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
