[GitHub] [spark] viirya commented on a diff in pull request #38785: [SPARK-41249][SS][TEST] Add acceptance test for self-union on streaming query

[GitBox <gi...@apache.org>]

viirya commented on code in PR #38785:
URL: https://github.com/apache/spark/pull/38785#discussion_r1031284628


##########
sql/core/src/test/scala/org/apache/spark/sql/streaming/StreamingSelfUnionSuite.scala:
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@@ -0,0 +1,160 @@
+/*
+ * 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.streaming
+
+import org.scalatest.BeforeAndAfter
+import org.scalatest.concurrent.PatienceConfiguration.Timeout
+
+import org.apache.spark.sql.SaveMode
+import org.apache.spark.sql.connector.catalog.Identifier
+import org.apache.spark.sql.execution.streaming.MemoryStream
+import org.apache.spark.sql.streaming.test.{InMemoryStreamTable, InMemoryStreamTableCatalog}
+import org.apache.spark.sql.streaming.util.StreamManualClock
+import org.apache.spark.sql.types.{LongType, StructField, StructType}
+
+class StreamingSelfUnionSuite extends StreamTest with BeforeAndAfter {
+
+  import testImplicits._
+  import org.apache.spark.sql.connector.catalog.CatalogV2Implicits._
+
+  before {
+    spark.conf.set("spark.sql.catalog.teststream", classOf[InMemoryStreamTableCatalog].getName)
+  }
+
+  after {
+    spark.sessionState.catalogManager.reset()
+    spark.sessionState.conf.clear()
+    sqlContext.streams.active.foreach(_.stop())
+  }
+
+  test("self-union, DSv1, read via DataStreamReader API") {
+    withTempPath { dir =>
+      val dataLocation = dir.getAbsolutePath
+      spark.range(1, 4).write.format("parquet").save(dataLocation)
+
+      val streamDf = spark.readStream.format("parquet")
+        .schema(StructType(Seq(StructField("id", LongType)))).load(dataLocation)
+      val unionedDf = streamDf.union(streamDf)
+
+      testStream(unionedDf)(
+        ProcessAllAvailable(),
+        CheckLastBatch(1, 2, 3, 1, 2, 3),
+        AssertOnQuery { q =>
+          val lastProgress = getLastProgressWithData(q)
+          assert(lastProgress.nonEmpty)
+          assert(lastProgress.get.numInputRows == 6)
+          assert(lastProgress.get.sources.length == 1)
+          assert(lastProgress.get.sources(0).numInputRows == 6)
+          true
+        }
+      )
+    }
+  }
+
+  test("self-union, DSv1, read via table API") {
+    withTable("parquet_streaming_tbl") {
+      spark.sql("CREATE TABLE parquet_streaming_tbl (key integer) USING parquet")
+
+      val streamDf = spark.readStream.table("parquet_streaming_tbl")
+      val unionedDf = streamDf.union(streamDf)
+
+      val clock = new StreamManualClock()
+      testStream(unionedDf)(
+        StartStream(triggerClock = clock, trigger = Trigger.ProcessingTime(100)),
+        Execute { _ =>
+          spark.range(1, 4).selectExpr("id AS key")
+            .write.format("parquet").mode(SaveMode.Append).saveAsTable("parquet_streaming_tbl")
+        },
+        AdvanceManualClock(150),
+        waitUntilBatchProcessed(clock),
+        CheckLastBatch(1, 2, 3, 1, 2, 3),
+        AssertOnQuery { q =>
+          val lastProgress = getLastProgressWithData(q)
+          assert(lastProgress.nonEmpty)
+          assert(lastProgress.get.numInputRows == 6)
+          assert(lastProgress.get.sources.length == 1)
+          assert(lastProgress.get.sources(0).numInputRows == 6)
+          true
+        }
+      )
+    }
+  }
+
+  test("self-union, DSv2, read via DataStreamReader API") {
+    val inputData = MemoryStream[Int]
+
+    val streamDf = inputData.toDF()
+    val unionedDf = streamDf.union(streamDf)
+
+    testStream(unionedDf)(
+      AddData(inputData, 1, 2, 3),
+      CheckLastBatch(1, 2, 3, 1, 2, 3),
+      AssertOnQuery { q =>
+        val lastProgress = getLastProgressWithData(q)
+        assert(lastProgress.nonEmpty)
+        assert(lastProgress.get.numInputRows == 6)
+        assert(lastProgress.get.sources.length == 1)
+        assert(lastProgress.get.sources(0).numInputRows == 6)
+        true
+      }
+    )
+  }
+
+  test("self-union, DSv2, read via table API") {
+    val tblName = "teststream.table_name"
+    withTable(tblName) {
+      spark.sql(s"CREATE TABLE $tblName (data int) USING foo")
+      val stream = MemoryStream[Int]
+      val testCatalog = spark.sessionState.catalogManager.catalog("teststream").asTableCatalog
+      val table = testCatalog.loadTable(Identifier.of(Array(), "table_name"))
+      table.asInstanceOf[InMemoryStreamTable].setStream(stream)
+
+      val streamDf = spark.readStream.table(tblName)
+      val unionedDf = streamDf.union(streamDf)
+
+      testStream(unionedDf) (
+        AddData(stream, 1, 2, 3),

Review Comment:
   If the data is written into the table location, instead of through the stream (i.e. like `self-union, DSv1, read via table API`), is it also working?



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