This is great information. Thanks Bruno. Keep us posted if you find
anything more when you have your isolated tests done.

Regards
Ram

On Thu, Nov 5, 2020 at 10:36 PM Bruno Dumon <bru...@ngdata.com> wrote:

> Hi Ram,
>
> Sorry I missed your question. Yes, we do use addColumns.
>
> Specifically, we also query the Phoenix existence marker, which is a column
> named "_0", which is typically the last column in the row (we query this
> through custom scans, not through Phoenix). It does seem that reading the
> last column in the row does have an extra impact compared to HBase 1.2.
>
> I have been trying to further pin down our performance issues in an
> isolated test but I have not yet arrived at anything conclusive. I'll try
> to look into it further next week.
>
> I did also notice that HBase 2.x spends some more time iterating over the
> coprocessors, and we quite a few of those (19, some of those are from
> Phoenix, then some endpoint coprocessors and quite some region observers).
> We don't do anything in the pre/postScannerNext but still it consumes quite
> some time during scanning. Replacing all the region observer coprocessors
> by a single one does have a nice effect, 15-20% improvement, though I still
> need to test with a wider variety of queries.
>
>
> On Fri, Oct 30, 2020 at 2:46 PM ramkrishna vasudevan <
> ramkrishna.s.vasude...@gmail.com> wrote:
>
> > Hi Bruno/Jan
> >
> > Just a query here. I read your emails in this thread. One simple question
> > just to ensure if your tests were similar to Andrew's test. Did your scan
> > query have addColumns explicitly added covering all (or most of) the
> > columns in the rows?
> >
> > Regards
> > Ram
> >
> >
> >
> >
> > On Wed, Jul 15, 2020 at 7:02 AM Andrew Purtell <apurt...@apache.org>
> > wrote:
> >
> > > This is a good finding, nice work!
> > > I added a comment on HBASE-24742 that mentions HBASE-24637 on the off
> > > chance they are related, although I suspect more changes are implicated
> > by
> > > the 2.x regression.
> > >
> > > On Tue, Jul 14, 2020 at 5:53 PM Bharath Vissapragada <
> > bhara...@apache.org>
> > > wrote:
> > >
> > > > FYI, we filed this today
> > > https://issues.apache.org/jira/browse/HBASE-24742
> > > > .
> > > > We ran into a similar regression when upgrading from 1.3 based branch
> > to
> > > > 1.6 based branch. After some profiling and code analysis we narrowed
> > down
> > > > the code paths.
> > > >
> > > > On Tue, Jul 14, 2020 at 11:38 AM Josh Elser <els...@apache.org>
> wrote:
> > > >
> > > > > Wow. Great stuff, Andrew!
> > > > >
> > > > > Thank you for compiling and posting it all here. I can only imagine
> > how
> > > > > time-consuming this was.
> > > > >
> > > > > On 6/26/20 1:57 PM, Andrew Purtell wrote:
> > > > > > Hey Anoop, I opened
> > > https://issues.apache.org/jira/browse/HBASE-24637
> > > > > and
> > > > > > attached the patches and script used to make the comparison.
> > > > > >
> > > > > > On Fri, Jun 26, 2020 at 2:33 AM Anoop John <
> anoop.hb...@gmail.com>
> > > > > wrote:
> > > > > >
> > > > > >> Great investigation Andy.  Do you know any Jiras which made
> > changes
> > > in
> > > > > SQM?
> > > > > >> Would be great if you can attach your patch which tracks the
> scan
> > > > > flow.  If
> > > > > >> we have a Jira for this issue, can you pls attach?
> > > > > >>
> > > > > >> Anoop
> > > > > >>
> > > > > >> On Fri, Jun 26, 2020 at 1:56 AM Andrew Purtell <
> > > > > andrew.purt...@gmail.com>
> > > > > >> wrote:
> > > > > >>
> > > > > >>> Related, I think I found a bug in branch-1 where we don’t
> > heartbeat
> > > > in
> > > > > >> the
> > > > > >>> filter all case until we switch store files, so scanning a very
> > > large
> > > > > >> store
> > > > > >>> file might time out with client defaults. Remarking on this
> here
> > > so I
> > > > > >> don’t
> > > > > >>> forget to follow up.
> > > > > >>>
> > > > > >>>> On Jun 25, 2020, at 12:27 PM, Andrew Purtell <
> > apurt...@apache.org
> > > >
> > > > > >>> wrote:
> > > > > >>>>
> > > > > >>>> 
> > > > > >>>> I repeated this test with pe --filterAll and the results were
> > > > > >> revealing,
> > > > > >>> at least for this case. I also patched in thread local hash map
> > for
> > > > > >> atomic
> > > > > >>> counters that I could update from code paths in SQM,
> > StoreScanner,
> > > > > >>> HFileReader*, and HFileBlock. Because a RPC is processed by a
> > > single
> > > > > >>> handler thread I could update counters and accumulate
> > micro-timings
> > > > via
> > > > > >>> System#nanoTime() per RPC and dump them out of CallRunner in
> some
> > > new
> > > > > >> trace
> > > > > >>> logging. I spent a couple of days making sure the
> instrumentation
> > > was
> > > > > >>> placed equivalently in both 1.6 and 2.2 code bases and was
> > > producing
> > > > > >>> consistent results. I can provide these patches upon request.
> > > > > >>>>
> > > > > >>>> Again, test tables with one family and 1, 5, 10, 20, 50, and
> 100
> > > > > >>> distinct column-qualifiers per row. After loading the table I
> > made
> > > a
> > > > > >>> snapshot and cloned the snapshot for testing, for both 1.6 and
> > 2.2,
> > > > so
> > > > > >> both
> > > > > >>> versions were tested using the exact same data files on HDFS. I
> > > also
> > > > > used
> > > > > >>> the 1.6 version of PE for both, so the only change is on the
> > server
> > > > > (1.6
> > > > > >> vs
> > > > > >>> 2.2 masters and regionservers).
> > > > > >>>>
> > > > > >>>> It appears a refactor to ScanQueryMatcher and friends has
> > disabled
> > > > the
> > > > > >>> ability of filters to provide SKIP hints, which prevents us
> from
> > > > > >> bypassing
> > > > > >>> version checking (so some extra cost in SQM), and appears to
> > > disable
> > > > an
> > > > > >>> optimization that avoids reseeking, leading to a serious and
> > > > > proportional
> > > > > >>> regression in reseek activity and time spent in that code path.
> > So
> > > > for
> > > > > >>> queries that use filters, there can be a substantial
> regression.
> > > > > >>>>
> > > > > >>>> Other test cases that did not use filters did not show a
> > > regression.
> > > > > >>>>
> > > > > >>>> A test case where I used ROW_INDEX_V1 encoding showed an
> > expected
> > > > > >> modest
> > > > > >>> proportional regression in seeking time, due to the fact it is
> > > > > optimized
> > > > > >>> for point queries and not optimized for the full table scan
> case.
> > > > > >>>>
> > > > > >>>> I will come back here when I understand this better.
> > > > > >>>>
> > > > > >>>> Here are the results for the pe --filterAll case:
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> 1.6.0 c1      2.2.5 c1
> > > > > >>>> 1.6.0 c5      2.2.5 c5
> > > > > >>>> 1.6.0 c10     2.2.5 c10
> > > > > >>>> 1.6.0 c20     2.2.5 c20
> > > > > >>>> 1.6.0 c50     2.2.5 c50
> > > > > >>>> 1.6.0 c100    2.2.5 c100
> > > > > >>>> Counts
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>      (better heartbeating)
> > > > > >>>>      (better heartbeating)
> > > > > >>>>      (better heartbeating)
> > > > > >>>>      (better heartbeating)
> > > > > >>>>      (better heartbeating)
> > > > > >>>> rpcs  1       2       200%    2       6       300%    2
>  10
> > > > > >>> 500%    3       17      567%    4       37      925%    8
> >  72
> > > > > >> 900%
> > > > > >>>> block_reads   11507   11508   100%    57255   57257   100%
> > > 114471
> > > > > >>> 114474  100%    230372  230377  100%    578292  578298  100%
> > > > 1157955
> > > > > >>> 1157963 100%
> > > > > >>>> block_unpacks 11507   11508   100%    57255   57257   100%
> > > 114471
> > > > > >>> 114474  100%    230372  230377  100%    578292  578298  100%
> > > > 1157955
> > > > > >>> 1157963 100%
> > > > > >>>> seeker_next   10000000        10000000        100%    50000000
> > > > > >>> 50000000        100%    100000000       100000000       100%
> > > > > 200000000
> > > > > >>>       200000000       100%    500000000       500000000
> >  100%
> > > > > >>> 1000000000      1000000000      100%
> > > > > >>>> store_next    10000000        9988268 100%    50000000
> > > > 49940082
> > > > > >>>        100%    100000000       99879401        100%
> 200000000
> > > > > >>>   199766539       100%    500000000       499414653       100%
> > > > > >>> 1000000000      998836518       100%
> > > > > >>>> store_reseek  1       11733   > !     2       59924   > !
>  8
> > > > > >>>   120607  > !     6       233467  > !     10      585357  > !
> >  8
> > > > > >>>   1163490 > !
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> cells_matched 20000000        20000000        100%    60000000
> > > > > >>> 60000000        100%    110000000       110000000       100%
> > > > > 210000000
> > > > > >>>       210000000       100%    510000000       510000000
> >  100%
> > > > > >>> 1010000000      1010000000      100%
> > > > > >>>> column_hint_include   10000000        10000000        100%
> > > > 50000000
> > > > > >>>        50000000        100%    100000000       100000000
> >  100%
> > > > > >>> 200000000       200000000       100%    500000000
>  500000000
> > > > > >>>   100%    1000000000      1000000000      100%
> > > > > >>>> filter_hint_skip      10000000        10000000        100%
> > > > 50000000
> > > > > >>>        50000000        100%    100000000       100000000
> >  100%
> > > > > >>> 200000000       200000000       100%    500000000
>  500000000
> > > > > >>>   100%    1000000000      1000000000      100%
> > > > > >>>> sqm_hint_done 9999999 9999999 100%    9999998 9999998 100%
> > > > 9999998
> > > > > >>> 9999998 100%    9999997 9999997 100%    9999996 9999996 100%
> > > > 9999992
> > > > > >>> 9999992 100%
> > > > > >>>> sqm_hint_seek_next_col        1       0       0%      2
> > > >  40000002
> > > > > >>>        > !     2       90000002        > !     3
>  190000003
> > > > >  > !
> > > > > >>>     4       490000004       > !     8       990000008       > !
> > > > > >>>> sqm_hint_seek_next_row        0       10000000        > !
>  2
> > > > > >>>   10000000        > !     0       10000000        > !     0
> > > > >  10000000
> > > > > >>>        > !     0       10000000        > !     0       10000000
> > > > > > !
> > > > > >>>> sqm_hint_skip 10000000        0       0%      50000000
> 0
> > > > > >>>   0%      100000000       0       0%      200000000       0
> > >  0%
> > > > > >>> 500000000       0       0%      1000000000      0       0%
> > > > > >>>> versions_hint_include_and_seek_next_col       0       0
>  0%
> > > > > 0
> > > > > >>>       40000000        > !     0       90000000        > !     0
> > > > > >>>   190000000       > !     0       490000000       > !     0
> > > > > >>   990000000
> > > > > >>>       > !
> > > > > >>>> versions_hint_include_and_seek_next_row       0       0
>  0%
> > > > > 0
> > > > > >>>       10000000        > !     0       10000000        > !     0
> > > > > >>>   10000000        > !     0       10000000        > !     0
> > > > >  10000000
> > > > > >>>        > !
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> Times
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> block_read_ms 174.12  215.96  124%    683.78  883.02  129%
> > > > 1724.66
> > > > > >>> 1937.87 112%    3199.93 3470.92 108%    7582.96 7941.45 105%
> > > > > 14701.52
> > > > > >>>      16022.57        109%
> > > > > >>>> block_unpack_ms       0.63    0.62    99%     2.35    2.35
> > 100%
> > > > > >>> 4.36    4.56    105%    9.10    8.30    91%     21.59   22.01
> > >  102%
> > > > > >>> 40.97   40.93   100%
> > > > > >>>> seeker_next_ms        1073.45 1053.51 98%     4452.52 4728.96
> > 106%
> > > > > >>> 9359.61 9706.06 104%    18879.28        18330.93        97%
> > > > >  47664.95
> > > > > >>>      46404.26        97%     96511.83        92121.30
> 95%
> > > > > >>>> store_next_ms 2651.11 2423.27 91%     12048.64        11398.63
> > > > > >>> 95%     24833.68        23586.20        95%     48493.26
> > > > > 46574.38
> > > > > >>>      96%     120786.00       115603.00       96%     240627.00
> > > > > >>>   227945.00       95%
> > > > > >>>> store_reseek_ms       2.71    62.17   2297%   10.93   233.67
> > > 2139%
> > > > > >>>   10.88   401.88  3693%   13.98   783.18  5601%   22.26
>  1939.28
> > > > 8714%
> > > > > >>>   24.32   4065.25 16714%
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> Rows=10000000
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> ValueSize=20
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> BlockEncoding=FAST_DIFF
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> Compress=NONE
> > > > > >>>> Filter=ALL
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> On Thu, Jun 11, 2020 at 5:08 PM Andrew Purtell <
> > > apurt...@apache.org
> > > > >
> > > > > >>> wrote:
> > > > > >>>>> I used PE to generate 10M row tables with one family with
> > either
> > > 1,
> > > > > >> 10,
> > > > > >>> 20, 50, or 100 values per row (unique column-qualifiers). An
> > > increase
> > > > > in
> > > > > >>> wall clock time was noticeable, for example:
> > > > > >>>>>
> > > > > >>>>> 1.6.0
> > > > > >>>>>
> > > > > >>>>> time ./bin/hbase pe --rows=5000000 --table=TestTable_f1_c20
> > > > > >>> --columns=20 --nomapred scan 2
> > > > > >>>>> real 1m20.179s
> > > > > >>>>> user 0m45.470s
> > > > > >>>>> sys 0m16.572s
> > > > > >>>>>
> > > > > >>>>> 2.2.5
> > > > > >>>>>
> > > > > >>>>> time ./bin/hbase pe --rows=5000000 --table=TestTable_f1_c20
> > > > > >>> --columns=20 --nomapred scan 2
> > > > > >>>>> real 1m31.016s
> > > > > >>>>> user 0m48.658s
> > > > > >>>>> sys 0m16.965s
> > > > > >>>>>
> > > > > >>>>> It didnt really make a difference if I used 1 thread or 4 or
> > 10,
> > > > the
> > > > > >>> delta was about the same, proportionally. I picked two threads
> in
> > > the
> > > > > end
> > > > > >>> so I'd have enough time to launch async-profiler twice in
> another
> > > > > shell,
> > > > > >> to
> > > > > >>> capture flamegraph and call tree output, respectively.
> > > async-profiler
> > > > > >>> captured 10 seconds at steady state per test case. Upon first
> > > > > inspection
> > > > > >>> what jumps out is an increasing proportion of CPU time spent in
> > GC
> > > in
> > > > > >> 2.2.5
> > > > > >>> vs 1.6.0. The difference increases as the number of column
> > families
> > > > > >>> increase. There is little apparent difference at 1 column
> family,
> > > > but a
> > > > > >> 2x
> > > > > >>> or more difference at 20 columns, and a 10x or more difference
> at
> > > 100
> > > > > >>> columns, eyeballing the charts, flipping back and forth between
> > > > browser
> > > > > >>> windows. This seems more than coincidental but obviously calls
> > for
> > > > > >> capture
> > > > > >>> and analysis of GC trace, with JFR. Will do that next.
> > > > > >>>>>
> > > > > >>>>> JVM: openjdk version "1.8.0_232" OpenJDK Runtime Environment
> > > (Zulu
> > > > > >>> 8.42.0.21-CA-macosx) (build 1.8.0_232-b18) OpenJDK 64-Bit
> Server
> > VM
> > > > > (Zulu
> > > > > >>> 8.42.0.21-CA-macosx) (build 25.232-b18, mixed mode)
> > > > > >>>>>
> > > > > >>>>> Regionserver JVM flags: -Xms10g -Xmx10g -XX:+UseG1GC
> > > > > >>> -XX:+AlwaysPreTouch -XX:+UseNUMA -XX:-UseBiasedLocking
> > > > > >>> -XX:+ParallelRefProcEnabled
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>> On Thu, Jun 11, 2020 at 7:06 AM Jan Van Besien <
> > ja...@ngdata.com
> > > >
> > > > > >>> wrote:
> > > > > >>>>>> This is promising, thanks a lot. Testing with hbase 2.2.5
> > shows
> > > an
> > > > > >>>>>> improvement, but we're not there yet.
> > > > > >>>>>>
> > > > > >>>>>> As reported earlier, hbase 2.1.0 was about 60% slower than
> > hbase
> > > > > >> 1.2.0
> > > > > >>>>>> in a test that simply scans all the regions in parallel
> > without
> > > > any
> > > > > >>>>>> filter. A test with hbase 2.2.5 shows it to be about 40%
> > slower
> > > > than
> > > > > >>>>>> 1.2.0. So that is better than 2.1.0, but still substantially
> > > > slower
> > > > > >>>>>> than what hbase 1.2.0 was.
> > > > > >>>>>>
> > > > > >>>>>> As before, I tested this both on a 3 node cluster as well as
> > > with
> > > > a
> > > > > >>>>>> unit test using HBaseTestingUtility. Both tests show very
> > > similar
> > > > > >>>>>> relative differences.
> > > > > >>>>>>
> > > > > >>>>>> Jan
> > > > > >>>>>>
> > > > > >>>>>> On Thu, Jun 11, 2020 at 2:16 PM Anoop John <
> > > anoop.hb...@gmail.com
> > > > >
> > > > > >>> wrote:
> > > > > >>>>>>>
> > > > > >>>>>>> In another mail thread Zheng Hu brought up an important Jra
> > fix
> > > > > >>>>>>> https://issues.apache.org/jira/browse/HBASE-21657
> > > > > >>>>>>> Can u pls check with this once?
> > > > > >>>>>>>
> > > > > >>>>>>> Anoop
> > > > > >>>>>>>
> > > > > >>>>>>>
> > > > > >>>>>>> On Tue, Jun 9, 2020 at 8:08 PM Jan Van Besien <
> > > ja...@ngdata.com>
> > > > > >>> wrote:
> > > > > >>>>>>>
> > > > > >>>>>>>> On Sun, Jun 7, 2020 at 7:49 AM Anoop John <
> > > > anoop.hb...@gmail.com
> > > > > >>>
> > > > > >>> wrote:
> > > > > >>>>>>>>> As per the above configs, it looks like Bucket Cache is
> not
> > > > > >>> being used.
> > > > > >>>>>>>>> Only on heap LRU cache in use.
> > > > > >>>>>>>>
> > > > > >>>>>>>> True (but it is large enough to hold everything, so I
> don't
> > > > think
> > > > > >>> it
> > > > > >>>>>>>> matters).
> > > > > >>>>>>>>
> > > > > >>>>>>>>> @Jan - Is it possible for you to test with off heap
> Bucket
> > > > > >> Cache?
> > > > > >>>>>>>>   Config
> > > > > >>>>>>>>> bucket cache off heap mode with size ~7.5 GB
> > > > > >>>>>>>>
> > > > > >>>>>>>> I did a quick test but it seems not to make a measurable
> > > > > >>> difference.
> > > > > >>>>>>>> If anything, it is actually slightly slower even. I see
> 100%
> > > hit
> > > > > >>> ratio
> > > > > >>>>>>>> in the L1
> > > > > >>>>>>>> LruBlockCache and effectively also 100% in the L2
> > BucketCache
> > > > > >> (hit
> > > > > >>>>>>>> ratio is not yet at 100% but hits increase with every test
> > and
> > > > > >>> misses
> > > > > >>>>>>>> do not).
> > > > > >>>>>>>>
> > > > > >>>>>>>> Given that the LruBlockCache was already large enough to
> > cache
> > > > > >> all
> > > > > >>> the
> > > > > >>>>>>>> data anyway, I did not expect this to help either, to be
> > > honest.
> > > > > >>>>>>>>
> > > > > >>>>>>>>> Do you have any DataBlockEncoding enabled on the CF?
> > > > > >>>>>>>>
> > > > > >>>>>>>> Yes, FAST_DIFF. But this is of course true in both the
> tests
> > > > with
> > > > > >>>>>>>> hbase2 and hbase1.
> > > > > >>>>>>>>
> > > > > >>>>>>>> Jan
> > > > > >>>>>>>>
> > > > > >>>>>
> > > > > >>>>>
> > > > > >>>>> --
> > > > > >>>>> Best regards,
> > > > > >>>>> Andrew
> > > > > >>>>>
> > > > > >>>>> Words like orphans lost among the crosstalk, meaning torn
> from
> > > > > truth's
> > > > > >>> decrepit hands
> > > > > >>>>>     - A23, Crosstalk
> > > > > >>>>
> > > > > >>>>
> > > > > >>>> --
> > > > > >>>> Best regards,
> > > > > >>>> Andrew
> > > > > >>>>
> > > > > >>>> Words like orphans lost among the crosstalk, meaning torn from
> > > > truth's
> > > > > >>> decrepit hands
> > > > > >>>>     - A23, Crosstalk
> > > > > >>>
> > > > > >>
> > > > > >
> > > > > >
> > > > >
> > > >
> > >
> > >
> > > --
> > > Best regards,
> > > Andrew
> > >
> > > Words like orphans lost among the crosstalk, meaning torn from truth's
> > > decrepit hands
> > >    - A23, Crosstalk
> > >
> >
>
>
> --
> Bruno Dumon
> NGDATA
> http://www.ngdata.com/
>

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