Fixed failing integ tests

Signed-off-by: Martin Gaievski <gaievski@amazon.com>
opensearch-project · Dec 6, 2023 · d754563 · d754563
1 parent 0236cc3
commit d754563
Showing 1 changed file with 10 additions and 9 deletions.
diff --git a/src/test/java/org/opensearch/neuralsearch/query/NeuralQueryIT.java b/src/test/java/org/opensearch/neuralsearch/query/NeuralQueryIT.java
@@ -5,10 +5,10 @@
 
 package org.opensearch.neuralsearch.query;
 
+import static org.opensearch.neuralsearch.TestUtils.DELTA_FOR_SCORE_ASSERTION;
 import static org.opensearch.neuralsearch.TestUtils.createRandomVector;
 import static org.opensearch.neuralsearch.TestUtils.objectToFloat;
 
-import java.io.IOException;
 import java.util.Collections;
 import java.util.List;
 import java.util.Map;
@@ -92,7 +92,7 @@ public void testBasicQuery() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -131,7 +131,7 @@ public void testBoostQuery() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = 2 * computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -174,7 +174,7 @@ public void testRescoreQuery() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -234,7 +234,7 @@ public void testBooleanQuery_withMultipleNeuralQueries() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = 2 * computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -326,7 +326,7 @@ public void testNestedQuery() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -368,7 +368,7 @@ public void testFilterQuery() {
         Map<String, Object> firstInnerHit = getFirstInnerHit(searchResponseAsMap);
         assertEquals("3", firstInnerHit.get("_id"));
         float expectedScore = computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
     /**
@@ -404,10 +404,11 @@ public void testMultimodalQuery() {
 
         assertEquals("1", firstInnerHit.get("_id"));
         float expectedScore = computeExpectedScore(modelId, testVector, TEST_SPACE_TYPE, TEST_QUERY_TEXT);
-        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), 0.0);
+        assertEquals(expectedScore, objectToFloat(firstInnerHit.get("_score")), DELTA_FOR_SCORE_ASSERTION);
     }
 
-    private void initializeIndexIfNotExist(String indexName) throws IOException {
+    @SneakyThrows
+    private void initializeIndexIfNotExist(String indexName) {
         if (TEST_BASIC_INDEX_NAME.equals(indexName) && !indexExists(TEST_BASIC_INDEX_NAME)) {
             prepareKnnIndex(
                 TEST_BASIC_INDEX_NAME,