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This is an optimization on the existing append in OOOChunk. What we've been doing so far is find the place inside the out-of-order slice where the new sample should go in and then place it there and move any samples to the right if necessary. This is OK but requires a binary search every time the slice is bigger than 0. The optimization is opinionated and suggests that although out-of-order samples can be out-of-order amongst themselves they'll probably be in order thus we can probably optimistically append at the end and if not do the binary search. OOOChunks are capped to 30 samples by default so this is a small optimization but everything adds up, specially if you handle many active timeseries with out-of-order samples. Signed-off-by: Jesus Vazquez <jesus.vazquez@grafana.com> Signed-off-by: Jesus Vazquez <jesusvazquez@users.noreply.github.com> Co-authored-by: Ganesh Vernekar <ganeshvern@gmail.com> |
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agent | ||
chunkenc | ||
chunks | ||
docs | ||
encoding | ||
errors | ||
fileutil | ||
goversion | ||
index | ||
record | ||
test | ||
testdata | ||
tombstones | ||
tsdbutil | ||
wlog | ||
.gitignore | ||
block.go | ||
block_test.go | ||
blockwriter.go | ||
blockwriter_test.go | ||
CHANGELOG.md | ||
compact.go | ||
compact_test.go | ||
db.go | ||
db_test.go | ||
example_test.go | ||
exemplar.go | ||
exemplar_test.go | ||
head.go | ||
head_append.go | ||
head_bench_test.go | ||
head_read.go | ||
head_read_test.go | ||
head_test.go | ||
head_wal.go | ||
isolation.go | ||
isolation_test.go | ||
mocks_test.go | ||
ooo_head.go | ||
ooo_head_read.go | ||
ooo_head_read_test.go | ||
ooo_head_test.go | ||
querier.go | ||
querier_bench_test.go | ||
querier_test.go | ||
README.md | ||
repair.go | ||
repair_test.go | ||
tsdbblockutil.go | ||
wal.go | ||
wal_test.go |
TSDB
This directory contains the Prometheus TSDB (Time Series DataBase) library, which handles storage and querying of all Prometheus v2 data.
Documentation
External resources
- A writeup of the original design can be found here.
- Video: Storing 16 Bytes at Scale from PromCon 2017.
- Compression is based on the Gorilla TSDB white paper.
A series of blog posts explaining different components of TSDB: