Add filter_type to allowed option keys with post|efficient validation

Signed-off-by: Eric Wei <mengwei.eric@gmail.com>

Author: mengweieric

opensearch/src/main/java/org/opensearch/sql/opensearch/storage/VectorSearchTableFunctionImplementation.java

@@ -34,7 +34,8 @@ public class VectorSearchTableFunctionImplementation extends FunctionExpression
     implements TableFunctionImplementation {
 
   /** P0 allowed option keys. Rejects unknown/future keys to prevent unvalidated DSL injection. */
-  static final Set<String> ALLOWED_OPTION_KEYS = Set.of("k", "max_distance", "min_score");
+  static final Set<String> ALLOWED_OPTION_KEYS =
+      Set.of("k", "max_distance", "min_score", "filter_type");
 
   /**
    * Field names must be safe for JSON interpolation: alphanumeric, dots (nested), underscores,
@@ -190,6 +191,10 @@ private void validateOptions(Map<String, String> options) {
             String.format("Unknown option key '%s'. Supported keys: %s", key, ALLOWED_OPTION_KEYS));
       }
     }
+    if (options.containsKey("filter_type")) {
+      // Validate early — fromString throws if invalid
+      FilterType.fromString(options.get("filter_type"));
+    }
     boolean hasK = options.containsKey("k");
     boolean hasMaxDistance = options.containsKey("max_distance");
     boolean hasMinScore = options.containsKey("min_score");

opensearch/src/test/java/org/opensearch/sql/opensearch/storage/VectorSearchTableFunctionImplementationTest.java

@@ -388,6 +388,45 @@ void testCaseInsensitiveArgLookup() {
     assertTrue(table instanceof VectorSearchIndex);
   }
 
+  @Test
+  void testInvalidFilterTypeRejects() {
+    FunctionName functionName = FunctionName.of("vectorsearch");
+    List<Expression> args =
+        List.of(
+            DSL.namedArgument("table", DSL.literal("my-index")),
+            DSL.namedArgument("field", DSL.literal("embedding")),
+            DSL.namedArgument("vector", DSL.literal("[1.0, 2.0]")),
+            DSL.namedArgument("option", DSL.literal("k=5,filter_type=invalid")));
+    VectorSearchTableFunctionImplementation impl =
+        new VectorSearchTableFunctionImplementation(functionName, args, client, settings);
+    ExpressionEvaluationException ex =
+        assertThrows(ExpressionEvaluationException.class, impl::applyArguments);
+    assertTrue(ex.getMessage().contains("filter_type must be one of"));
+  }
+
+  @Test
+  void testFilterTypePostAccepted() {
+    VectorSearchTableFunctionImplementation impl =
+        createImplWithArgs("my-index", "embedding", "[1.0, 2.0]", "k=5,filter_type=post");
+    Table table = impl.applyArguments();
+    assertTrue(table instanceof VectorSearchIndex);
+  }
+
+  @Test
+  void testFilterTypeEfficientAccepted() {
+    VectorSearchTableFunctionImplementation impl =
+        createImplWithArgs("my-index", "embedding", "[1.0, 2.0]", "k=5,filter_type=efficient");
+    Table table = impl.applyArguments();
+    assertTrue(table instanceof VectorSearchIndex);
+  }
+
+  @Test
+  void testParseOptionsPreservesFilterTypeValue() {
+    Map<String, String> options =
+        VectorSearchTableFunctionImplementation.parseOptions("k=5,filter_type=post");
+    assertEquals("post", options.get("filter_type"));
+  }
+
   private VectorSearchTableFunctionImplementation createImpl() {
     return createImplWithArgs("my-index", "embedding", "[1.0, 2.0, 3.0]", "k=5");
   }