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docs/MetricsQL.md: add missing whitespace

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Aliaksandr Valialkin 2020-11-02 23:49:38 +02:00
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@ -112,7 +112,8 @@ This functionality can be tried at [an editable Grafana dashboard](http://play-g
- `bottomk_min(k, q)` - returns bottom K time series with the min minimums on the given time range - `bottomk_min(k, q)` - returns bottom K time series with the min minimums on the given time range
- `bottomk_max(k, q)` - returns bottom K time series with the min maximums on the given time range - `bottomk_max(k, q)` - returns bottom K time series with the min maximums on the given time range
- `bottomk_avg(k, q)` - returns bottom K time series with the min averages on the given time range - `bottomk_avg(k, q)` - returns bottom K time series with the min averages on the given time range
- `bottomk_median(k, q)` - returns bottom K time series with the min medians on the given time range - `bottomk_median(k, q)` - returns bottom K time series with the min medians on the given time range.
All the `topk_*` and `bottomk_*` functions accept optional third argument - label name for the sum of the remaining time series outside top K or bottom K time series. For example, `topk_max(3, process_resident_memory_bytes, "remaining_sum")` would return up to 3 time series with the maximum value for `process_resident_memory_bytes` plus fourth time series with the sum of the remaining time series if any. The fourth time series will contain `remaining_sum="remaining_sum"` additional label. All the `topk_*` and `bottomk_*` functions accept optional third argument - label name for the sum of the remaining time series outside top K or bottom K time series. For example, `topk_max(3, process_resident_memory_bytes, "remaining_sum")` would return up to 3 time series with the maximum value for `process_resident_memory_bytes` plus fourth time series with the sum of the remaining time series if any. The fourth time series will contain `remaining_sum="remaining_sum"` additional label.
- `share_le_over_time(m[d], le)` - returns share (in the range 0..1) of values in `m` over `d`, which are smaller or equal to `le`. Useful for calculating SLI and SLO. - `share_le_over_time(m[d], le)` - returns share (in the range 0..1) of values in `m` over `d`, which are smaller or equal to `le`. Useful for calculating SLI and SLO.
Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns the share of time series values for the last 24 hours when memory usage was below or equal to 100MB. Example: `share_le_over_time(memory_usage_bytes[24h], 100*1024*1024)` returns the share of time series values for the last 24 hours when memory usage was below or equal to 100MB.