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From Lars Hofhansl <lhofha...@yahoo.com>
Subject Re: Essential column family performance
Date Wed, 10 Apr 2013 01:17:43 GMT
Also the unittest tests with only 10000 rows that would all fit in the memstore. Seek vs reseek
should make little difference for the memstore.

We tested with 1m and 10m rows, and flushed the memstore  and compacted the store.

Will do some more verification later tonight.

-- Lars


Lars H <lhofhansl@yahoo.com> wrote:

>Your slow scanner performance seems to vary as well. How come? Slow is with the feature
off.
>
>I don't how reseek can be slower than seek in any scenario.
>
>-- Lars
>
>Ted Yu <yuzhihong@gmail.com> schrieb:
>
>>I tried using reseek() as suggested, along with my patch from HBASE-8306 (30%
>>selection rate, random distribution and FAST_DIFF encoding on both column
>>families).
>>I got uneven results:
>>
>>2013-04-09 16:59:01,324 INFO  [main] regionserver.TestJoinedScanners(167):
>>Slow scanner finished in 7.529083 seconds, got 1546 rows
>>
>>2013-04-09 16:59:06,760 INFO  [main] regionserver.TestJoinedScanners(167):
>>Joined scanner finished in 5.43579 seconds, got 1546 rows
>>...
>>2013-04-09 16:59:12,711 INFO  [main] regionserver.TestJoinedScanners(167):
>>Slow scanner finished in 5.95016 seconds, got 1546 rows
>>
>>2013-04-09 16:59:20,240 INFO  [main] regionserver.TestJoinedScanners(167):
>>Joined scanner finished in 7.529044 seconds, got 1546 rows
>>
>>FYI
>>
>>On Tue, Apr 9, 2013 at 4:47 PM, lars hofhansl <larsh@apache.org> wrote:
>>
>>> We did some tests here.
>>> I ran this through the profiler against a local RegionServer and found the
>>> part that causes the slowdown is a seek called here:
>>>              boolean mayHaveData =
>>>               (nextJoinedKv != null &&
>>> nextJoinedKv.matchingRow(currentRow, offset, length))
>>>               ||
>>> (this.joinedHeap.seek(KeyValue.createFirstOnRow(currentRow, offset, length))
>>>                   && joinedHeap.peek() != null
>>>                   && joinedHeap.peek().matchingRow(currentRow, offset,
>>> length));
>>>
>>> Looking at the code, this is needed because the joinedHeap can fall
>>> behind, and hence we have to catch it up.
>>> The key observation, though, is that the joined heap can only ever be
>>> behind, and hence we do not need a seek, but only a reseek.
>>>
>>> Deploying a RegionServer with the seek replaced with reseek we see an
>>> improvement in *all* cases.
>>>
>>> I'll file a jira with a fix later.
>>>
>>> -- Lars
>>>
>>>
>>>
>>> ________________________________
>>>  From: James Taylor <jtaylor@salesforce.com>
>>> To: user@hbase.apache.org
>>> Sent: Monday, April 8, 2013 6:53 PM
>>> Subject: Re: Essential column family performance
>>>
>>> Good idea, Sergey. We'll rerun with larger non essential column family
>>> values and see if there's a crossover point. One other difference for us
>>> is that we're using FAST_DIFF encoding. We'll try with no encoding too.
>>> Our table has 20 million rows across four regions servers.
>>>
>>> Regarding the parallelization we do, we run multiple scans in parallel
>>> instead of one single scan over the table. We use the region boundaries
>>> of the table to divide up the work evenly, adding a start/stop key for
>>> each scan that corresponds to the region boundaries. Our client then
>>> does a final merge/aggregation step (i.e. adding up the count it gets
>>> back from the scan for each region).
>>>
>>> On 04/08/2013 01:34 PM, Sergey Shelukhin wrote:
>>> > IntegrationTestLazyCfLoading uses randomly distributed keys with the
>>> > following condition for filtering:
>>> > 1 == (Long.parseLong(Bytes.toString(rowKey, 0, 4), 16) & 1); where rowKey
>>> > is hex string of MD5 key.
>>> > Then, there are 2 "lazy" CFs, each of which has a value of 4-64k.
>>> > This test also showed significant improvement IIRC, so random
>>> distribution
>>> > and high %%ge of values selected should not be a problem as such.
>>> >
>>> > My hunch would be that the additional cost of seeks/merging the results
>>> > from two CFs outweights the benefit of lazy loading on such small values
>>> > for the "lazy" CF with lots of data selected. This feature definitely
>>> makes
>>> > no sense if you are selecting all values, because then extra work is
>>> being
>>> > done for no benefit (everything is read anyway).
>>> > So the use cases would be larger "lazy" CFs or/and low percentage of
>>> values
>>> > selected.
>>> >
>>> > Can you try to increase the 2nd CF values' size and rerun the test?
>>> >
>>> >
>>> > On Mon, Apr 8, 2013 at 10:38 AM, James Taylor <jtaylor@salesforce.com
>>> >wrote:
>>> >
>>> >> In the TestJoinedScanners.java, is the 40% randomly distributed or
>>> >> sequential?
>>> >>
>>> >> In our test, the % is randomly distributed. Also, our custom filter
does
>>> >> the same thing that SingleColumnValueFilter does.  On the client-side,
>>> we'd
>>> >> execute the query in parallel, through multiple scans along the region
>>> >> boundaries. Would that have a negative impact on performance for this
>>> >> "essential column family" feature?
>>> >>
>>> >> Thanks,
>>> >>
>>> >>      James
>>> >>
>>> >>
>>> >> On 04/08/2013 10:10 AM, Anoop John wrote:
>>> >>
>>> >>> Agree here. The effectiveness depends on what % of data satisfies
the
>>> >>> condition, how it is distributed across HFile blocks. We will get
>>> >>> performance gain when the we will be able to skip some HFile blocks
>>> (from
>>> >>> non essential CFs). Can test with different HFile block size (lower
>>> >>> value)?
>>> >>>
>>> >>> -Anoop-
>>> >>>
>>> >>>
>>> >>> On Mon, Apr 8, 2013 at 8:19 PM, Ted Yu <yuzhihong@gmail.com>
wrote:
>>> >>>
>>> >>>   I made the following change in TestJoinedScanners.java:
>>> >>>> -      int flag_percent = 1;
>>> >>>> +      int flag_percent = 40;
>>> >>>>
>>> >>>> The test took longer but still favors joined scanner.
>>> >>>> I got some new results:
>>> >>>>
>>> >>>> 2013-04-08 07:46:06,959 INFO  [main] regionserver.**
>>> >>>> TestJoinedScanners(157):
>>> >>>> Slow scanner finished in 7.424388 seconds, got 2050 rows
>>> >>>> ...
>>> >>>> 2013-04-08 07:46:12,010 INFO  [main] regionserver.**
>>> >>>> TestJoinedScanners(157):
>>> >>>> Joined scanner finished in 5.05063 seconds, got 2050 rows
>>> >>>>
>>> >>>> 2013-04-08 07:46:18,358 INFO  [main] regionserver.**
>>> >>>> TestJoinedScanners(157):
>>> >>>> Slow scanner finished in 6.348517 seconds, got 2050 rows
>>> >>>> ...
>>> >>>> 2013-04-08 07:46:22,946 INFO  [main] regionserver.**
>>> >>>> TestJoinedScanners(157):
>>> >>>> Joined scanner finished in 4.587545 seconds, got 2050 rows
>>> >>>>
>>> >>>> Looks like effectiveness of joined scanner is affected by
>>> distribution of
>>> >>>> data.
>>> >>>>
>>> >>>> Cheers
>>> >>>>
>>> >>>> On Sun, Apr 7, 2013 at 8:52 PM, lars hofhansl <larsh@apache.org>
>>> wrote:
>>> >>>>
>>> >>>>   Looking at the joined scanner test code, it sets it up such
that 1%
>>> of
>>> >>>> the
>>> >>>>
>>> >>>>> rows match, which would somewhat be in line with James'
results.
>>> >>>>>
>>> >>>>> In my own testing a while ago I found a 100% improvement
with 0%
>>> match.
>>> >>>>>
>>> >>>>>
>>> >>>>> -- Lars
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>> ______________________________**__
>>> >>>>>    From: Ted Yu <yuzhihong@gmail.com>
>>> >>>>> To: user@hbase.apache.org
>>> >>>>> Sent: Sunday, April 7, 2013 4:13 PM
>>> >>>>> Subject: Re: Essential column family performance
>>> >>>>>
>>> >>>>> I have attached 5416-TestJoinedScanners-0.94.**txt to HBASE-5416
for
>>> >>>>> your
>>> >>>>> reference.
>>> >>>>>
>>> >>>>> On my MacBook, I got the following results from the test:
>>> >>>>>
>>> >>>>> 2013-04-07 16:08:17,474 INFO  [main]
>>> >>>>>
>>> >>>> regionserver.**TestJoinedScanners(157):
>>> >>>>
>>> >>>>> Slow scanner finished in 7.973822 seconds, got 100 rows
>>> >>>>> ...
>>> >>>>> 2013-04-07 16:08:17,946 INFO  [main]
>>> >>>>>
>>> >>>> regionserver.**TestJoinedScanners(157):
>>> >>>>
>>> >>>>> Joined scanner finished in 0.47235 seconds, got 100 rows
>>> >>>>>
>>> >>>>> Cheers
>>> >>>>>
>>> >>>>> On Sun, Apr 7, 2013 at 4:03 PM, Ted Yu <yuzhihong@gmail.com>
wrote:
>>> >>>>>
>>> >>>>>   Looking at
>>> >>>>>>  https://issues.apache.org/**jira/secure/attachment/**
>>> >>>> 12564340/5416-0.94-v3.txt<
>>> https://issues.apache.org/jira/secure/attachment/12564340/5416-0.94-v3.txt
>>> >
>>> >>>> ,
>>> >>>>
>>> >>>>> I found that it didn't contain TestJoinedScanners which
shows
>>> >>>>>
>>> >>>>>> difference in scanner performance:
>>> >>>>>>
>>> >>>>>>      LOG.info((slow ? "Slow" : "Joined") + " scanner
finished in " +
>>> >>>>>> Double.toString(timeSec)
>>> >>>>>>
>>> >>>>>>         + " seconds, got " + Long.toString(rows_count/2)
+ " rows");
>>> >>>>>>
>>> >>>>>> The test uses SingleColumnValueFilter:
>>> >>>>>>
>>> >>>>>>       SingleColumnValueFilter filter = new SingleColumnValueFilter(
>>> >>>>>>
>>> >>>>>>           cf_essential, col_name, CompareFilter.CompareOp.EQUAL,
>>> >>>>>>
>>> >>>>> flag_yes);
>>> >>>>> It is possible that the custom filter you were using would
exhibit
>>> >>>>>> different access pattern compared to SingleColumnValueFilter.
e.g.
>>> does
>>> >>>>>> your filter utilize hint ?
>>> >>>>>> It would be easier for me and other people to reproduce
the issue
>>> you
>>> >>>>>> experienced if you put your scenario in some test similar
to
>>> >>>>>> TestJoinedScanners.
>>> >>>>>>
>>> >>>>>> Will take a closer look at the code Monday.
>>> >>>>>>
>>> >>>>>> Cheers
>>> >>>>>>
>>> >>>>>> On Sun, Apr 7, 2013 at 11:37 AM, James Taylor <
>>> jtaylor@salesforce.com
>>> >>>>>> wrote:
>>> >>>>>>
>>> >>>>>>   Yes, on 0.94.6. We have our own custom filter derived
from
>>> FilterBase,
>>> >>>>>> so
>>> >>>>>> filterIfMissing isn't the issue - the results of the
scan are
>>> correct.
>>> >>>>>>> I can see that if the essential column family has
more data
>>> compared
>>> >>>>>>>
>>> >>>>>> to
>>> >>>>> the non essential column family that the results would eventually
>>> even
>>> >>>>>> out.
>>> >>>>>> I was hoping to always be able to enable the essential
column family
>>> >>>>>>> feature. Is there an inherent reason why performance
would degrade
>>> >>>>>>>
>>> >>>>>> like
>>> >>>>> this? Does it boil down to a single sequential scan versus
many
>>> seeks?
>>> >>>>>>> Thanks,
>>> >>>>>>>
>>> >>>>>>> James
>>> >>>>>>>
>>> >>>>>>>
>>> >>>>>>> On 04/07/2013 07:44 AM, Ted Yu wrote:
>>> >>>>>>>
>>> >>>>>>>   James:
>>> >>>>>>>> Your test was based on 0.94.6.1, right ?
>>> >>>>>>>>
>>> >>>>>>>> What Filter were you using ?
>>> >>>>>>>>
>>> >>>>>>>> If you used SingleColumnValueFilter, have you
seen my comment
>>> here ?
>>> >>>>>>>> https://issues.apache.org/****jira/browse/HBASE-5416?**<
>>> https://issues.apache.org/**jira/browse/HBASE-5416?**>
>>> >>>>>>>> focusedCommentId=13541229&****page=com.atlassian.jira.**
>>> >>>>>>>> plugin.system.issuetabpanels:****comment-tabpanel#comment-****
>>> >>>>>>>> 13541229<
>>> >>>>>>>>
>>> >>>>>>> https://issues.apache.org/**jira/browse/HBASE-5416?**
>>> >>>> focusedCommentId=13541229&**page=com.atlassian.jira.**
>>> >>>> plugin.system.issuetabpanels:**comment-tabpanel#comment-**13541229<
>>> https://issues.apache.org/jira/browse/HBASE-5416?focusedCommentId=13541229&page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel#comment-13541229
>>> >
>>> >>>>
>>> >>>>>   BTW the use case Max Lapan tried to address has non essential
>>> column
>>> >>>>>>>> family
>>> >>>>>>>> carrying considerably more data compared to
essential column
>>> family.
>>> >>>>>>>>
>>> >>>>>>>> Cheers
>>> >>>>>>>>
>>> >>>>>>>>
>>> >>>>>>>>
>>> >>>>>>>> On Sat, Apr 6, 2013 at 11:05 PM, James Taylor
<
>>> >>>>>>>>
>>> >>>>>>> jtaylor@salesforce.com
>>> >>>>>   wrote:
>>> >>>>>>>>    Hello,
>>> >>>>>>>>
>>> >>>>>>>>> We're doing some performance testing of
the essential column
>>> family
>>> >>>>>>>>> feature, and we're seeing some performance
degradation when
>>> >>>>>>>>>
>>> >>>>>>>> comparing
>>> >>>>>   with
>>> >>>>>>>>> and without the feature enabled:
>>> >>>>>>>>>
>>> >>>>>>>>>                              Performance
of scan relative
>>> >>>>>>>>> % of rows selected        to not enabling
the feature
>>> >>>>>>>>> ---------------------    ------------------------------******--
>>> >>>>>>>>>
>>> >>>>>>>>> 100%                            1.0x
>>> >>>>>>>>>     80%                            2.0x
>>> >>>>>>>>>     60%                            2.3x
>>> >>>>>>>>>     40%                            2.2x
>>> >>>>>>>>>     20%                            1.5x
>>> >>>>>>>>>     10%                            1.0x
>>> >>>>>>>>>      5%                            0.67x
>>> >>>>>>>>>      0%                            0.30%
>>> >>>>>>>>>
>>> >>>>>>>>> In our scenario, we have two column families.
The key value from
>>> the
>>> >>>>>>>>> essential column family is used in the filter,
while the key
>>> value
>>> >>>>>>>>>
>>> >>>>>>>> from
>>> >>>>>>   the
>>> >>>>>>>>> other, non essential column family is returned
by the scan. Each
>>> row
>>> >>>>>>>>> contains values for both key values, with
the values being
>>> >>>>>>>>>
>>> >>>>>>>> relatively
>>> >>>>>   narrow (less than 50 bytes). In this scenario, the only
time we're
>>> >>>>>>>>> seeing a
>>> >>>>>>>>> performance gain is when less than 10% of
the rows are selected.
>>> >>>>>>>>>
>>> >>>>>>>>> Is this a reasonable test? Has anyone else
measured this?
>>> >>>>>>>>>
>>> >>>>>>>>> Thanks,
>>> >>>>>>>>>
>>> >>>>>>>>> James
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>> >>>>>>>>>
>>>
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