Add back Windows CI, we lost it when tsdb was merged into the prometheus
repo. There's many tests failing outside tsdb, so only test tsdb for
now.
Fixes#6513
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
* Cleanup PromQL functions
The engine ensures, for Matrix functions, that functions are called with exactly one series at the time.
Therefore a lot of code can be inlined and we can directly assume the first element of the arguments exists and contains all the samples needed.
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
Add back Windows CI, we lost it when tsdb was merged into the prometheus
repo. There's many tests failing outside tsdb, so only test tsdb for
now.
Fixes#6513
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
strings.Compare isn't meant to be used, and this way we save one
comparison which is thus very slightly cheaper.
benchmark old ns/op new ns/op delta
BenchmarkPostingsForMatchers/Head/n="1"-4 236305440 233515705 -1.18%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
This function is only used in one place to format an error message when
encountering multiple matches on the "one" side of a
one-to-many/many-to-one vector match, which is probably why nobodoy has
noticed this before. The hashing is already done correctly and excludes
the metric name label when using the "ignoring" matching modifier.
Signed-off-by: Julius Volz <julius.volz@gmail.com>
The parser benchmarks called the `ParseMetric` function instead of the `ParseExpr` function, which resulted in parsing failing every time.
This means only the case of PromQL parser failure was benchmarked.
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
* Add parser method to produce errors messages about unexpected items
* PromQL: use parser.unexpected in generated parser
Signed-off-by: Tobias Guggenmos <tguggenm@redhat.com>
Also improves TestPopulateLabels: testutil.ErrorEqual just returned a
bool without failing the test.
Signed-off-by: Julien Pivotto <roidelapluie@inuits.eu>
Rather than buffer up symbols in RAM, do it one by one
during compaction. Then use the reader's symbol handling
for symbol lookups during the rest of the index write.
There is some slowdown in compaction, due to having to look through a file
rather than a hash lookup. This is noise to the overall cost of compacting
series with thousands of samples though.
benchmark old ns/op new ns/op delta
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 539917175 675341565 +25.08%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 2441815993 2477453524 +1.46%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 3978543559 3922909687 -1.40%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 8430219716 8586610007 +1.86%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 1786424591 1909552782 +6.89%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 5328998202 6020839950 +12.98%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 10085059958 11085278690 +9.92%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 25497010155 27018079806 +5.97%
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4 2427391406 2817217987 +16.06%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4 2592965497 2538805050 -2.09%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4 2437388343 2668012858 +9.46%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4 2317095324 2787423966 +20.30%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4 2600239857 2096973860 -19.35%
benchmark old allocs new allocs delta
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 500851 470794 -6.00%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 821527 791451 -3.66%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 1141562 1111508 -2.63%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 2141576 2111504 -1.40%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 871466 841424 -3.45%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 1941428 1911415 -1.55%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 3071573 3041510 -0.98%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 6771648 6741509 -0.45%
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4 731493 824888 +12.77%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4 793918 887311 +11.76%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4 811842 905204 +11.50%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4 832244 925081 +11.16%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4 921553 1019162 +10.59%
benchmark old bytes new bytes delta
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 40532648 35698276 -11.93%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 60340216 53409568 -11.49%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 81087336 72065552 -11.13%
BenchmarkCompaction/type=normal,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 142485576 120878544 -15.16%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=101-4 208661368 203831136 -2.31%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=1001-4 347345904 340484696 -1.98%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=2001-4 585185856 576244648 -1.53%
BenchmarkCompaction/type=vertical,blocks=4,series=10000,samplesPerSeriesPerBlock=5001-4 1357641792 1358966528 +0.10%
BenchmarkCompactionFromHead/labelnames=1,labelvalues=100000-4 126486664 119666744 -5.39%
BenchmarkCompactionFromHead/labelnames=10,labelvalues=10000-4 122323192 115117224 -5.89%
BenchmarkCompactionFromHead/labelnames=100,labelvalues=1000-4 126404504 119469864 -5.49%
BenchmarkCompactionFromHead/labelnames=1000,labelvalues=100-4 119047832 112230408 -5.73%
BenchmarkCompactionFromHead/labelnames=10000,labelvalues=10-4 136576016 116634800 -14.60%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
Rather than keeping the entire symbol table in memory, keep every nth
offset and walk from there to the entry we need. This ends up slightly
slower, ~360ms per 1M series returned from PostingsForMatchers which is
not much considering the rest of the CPU such a query would go on to
use.
Make LabelValues use the postings tables, rather than having
to do symbol lookups. Use yoloString, as PostingsForMatchers
doesn't need the strings to stick around and adjust the API
call to keep the Querier open until it's all marshalled.
Remove allocatedSymbols memory optimisation, we no longer keep all the
symbol strings in heap memory. Remove LabelValuesFor and LabelIndices,
they're dead code. Ensure we've still tests for label indices,
and add missing test that we can work with old V1 Format index files.
PostingForMatchers performance is slightly better, with a big drop in
allocation counts due to using yoloString for LabelValues:
benchmark old ns/op new ns/op delta
BenchmarkPostingsForMatchers/Block/n="1"-4 36698 36681 -0.05%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4 522786 560887 +7.29%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4 511652 537680 +5.09%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4 522102 564239 +8.07%
BenchmarkPostingsForMatchers/Block/i=~".*"-4 113689911 111795919 -1.67%
BenchmarkPostingsForMatchers/Block/i=~".+"-4 135825572 132871085 -2.18%
BenchmarkPostingsForMatchers/Block/i=~""-4 40782628 38038181 -6.73%
BenchmarkPostingsForMatchers/Block/i!=""-4 31267869 29194327 -6.63%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4 112733329 111568823 -1.03%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4 112868153 111232029 -1.45%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4 31338257 29349446 -6.35%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4 32054482 29972436 -6.50%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4 136504654 133968442 -1.86%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4 27960350 27264997 -2.49%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4 136765564 133860724 -2.12%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4 163714583 159453668 -2.60%
benchmark old allocs new allocs delta
BenchmarkPostingsForMatchers/Block/n="1"-4 6 6 +0.00%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4 11 11 +0.00%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4 11 11 +0.00%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4 17 15 -11.76%
BenchmarkPostingsForMatchers/Block/i=~".*"-4 100012 12 -99.99%
BenchmarkPostingsForMatchers/Block/i=~".+"-4 200040 100040 -49.99%
BenchmarkPostingsForMatchers/Block/i=~""-4 200045 100045 -49.99%
BenchmarkPostingsForMatchers/Block/i!=""-4 200041 100041 -49.99%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4 100017 17 -99.98%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4 100023 23 -99.98%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4 200046 100046 -49.99%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4 200050 100050 -49.99%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4 200049 100049 -49.99%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4 111150 11150 -89.97%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4 200055 100055 -49.99%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4 311238 111238 -64.26%
benchmark old bytes new bytes delta
BenchmarkPostingsForMatchers/Block/n="1"-4 296 296 +0.00%
BenchmarkPostingsForMatchers/Block/n="1",j="foo"-4 424 424 +0.00%
BenchmarkPostingsForMatchers/Block/j="foo",n="1"-4 424 424 +0.00%
BenchmarkPostingsForMatchers/Block/n="1",j!="foo"-4 552 1544 +179.71%
BenchmarkPostingsForMatchers/Block/i=~".*"-4 1600482 1606125 +0.35%
BenchmarkPostingsForMatchers/Block/i=~".+"-4 17259065 17264709 +0.03%
BenchmarkPostingsForMatchers/Block/i=~""-4 17259150 17264780 +0.03%
BenchmarkPostingsForMatchers/Block/i!=""-4 17259048 17264680 +0.03%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",j="foo"-4 1600610 1606242 +0.35%
BenchmarkPostingsForMatchers/Block/n="1",i=~".*",i!="2",j="foo"-4 1600813 1606434 +0.35%
BenchmarkPostingsForMatchers/Block/n="1",i!=""-4 17259176 17264808 +0.03%
BenchmarkPostingsForMatchers/Block/n="1",i!="",j="foo"-4 17259304 17264936 +0.03%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",j="foo"-4 17259333 17264965 +0.03%
BenchmarkPostingsForMatchers/Block/n="1",i=~"1.+",j="foo"-4 3142628 3148262 +0.18%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!="2",j="foo"-4 17259509 17265141 +0.03%
BenchmarkPostingsForMatchers/Block/n="1",i=~".+",i!~"2.*",j="foo"-4 20405680 20416944 +0.06%
However overall Select performance is down and involves more allocs, due to
having to do more than a simple map lookup to resolve a symbol and that all the strings
returned are allocated:
benchmark old ns/op new ns/op delta
BenchmarkQuerierSelect/Block/1of1000000-4 506092636 862678244 +70.46%
BenchmarkQuerierSelect/Block/10of1000000-4 505638968 860917636 +70.26%
BenchmarkQuerierSelect/Block/100of1000000-4 505229450 882150048 +74.60%
BenchmarkQuerierSelect/Block/1000of1000000-4 515905414 862241115 +67.13%
BenchmarkQuerierSelect/Block/10000of1000000-4 516785354 874841110 +69.29%
BenchmarkQuerierSelect/Block/100000of1000000-4 540742808 907030187 +67.74%
BenchmarkQuerierSelect/Block/1000000of1000000-4 815224288 1181236903 +44.90%
benchmark old allocs new allocs delta
BenchmarkQuerierSelect/Block/1of1000000-4 4000020 6000020 +50.00%
BenchmarkQuerierSelect/Block/10of1000000-4 4000038 6000038 +50.00%
BenchmarkQuerierSelect/Block/100of1000000-4 4000218 6000218 +50.00%
BenchmarkQuerierSelect/Block/1000of1000000-4 4002018 6002018 +49.97%
BenchmarkQuerierSelect/Block/10000of1000000-4 4020018 6020018 +49.75%
BenchmarkQuerierSelect/Block/100000of1000000-4 4200018 6200018 +47.62%
BenchmarkQuerierSelect/Block/1000000of1000000-4 6000018 8000019 +33.33%
benchmark old bytes new bytes delta
BenchmarkQuerierSelect/Block/1of1000000-4 176001468 227201476 +29.09%
BenchmarkQuerierSelect/Block/10of1000000-4 176002620 227202628 +29.09%
BenchmarkQuerierSelect/Block/100of1000000-4 176014140 227214148 +29.09%
BenchmarkQuerierSelect/Block/1000of1000000-4 176129340 227329348 +29.07%
BenchmarkQuerierSelect/Block/10000of1000000-4 177281340 228481348 +28.88%
BenchmarkQuerierSelect/Block/100000of1000000-4 188801340 240001348 +27.12%
BenchmarkQuerierSelect/Block/1000000of1000000-4 304001340 355201616 +16.84%
Signed-off-by: Brian Brazil <brian.brazil@robustperception.io>
