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:
is also the key, but graph resolution rejects key columns in an ignore-null
selection. Because 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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