phoenix-user mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From Gary Schulte <gschu...@marinsoftware.com>
Subject Re: high cardinality aggregation query performance
Date Sat, 28 Feb 2015 00:06:31 GMT
I have the query timeout set too low, but I believe the stats update
completed as I see related rows in the stats table.

Both skip and in-list queries run fine - no exceptions.  Still null for the
guideposts though - is it likely this is due to the timeout in the stats
update?

-Gary

On Fri, Feb 27, 2015 at 12:30 PM, James Taylor <jamestaylor@apache.org>
wrote:

> See inline. Thanks for your help on this one, Gary. It'd be good to
> get to the bottom of it so it doesn't bite you again.
>
> On Fri, Feb 27, 2015 at 11:13 AM, Gary Schulte
> <gschulte@marinsoftware.com> wrote:
> > James,
> >
> > When I simply added the skip scan hint, I got the same exception (even
> with
> > device_type criteria removed) but the indexes in the exception changed.
> > Interesting - I wouldn't have expected adding a skip scan hint would have
> > altered the plan, since it was already doing a skip scan.
>
> The hint tells Phoenix to keep using PK columns in the skip scan,
> rather than stopping at the first PK column that isn't being filtered
> on. We don't do this by default, because if the cardinality was very
> high, we wouldn't want to do this. Since our stats don't yet capture
> cardinality, we can't yet automatically do this.
>
> >
> > 1: current region boundaries, linked so as not to clutter the list with
> hex
> > :  http://goo.gl/hFSzYJ
> >
> > 2: table stats/guideposts, it looks like there are/were none.  The output
> > from the guidepost loop was :
> >
> > null
> >
> > (this was prior to deleting from system.stats)
> >
> >
> > 3: deleting system.stats appears to have resolved the exception for both
> the
> > explicit varchar inlist and the skip_scan hint.  Skip scanning the
> reduced
> > index space yields much faster results, ~5 seconds as opposed to 27.
>
> Glad to hear it's faster with the hint forcing the skip scan across
> all your columns.
>
> I can't explain why deleting the stats resolved the issue, though, as
> I would have expected (2) to have returned the stats. FYI, it looks
> like the bug is in the code that intersects the guideposts with the
> region boundaries.
>
> >
> > Should I expect to rebuild stats often or is this more of an error case?
>
> Stats are rebuilt automatically when a major compaction occurs and are
> updated as splits happen. They can also be manually updated by running
> the following command:
>
> UPDATE STATISTICS PERF.BIG_OLAP_DOC
>
> For more info on stats, see
> http://phoenix.apache.org/update_statistics.html
>
> If you run this command, does the problem start to reoccur? If so,
> would you mind adding this command before running the loop to collect
> the guideposts and let me know if you see that stats output?
>
> >
> > Thanks again.
> >
> >
> >
> > On Thu, Feb 26, 2015 at 5:55 PM, James Taylor <jamestaylor@apache.org>
> > wrote:
> >>
> >> Gary,
> >> I'm not able to repro the issue - I filed PHOENIX-1690 to track it and
> >> attached my test case there. It looks related to the particular state
> >> the table is in wrt its region boundaries and current statistics, so
> >> I'll need the following additional information to try to help me repro
> >> this:
> >>
> >> 1) What are the current region boundaries of your table? You can get
> >> this programmatically through code like this:
> >>
> >>         Connection conn = DriverManager.getConnection(getUrl(), props);
> >>         List<HRegionLocation> splits =
> >>
> >>
> conn.unwrap(PhoenixConnection.class).getQueryServices().getAllTableRegions(Bytes.toBytes("PERF.BIG_OLAP_DOC"));
> >>         for (HRegionLocation split : splits) {
> >>
> >>
> System.out.println(Bytes.toStringBinary(split.getRegionInfo().getEndKey()));
> >>         }
> >>
> >> 2) What are the current stats for the table. You can get this by
> >> programmatically through code like this:
> >>
> >>         PTable table =
> >> conn.unwrap(PhoenixConnection.class).getMetaDataCache().getTable(new
> >> PTableKey(null, "PERF.BIG_OLAP_DOC"));
> >>         for (GuidePostsInfo info :
> >> table.getTableStats().getGuidePosts().values()) {
> >>             for (byte[] gp : info.getGuidePosts()) {
> >>                 System.out.println(Bytes.toStringBinary(gp));
> >>             }
> >>         }
> >>
> >> 3) If you can try after removing all rows from the SYSTEM.STATS table
> >> and let me know if the problem still occurs, that'd be helpful too.
> >> You can just do the following from sqlline: DELETE FROM SYSTEM.STATS
> >> and then exit sqlline, start it again, and rerun the original query.
> >>
> >> Thanks,
> >> James
> >>
> >> On Thu, Feb 26, 2015 at 10:52 AM, James Taylor <jamestaylor@apache.org>
> >> wrote:
> >> > Gary,
> >> > One possible workaround. Can you try adding the SKIP_SCAN hint to your
> >> > query (instead of the AND device_type in
> >> > ('MOBILE','DESKTOP','OTHER','TABLET')), like this?
> >> >
> >> > SELECT /*+ SKIP_SCAN */ count(1) cnt,
> >> > ...
> >> >
> >> > Thanks,
> >> > James
> >> >
> >> > On Wed, Feb 25, 2015 at 10:16 AM, James Taylor <
> jamestaylor@apache.org>
> >> > wrote:
> >> >> Sounds like a bug. I'll try to repro on my end. Thanks for the
> details,
> >> >> Gary.
> >> >>
> >> >>     James
> >> >>
> >> >> On Tue, Feb 24, 2015 at 1:49 PM, Gary Schulte
> >> >> <gschulte@marinsoftware.com> wrote:
> >> >>> On Tue, Feb 24, 2015 at 12:29 AM, James Taylor
> >> >>> <jamestaylor@apache.org>
> >> >>> wrote:
> >> >>>>
> >> >>>> Based on your query plan, the skip scan is being done solely
based
> on
> >> >>>> your
> >> >>>> salt bucket while the rest of the filtering is being done by
a
> >> >>>> filter, which
> >> >>>> means that you're not filtering based on the leading part of
your
> >> >>>> primary
> >> >>>> key. We'll know more once you post your schema, but if NETWORK,
> >> >>>> KEYWORD_ID
> >> >>>> and CUSTOMER_ID formed your primary key constraint, then the
skip
> >> >>>> scan would
> >> >>>> work well.
> >> >>>>
> >> >>>
> >> >>> Thanks for your response James.  Sorry for the slow reply - I had
> >> >>> difficulty
> >> >>> finding the exact set of test queries I was using for timings.
> >> >>>
> >> >>> The relevant portion of the olap doc schema is:
> >> >>>
> >> >>> create table PERF.BIG_OLAP_DOC (
> >> >>> client_id                           integer not null
> >> >>> ,customer_id                        integer
> >> >>> ,time_id                            integer not null
> >> >>> ,conversion_type_id                 integer not null
> >> >>> ,device_type                        varchar(16)
> >> >>> ,keyword_id                         bigint not null
> >> >>> ,creative_id                        bigint not null
> >> >>> ,placement_id                       bigint not null
> >> >>> ,product_target_id                  bigint not null
> >> >>> ,network                            varchar(7)
> >> >>> ,impressions                        decimal(18, 4)
> >> >>> ,publisher_clicks                   decimal(18, 4)
> >> >>> ,publisher_cost                     decimal(18, 4)
> >> >>> ,conversions                        decimal(18, 4)
> >> >>> ,revenue                            decimal(18, 4)
> >> >>>
> >> >>> [ ...additional metric and dimensional colums ... ]
> >> >>>
> >> >>>     constraint perf_fact_pk primary key (client_id, time_id,
> >> >>> conversion_type_id, device_type, keyword_id, creative_id,
> >> >>> placement_id,
> >> >>> product_target_id))SALT_BUCKETS=10;
> >> >>>
> >> >>>
> >> >>> I am evaluating a 'stitch' case where results from an external
> system
> >> >>> are
> >> >>> injected either via table or (as in this case) an in-list.  An
> example
> >> >>> of
> >> >>> one of these test agg queries I am using is:
> >> >>>
> >> >>> SELECT count(1) cnt,
> >> >>>        coalesce(SUM(impressions), 0.0) AS "impressions",
> >> >>>        coalesce(SUM(publisher_clicks), 0.0) AS "pub_clicks",
> >> >>>        coalesce(SUM(publisher_cost), 0.0) AS "pub_cost",
> >> >>>        coalesce(SUM(conversions), 0.0) AS "conversions",
> >> >>>        coalesce(SUM(revenue), 0.0) AS "revenue"
> >> >>>   FROM perf.big_olap_doc
> >> >>>  WHERE time_id between 3000 and 3700
> >> >>>    AND network in ('SEARCH')
> >> >>>    AND conversion_type_id = 1
> >> >>>    AND client_id = 10724
> >> >>> --   AND device_type in ('MOBILE','DESKTOP','OTHER','TABLET')
> >> >>>    AND keyword_id in (
> >> >>> 613214369, 613217307, 613247509, 613248897, 613250382, 613250387,
> >> >>> 613252322,
> >> >>> 613260252, 613261753, 613261754, 613261759,
> >> >>> 613261770, 613261873, 613261884, 613261885, 613261888, 613261889,
> >> >>> 613261892,
> >> >>> 613261897, 613261913, 613261919, 613261927,
> >> >>> 614496021, 843606367, 843606967, 843607021, 843607033, 843607089,
> >> >>> 1038731600, 1038731672, 1038731673, 1038731675,
> >> >>> 1038731684, 1038731693, 1046990487, 1046990488, 1046990499,
> >> >>> 1046990505,
> >> >>> 1046990506, 1049724722, 1051109548, 1051311275,
> >> >>> 1051311904, 1060574377, 1060574395, 1060574506, 1060574562,
> >> >>> 1115915938,
> >> >>> 1115915939, 1115915941, 1116310571, 1367495544,
> >> >>> 1367495545, 1367497297, 1367497298, 1367497299, 1367497300,
> >> >>> 1367497303,
> >> >>> 1367497313, 1367497813, 1367497816, 1367497818,
> >> >>> 1367497821, 1367497822, 1367497823, 1624976423, 1624976451,
> >> >>> 1624976457,
> >> >>> 3275636061, 3275640505, 3275645765, 3275645807,
> >> >>> 3275649138, 3275651456, 3275651460, 3275651478, 3275651479,
> >> >>> 3275654566,
> >> >>> 3275654568, 3275654570, 3275654575, 3275659612,
> >> >>> 3275659616, 3275659620, 3275668880, 3275669693, 3275675627,
> >> >>> 3275675634,
> >> >>> 3275677479, 3275677504, 3275678855, 3275679524,
> >> >>> 3275679532, 3275680014, 3275682307, 3275682308, 3275682309,
> >> >>> 3275682310,
> >> >>> 3275682420, 3275682423, 3275682436, 3275682448,
> >> >>> 3275682460, 3275682462, 3275682474, 3275684831, 3275688903,
> >> >>> 3275694023,
> >> >>> 3275694025, 3275694027, 3275695054, 3275695056,
> >> >>> 3275695062, 3275699512, 3275699514, 3275699518, 3275701682,
> >> >>> 3275701683,
> >> >>> 3275701685, 3275701688, 3275703633, 3275703634,
> >> >>> 3275703635, 3275703636, 3275703638, 3275703639, 3275704860,
> >> >>> 3275704861,
> >> >>> 3275764577, 3275797149, 3275798566, 3275798567,
> >> >>> 3275798568, 3275798592, 3275931147, 3275942728, 3275945337,
> >> >>> 3275945338,
> >> >>> 3275945339, 3275945340, 3275945342, 3275945344,
> >> >>> 3275946319, 3275946322, 3275946324, 3275946643, 3275949495,
> >> >>> 3275949498,
> >> >>> 3275949500, 3275950250, 3275955128, 3275955129,
> >> >>> 3275955130, 3427017435, 3427017450, 3438304254, 3438304257,
> >> >>> 3447068169,
> >> >>> 3505227849, 3505227890, 3505556908, 3506351285,
> >> >>> 3506351389, 3506351398, 3506351468, 3510037138, 3510038610,
> >> >>> 3545590644,
> >> >>> 3545594378, 3545595073, 3545595318, 3545595506,
> >> >>> 3545597841, 3545598818, 3545599658, 3545599663, 3545601215,
> >> >>> 3556080898,
> >> >>> 3556080980, 3556080999, 3556081323, 3565122663,
> >> >>> 3565122679, 3565122801, 3565122858, 3565122908, 3565122929,
> >> >>> 3565122952,
> >> >>> 3565122984, 3565123028, 3565123047, 3565123048,
> >> >>> 3565123203, 3565123230, 3949988054, 3949988056, 3949988070,
> >> >>> 3972992248,
> >> >>> 3972992252, 3972992254, 3972992257, 3972992263,
> >> >>> 3972992267, 3972992268, 3972992269, 3972992270, 3972992274,
> >> >>> 3972992275,
> >> >>> 3972992277, 3972992281, 3972992293, 3972992298,
> >> >>> 3972992299, 3972992305, 3972992307, 3972992313, 3972992316,
> >> >>> 3972992322,
> >> >>> 3972992338, 3978471261, 3978471272, 4266318185,
> >> >>> 4298107404, 4308853119, 4308853123, 4308853500, 4451174646,
> >> >>> 4451174656,
> >> >>> 4451174701, 4569827278, 4569827284, 4569827287,
> >> >>> 4569827379, 4569827523, 4569827524, 4896589676, 4979049725,
> >> >>> 5054587609,
> >> >>> 5136433884, 5362640372, 5393109964, 5393405364,
> >> >>> 5393405365, 5393405620, 5393405625, 5393405675, 5393405677,
> >> >>> 5393405858,
> >> >>> 5393405970)
> >> >>>
> >> >>>
> >> >>> Reading your interpretation of the skip scan, I see that the plan
is
> >> >>> indicating it is only using the salt and the first three columns
of
> >> >>> the
> >> >>> index, client_id, and time_id and conversion_type.  I hadn't
> >> >>> considered the
> >> >>> salt - that bit of detail in the plan makes more sense to me now.
> It
> >> >>> looks
> >> >>> now like the lackluster performance for higher cardinality
> >> >>> aggregations is
> >> >>> related to scanning a much larger portion of the key space.  For
> >> >>> aggregations where I am not relying on filtering, I am seeing much
> >> >>> better
> >> >>> performance.
> >> >>>
> >> >>> So to tune this particular stitch case / skip scan, it looks like
I
> >> >>> need to
> >> >>> get the 4th index column into the criteria.  There are only four
> >> >>> distinct
> >> >>> values in the fourth index column (these can/should probably be
> >> >>> something
> >> >>> other than varchar, but this is what I have loaded currently).
 In
> >> >>> order to
> >> >>> use the keyword_id portion of the index I tried explicitly
> specifying
> >> >>> all
> >> >>> device_types via in-list (the commented portion of the query above),
> >> >>> but I
> >> >>> get a peculiar error:
> >> >>>
> >> >>> java.lang.IndexOutOfBoundsException: end index (1) must not be
less
> >> >>> than
> >> >>> start index (2)
> >> >>> at
> >> >>>
> >> >>>
> com.google.common.base.Preconditions.checkPositionIndexes(Preconditions.java:388)
> >> >>> at
> >> >>>
> com.google.common.collect.ImmutableList.subList(ImmutableList.java:362)
> >> >>> at
> >> >>>
> com.google.common.collect.ImmutableList.subList(ImmutableList.java:62)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.filter.SkipScanFilter.intersect(SkipScanFilter.java:291)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.filter.SkipScanFilter.intersect(SkipScanFilter.java:177)
> >> >>> at
> >> >>>
> org.apache.phoenix.compile.ScanRanges.intersectScan(ScanRanges.java:316)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.iterate.BaseResultIterators.getParallelScans(BaseResultIterators.java:464)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.iterate.BaseResultIterators.getParallelScans(BaseResultIterators.java:394)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.iterate.BaseResultIterators.<init>(BaseResultIterators.java:184)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.iterate.ParallelIterators.<init>(ParallelIterators.java:54)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.execute.AggregatePlan.newIterator(AggregatePlan.java:173)
> >> >>> at
> >> >>>
> org.apache.phoenix.execute.BaseQueryPlan.iterator(BaseQueryPlan.java:227)
> >> >>> at
> >> >>>
> org.apache.phoenix.execute.BaseQueryPlan.iterator(BaseQueryPlan.java:154)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.jdbc.PhoenixStatement$1.call(PhoenixStatement.java:226)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.jdbc.PhoenixStatement$1.call(PhoenixStatement.java:217)
> >> >>> at org.apache.phoenix.call.CallRunner.run(CallRunner.java:53)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.jdbc.PhoenixStatement.executeQuery(PhoenixStatement.java:216)
> >> >>> at
> >> >>>
> >> >>>
> org.apache.phoenix.jdbc.PhoenixStatement.execute(PhoenixStatement.java:1057)
> >> >>> at sqlline.SqlLine$Commands.execute(SqlLine.java:3673)
> >> >>> at sqlline.SqlLine$Commands.sql(SqlLine.java:3584)
> >> >>> at sqlline.SqlLine.dispatch(SqlLine.java:821)
> >> >>> at sqlline.SqlLine.begin(SqlLine.java:699)
> >> >>> at sqlline.SqlLine.mainWithInputRedirection(SqlLine.java:441)
> >> >>> at sqlline.SqlLine.main(SqlLine.java:424)
> >> >>>
> >> >>>
> >> >>> I thought perhaps I was hitting an upper limit on the number of
> >> >>> elements in
> >> >>> an in-list for a skip scan, and so tried removing the 250 element
> >> >>> keyword
> >> >>> in-list entirely and leaving only the device_type in-list, but
I
> still
> >> >>> get
> >> >>> the same error.  It happens immediately, even for an explain, so
I
> >> >>> presume
> >> >>> this is a query parsing problem.  Is there a bug or limitation
of
> skip
> >> >>> scans
> >> >>> and/or sub lists involving varchar?
> >> >>>
> >> >>> Thx
> >> >>>
> >> >>>
> >> >>>
> >
> >
>

Mime
View raw message