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From Hsuan Yi Chu <hyi...@maprtech.com>
Subject Re: In list filter evaluation : room for improvement in run-time code generation.
Date Thu, 10 Sep 2015 17:40:08 GMT
I believe the usage of Semi-Join had been proposed before.

Would that new operator help in this scenario you think?

On Wed, Sep 9, 2015 at 8:16 PM, Jinfeng Ni <jinfengni99@gmail.com> wrote:

> The reason that the in-list join approach is not fast enough :
> the query has 5 in-lists ORed together. Each in-list is converted
> to a left outer join.  After the 5 left outer join, there is a filter.
>
> Since left outer join does not prune any row from left side,
> which is the base table in this case, essentially each join has
> to scan the same # of rows as the base table, and copy
> to the outgoing batch. That is, although the in-list evaluation
> is using hash-based probe, which is faster than the original
> filter evaluation, still 5 left out join incurs big overhead
> in scanning/copying the data.
>
> The UDF idea in #2 is essentially doing the same kind of hash-based
> probe in filter evaluation. The hash-table will be initialized as
> a workspace variable in the doSetup(). Then, the doEval() will
> simply probe the hash-table.  I feel it would achieve the same
> benefit of join approach, while avoid the overhead of re-scanning
> the data multiple times.
>
> However, the current infrastructure seems miss the support
> of VarArg in Drill's build-in or UDF, which is required to implement
> this idea.
>
>
>
> On Wed, Sep 9, 2015 at 5:40 PM, Aman Sinha <amansinha@apache.org> wrote:
>
> > Yes, this would be a good enhancement.  Any improvement to the
> > efficiency/compactness of the generated code is complimentary to other
> > optimizations such as parquet filter pushdown.  I recall that there was a
> > JIRA a while ago with hundreds or thousands of filter conditions
> creating a
> > really bloated generated code  - we should revisit that at some point to
> > identify scope for improvement.
> > I am not so sure about the UDF suggestion in #2.   It seems like
> > identifying why the large IN-list join approach was slow and fixing that
> > would be a general solution.
> >
> > Aman
> >
> > On Wed, Sep 9, 2015 at 1:31 PM, Jinfeng Ni <jinfengni99@gmail.com>
> wrote:
> >
> > > Weeks ago there was a message on drill user list, reporting performance
> > > issues caused by in list filter [1].  The query has filter:
> > >
> > > WHERE
> > >    c0 IN (v_00, v_01, v_02, v_03, ... )
> > > OR
> > >    c1 IN (v_11, v_11, v_12, v_13, ....)
> > > OR
> > >    c2 IN ...
> > > OR
> > >    c3 IN ...
> > > OR
> > >    ....
> > >
> > > The profile shows that most of query time is spent on filter
> evaluation.
> > > One workaround that we recommend was to re-write the query so that the
> > > planner would convert in list into join operation. Turns out that
> > > converting
> > > into join did help improve performance, but not as much as we wanted.
> > >
> > > The original query has parquet as the data source. Therefore, the ideal
> > > solution is parquet filter pushdown, which DRILL-1950 would address.
> > >
> > > On the other hand, I noticed that there seems to be room for
> improvement
> > > in the run-time generated code. In particular, for " c0 in (v_00, v_01,
> > > ...)",
> > > Drill will evaluate it as :
> > >     c0 = v_00  OR c0 = v_01 OR ...
> > >
> > > Each reference of "c0" will lead to initialization of vector and holder
> > > assignment in the generated code. There is redundant evaluation for
> > > the common reference.
> > >
> > > I put together a patch,which will avoid the redundant evaluation for
> the
> > > common reference.  Using TPCH scale factor 10's lineitem table, I saw
> > > quite surprising improvement. (run on Mac with embedded drillbit)
> > >
> > > 1) In List uses integer type [2]
> > >   master branch :  12.53 seconds
> > >   patch on top of master branch : 7.073 seconds
> > > That's almost 45% improvement.
> > >
> > > 2) In List uses binary type [3]
> > >   master branch :  198.668 seconds
> > > patch on top of master branch: 20.37 seconds
> > >
> > > Two thoughts:
> > > 1. Will code size impact Janino compiler optimization or jvm hotspot
> > > optimization? Otherwise, it seems hard to explain the performance
> > > difference of removing the redundant evaluation. That might imply
> > > that the efficiency of run-time generated code may degrade with
> > > more expressions in the query (?)
> > >
> > > 2. For In-List filter, it might make sense to create a Drill UDF. The
> > > UDF will build a heap-based hashtable in setup, in a similar way
> > > as what the join approach will do.
> > >
> > >  I'm going to open a JIRA to submit the patch for review, as I feel
> > > it will benefit not only the in list filter, but also expressions with
> > > common column references.
> > >
> > >
> > > [1]
> > >
> > >
> >
> https://mail-archives.apache.org/mod_mbox/drill-user/201508.mbox/%3CCAC-7oTym0Yzr2RmXhDPag6k41se-uTkWu0QC%3DMABb7s94DJ0BA%40mail.gmail.com%3E
> > >
> > > [2] https://gist.github.com/jinfengni/7f6df9ed7d2c761fed33
> > >
> > > [3]  https://gist.github.com/jinfengni/7460f6d250f0d00009ed
> > >
> >
>

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