Github user jose-torres commented on a diff in the pull request:
https://github.com/apache/spark/pull/20243#discussion_r161954315
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/streaming/sources/StreamingDataSourceV2Suite.scala
---
@@ -0,0 +1,199 @@
+/*
+ * 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.sources
+
+import java.util.Optional
+
+import org.apache.spark.sql.{AnalysisException, Row}
+import org.apache.spark.sql.execution.streaming.{LongOffset,
RateStreamOffset}
+import org.apache.spark.sql.sources.DataSourceRegister
+import org.apache.spark.sql.sources.v2.{DataSourceV2, DataSourceV2Options}
+import org.apache.spark.sql.sources.v2.reader.ReadTask
+import org.apache.spark.sql.sources.v2.streaming.{ContinuousReadSupport,
ContinuousWriteSupport, MicroBatchReadSupport, MicroBatchWriteSupport}
+import org.apache.spark.sql.sources.v2.streaming.reader.{ContinuousReader,
MicroBatchReader, Offset, PartitionOffset}
+import org.apache.spark.sql.sources.v2.streaming.writer.ContinuousWriter
+import org.apache.spark.sql.sources.v2.writer.DataSourceV2Writer
+import org.apache.spark.sql.streaming.{OutputMode, StreamTest, Trigger}
+import org.apache.spark.sql.types.StructType
+import org.apache.spark.util.Utils
+
+object FakeReader extends MicroBatchReader with ContinuousReader {
+ def setOffsetRange(start: Optional[Offset], end: Optional[Offset]): Unit
= {}
+ def getStartOffset: Offset = RateStreamOffset(Map())
+ def getEndOffset: Offset = RateStreamOffset(Map())
+ def deserializeOffset(json: String): Offset = RateStreamOffset(Map())
+ def commit(end: Offset): Unit = {}
+ def readSchema(): StructType = StructType(Seq())
+ def createReadTasks(): java.util.ArrayList[ReadTask[Row]] = new
java.util.ArrayList()
+ def stop(): Unit = {}
+ def mergeOffsets(offsets: Array[PartitionOffset]): Offset =
RateStreamOffset(Map())
+ def setOffset(start: Optional[Offset]): Unit = {}
+}
+
+class FakeStreamingMicroBatchOnly extends DataSourceRegister
+ with DataSourceV2 with MicroBatchReadSupport with
MicroBatchWriteSupport {
+ override def createMicroBatchReader(
+ schema: Optional[StructType],
+ checkpointLocation: String,
+ options: DataSourceV2Options): MicroBatchReader = FakeReader
+
+ def createMicroBatchWriter(
+ queryId: String,
+ epochId: Long,
+ schema: StructType,
+ mode: OutputMode,
+ options: DataSourceV2Options): Optional[DataSourceV2Writer] = {
+ throw new IllegalStateException("fake sink - cannot actually write")
+ }
+
+ override def shortName(): String = "fake-microbatch-only"
+}
+
+class FakeStreamingContinuousOnly extends DataSourceRegister
+ with DataSourceV2 with ContinuousReadSupport with
ContinuousWriteSupport {
+ override def createContinuousReader(
+ schema: Optional[StructType],
+ checkpointLocation: String,
+ options: DataSourceV2Options): ContinuousReader = FakeReader
+
+ def createContinuousWriter(
+ queryId: String,
+ schema: StructType,
+ mode: OutputMode,
+ options: DataSourceV2Options): Optional[ContinuousWriter] = {
+ throw new IllegalStateException("fake sink - cannot actually write")
+ }
+
+ override def shortName(): String = "fake-continuous-only"
+}
+
+class FakeStreamingBothModes extends DataSourceRegister
+ with DataSourceV2 with MicroBatchReadSupport with ContinuousReadSupport
+ with MicroBatchWriteSupport with ContinuousWriteSupport {
+ override def createMicroBatchReader(
+ schema: Optional[StructType],
+ checkpointLocation: String,
+ options: DataSourceV2Options): MicroBatchReader = FakeReader
+
+ def createMicroBatchWriter(
+ queryId: String,
+ epochId: Long,
+ schema: StructType,
+ mode: OutputMode,
+ options: DataSourceV2Options): Optional[DataSourceV2Writer] = {
+ throw new IllegalStateException("fake sink - cannot actually write")
+ }
+
+ override def createContinuousReader(
+ schema: Optional[StructType],
+ checkpointLocation: String,
+ options: DataSourceV2Options): ContinuousReader = FakeReader
+
+ def createContinuousWriter(
+ queryId: String,
+ schema: StructType,
+ mode: OutputMode,
+ options: DataSourceV2Options): Optional[ContinuousWriter] = {
+ throw new IllegalStateException("fake sink - cannot actually write")
+ }
+
+ override def shortName(): String = "fake-both-modes"
+}
+
+class FakeStreamingNeitherMode extends DataSourceRegister with
DataSourceV2 {
+ override def shortName(): String = "fake-neither-mode"
+}
+
+class StreamingDataSourceV2Suite extends StreamTest {
+
+ private def df = spark.readStream.format("rate").load()
+
+ override def beforeAll(): Unit = {
+ super.beforeAll()
+ val fakeCheckpoint = Utils.createTempDir()
+ spark.conf.set("spark.sql.streaming.checkpointLocation",
fakeCheckpoint.getCanonicalPath)
+ }
+
+ testQuietly("create microbatch with only microbatch support") {
+ val query = df.writeStream.format("fake-microbatch-only").start()
+ query.stop()
+ }
+
+ testQuietly("create microbatch with both support") {
+ val query = df.writeStream.format("fake-both-modes").start()
+ query.stop()
+ }
+
+ testQuietly("create continuous with only continuous support") {
+ val query = df.writeStream
+ .format("fake-continuous-only")
+ .trigger(Trigger.Continuous(100))
+ .start()
+ query.stop()
+ }
+
+ testQuietly("create continuous with both support") {
+ val query = df.writeStream
+ .format("fake-both-modes")
+ .trigger(Trigger.Continuous(100))
+ .start()
+ query.stop()
+ }
+
+ test("microbatch with only continuous support") {
+ val ex = intercept[UnsupportedOperationException] {
+ df.writeStream.format("fake-continuous-only").start()
+ }
+
+ assert(ex.getMessage.contains(
+ "Data source fake-continuous-only does not support streamed
writing"))
+ }
+
+ test("microbatch with no support") {
+ val ex = intercept[UnsupportedOperationException] {
+ df.writeStream.format("fake-neither-mode").start()
+ }
+
+ assert(ex.getMessage.contains(
+ "Data source fake-neither-mode does not support streamed writing"))
+ }
+
+ test("continuous with only microbatch support") {
+ val ex = intercept[AnalysisException] {
+ df.writeStream
+ .format("fake-microbatch-only")
+ .trigger(Trigger.Continuous(100))
+ .start()
+ }
+
+ assert(ex.getMessage.contains(
+ "Data source fake-microbatch-only does not support continuous
writing"))
+ }
+
+ test("continuous with no support") {
+ val ex = intercept[AnalysisException] {
+ df.writeStream
+ .format("fake-neither-mode")
+ .trigger(Trigger.Continuous(100))
+ .start()
+ }
+
+ assert(ex.getMessage.contains(
+ "Data source fake-neither-mode does not support continuous writing"))
+ }
--- End diff --
Added tests for all 4*4*3 combinations of source/sink/trigger. Note that:
* I had to revert the earlier change to initialize
ContinuousExecution.sources to null, because it turns out this interferes with
error generation on newly constructed executions.
* Two of the cases don't throw the error until after start(). This will
take a decent amount of disruptive changes to fix; the problem is that
DataStreamWriter doesn't have direct visibility to what sources were used to
generate it. We'd need to crawl the tree similarly to how we do it in the
execution.
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