anew commented on code in PR #57584:
URL: https://github.com/apache/spark/pull/57584#discussion_r3662068538


##########
sql/pipelines/src/test/scala/org/apache/spark/sql/pipelines/graph/AutoCdcScd2SinglePipelineSuite.scala:
##########
@@ -0,0 +1,191 @@
+/*
+ * 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.spark.sql.pipelines.graph
+
+import org.apache.spark.sql.Row
+import org.apache.spark.sql.execution.streaming.runtime.MemoryStream
+import org.apache.spark.sql.functions
+import org.apache.spark.sql.pipelines.autocdc.{
+  AutoCdcReservedNames,
+  ColumnSelection,
+  ScdType,
+  UnqualifiedColumnName
+}
+import org.apache.spark.sql.pipelines.utils.{ExecutionTest, 
TestGraphRegistrationContext}
+import org.apache.spark.sql.test.SharedSparkSession
+
+/**
+ * End-to-end smoke tests for AutoCDC SCD Type 2 flows running within a single 
pipeline: one
+ * [[DataflowGraph]] / [[TestPipelineUpdateContext]] executes an SCD2 AutoCDC 
flow through the
+ * [[Scd2MergeStreamingWrite]] streaming write, and both the target table and 
the auxiliary
+ * table contents are asserted at the end.
+ *
+ * This exercises the full wiring landed for SCD2: the flow planner routing an 
SCD2
+ * [[AutoCdcMergeFlow]] to [[Scd2MergeStreamingWrite]], the auxiliary-table 
materialization, and
+ * the [[org.apache.spark.sql.pipelines.autocdc.Scd2ForeachBatchHandler]] 
reconciliation.
+ */
+class AutoCdcScd2SinglePipelineSuite
+    extends ExecutionTest
+    with SharedSparkSession
+    with AutoCdcGraphExecutionTestMixin {
+
+  /** The SCD2 target's `_cdc_metadata` struct value for a given 
recordStartAt. */
+  private def scd2Meta(recordStartAt: Long): Row = Row(recordStartAt)
+
+  /**
+   * DDL for an SCD2 target table with user columns `(id, name, version)` plus 
the framework
+   * columns `__START_AT` / `__END_AT` (sequencing type BIGINT) and the SCD2 
`_cdc_metadata`
+   * struct. `version` is the sequencing column and, unless excluded via a 
column selection, is
+   * retained as an ordinary user column in the target.
+   */
+  private def createScd2Target(table: String): Unit = {
+    val meta = AutoCdcReservedNames.cdcMetadataColName
+    spark.sql(
+      s"CREATE TABLE $table (" +
+      "id INT NOT NULL, name STRING, version BIGINT NOT NULL, " +
+      "__START_AT BIGINT, __END_AT BIGINT, " +
+      s"$meta STRUCT<__RECORD_START_AT:BIGINT> NOT NULL)"
+    )
+  }
+
+  test("SCD2: an upsert lands an open current record in an empty target 
table") {

Review Comment:
   note: the test coverage here s not exhaustive, but it would be hard to test 
all possible cases in an end-to-end suite. This suite merely asserts that it 
works end-to-end



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