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From <de...@segel.com>
Subject RE: URGENT!!! JDBC SQL query taking long time for large IN clause
Date Wed, 08 Apr 2009 12:53:16 GMT





Just a few things.


1)       Derby is a free, open source, product. Warts and all, its not going
to be your best choice for a commercial rdbms product. (Sorry Derby fans,
you get what you pay for.)

2)       You want speed, you're going to have to consider IBM's SolidDB
which is an in memory database along with Oracle's TimesTen database. This
will give you the speed that you want.

3)       You're running on a laptop where your disk drive could be a 5400
rpm IDE drive. Laptop drive == low energy consumption and low performance.
Disk based solutions will be much slower on a laptop than on a 'comparable'
desktop and/or server.

4)       I'm not sure why you had to load and then compress your tables. I
could understand that if you created your index prior to loading the data
that you could have to update the statistics.

5)       Since we don't know what you're actually trying to do, there could
be a better or more efficient design. Having an IN clause with 1000's of
entries is definitely not a good design for any database. 

6)       You never did answer the question about the object ids that were in
the IN clause. Were they unique or were there duplicates?







From: Arindam Bhattacharjee [mailto:mr.arindam.bhattacharjee@gmail.com] 
Sent: Wednesday, April 08, 2009 2:14 AM
To: Derby Discussion; msegel@segel.com
Subject: Re: URGENT!!! JDBC SQL query taking long time for large IN clause


Few inputs/observations:

a) This is not a school project. This is a project which makes money for us
today. We have functioning product running today, developed by us which
doesn't use any RDBMS's to achieve what I am trying to achieve with the
tables. For 200,000 object master we get 45 - 60 millis performance. The
reason we are trying to use an RDBMS is to ensure that we can scale even
higher and updates are easier and more maintenable. Hence all these

b) I tried removing the "preserve rows" from the declare temp table clause -
and that didn't help me either.

c) The data base which I have created is just a sample database which
vaguely represents the load which we will see if we implement the existing
feature of ours, using Derby RDBMS. It doesn't contain REAL data.

d) The entire database was created in one shot, as I have stated earlier,
and records are populated in one go. That was the actual problem - thanks to
Knuth for indicating that as a possibility. When I compress the tables - the
quries start performing a LOT faster! 1 million in object master, 20 million
in object category mapping and 10 K in category master and 1000 in IN clause
gives me 1100 millis speed now - down from 30 seconds. That probably
explains why the object master index scans were taking nearly 30 seconds in
the runtimestats which I posted. Which is slow, but still manageable since
the 100 and 500s are much faster. However, that is still a lot slower than
other databases we are testing on. Since Derby is embedded we expected it to
be much faster since no IPC is required between the client driver and the
network server. 

e) IN doesn't function properly beyond 1000 object ids, and we used a
regular table CREATE TABLE DUMMY (ID INTEGER PRIMARY KEY). Insertion of 5000
records into this happened in 100 millis (after compression of the tables)
and the query took 4 seconds. With executeUpdate() or execute() (as
suggested) insertion was at least 200% slower. So the execute batch works
better for the inserts into the table for the payloads required by us. The
temp table query took 10 MINS (this time I waited patiently for it to finish
- there was nothing wrong there - the query just takes too much time and I
didn't have patience to wait for it to finish the first time :) ) to execute
while the regular table with primary key took just 4 seconds. 

f) The stack overflow exception for "select ... values...union" was much
less of a problem in 10.4 compared to 10.1 since the memory usage is
tapering off to the -mx<Size In Megs> for the JVM. But, since it cannot be
parameterized it isn't of much use to us. IN clause based queries are
getting parsed with much lower memory footprints.

Best regards,


On Wed, Apr 8, 2009 at 2:39 AM, <derby@segel.com> wrote:

> -----Original Message-----
> From: Mike Matrigali [mailto:mikem_app@sbcglobal.net]
> Sent: Tuesday, April 07, 2009 2:05 PM
> To: Derby Discussion

> Subject: Re: URGENT!!! JDBC SQL query taking long time for large IN clause

> It is impossible to say what the performance of the query can be without
> knowing exact values of all the values of the IN LIST.  But it is
> possible to get some idea assuming some worst case behavior, and from
> that I am going to guess you will never come close to 100ms with an
> uncached database, on hardware using some sort of standard disk based
> hard drive.
> I do think the query may go faster with index and query tweeking, but
> 100ms to an uncached db and non-clustered unique values in that IN list
> is never going to go that fast.  Adding up just what is posted it looks
> like this is a 1.2 gig db.

Drop the unnecessary indexes and you'll see the database size shrink fast.
Also note that he's running this on a Windows XP laptop. Depending on the
model of the lap top, you will have not only CPU issues but also disk i/o
issues as well. (5400 rpm IDE as an example....)

However, it is possible for the OP to get better performance, if not
realistically 100ms performance. (BTW where did 100ms come from? I'm sorry
but this really sounds like a class project...)

> You posted the space for the tables and indexes.  The interesting ones
> are the big ones.  You have 5 tables or indexes over 1000 pages big.  If
> in the worst case your 1000 value IN list happens to be on 1000
> different pages then Derby is going to need to do at least 1000 i/o's to
> get to them - I usually use back of envelope of max 100 i/o's per second
> (even if your disk has specs that say higher rate this I/O is not
> going to
> get streamed as fast as possible by this query, it is going to ask for
> page, process it, do some join work then later ask for another page, ...)
> :
> > CATEGORY_MASTER            0    103    0    0    4096    0
> > SQL090406091302600        1    55    0    0    4096    0
> > SQL090406091302601        1    160    0    1    4096    0
> > SQL090406091302730        1    1    0    1    4096    0
> > OBJECT_MASTER            0    10497    0    0    4096    0
> > SQL090406091302760        1    5340    0    1    4096    0
> > SQL090406091302761        1    16708    0    410    4096    0
> > OBJECT_CATEGORY_MAPPING        0    150794    0    0    4096    0
> > OBJECT_CATEGORY_MAPPING_INDEX    1    112177    0    57    4096    0


I think that a lot of this information is a bit skewed. Outside of the
primary index, the indexes he created included the varchar field. Not sure
why he did this except under the impression that he'd only have to hit the
index and not the underlying table. While there is some potential merit to
this, I think that there are things that he can do to improve performance.
(Hence my post about reworking the query itself and using a temp table.)
Drop those indexes and you'll see a big change in database size.

> There was work done in 10.3 on IN-LISTS, making them perform more like
> unions,  See DERBY-47.  So if you have a choice of releases I would
> suggest you move to 10.4 and post query plan and results against that.
> The basic idea of that change was to allow the
> system to do 1 probe into an index for each value in the IN-LIST, before
> this change DERBY could only sort the values in the IN list and then
> limit a index scan to the lowest and biggest values in the in list.
> So for instance for OBJECT_CATEGORY_MAPPING_INDEX, worst case it might
> have to scan 112177 pages to find the 1000 rows, where worst case for
> probing would be 1000 page (plus btree parent index pages, but those
> are much more likely cached).  The problem is that there is definitely
> overhead for probing one at a time, scans go much faster - so there is
> a crossover point - ie. I would guess it would likely better to scan all
> 112177 pages then do 100,000 probes.

I believe that it was already recommended that he do just that.
There are two ways he could use the temp table. As a sub-select statement,
or as part of the table join.

I think this would bypass the whole use of the IN list. I'm still not 100%
sure why there's 100+ values coming from an outside source. Based on his
query below it looks like the object_ids in the IN clause are not unique...

Its kind of hard trying to help someone when you don't know the whole


> arindam.bhattacharjee wrote:
> > Hello Knut,
> >
> > Thanks for your quick response. This is a sample database which I have
> > created just for testing out the performance and has been written to
> only
> > once in one go. I tried temp tables but that is just too slow. The IN
> clause
> > has values which comes from another source and I can't modify that.
> >
> > However, I will try out what you state below. But still, I wanted to get
> > your pulse about whether Derby can respond in sub 100 millisec time with
> the
> > table sizes you see above?
> >
> > I find that:
> >
> > select category_master.category_name,
> count(category_master.category_name)
> > as category_count
> > from
> >     (
> >             select internal.object_id
> >             from
> >             (
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1002) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all
> >                     values(1001) union all .......
> >                     values(9999)
> >             ) as internal(object_id)
> >
> >     ) as external_ids,
> >     object_master,
> >     category_master,
> >     object_category_mapping
> > where
> >     external_ids.object_id = object_master.object_id and
> >     external_ids.object_id = object_category_mapping.object_id and
> >     object_master.object_id = object_category_mapping.object_id and
> >     category_master.category_id = object_category_mapping.category_id
> > group by
> >     category_master.category_name
> > order by
> >     category_count desc
> >
> > is much faster unfortunately connection.prepareStatement() is taking way
> too
> > much memory (both stack and heap - I have a constraint of 256 MB MAX
> memory
> > for my JVM) which goes beyond my applications resources. Is there a way
> I
> > can precompile some SQLs which are very expensive to parse during
> execution.
> >
> > Best regards,
> >
> > Arindam.
> >
> >
> > Knut Anders Hatlen wrote:
> >> "arindam.bhattacharjee" <mr.arindam.bhattacharjee@gmail.com> writes:
> >>
> >>> Hello,
> >>>
> >>> I would like my query below to return within 100 millisecs. Please
> help
> >>> me,
> >>> and the values for the IN clause comes from outside hence cannot
> really
> >>> change the IN clause to a join on an existing table.
> >> Hi Arindam,
> >>
> >> Does the query run faster if you compress all the tables involved, or
> if
> >> you drop and recreate all the indexes? If so, it is likely that the
> >> index cardinality statistics are out of date, which may make the
> >> optimizer pick a bad execution plan. Currently, index cardinality
> >> statistics are only updated at index creation time, when tables are
> >> compressed, and when columns are dropped. A more automatic solution is
> >> being worked on. For more details, see:
> >>
> >> https://issues.apache.org/jira/browse/DERBY-269
> >> https://issues.apache.org/jira/browse/DERBY-3788
> >> http://db.apache.org/derby/docs/10.4/tuning/ctunstats18908.html
> >>
> >> You may be experiencing some other problem, but this is a problem that
> >> keeps coming up, so I think it's worth checking.
> >>
> >> Hope this helps,
> >>
> >> --
> >> Knut Anders
> >>
> >>
> >


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