Add tests for ranking evaluation with aliases (#29452)
The ranking evaluation requests so far were not tested against aliases but they should run regardless of the targeted index is a real index or an alias. This change adds cases for this to the integration and rest tests.
This commit is contained in:
Christoph Büscher
GitHub
parent
24763d881e
commit
d0f6657d90
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@ -20,6 +20,7 @@
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package org.elasticsearch.index.rankeval;
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import org.elasticsearch.ElasticsearchException;
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import org.elasticsearch.action.admin.indices.alias.IndicesAliasesRequest.AliasActions;
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import org.elasticsearch.action.search.SearchRequest;
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import org.elasticsearch.action.support.IndicesOptions;
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import org.elasticsearch.index.IndexNotFoundException;
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@ -40,10 +41,13 @@ import java.util.Map.Entry;
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import java.util.Set;
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import static org.elasticsearch.index.rankeval.EvaluationMetric.filterUnknownDocuments;
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import static org.elasticsearch.test.hamcrest.ElasticsearchAssertions.assertAcked;
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import static org.hamcrest.Matchers.instanceOf;
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public class RankEvalRequestIT extends ESIntegTestCase {
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private static final String TEST_INDEX = "test";
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private static final String INDEX_ALIAS = "alias0";
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private static final int RELEVANT_RATING_1 = 1;
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@Override
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@ -58,20 +62,23 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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@Before
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public void setup() {
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createIndex("test");
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createIndex(TEST_INDEX);
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ensureGreen();
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client().prepareIndex("test", "testtype").setId("1")
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client().prepareIndex(TEST_INDEX, "testtype").setId("1")
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.setSource("text", "berlin", "title", "Berlin, Germany", "population", 3670622).get();
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client().prepareIndex("test", "testtype").setId("2").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex("test", "testtype").setId("3").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex("test", "testtype").setId("4").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex("test", "testtype").setId("5").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex("test", "testtype").setId("6").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex(TEST_INDEX, "testtype").setId("2").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex(TEST_INDEX, "testtype").setId("3").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex(TEST_INDEX, "testtype").setId("4").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex(TEST_INDEX, "testtype").setId("5").setSource("text", "amsterdam", "population", 851573).get();
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client().prepareIndex(TEST_INDEX, "testtype").setId("6").setSource("text", "amsterdam", "population", 851573).get();
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// add another index for testing closed indices etc...
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client().prepareIndex("test2", "testtype").setId("7").setSource("text", "amsterdam", "population", 851573).get();
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refresh();
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// set up an alias that can also be used in tests
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assertAcked(client().admin().indices().prepareAliases().addAliasAction(AliasActions.add().index(TEST_INDEX).alias(INDEX_ALIAS)));
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}
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/**
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@ -101,7 +108,8 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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RankEvalAction.INSTANCE, new RankEvalRequest());
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builder.setRankEvalSpec(task);
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, builder.request().indices("test"))
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String indexToUse = randomBoolean() ? TEST_INDEX : INDEX_ALIAS;
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, builder.request().indices(indexToUse))
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.actionGet();
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// the expected Prec@ for the first query is 4/6 and the expected Prec@ for the
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// second is 1/6, divided by 2 to get the average
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@ -143,7 +151,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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metric = new PrecisionAtK(1, false, 3);
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task = new RankEvalSpec(specifications, metric);
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { "test" }));
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { TEST_INDEX }));
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response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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// if we look only at top 3 documente, the expected P@3 for the first query is
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@ -163,19 +171,19 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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List<RatedRequest> specifications = new ArrayList<>();
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List<RatedDocument> ratedDocs = Arrays.asList(
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new RatedDocument("test", "1", 3),
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new RatedDocument("test", "2", 2),
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new RatedDocument("test", "3", 3),
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new RatedDocument("test", "4", 0),
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new RatedDocument("test", "5", 1),
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new RatedDocument("test", "6", 2));
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new RatedDocument(TEST_INDEX, "1", 3),
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new RatedDocument(TEST_INDEX, "2", 2),
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new RatedDocument(TEST_INDEX, "3", 3),
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new RatedDocument(TEST_INDEX, "4", 0),
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new RatedDocument(TEST_INDEX, "5", 1),
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new RatedDocument(TEST_INDEX, "6", 2));
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specifications.add(new RatedRequest("amsterdam_query", ratedDocs, testQuery));
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DiscountedCumulativeGain metric = new DiscountedCumulativeGain(false, null, 10);
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RankEvalSpec task = new RankEvalSpec(specifications, metric);
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RankEvalRequestBuilder builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE,
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new RankEvalRequest(task, new String[] { "test" }));
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new RankEvalRequest(task, new String[] { TEST_INDEX }));
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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assertEquals(DiscountedCumulativeGainTests.EXPECTED_DCG, response.getEvaluationResult(), 10E-14);
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@ -184,7 +192,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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metric = new DiscountedCumulativeGain(false, null, 3);
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task = new RankEvalSpec(specifications, metric);
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { "test" }));
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { TEST_INDEX }));
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response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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assertEquals(12.39278926071437, response.getEvaluationResult(), 10E-14);
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@ -203,7 +211,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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RankEvalSpec task = new RankEvalSpec(specifications, metric);
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RankEvalRequestBuilder builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE,
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new RankEvalRequest(task, new String[] { "test" }));
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new RankEvalRequest(task, new String[] { TEST_INDEX }));
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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// the expected reciprocal rank for the amsterdam_query is 1/5
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@ -216,7 +224,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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metric = new MeanReciprocalRank(1, 3);
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task = new RankEvalSpec(specifications, metric);
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { "test" }));
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builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE, new RankEvalRequest(task, new String[] { TEST_INDEX }));
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response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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// limiting to top 3 results, the amsterdam_query has no relevant document in it
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@ -247,7 +255,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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RankEvalSpec task = new RankEvalSpec(specifications, new PrecisionAtK());
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RankEvalRequestBuilder builder = new RankEvalRequestBuilder(client(), RankEvalAction.INSTANCE,
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new RankEvalRequest(task, new String[] { "test" }));
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new RankEvalRequest(task, new String[] { TEST_INDEX }));
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builder.setRankEvalSpec(task);
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, builder.request()).actionGet();
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@ -267,7 +275,7 @@ public class RankEvalRequestIT extends ESIntegTestCase {
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specifications.add(new RatedRequest("amsterdam_query", relevantDocs, amsterdamQuery));
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RankEvalSpec task = new RankEvalSpec(specifications, new PrecisionAtK());
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RankEvalRequest request = new RankEvalRequest(task, new String[] { "test", "test2" });
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RankEvalRequest request = new RankEvalRequest(task, new String[] { TEST_INDEX, "test2" });
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request.setRankEvalSpec(task);
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RankEvalResponse response = client().execute(RankEvalAction.INSTANCE, request).actionGet();
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@ -1,10 +1,4 @@
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---
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"Response format":
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- skip:
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version: " - 6.2.99"
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reason: response format was updated in 6.3
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setup:
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- do:
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indices.create:
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index: foo
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@ -43,8 +37,21 @@
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- do:
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indices.refresh: {}
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- do:
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indices.put_alias:
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index: foo
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name: alias
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---
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"Response format":
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- skip:
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version: " - 6.2.99"
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reason: response format was updated in 6.3
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- do:
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rank_eval:
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index: foo,
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body: {
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"requests" : [
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{
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@ -84,7 +91,36 @@
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- match: { details.berlin_query.hits.0.hit._id: "doc1" }
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- match: { details.berlin_query.hits.0.rating: 1}
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- match: { details.berlin_query.hits.1.hit._id: "doc4" }
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- is_false: details.berlin_query.hits.1.rating
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- is_false: details.berlin_query.hits.1.rating
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---
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"Alias resolution":
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- do:
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rank_eval:
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index: alias
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body: {
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"requests" : [
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{
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"id": "amsterdam_query",
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"request": { "query": { "match" : {"text" : "amsterdam" }}},
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"ratings": [
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{"_index": "foo", "_id": "doc1", "rating": 0},
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{"_index": "foo", "_id": "doc2", "rating": 1},
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{"_index": "foo", "_id": "doc3", "rating": 1}]
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},
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{
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"id" : "berlin_query",
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"request": { "query": { "match" : { "text" : "berlin" } }, "size" : 10 },
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"ratings": [{"_index": "foo", "_id": "doc1", "rating": 1}]
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}
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],
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"metric" : { "precision": { "ignore_unlabeled" : true }}
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}
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- match: { quality_level: 1}
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- match: { details.amsterdam_query.quality_level: 1.0}
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- match: { details.berlin_query.quality_level: 1.0}
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---
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"Mean Reciprocal Rank":
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@ -93,44 +129,6 @@
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version: " - 6.2.99"
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reason: response format was updated in 6.3
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- do:
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indices.create:
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index: foo
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body:
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settings:
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index:
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number_of_shards: 1
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- do:
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index:
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index: foo
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type: bar
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id: doc1
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body: { "text": "berlin" }
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- do:
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index:
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index: foo
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type: bar
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id: doc2
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body: { "text": "amsterdam" }
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- do:
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index:
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index: foo
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type: bar
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id: doc3
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body: { "text": "amsterdam" }
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- do:
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index:
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index: foo
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type: bar
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id: doc4
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body: { "text": "something about amsterdam and berlin" }
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- do:
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indices.refresh: {}
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- do:
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rank_eval:
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body: {
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