github-vet / github-vet/rangeloop-pointer-findings
circonus-labs/irondb-prometheus-adapter: handlers/prometheus2_0.go; 37 LoC
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Description
Found a possible issue in [circonus-labs/irondb-prometheus-adapter](https://www.github.com/circonus-labs/irondb-prometheus-adapter) at [handlers/prometheus2_0.go](https://github.com/circonus-labs/irondb-prometheus-adapter/blob/aa026c9e0fcc3b5c2cc286df9ee1e3f64ec8296e/handlers/prometheus2_0.go#L274-L310)
Below is the message reported by the analyzer for this snippet of code. Beware that the analyzer only reports the first issue it finds, so please do not limit your consideration to the contents of the below message.
> range-loop variable v used in defer or goroutine at line 281
[Click here to see the code in its original context.](https://github.com/circonus-labs/irondb-prometheus-adapter/blob/aa026c9e0fcc3b5c2cc286df9ee1e3f64ec8296e/handlers/prometheus2_0.go#L274-L310)
Click here to show the 37 line(s) of Go which triggered the analyzer.
```go
for _, v := range tagResp {
wg.Add(1)
go func() {
defer wg.Done()
// for all of our tag responses, grab the rollups
start := time.Now()
values, err := snowthClient.ReadRollupValues(
node, prp.checkUUID.String(), v.MetricName, []string{}, step,
time.Unix(0, q.StartTimestampMs*int64(time.Millisecond)),
time.Unix(0, q.EndTimestampMs*int64(time.Millisecond)),
)
ctx.Logger().Warnf("timing rollup query: %s, %s, %d, %d, %d, result length: %d, duration: %v",
prp.checkUUID.String(), v.MetricName, int64(step), q.StartTimestampMs*int64(time.Millisecond),
q.EndTimestampMs*int64(time.Millisecond), len(values), time.Now().Sub(start))
ctx.Logger().Debugf("rollup results: %+v", values)
timeSeries := new(prompb.TimeSeries)
if err != nil {
ctx.Logger().Errorf("failed to read rollup: %s", err.Error())
tsChan <- timeSeries
return
}
timeSeries.Labels = metricNameToLabelPairs(v.MetricName)
for _, v := range values {
// convert value to time series
timeSeries.Samples = append(timeSeries.Samples,
&prompb.Sample{
Value: v.Value,
Timestamp: v.Timestamp * 1000, // prom does ms
})
}
// add the timeseries to the query result
tsChan <- timeSeries
}()
}
```
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See the descriptions of the classifications [here](https://github.com/github-vet/rangeclosure-findings#how-can-i-help) for more information.
commit ID: aa026c9e0fcc3b5c2cc286df9ee1e3f64ec8296e
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