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8 commits

Author SHA1 Message Date
Ganesh Vernekar ee7e0071d1
Snapshot in-memory chunks on shutdown for faster restarts (#7229)
Signed-off-by: Ganesh Vernekar <ganeshvern@gmail.com>
2021-08-06 17:51:01 +01:00
Bryan Boreham dea37853d9
tsdb: use dennwc/varint to speed up WAL decoding (#9106)
* tsdb: use dennwc/varint to speed up decoding

This is a tiny library, MIT-licensed, which unrolls the loop to go
about twice as fast.

Needed to copy the sign-inverting logic inline, previously provided by
the `binary` package.

Signed-off-by: Bryan Boreham <bjboreham@gmail.com>

* More comments to explain varint decoding

Signed-off-by: Bryan Boreham <bjboreham@gmail.com>
2021-07-27 10:02:57 +05:30
Brian Brazil cf76daed2f Avoid WriteAt for Postings.
Flushing buffers and doing a pwrite per posting is expensive
time wise, so go back to the old way for those. This doubles
our memory usage, but that's still small as it's only
~8 bytes per time series in the index. This is 30-40% faster.

benchmark                                                         old ns/op      new ns/op     delta
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4     1101429174     724362123     -34.23%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4     1074466374     720977022     -32.90%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4     1166510282     677702636     -41.90%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4     1075013071     696855960     -35.18%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4     1231673790     829328610     -32.67%

benchmark                                                         old allocs     new allocs     delta
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4     832571         731435         -12.15%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4     894875         793823         -11.29%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4     912931         811804         -11.08%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4     933511         832366         -10.83%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4     1022791        921554         -9.90%

benchmark                                                         old bytes     new bytes     delta
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4     129063496     126472364     -2.01%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4     124154888     122300764     -1.49%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4     128790648     126394856     -1.86%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4     120570696     118946548     -1.35%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4     138754288     136317432     -1.76%

Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
2019-12-16 15:30:49 +00:00
Brian Brazil 971dafdfbe Coalesce series reads where we can.
When compacting rather than doing a read of all
series in the index per label name, do many at once
but only when it won't use (much) more ram than writing the
special all index does.

original in-memory postings:
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4                  1        1202383447 ns/op        158936496 B/op   1031511 allocs/op
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4                  1        1141792706 ns/op        154453408 B/op   1093453 allocs/op
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4                  1        1169288829 ns/op        161072336 B/op   1110021 allocs/op
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4                  1        1115700103 ns/op        149480472 B/op   1129180 allocs/op
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4                  1        1283813141 ns/op        162937800 B/op   1202771 allocs/op

before:
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4                  1        1145195941 ns/op        131749984 B/op    834400 allocs/op
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4                  1        1233526345 ns/op        127889416 B/op    897033 allocs/op
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4                  1        1821942296 ns/op        131665648 B/op    914836 allocs/op
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4                  1        8035568665 ns/op        123811832 B/op    934312 allocs/op
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4                  1       71325926267 ns/op        140722648 B/op   1016824 allocs/op

after:
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4                  1        1101429174 ns/op        129063496 B/op    832571 allocs/op
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4                  1        1074466374 ns/op        124154888 B/op    894875 allocs/op
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4                  1        1166510282 ns/op        128790648 B/op    912931 allocs/op
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4                  1        1075013071 ns/op        120570696 B/op    933511 allocs/op
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4                  1        1231673790 ns/op        138754288 B/op   1022791 allocs/op

Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
2019-12-12 08:38:14 +00:00
Brian Brazil 373a1fdfbf Reread index series rather than storing in memory.
Rather than building up a 2nd copy of all the posting
tables, construct it from the data we've already written
to disk. This takes more time, but saves memory.

Current benchmark numbers have this as slightly faster, but that's
likely due to the synthetic data not having many label names.
Memory usage is roughly halved for the relevant bits.

Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
2019-12-11 22:23:39 +00:00
Brian Brazil 48d25e6fe7 Reduce memory used by postings offset table.
Rather than keeping the offset of each postings list, instead
keep the nth offset of the offset of the posting list. As postings
list offsets have always been sorted, we can then get to the closest
entry before the one we want an iterate forwards.

I haven't done much tuning on the 32 number, it was chosen to try
not to read through more than a 4k page of data.

Switch to a bulk interface for fetching postings. Use it to avoid having
to re-read parts of the posting offset table when querying lots of it.

For a index with what BenchmarkHeadPostingForMatchers uses RAM
for r.postings drops from 3.79MB to 80.19kB or about 48x.
Bytes allocated go down by 30%, and suprisingly CPU usage drops by
4-6% for typical queries too.

benchmark                                                               old ns/op      new ns/op      delta
BenchmarkPostingsForMatchers/Block/n="1"-4                              35231          36673          +4.09%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4                      563380         540627         -4.04%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4                      536782         534186         -0.48%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4                     533990         541550         +1.42%
BenchmarkPostingsForMatchers/Block/i=~".*"-4                            113374598      117969608      +4.05%
BenchmarkPostingsForMatchers/Block/i=~".+"-4                            146329884      139651442      -4.56%
BenchmarkPostingsForMatchers/Block/i=~""-4                              50346510       44961127       -10.70%
BenchmarkPostingsForMatchers/Block/i!=""-4                              41261550       35356165       -14.31%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4              112544418      116904010      +3.87%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4       112487086      116864918      +3.89%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4                        41094758       35457904       -13.72%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4                41906372       36151473       -13.73%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4              147262414      140424800      -4.64%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4             28615629       27872072       -2.60%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4       147117177      140462403      -4.52%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4     175096826      167902298      -4.11%

benchmark                                                               old allocs     new allocs     delta
BenchmarkPostingsForMatchers/Block/n="1"-4                              4              6              +50.00%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4                      7              11             +57.14%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4                      7              11             +57.14%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4                     15             17             +13.33%
BenchmarkPostingsForMatchers/Block/i=~".*"-4                            100010         100012         +0.00%
BenchmarkPostingsForMatchers/Block/i=~".+"-4                            200069         200040         -0.01%
BenchmarkPostingsForMatchers/Block/i=~""-4                              200072         200045         -0.01%
BenchmarkPostingsForMatchers/Block/i!=""-4                              200070         200041         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4              100013         100017         +0.00%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4       100017         100023         +0.01%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4                        200073         200046         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4                200075         200050         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4              200074         200049         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4             111165         111150         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4       200078         200055         -0.01%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4     311282         311238         -0.01%

benchmark                                                               old bytes     new bytes     delta
BenchmarkPostingsForMatchers/Block/n="1"-4                              264           296           +12.12%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4                      360           424           +17.78%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4                      360           424           +17.78%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4                     520           552           +6.15%
BenchmarkPostingsForMatchers/Block/i=~".*"-4                            1600461       1600482       +0.00%
BenchmarkPostingsForMatchers/Block/i=~".+"-4                            24900801      17259077      -30.69%
BenchmarkPostingsForMatchers/Block/i=~""-4                              24900836      17259151      -30.69%
BenchmarkPostingsForMatchers/Block/i!=""-4                              24900760      17259048      -30.69%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4              1600557       1600621       +0.00%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4       1600717       1600813       +0.01%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4                        24900856      17259176      -30.69%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4                24900952      17259304      -30.69%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4              24900993      17259333      -30.69%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4             3788311       3142630       -17.04%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4       24901137      17259509      -30.69%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4     28693086      20405680      -28.88%

Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
2019-12-11 19:59:31 +00:00
Brian Brazil 4df814f509
Don't buffer up tables in memory on compaction. (#6422)
We can instead write it as we go, and then go back and write in the
length at the end.

Also fix the compaction benchmark, which indicates no changes.

For the benchmark, this brings maximum memory usage of the buffers 
from ~200kB down to 128B.

Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
2019-12-11 12:49:13 +00:00
Ganesh Vernekar 7cf09b0395
Moving tsdb into its own subdirectory
Signed-off-by: Ganesh Vernekar <cs15btech11018@iith.ac.in>
2019-08-13 13:58:49 +05:30
Renamed from encoding/encoding.go (Browse further)