szehon-ho commented on code in PR #58843:
URL: https://github.com/apache/spark/pull/58843#discussion_r4031310389


##########
sql/connect/server/src/test/scala/org/apache/spark/sql/connect/pipelines/PythonPipelineSuite.scala:
##########
@@ -1084,6 +1084,74 @@ class PythonPipelineSuite
         
ColumnSelection.ExcludeColumns(Seq(UnqualifiedColumnName("timestamp")))))
   }
 
+  test(
+    "AutoCDC API: ignore_null_updates=True is forwarded as an all-columns 
ignore-null " +
+      "selection") {
+    val flow = buildAutoCdcFlow("""
+        |@dp.table
+        |def src():
+        |  return spark.readStream.format("rate").load()
+        |
+        |dp.create_streaming_table("target")
+        |
+        |dp.create_auto_cdc_flow(
+        |    target = "target",
+        |    source = "src",
+        |    keys = ["value"],
+        |    sequence_by = "timestamp",
+        |    ignore_null_updates = True,
+        |)
+        |""".stripMargin)
+
+    // "All columns" is an ExcludeColumns selection with an empty list.
+    assert(
+      
flow.changeArgs.ignoreNullSelection.contains(ColumnSelection.ExcludeColumns(Seq.empty)))
+  }
+
+  test("AutoCDC API: ignore_null_updates_column_list is forwarded as 
IncludeColumns") {
+    val flow = buildAutoCdcFlow("""
+        |@dp.table
+        |def src():
+        |  return spark.readStream.format("rate").load()
+        |
+        |dp.create_streaming_table("target")
+        |
+        |dp.create_auto_cdc_flow(
+        |    target = "target",
+        |    source = "src",
+        |    keys = ["value"],
+        |    sequence_by = "timestamp",
+        |    ignore_null_updates_column_list = ["value"],

Review Comment:
   `value` is also the key, but graph resolution rejects key columns in an 
ignore-null selection. Because `buildAutoCdcFlow` does not resolve the graph, 
this test passes with an unusable configuration. Could we use a non-key payload 
column and resolve or execute the graph?



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