[SPARK-56614][SQL][CONNECT][TESTS][FOLLOWUP] Pin strictDataFrameColumnResolution=true for lazy column validation test

sql/connect/client/jvm/src/test/scala/org/apache/spark/sql/connect/DataFrameSuite.scala

@@ -68,14 +68,24 @@ class DataFrameSuite extends QueryTest with RemoteSparkSession {
   }
 
   test("lazy column validation") {
-    val session = spark
-    import session.implicits._
-
-    val df1 = Seq(1 -> "y").toDF("a", "y")
-    val df2 = Seq(1 -> "x").toDF("a", "x")
-    val df3 = df1.join(df2, df1("a") === df2("a"))
-    val df4 = df3.select(df1("x")) // <- No exception here
-
-    intercept[AnalysisException] { df4.schema }
+    // The test relies on strict plan-id-based resolution: with the name-based fallback
+    // enabled, df1("x") would resolve to df2.x via the join output and df4.schema would
+    // succeed. Pin the config directly via spark.conf.set/unset; the lazy SQLConf entry
+    // trips withSQLConf's isModifiable check on the Connect server, so we cannot use that
+    // helper here.
+    spark.conf.set("spark.sql.analyzer.strictDataFrameColumnResolution", "true")
+    try {
+      val session = spark
+      import session.implicits._
+
+      val df1 = Seq(1 -> "y").toDF("a", "y")
+      val df2 = Seq(1 -> "x").toDF("a", "x")
+      val df3 = df1.join(df2, df1("a") === df2("a"))
+      val df4 = df3.select(df1("x")) // <- No exception here
+
+      intercept[AnalysisException] { df4.schema }
+    } finally {
+      spark.conf.unset("spark.sql.analyzer.strictDataFrameColumnResolution")
+    }
   }
 }