diff --git a/backends-velox/src/test/scala/org/apache/gluten/execution/FallbackSuite.scala b/backends-velox/src/test/scala/org/apache/gluten/execution/FallbackSuite.scala
index ddc9cc923e6..53af1664c85 100644
--- a/backends-velox/src/test/scala/org/apache/gluten/execution/FallbackSuite.scala
+++ b/backends-velox/src/test/scala/org/apache/gluten/execution/FallbackSuite.scala
@@ -23,6 +23,7 @@ import org.apache.spark.sql.execution.{ColumnarBroadcastExchangeExec, ColumnarSh
 import org.apache.spark.sql.execution.adaptive.{AdaptiveSparkPlanHelper, AQEShuffleReadExec}
 import org.apache.spark.sql.execution.exchange.ShuffleExchangeExec
 import org.apache.spark.sql.execution.joins.{BroadcastHashJoinExec, BroadcastNestedLoopJoinExec, SortMergeJoinExec}
+import org.apache.spark.sql.internal.SQLConf
 import org.apache.spark.utils.GlutenSuiteUtils
 
 class FallbackSuite extends VeloxWholeStageTransformerSuite with AdaptiveSparkPlanHelper {
@@ -62,12 +63,53 @@ class FallbackSuite extends VeloxWholeStageTransformerSuite with AdaptiveSparkPl
       .write
       .format("parquet")
       .saveAsTable("tmp3")
+    // ORC files are written with DECIMAL(38, 18) (Hive's native storage precision).
+    // tmp4/tmp5 declare DECIMAL(20, 0) pointing to the same ORC files,
+    // so the reader must handle a precision/scale mismatch.
+    spark
+      .range(100)
+      .selectExpr(
+        "cast(id as decimal(38, 18)) as c1",
+        "cast(id % 3 as int) as c2",
+        "cast(id % 9 as timestamp) as c3")
+      .write
+      .format("orc")
+      .saveAsTable("tmp4_wide")
+    spark
+      .range(100)
+      .selectExpr(
+        "cast(id as decimal(38, 18)) as c1",
+        "cast(id % 3 as int) as c2",
+        "cast(id % 5 as timestamp) as c3")
+      .write
+      .format("orc")
+      .saveAsTable("tmp5_wide")
+    val loc4 = spark
+      .sql("DESCRIBE FORMATTED tmp4_wide")
+      .filter("col_name = 'Location'")
+      .select("data_type")
+      .collect()(0)
+      .getString(0)
+    val loc5 = spark
+      .sql("DESCRIBE FORMATTED tmp5_wide")
+      .filter("col_name = 'Location'")
+      .select("data_type")
+      .collect()(0)
+      .getString(0)
+    spark.sql(
+      s"CREATE TABLE tmp4 (c1 DECIMAL(20, 0), c2 INT, c3 TIMESTAMP) USING ORC LOCATION '$loc4'")
+    spark.sql(
+      s"CREATE TABLE tmp5 (c1 DECIMAL(20, 0), c2 INT, c3 TIMESTAMP) USING ORC LOCATION '$loc5'")
   }
 
   override protected def afterAll(): Unit = {
     spark.sql("drop table tmp1")
     spark.sql("drop table tmp2")
     spark.sql("drop table tmp3")
+    spark.sql("drop table tmp4_wide")
+    spark.sql("drop table tmp5_wide")
+    spark.sql("drop table tmp4")
+    spark.sql("drop table tmp5")
 
     super.afterAll()
   }
@@ -382,4 +424,127 @@ class FallbackSuite extends VeloxWholeStageTransformerSuite with AdaptiveSparkPl
       }
     }
   }
+
+  test("For decimal-key joins, if one side falls back to Spark, force fallback the other side") {
+    // ORC files are written with DECIMAL(38, 18) (Hive's native storage precision).
+    // The metastore tables tmp4/tmp5 declare DECIMAL(20, 0) and point to the
+    // same ORC files, so the reader must handle a precision/scale mismatch.
+    // Selecting only c2 (INT) -> native FileSourceScanExecTransformer.
+    // Selecting c3 (TIMESTAMP) in addition -> native validation fails ->
+    //   vanilla FileSourceScanExec.
+
+    // -- SortMergeJoin ------------------------------------------------------------------
+
+    val sql1 = "SELECT /*+ MERGE(tmp4) */ tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(
+      GlutenConfig.COLUMNAR_FORCE_SHUFFLED_HASH_JOIN_ENABLED.key -> "false",
+      GlutenConfig.COLUMNAR_SHUFFLED_HASH_JOIN_ENABLED.key -> "false") {
+      checkAnswer(
+        spark.sql(sql1),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+            "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    val sql2 = "SELECT /*+ MERGE(tmp4) */ tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(
+      GlutenConfig.COLUMNAR_FORCE_SHUFFLED_HASH_JOIN_ENABLED.key -> "false",
+      GlutenConfig.COLUMNAR_SHUFFLED_HASH_JOIN_ENABLED.key -> "false") {
+      checkAnswer(
+        spark.sql(sql2),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+            "tmp5_wide.c2 AS 5c2 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    val sql3 = "SELECT /*+ MERGE(tmp4) */ tmp4.c2 AS 4c2, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(
+      GlutenConfig.COLUMNAR_FORCE_SHUFFLED_HASH_JOIN_ENABLED.key -> "false",
+      GlutenConfig.COLUMNAR_SHUFFLED_HASH_JOIN_ENABLED.key -> "false") {
+      checkAnswer(
+        spark.sql(sql3),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, " +
+            "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    // -- ShuffledHashJoin ---------------------------------------------------------------
+
+    val sql4 = "SELECT /*+ SHUFFLE_HASH(tmp4) */ tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1") {
+      checkAnswer(
+        spark.sql(sql4),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+            "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    val sql5 = "SELECT /*+ SHUFFLE_HASH(tmp4) */ tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1") {
+      checkAnswer(
+        spark.sql(sql5),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+            "tmp5_wide.c2 AS 5c2 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    val sql6 = "SELECT /*+ SHUFFLE_HASH(tmp4) */ tmp4.c2 AS 4c2, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    withSQLConf(SQLConf.AUTO_BROADCASTJOIN_THRESHOLD.key -> "-1") {
+      checkAnswer(
+        spark.sql(sql6),
+        spark.sql(
+          "SELECT tmp4_wide.c2 AS 4c2, " +
+            "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+            "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+      )
+    }
+
+    // -- BroadcastHashJoin --------------------------------------------------------------
+
+    val sql7 = "SELECT tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    checkAnswer(
+      spark.sql(sql7),
+      spark.sql(
+        "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+          "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+          "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+    )
+
+    val sql8 = "SELECT tmp4.c2 AS 4c2, tmp4.c3 AS 4c3, " +
+      "tmp5.c2 AS 5c2 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    checkAnswer(
+      spark.sql(sql8),
+      spark.sql(
+        "SELECT tmp4_wide.c2 AS 4c2, tmp4_wide.c3 AS 4c3, " +
+          "tmp5_wide.c2 AS 5c2 " +
+          "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+    )
+
+    val sql9 = "SELECT tmp4.c2 AS 4c2, " +
+      "tmp5.c2 AS 5c2, tmp5.c3 AS 5c3 FROM tmp4 JOIN tmp5 ON tmp4.c1 = tmp5.c1"
+    checkAnswer(
+      spark.sql(sql9),
+      spark.sql(
+        "SELECT tmp4_wide.c2 AS 4c2, " +
+          "tmp5_wide.c2 AS 5c2, tmp5_wide.c3 AS 5c3 " +
+          "FROM tmp4_wide JOIN tmp5_wide ON tmp4_wide.c1 = tmp5_wide.c1")
+    )
+  }
 }