diff --git a/backends-velox/src/test/scala/org/apache/gluten/execution/python/ArrowEvalPythonExecSuite.scala b/backends-velox/src/test/scala/org/apache/gluten/execution/python/ArrowEvalPythonExecSuite.scala
deleted file mode 100644
index c2a191a20d0b..000000000000
--- a/backends-velox/src/test/scala/org/apache/gluten/execution/python/ArrowEvalPythonExecSuite.scala
+++ /dev/null
@@ -1,102 +0,0 @@
-/*
- * 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.
- */
-package org.apache.gluten.execution.python
-
-import org.apache.gluten.execution.WholeStageTransformerSuite
-
-import org.apache.spark.SparkConf
-import org.apache.spark.api.python.ColumnarArrowEvalPythonExec
-import org.apache.spark.sql.IntegratedUDFTestUtils
-
-class ArrowEvalPythonExecSuite extends WholeStageTransformerSuite {
-
-  import IntegratedUDFTestUtils._
-  import testImplicits.localSeqToDatasetHolder
-  import testImplicits.newProductEncoder
-
-  override protected val resourcePath: String = "/tpch-data-parquet"
-  override protected val fileFormat: String = "parquet"
-  val pyarrowTestUDF = TestScalarPandasUDF(name = "pyarrowUDF")
-
-  override def sparkConf: SparkConf = {
-    super.sparkConf
-      .set("spark.sql.shuffle.partitions", "1")
-      .set("spark.default.parallelism", "1")
-      .set("spark.executor.cores", "1")
-  }
-
-  test("arrow_udf test: without projection") {
-    lazy val base =
-      Seq(("1", 1), ("1", 2), ("2", 1), ("2", 2), ("3", 1), ("3", 2), ("0", 1), ("3", 0))
-        .toDF("a", "b")
-    lazy val expected = Seq(
-      ("1", "1"),
-      ("1", "1"),
-      ("2", "2"),
-      ("2", "2"),
-      ("3", "3"),
-      ("3", "3"),
-      ("0", "0"),
-      ("3", "3")
-    ).toDF("a", "p_a")
-
-    val df2 = base.select("a").withColumn("p_a", pyarrowTestUDF(base("a")))
-    checkSparkOperatorMatch[ColumnarArrowEvalPythonExec](df2)
-    checkAnswer(df2, expected)
-  }
-
-  test("arrow_udf test: with unrelated projection") {
-    lazy val base =
-      Seq(("1", 1), ("1", 2), ("2", 1), ("2", 2), ("3", 1), ("3", 2), ("0", 1), ("3", 0))
-        .toDF("a", "b")
-    lazy val expected = Seq(
-      ("1", 1, "1", 2),
-      ("1", 2, "1", 4),
-      ("2", 1, "2", 2),
-      ("2", 2, "2", 4),
-      ("3", 1, "3", 2),
-      ("3", 2, "3", 4),
-      ("0", 1, "0", 2),
-      ("3", 0, "3", 0)
-    ).toDF("a", "b", "p_a", "d_b")
-
-    val df = base.withColumn("p_a", pyarrowTestUDF(base("a"))).withColumn("d_b", base("b") * 2)
-    checkSparkOperatorMatch[ColumnarArrowEvalPythonExec](df)
-    checkAnswer(df, expected)
-  }
-
-  test("arrow_udf test: with preprojection") {
-    lazy val base =
-      Seq(("1", 1), ("1", 2), ("2", 1), ("2", 2), ("3", 1), ("3", 2), ("0", 1), ("3", 0))
-        .toDF("a", "b")
-    lazy val expected = Seq(
-      ("1", 1, 2, "1", 2),
-      ("1", 2, 4, "1", 4),
-      ("2", 1, 2, "2", 2),
-      ("2", 2, 4, "2", 4),
-      ("3", 1, 2, "3", 2),
-      ("3", 2, 4, "3", 4),
-      ("0", 1, 2, "0", 2),
-      ("3", 0, 0, "3", 0)
-    ).toDF("a", "b", "d_b", "p_a", "p_b")
-    val df = base
-      .withColumn("d_b", base("b") * 2)
-      .withColumn("p_a", pyarrowTestUDF(base("a")))
-      .withColumn("p_b", pyarrowTestUDF(base("b") * 2))
-    checkAnswer(df, expected)
-  }
-}