Commit graph

18 commits

Author SHA1 Message Date
Aliaksandr Valialkin
b7cc1af3eb
app/vmselect/promql/aggr_incremental.go: eliminate unnecessary memory allocation in incrementalAggrFuncContext.updateTimeseries 2024-01-23 02:29:13 +02:00
Aliaksandr Valialkin
9661918bb4
app/vmselect/promql: optimize repeated SLI-like instant queries with lookbehind windows >= 1d
Repeated instant queries with long lookbehind windows, which contain one of the following rollup functions,
are optimized via partial result caching:

- sum_over_time()
- count_over_time()
- avg_over_time()
- increase()
- rate()

The basic idea of optimization is to calculate

  rf(m[d] @ t)

as

  rf(m[offset] @ t) + rf(m[d] @ (t-offset)) - rf(m[offset] @ (t-d))

where rf(m[d] @ (t-offset)) is cached query result, which was calculated previously

The offset may be in the range of up to 1 hour.
2023-10-31 20:08:38 +01:00
Nikolay
4a50e9400c
app/vmselect: reduce lock contention for heavy aggregation requests ()
reduce lock contention for heavy aggregation requests
previously lock contetion may happen on machine with big number of CPU due to enabled string interning. sync.Map was a choke point for all aggregation requests.
Now instead of interning, new string is created. It may increase CPU and memory usage for some cases.
https://github.com/VictoriaMetrics/VictoriaMetrics/issues/5087
2023-10-10 13:44:02 +02:00
Aliaksandr Valialkin
18af01c387
app/vmselect: optimize incremental aggregates a bit
Substitute sync.Map with an ordinary slice indexed by workerID.
This should reduce the overhead when updating the incremental aggregate state
2023-03-20 15:42:13 -07:00
Aliaksandr Valialkin
c0de651558
app/vmselect/promql: intern output series names during incremental aggregation
This should reduce the number of memory allocations for repeated queries
2023-01-09 22:12:05 -08:00
Aliaksandr Valialkin
5497997b72
app/vmselect/promql: increase scalability of incremental aggregate calculations on systems with many CPU cores
Use sync.Map instead of a global mutex there. This should lift scalability limits
on systems with many CPU cores.
2022-10-01 20:14:14 +03:00
Aliaksandr Valialkin
9dccedc599 app/vmselect/promql: return empty values from group() if all the time series have no values at the given timestamp
This aligns `group()` behaviour to Prometheus
2020-07-28 13:41:04 +03:00
Aliaksandr Valialkin
eb402a17bd app/vmselect/promql: optimize group(rollup(m)) calculations 2020-07-17 16:47:30 +03:00
Aliaksandr Valialkin
f3d9a5b0ec app/vmselect/promql: suppress "SA4006: this value of dstValues is never used" error in golangci-lint 2020-05-13 11:46:05 +03:00
Aliaksandr Valialkin
18a0caee43 app/vmselect/promql: fix any(..) calculations - return all the data points instead of the first one 2020-05-12 20:36:49 +03:00
Aliaksandr Valialkin
408ade27a9 app/vmselect/promql: add any(x) by (y) aggregate function, which returns any time series from q for each group y 2020-05-12 19:50:29 +03:00
Aliaksandr Valialkin
21c2982ac8 app/vmselect/promql: support for sum(x) by (y) limit N syntax in order to limit the number of output time series after aggregation 2020-05-12 19:50:12 +03:00
Aliaksandr Valialkin
9ed4951ec8 lib/metricsql: move it to a separate repository - github.com/VictoriaMetrics/metrics 2020-04-28 15:30:06 +03:00
Aliaksandr Valialkin
453d71d082 Rename lib/promql to lib/metricsql and apply small fixes 2019-12-25 22:09:09 +02:00
Mike Poindexter
009d1559db Split Extended PromQL parsing to a separate library 2019-12-25 22:09:07 +02:00
Aliaksandr Valialkin
aac482517f app/vmselect/promql: return NaN from count() over zero time series
This aligns `count` behavior with Prometheus.
2019-07-25 22:02:34 +03:00
Aliaksandr Valialkin
6875fb411a app/vmselect/promql: parallelize incremental aggregation to multiple CPU cores
This may reduce response times for aggregation over big number of time series
with small step between output data points.
2019-07-12 15:53:12 +03:00
Aliaksandr Valialkin
cbab86fd9d app/vmselect/promql: reduce RAM usage for aggregates over big number of time series
Calculate incremental aggregates for `aggr(metric_selector)` function instead of
keeping all the time series matching the given `metric_selector` in memory.
2019-07-10 13:03:36 +03:00