.org Subject: RE: PIG and Hive 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: Explain <QUERY> Thanks, -namit ------ Forwarded Message From: Ricky Ho <r...@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 ? Rgds, Ricky -----Original Message----- From: Scott Carey [mailto:sc...@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 better. 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" <ol...@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:r...@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:a...@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:ham...@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 >> <shara...@yahoo-inc.com>wrote<shara...@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 --- h...@lists.facebook.com http://lists.facebook.com/mailman/listinfo/hive
