2018-04-10 04:15:31 -04:00
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[[java-rest-high-rank-eval]]
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=== Ranking Evaluation API
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The `rankEval` method allows to evaluate the quality of ranked search
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results over a set of search request. Given sets of manually rated
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documents for each search request, ranking evaluation performs a
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<<java-rest-high-multi-search,multi search>> request and calculates
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information retrieval metrics like _mean reciprocal rank_, _precision_
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or _discounted cumulative gain_ on the returned results.
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[[java-rest-high-rank-eval-request]]
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==== Ranking Evaluation Request
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In order to build a `RankEvalRequest`, you first need to create an
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evaluation specification (`RankEvalSpec`). This specification requires
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to define the evaluation metric that is going to be calculated, as well
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as a list of rated documents per search requests. Creating the ranking
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evaluation request then takes the specification and a list of target
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indices as arguments:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests}/SearchDocumentationIT.java[rank-eval-request-basic]
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--------------------------------------------------
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<1> Define the metric used in the evaluation
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<2> Add rated documents, specified by index name, id and rating
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<3> Create the search query to evaluate
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<4> Combine the three former parts into a `RatedRequest`
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<5> Create the ranking evaluation specification
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<6> Create the ranking evaluation request
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[[java-rest-high-rank-eval-sync]]
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==== Synchronous Execution
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The `rankEval` method executes `RankEvalRequest`s synchronously:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests}/SearchDocumentationIT.java[rank-eval-execute]
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--------------------------------------------------
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[[java-rest-high-rank-eval-async]]
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==== Asynchronous Execution
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The `rankEvalAsync` method executes `RankEvalRequest`s asynchronously,
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calling the provided `ActionListener` when the response is ready.
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests}/SearchDocumentationIT.java[rank-eval-execute-async]
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--------------------------------------------------
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<1> The `RankEvalRequest` to execute and the `ActionListener` to use when
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the execution completes
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The asynchronous method does not block and returns immediately. Once it is
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completed the `ActionListener` is called back using the `onResponse` method
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if the execution successfully completed or using the `onFailure` method if
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it failed.
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A typical listener for `RankEvalResponse` looks like:
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests}/SearchDocumentationIT.java[rank-eval-execute-listener]
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--------------------------------------------------
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<1> Called when the execution is successfully completed.
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<2> Called when the whole `RankEvalRequest` fails.
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==== RankEvalResponse
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The `RankEvalResponse` that is returned by executing the request
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contains information about the overall evaluation score, the
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scores of each individual search request in the set of queries and
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detailed information about search hits and details about the metric
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calculation per partial result.
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["source","java",subs="attributes,callouts,macros"]
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--------------------------------------------------
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include-tagged::{doc-tests}/SearchDocumentationIT.java[rank-eval-response]
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--------------------------------------------------
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<1> The overall evaluation result
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<2> Partial results that are keyed by their query id
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<3> The metric score for each partial result
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<4> Rated search hits contain a fully fledged `SearchHit`
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2019-01-07 08:44:12 -05:00
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<5> Rated search hits also contain an `Optional<Integer>` rating that
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2018-04-10 04:15:31 -04:00
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is not present if the document did not get a rating in the request
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<6> Metric details are named after the metric used in the request
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<7> After casting to the metric used in the request, the
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metric details offers insight into parts of the metric calculation
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