RE: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
Liquan, yes, for full outer join, one hash table on both sides is more efficient. For the left/right outer join, it looks like one hash table should be enought. From: Liquan Pei [mailto:liquan...@gmail.com] Sent: 2014年9月30日 18:34 To: Haopu Wang Cc: d...@spark.apache.org; user Subject: Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, How about full outer join? One hash table may not be efficient for this case. Liquan On Mon, Sep 29, 2014 at 11:47 PM, Haopu Wang hw...@qilinsoft.com wrote: Hi, Liquan, thanks for the response. In your example, I think the hash table should be built on the right side, so Spark can iterate through the left side and find matches in the right side from the hash table efficiently. Please comment and suggest, thanks again! From: Liquan Pei [mailto:liquan...@gmail.com] Sent: 2014年9月30日 12:31 To: Haopu Wang Cc: d...@spark.apache.org; user Subject: Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst -- Liquan Pei Department of Physics University of Massachusetts Amherst
Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
I'm pretty sure inner joins on Spark SQL already build only one of the sides. Take a look at ShuffledHashJoin, which calls HashJoin.joinIterators. Only outer joins do both, and it seems like we could optimize it for those that are not full. Matei On Oct 7, 2014, at 11:04 PM, Haopu Wang hw...@qilinsoft.com wrote: Liquan, yes, for full outer join, one hash table on both sides is more efficient. For the left/right outer join, it looks like one hash table should be enought. From: Liquan Pei [mailto:liquan...@gmail.com] Sent: 2014年9月30日 18:34 To: Haopu Wang Cc: d...@spark.apache.org; user Subject: Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, How about full outer join? One hash table may not be efficient for this case. Liquan On Mon, Sep 29, 2014 at 11:47 PM, Haopu Wang hw...@qilinsoft.com wrote: Hi, Liquan, thanks for the response. In your example, I think the hash table should be built on the right side, so Spark can iterate through the left side and find matches in the right side from the hash table efficiently. Please comment and suggest, thanks again! From: Liquan Pei [mailto:liquan...@gmail.com] Sent: 2014年9月30日 12:31 To: Haopu Wang Cc: d...@spark.apache.org; user Subject: Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst -- Liquan Pei Department of Physics University of Massachusetts Amherst
Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
I am working on a PR to leverage the HashJoin trait code to optimize the Left/Right outer join. It's already been tested locally and will send out the PR soon after some clean up. Thanks, Liquan On Wed, Oct 8, 2014 at 12:09 AM, Matei Zaharia matei.zaha...@gmail.com wrote: I'm pretty sure inner joins on Spark SQL already build only one of the sides. Take a look at ShuffledHashJoin, which calls HashJoin.joinIterators. Only outer joins do both, and it seems like we could optimize it for those that are not full. Matei On Oct 7, 2014, at 11:04 PM, Haopu Wang hw...@qilinsoft.com wrote: Liquan, yes, for full outer join, one hash table on both sides is more efficient. For the left/right outer join, it looks like one hash table should be enought. -- *From:* Liquan Pei [mailto:liquan...@gmail.com liquan...@gmail.com] *Sent:* 2014年9月30日 18:34 *To:* Haopu Wang *Cc:* d...@spark.apache.org; user *Subject:* Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, How about full outer join? One hash table may not be efficient for this case. Liquan On Mon, Sep 29, 2014 at 11:47 PM, Haopu Wang hw...@qilinsoft.com wrote: Hi, Liquan, thanks for the response. In your example, I think the hash table should be built on the right side, so Spark can iterate through the left side and find matches in the right side from the hash table efficiently. Please comment and suggest, thanks again! -- *From:* Liquan Pei [mailto:liquan...@gmail.com] *Sent:* 2014年9月30日 12:31 *To:* Haopu Wang *Cc:* d...@spark.apache.org; user *Subject:* Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst -- Liquan Pei Department of Physics University of Massachusetts Amherst -- Liquan Pei Department of Physics University of Massachusetts Amherst
RE: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
Hi, Liquan, thanks for the response. In your example, I think the hash table should be built on the right side, so Spark can iterate through the left side and find matches in the right side from the hash table efficiently. Please comment and suggest, thanks again! From: Liquan Pei [mailto:liquan...@gmail.com] Sent: 2014年9月30日 12:31 To: Haopu Wang Cc: d...@spark.apache.org; user Subject: Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst
Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
Hi Haopu, How about full outer join? One hash table may not be efficient for this case. Liquan On Mon, Sep 29, 2014 at 11:47 PM, Haopu Wang hw...@qilinsoft.com wrote: Hi, Liquan, thanks for the response. In your example, I think the hash table should be built on the right side, so Spark can iterate through the left side and find matches in the right side from the hash table efficiently. Please comment and suggest, thanks again! -- *From:* Liquan Pei [mailto:liquan...@gmail.com] *Sent:* 2014年9月30日 12:31 *To:* Haopu Wang *Cc:* d...@spark.apache.org; user *Subject:* Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin? Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst -- Liquan Pei Department of Physics University of Massachusetts Amherst
Spark SQL question: why build hashtable for both sides in HashOuterJoin?
I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org
Re: Spark SQL question: why build hashtable for both sides in HashOuterJoin?
Hi Haopu, My understanding is that the hashtable on both left and right side is used for including null values in result in an efficient manner. If hash table is only built on one side, let's say left side and we perform a left outer join, for each row in left side, a scan over the right side is needed to make sure that no matching tuples for that row on left side. Hope this helps! Liquan On Mon, Sep 29, 2014 at 8:36 PM, Haopu Wang hw...@qilinsoft.com wrote: I take a look at HashOuterJoin and it's building a Hashtable for both sides. This consumes quite a lot of memory when the partition is big. And it doesn't reduce the iteration on streamed relation, right? Thanks! - To unsubscribe, e-mail: user-unsubscr...@spark.apache.org For additional commands, e-mail: user-h...@spark.apache.org -- Liquan Pei Department of Physics University of Massachusetts Amherst
