Rename the inference rescorer into learn_to_rank

afoucret · Nov 23, 2023 · 2113447 · 2113447
1 parent 99cacab
commit 2113447
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Showing 21 changed files with 512 additions and 488 deletions.
diff --git a/x-pack/plugin/core/src/main/java/module-info.java b/x-pack/plugin/core/src/main/java/module-info.java
@@ -223,6 +223,7 @@
     exports org.elasticsearch.xpack.core.watcher.trigger;
     exports org.elasticsearch.xpack.core.watcher.watch;
     exports org.elasticsearch.xpack.core.watcher;
+    exports org.elasticsearch.xpack.core.ml.ltr;
 
     provides org.elasticsearch.action.admin.cluster.node.info.ComponentVersionNumber
         with

diff --git a/...inference/MlLTRNamedXContentProvider.java → ...re/ml/ltr/MlLTRNamedXContentProvider.java b/...inference/MlLTRNamedXContentProvider.java → ...re/ml/ltr/MlLTRNamedXContentProvider.java
@@ -4,7 +4,7 @@
  * 2.0; you may not use this file except in compliance with the Elastic License
  * 2.0.
  */
-package org.elasticsearch.xpack.core.ml.inference;
+package org.elasticsearch.xpack.core.ml.ltr;
 
 import org.elasticsearch.common.io.stream.NamedWriteableRegistry;
 import org.elasticsearch.plugins.spi.NamedXContentProvider;

diff --git a/x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/utils/QueryProvider.java b/x-pack/plugin/core/src/main/java/org/elasticsearch/xpack/core/ml/utils/QueryProvider.java
@@ -30,10 +30,9 @@
 public class QueryProvider implements Writeable, ToXContentObject, Rewriteable<QueryProvider> {
 
     private static final Logger logger = LogManager.getLogger(QueryProvider.class);
-
-    private Exception parsingException;
-    private QueryBuilder parsedQuery;
-    private Map<String, Object> query;
+    private final Exception parsingException;
+    private final QueryBuilder parsedQuery;
+    private final Map<String, Object> query;
 
     public static QueryProvider defaultQuery() {
         return new QueryProvider(

diff --git a/.../src/test/java/org/elasticsearch/xpack/core/ml/inference/InferenceConfigItemTestCase.java b/.../src/test/java/org/elasticsearch/xpack/core/ml/inference/InferenceConfigItemTestCase.java
@@ -35,6 +35,7 @@
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.TextSimilarityConfigTests;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ZeroShotClassificationConfig;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ZeroShotClassificationConfigTests;
+import org.elasticsearch.xpack.core.ml.ltr.MlLTRNamedXContentProvider;
 
 import java.util.ArrayList;
 import java.util.Collections;

diff --git a/...t/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/LearnToRankConfigTests.java b/...t/java/org/elasticsearch/xpack/core/ml/inference/trainedmodel/LearnToRankConfigTests.java
@@ -21,9 +21,9 @@
 import org.elasticsearch.xcontent.XContentParser;
 import org.elasticsearch.xpack.core.ml.inference.InferenceConfigItemTestCase;
 import org.elasticsearch.xpack.core.ml.inference.MlInferenceNamedXContentProvider;
-import org.elasticsearch.xpack.core.ml.inference.MlLTRNamedXContentProvider;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ltr.LearnToRankFeatureExtractorBuilder;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ltr.QueryExtractorBuilderTests;
+import org.elasticsearch.xpack.core.ml.ltr.MlLTRNamedXContentProvider;
 import org.junit.Before;
 
 import java.io.IOException;

diff --git a/.../org/elasticsearch/xpack/core/ml/inference/trainedmodel/LearnToRankConfigUpdateTests.java b/.../org/elasticsearch/xpack/core/ml/inference/trainedmodel/LearnToRankConfigUpdateTests.java
@@ -16,10 +16,10 @@
 import org.elasticsearch.xcontent.XContentParser;
 import org.elasticsearch.xpack.core.ml.AbstractBWCSerializationTestCase;
 import org.elasticsearch.xpack.core.ml.inference.MlInferenceNamedXContentProvider;
-import org.elasticsearch.xpack.core.ml.inference.MlLTRNamedXContentProvider;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ltr.LearnToRankFeatureExtractorBuilder;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ltr.QueryExtractorBuilder;
 import org.elasticsearch.xpack.core.ml.inference.trainedmodel.ltr.QueryExtractorBuilderTests;
+import org.elasticsearch.xpack.core.ml.ltr.MlLTRNamedXContentProvider;
 import org.elasticsearch.xpack.core.ml.utils.QueryProvider;
 
 import java.io.IOException;

diff --git a/...multi-node/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/MlRescorerIT.java b/...multi-node/src/javaRestTest/java/org/elasticsearch/xpack/ml/integration/MlRescorerIT.java
@@ -29,15 +29,15 @@ public class MlRescorerIT extends ESRestTestCase {
     @Before
     public void setupModelAndData() throws IOException {
         putRegressionModel(MODEL_ID, """
-             {
+            {
               "description": "super complex model for tests",
               "input": {"field_names": ["cost", "product"]},
               "inference_config": {
                 "learn_to_rank": {
                   "feature_extractors": [{
                     "query_extractor": {
                       "feature_name": "two",
-                      "query": {"script_score": {"query": {"match_all":{}}, "script": {"source": "return 2.0;"}}}
+                      "query": { "script_score": { "query": { "match_all":{} }, "script": { "source": "return 2.0;" } } }
                     }
                   }]
                 }
@@ -174,11 +174,13 @@ public void setupModelAndData() throws IOException {
                   }
                 }
               }
-            }""");
+            }
+            """);
         createIndex(INDEX_NAME, Settings.builder().put("number_of_shards", randomIntBetween(1, 3)).build(), """
-            "properties":{
-             "product":{"type": "keyword"},
-             "cost":{"type": "integer"}}""");
+            "properties": {
+              "product": {"type": "keyword"},
+              "cost": {"type": "integer"}
+            }""");
         indexData("{ \"product\": \"TV\", \"cost\": 300 }");
         indexData("{ \"product\": \"TV\", \"cost\": 400 }");
         indexData("{ \"product\": \"VCR\", \"cost\": 150 }");
@@ -190,18 +192,18 @@ public void setupModelAndData() throws IOException {
     @SuppressWarnings("unchecked")
     public void testLtrSimple() throws Exception {
         Response searchResponse = search("""
-            {
-            "query": {
-              "match": { "product": { "query": "TV"}}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model"
-                        }
+              {
+                "query": {
+                  "match": { "product": { "query": "TV" } }
+                },
+                "rescore": {
+                  "window_size": 10,
+                  "learn_to_rank": {
+                    "model_id": "basic-ltr-model"
+                  }
                 }
-
-            }""");
+              }
+            """);
 
         Map<String, Object> response = responseAsMap(searchResponse);
         assertThat((List<Double>) XContentMapValues.extractValue("hits.hits._score", response), contains(20.0, 20.0));
@@ -211,44 +213,42 @@ public void testLtrSimple() throws Exception {
     public void testLtrSimpleDFS() throws Exception {
         Response searchResponse = searchDfs("""
             {
-            "query": {
-              "match": { "product": { "query": "TV"}}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model",
-                        "inference_config": {
-                          "learn_to_rank": {
-                            "feature_extractors":[
-                              {"query_extractor": {"feature_name": "product_bm25", "query": {"term": {"product": "TV"}}}}
-                            ]
-                          }
-                        }
-                      }
+              "query": {
+                "match": { "product": { "query": "TV" } }
+                },
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model",
+                  "inference_config": {
+                    "learn_to_rank": {
+                      "feature_extractors":[
+                        { "query_extractor": { "feature_name": "product_bm25", "query": { "term": { "product": "TV" } } } }
+                      ]
+                    }
+                  }
                 }
-
+              }
             }""");
 
         Map<String, Object> response = responseAsMap(searchResponse);
         assertThat(response.toString(), (List<Double>) XContentMapValues.extractValue("hits.hits._score", response), contains(20.0, 20.0));
 
         searchResponse = searchDfs("""
             {
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model",
-                        "inference_config": {
-                          "learn_to_rank": {
-                            "feature_extractors":[
-                              {"query_extractor": {"feature_name": "product_bm25", "query": {"term": {"product": "TV"}}}}
-                              ]
-                            }
-                          }
-                        }
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model",
+                  "inference_config": {
+                    "learn_to_rank": {
+                      "feature_extractors":[
+                        { "query_extractor": { "feature_name": "product_bm25", "query": { "term": { "product": "TV" } } } }
+                      ]
+                    }
+                  }
                 }
-
+              }
             }""");
 
         response = responseAsMap(searchResponse);
@@ -262,16 +262,16 @@ public void testLtrSimpleDFS() throws Exception {
     @SuppressWarnings("unchecked")
     public void testLtrSimpleEmpty() throws Exception {
         Response searchResponse = search("""
-            { "query": {
-              "term": { "product": "computer"}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model"
-                        }
+            {
+              "query": {
+                "term": { "product": "computer" }
+              },
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model"
                 }
-
+              }
             }""");
 
         Map<String, Object> response = responseAsMap(searchResponse);
@@ -281,16 +281,16 @@ public void testLtrSimpleEmpty() throws Exception {
     @SuppressWarnings("unchecked")
     public void testLtrEmptyDFS() throws Exception {
         Response searchResponse = searchDfs("""
-            { "query": {
-              "match": { "product": { "query": "computer"}}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model"
-                        }
+            {
+              "query": {
+                "match": { "product": { "query": "computer"} }
+              },
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model"
                 }
-
+              }
             }""");
 
         Map<String, Object> response = responseAsMap(searchResponse);
@@ -300,32 +300,32 @@ public void testLtrEmptyDFS() throws Exception {
     @SuppressWarnings("unchecked")
     public void testLtrCanMatch() throws Exception {
         Response searchResponse = searchCanMatch("""
-            { "query": {
-              "match": { "product": { "query": "TV"}}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model"
-                        }
+            {
+              "query": {
+                "match": { "product": { "query": "TV"}}
+              },
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model"
                 }
-
+              }
             }""", false);
 
         Map<String, Object> response = responseAsMap(searchResponse);
         assertThat(response.toString(), (List<Double>) XContentMapValues.extractValue("hits.hits._score", response), contains(20.0, 20.0));
 
         searchResponse = searchCanMatch("""
-            { "query": {
-              "match": { "product": { "query": "TV"}}
-            },
-            "rescore": {
-                    "window_size": 10,
-                    "inference": {
-                        "model_id": "basic-ltr-model"
-                        }
+            {
+              "query": {
+                "match": { "product": { "query": "TV"} }
+              },
+              "rescore": {
+                "window_size": 10,
+                "learn_to_rank": {
+                  "model_id": "basic-ltr-model"
                 }
-
+              }
             }""", true);
 
         response = responseAsMap(searchResponse);