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https://issues.apache.org/jira/browse/PIO-115?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16137419#comment-16137419
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ASF GitHub Bot commented on PIO-115:
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Github user mars commented on the issue:
https://github.com/apache/incubator-predictionio/pull/424
Thanks for your feedback @dszeto. I've addressed the code style & JIRA
issue.
> Cache name-to-ID lookups for Storage app & channel
> --------------------------------------------------
>
> Key: PIO-115
> URL: https://issues.apache.org/jira/browse/PIO-115
> Project: PredictionIO
> Issue Type: Improvement
> Components: Core
> Affects Versions: 0.11.0-incubating
> Reporter: Mars Hall
> Assignee: Mars Hall
>
> When stress testing the Universal Recommender with high-concurrency HTTP/REST
> queries, we observed that Elasticsearch traffic was majority composed of
> requests resolving the Storage app's name & channel, over and over and over
> again! In this case, [each per-query call to
> `LEventStore.findByEntity`|https://github.com/heroku/predictionio-engine-ur/blob/master/src/main/scala/URAlgorithm.scala#L694]
> re-resolves the app name to an ID.
> This changeset implements memoization for the function that performs these
> name-to-ID lookups, so that only one set of lookups is performed per process
> for each app+channel combination. As a result, we've seen overall throughput
> increase 📈 and error rate drop dramatically 📉.
> This common optimization effects all storage backends, not just Elasticsearch.
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