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Revert "app/vmselect: add -search.estimatedSeriesCountAfterAggregation command-line flag for tuning the probability of OOMs or false-positive not enough memory errors"

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This reverts commit fbb7986dd2380fce2fc8633b7eda8b67f419e74c.

Reason for revert: this commit has been removed from single-node version
This commit is contained in:
Aliaksandr Valialkin 2020-05-12 19:47:33 +03:00
parent d54a93fc81
commit f341c6fcc4
1 changed files with 5 additions and 7 deletions
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12
app/vmselect/promql/eval.go
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@ -18,10 +18,7 @@ import (
)
var (
maxPointsPerTimeseries = flag.Int("search.maxPointsPerTimeseries", 30e3, "The maximum points per a single timeseries returned from the search")
estimatedSeriesCountAfterAggregation = flag.Int("search.estimatedSeriesCountAfterAggregation", 1000, "Estimated number of series returned by aggregation with grouping "+
"such as `sum(...) by (...)`. Increase this value in order to reduce the probability of OOMs. Reduce this value in order to reduce 'not enough memory' errors "+
"for queries containing aggregation with grouping")
maxPointsPerTimeseries = flag.Int("search.maxPointsPerTimeseries", 30e3, "The maximum points per a single timeseries returned from the search")
)
// The minimum number of points per timeseries for enabling time rounding.
@ -682,7 +679,8 @@ func evalRollupFuncWithMetricExpr(ec *EvalConfig, name string, rf rollupFunc,
if iafc.ae.Modifier.Op != "" {
// Increase the number of timeseries for non-empty group list: `aggr() by (something)`,
// since each group can have own set of time series in memory.
timeseriesLen *= *estimatedSeriesCountAfterAggregation
// Estimate the number of such groups is lower than 1000 :)
timeseriesLen *= 1000
}
}
rollupPoints := mulNoOverflow(pointsPerTimeseries, int64(timeseriesLen*len(rcs)))
@ -692,8 +690,8 @@ func evalRollupFuncWithMetricExpr(ec *EvalConfig, name string, rf rollupFunc,
rss.Cancel()
return nil, fmt.Errorf("not enough memory for processing %d data points across %d time series with %d points in each time series; "+
"possible solutions are: reducing the number of matching time series; switching to node with more RAM; "+
"increasing -memory.allowedPercent; increasing `step` query arg (%gs); reducing -search.estimatedSeriesCountAfterAggregation",
rollupPoints, timeseriesLen*len(rcs), pointsPerTimeseries, float64(ec.Step)/1e3)
"increasing -memory.allowedPercent; increasing `step` query arg (%gs)",
rollupPoints, rssLen*len(rcs), pointsPerTimeseries, float64(ec.Step)/1e3)
}
defer rml.Put(uint64(rollupMemorySize))