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Add changelog & readme entries for #281

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explain the tradeoffs for the cache strategies based on this comment:

https://github.com/prometheus/statsd_exporter/pull/281#issuecomment-573103251

Signed-off-by: Matthias Rampke <mr@soundcloud.com>
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Matthias Rampke 2020-03-05 09:34:47 +00:00
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CHANGELOG.md
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@ -1,6 +1,7 @@
## 0.15.0 / unreleased ## 0.15.0 / unreleased
* [ENHANCEMENT] Allow setting granularity for summary metrics ([#290](https://github.com/prometheus/statsd_exporter/pull/290)) * [ENHANCEMENT] Allow setting granularity for summary metrics ([#290](https://github.com/prometheus/statsd_exporter/pull/290))
* [ENHANCEMENT] Support a random-replacement cache invalidation strategy ([#281](https://github.com/prometheus/statsd_exporter/pull/281)
To facilitate the expanded settings for summaries, the configuration format changes from To facilitate the expanded settings for summaries, the configuration format changes from

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README.md
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@ -431,10 +431,11 @@ There is a cache used to improve the performance of the metric mapping, that can
The cache has a default maximum of 1000 unique statsd metric names -> prometheus metrics mappings that it can store. The cache has a default maximum of 1000 unique statsd metric names -> prometheus metrics mappings that it can store.
This maximum can be adjust using the `statsd.cache-size` flag. This maximum can be adjust using the `statsd.cache-size` flag.
If the maximum is reached, entries are rotated using the [least recently used replacement policy](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)). If the maximum is reached, entries are by default rotated using the [least recently used replacement policy](https://en.wikipedia.org/wiki/Cache_replacement_policies#Least_recently_used_(LRU)). This strategy is optimal when memory is constrained as only the most recent entries are retained.
If you are using this exporter to reduce the cardinality of your data, a high maximum cache size can be a costly use of memory. Alternatively, you can choose a [random-replacement cache strategy](https://en.wikipedia.org/wiki/Cache_replacement_policies#Random_replacement_(RR)). This is less optimal if the cache is smaller than the cacheable set, but requires less locking. Use this for very high throughput, but make sure to allow for a cache that holds all metrics.
The optimal cache size is determined by the cardinality of the _incoming_ metrics.
### Time series expiration ### Time series expiration