diff --git a/superset/db_engine_specs/spark.py b/superset/db_engine_specs/spark.py
index 733a374bf82..5c5360a718d 100644
--- a/superset/db_engine_specs/spark.py
+++ b/superset/db_engine_specs/spark.py
@@ -16,6 +16,8 @@
 # under the License.
 from __future__ import annotations
 
+from sqlalchemy.dialects import registry
+
 from superset.constants import TimeGrain
 from superset.db_engine_specs.base import DatabaseCategory
 from superset.db_engine_specs.hive import HiveEngineSpec
@@ -40,6 +42,8 @@ time_grain_expressions: dict[str | None, str] = {
 
 
 class SparkEngineSpec(HiveEngineSpec):
+    engine = "spark"
+    registry.register("spark", "pyhive.sqlalchemy_hive", "HiveDialect")
     _time_grain_expressions = time_grain_expressions
     engine_name = "Apache Spark SQL"
 
@@ -53,6 +57,6 @@ class SparkEngineSpec(HiveEngineSpec):
             DatabaseCategory.OPEN_SOURCE,
         ],
         "pypi_packages": ["pyhive"],
-        "connection_string": "hive://hive@{hostname}:{port}/{database}",
+        "connection_string": "spark://hive@{hostname}:{port}/{database}",
         "default_port": 10000,
     }
diff --git a/tests/unit_tests/sql/test_spark_dialect.py b/tests/unit_tests/sql/test_spark_dialect.py
new file mode 100644
index 00000000000..2ac4d2cc8cb
--- /dev/null
+++ b/tests/unit_tests/sql/test_spark_dialect.py
@@ -0,0 +1,94 @@
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied.  See the License for the
+# specific language governing permissions and limitations
+# under the License.
+
+"""Tests for Spark dialect support in sqlglot.
+
+Verifies that a spark:// SQLAlchemy connection resolves to SparkEngineSpec,
+which uses the sqlglot Spark dialect and preserves Spark SQL functions like
+BOOL_OR (instead of rewriting them to LOGICAL_OR as the Hive dialect does).
+"""
+
+import pytest
+from sqlalchemy.engine.url import make_url
+
+from superset.db_engine_specs import get_engine_spec
+from superset.db_engine_specs.spark import SparkEngineSpec
+from superset.sql.parse import LimitMethod, SQLScript, SQLStatement
+
+
+def test_spark_url_resolves_to_spark_engine_spec() -> None:
+    """A spark:// SQLAlchemy URI should resolve to SparkEngineSpec."""
+    url = make_url("spark://localhost:10009/default")
+    backend = url.get_backend_name()
+    engine_spec = get_engine_spec(backend)
+    assert engine_spec is SparkEngineSpec
+
+
+def test_spark_engine_spec_engine_attribute() -> None:
+    """SparkEngineSpec.engine should be 'spark', not inherited 'hive'."""
+    assert SparkEngineSpec.engine == "spark"
+
+
+@pytest.mark.parametrize(
+    ("sql", "expected"),
+    [
+        (
+            "SELECT BOOL_OR(col) FROM my_table",
+            "SELECT\n  BOOL_OR(col)\nFROM my_table",
+        ),
+        (
+            "SELECT BOOL_OR('test_value' IN ('test', 'test_value'))",
+            "SELECT\n  BOOL_OR('test_value' IN ('test', 'test_value'))",
+        ),
+    ],
+)
+def test_spark_preserves_bool_or(sql: str, expected: str) -> None:
+    """BOOL_OR should be preserved when using the Spark engine.
+
+    The Hive dialect rewrites BOOL_OR to LOGICAL_OR via sqlglot, but Spark SQL
+    supports BOOL_OR natively so it must remain unchanged.
+    """
+    script = SQLScript(sql, SparkEngineSpec.engine)
+    result = script.statements[0].format()
+    assert result == expected
+
+
+def test_spark_preserves_bool_or_with_limit() -> None:
+    """BOOL_OR should be preserved after applying a LIMIT (the SQLLab flow).
+
+    In SQLLab, Superset parses the user's SQL, applies a LIMIT, and regenerates
+    the SQL using the engine's sqlglot dialect. This test replicates that full
+    flow for a spark:// connection.
+    """
+    sql = "SELECT BOOL_OR('test_value' IN ('test', 'test_value'))"
+    statement = SQLStatement(sql, SparkEngineSpec.engine)
+    statement.set_limit_value(1001, LimitMethod.FORCE_LIMIT)
+    result = statement.format()
+
+    expected = "SELECT\n  BOOL_OR('test_value' IN ('test', 'test_value'))\nLIMIT 1001"
+    assert result == expected
+
+
+def test_hive_rewrites_bool_or_to_logical_or() -> None:
+    """Contrast: the Hive dialect rewrites BOOL_OR to LOGICAL_OR."""
+    sql = "SELECT BOOL_OR('test_value' IN ('test', 'test_value'))"
+    statement = SQLStatement(sql, "hive")
+    statement.set_limit_value(1001, LimitMethod.FORCE_LIMIT)
+    result = statement.format()
+
+    assert "LOGICAL_OR" in result
+    assert "BOOL_OR" not in result