Extend WriteMetricsTransform in Ingestion to write feature value stats to StatsD #486
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: davidheryanto The full list of commands accepted by this bot can be found here. The pull request process is described here
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ingestion/src/main/java/feast/ingestion/options/ImportOptions.java
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ingestion/src/main/java/feast/ingestion/transform/metrics/WriteFeatureValueMetricsDoFn.java
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Since there are other exception like UnknownHostException that can be thrown and we want to know such error. Also change the log level to error because so it's not normal for client to fail to be created"
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…warn) On 2nd thought, this should constitute an error not a warning
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…s to StatsD (feast-dev#486) * Extend WriteMetricsTransform to write feature value stats to StatsD * Apply mvn spotless * Catch all exception not just StatsDClientException during init Since there are other exception like UnknownHostException that can be thrown and we want to know such error. Also change the log level to error because so it's not normal for client to fail to be created" * Change log level due to invalid feature set ref to error (previously warn) On 2nd thought, this should constitute an error not a warning * Apply maven spotless to metric transform codes (cherry picked from commit 5508c92)
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…s to StatsD (#486) * Extend WriteMetricsTransform to write feature value stats to StatsD * Apply mvn spotless * Catch all exception not just StatsDClientException during init Since there are other exception like UnknownHostException that can be thrown and we want to know such error. Also change the log level to error because so it's not normal for client to fail to be created" * Change log level due to invalid feature set ref to error (previously warn) On 2nd thought, this should constitute an error not a warning * Apply maven spotless to metric transform codes (cherry picked from commit 5508c92)
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What this PR does / why we need it:
This PR adds a step (blue coloured box) to write stats for numerical value of every feature to StatsD.
A fixed window (default to 30s) will first be applied, before the stats calculation of each feature. This is to ensure the metrics collector is not overwhelmed with metrics data (and drop the metrics as a result). For validation of features by value, an aggregated windowed view of the values is also usually adequate.
The following
gaugemetrics will be sent to StatsD for every feature at the end of the window:Which issue(s) this PR fixes:
Related to #172
Does this PR introduce a user-facing change?: