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Implement Summary metric #40
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Glad that it is useful. ❤️
Would be good to support the Whoever is picking this up, let me know if you need any help. |
@mxinden hi i would like to work on this could you assign the issue to me? |
Done. Thanks @palash25. Let me know in case you need any help. |
hi @mxinden do you have any preference on what crate to use for the underlying quantile algorithm? I found one that implements CKMS would it be ok to use this? https://github.com/blt/quantiles |
@palash25 unfortunately I don't have any experience with quantile algorithms, neither in general nor in Rust. Thus no preference. Sorry.
Looks fine to me. |
hi @mxinden sorry for the multiple pings but can you please take a look at this #67 (comment) ? i updated the PR |
Hi! Thank your for the project :)
I found myself missing an implementation of the Summary metric, so decided to file an issue in case anyone (maybe myself) decides to contribute an implementation.
Open Metrics spec defines a metric type that computes quantiles locally on the client: Summary.
It's quite useful if you want to learn/discover how a system behaves, especially if you don't have much data a-priori. In that sense, Summary is dual to Histogram - both can be used to understand data distribution (e.g. latency data), but with different use-cases and tradeoffs.
Good overview on the differences between Summary and Histogram metrics is given in Prometheus doc https://prometheus.io/docs/practices/histograms/
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