Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/19269#discussion_r145018796
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/sources/v2/SimpleWritableDataSource.scala
---
@@ -0,0 +1,252 @@
+/*
+ * 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.sources.v2
+
+import java.io.{BufferedReader, InputStreamReader, IOException}
+import java.text.SimpleDateFormat
+import java.util.{Collections, Date, List => JList, Locale, Optional, UUID}
+
+import scala.collection.JavaConverters._
+
+import org.apache.hadoop.conf.Configuration
+import org.apache.hadoop.fs.{FileSystem, FSDataInputStream, Path}
+
+import org.apache.spark.SparkContext
+import org.apache.spark.sql.{Row, SaveMode}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.sources.v2.reader.{DataReader,
DataSourceV2Reader, ReadTask}
+import org.apache.spark.sql.sources.v2.writer._
+import org.apache.spark.sql.types.{DataType, StructType}
+import org.apache.spark.util.SerializableConfiguration
+
+/**
+ * A HDFS based transactional writable data source.
+ * Each task writes data to
`target/_temporary/jobId/$jobId-$partitionId-$attemptNumber`.
+ * Each job moves files from `target/_temporary/jobId/` to `target`.
+ */
+class SimpleWritableDataSource extends DataSourceV2 with ReadSupport with
WriteSupport {
+
+ private val schema = new StructType().add("i", "long").add("j", "long")
+
+ class Reader(path: String, conf: Configuration) extends
DataSourceV2Reader {
+ override def readSchema(): StructType = schema
+
+ override def createReadTasks(): JList[ReadTask[Row]] = {
+ val dataPath = new Path(path)
+ val fs = dataPath.getFileSystem(conf)
+ if (fs.exists(dataPath)) {
+ fs.listStatus(dataPath).filterNot { status =>
+ val name = status.getPath.getName
+ name.startsWith("_") || name.startsWith(".")
+ }.map { f =>
+ val serializableConf = new SerializableConfiguration(conf)
+ new SimpleCSVReadTask(f.getPath.toUri.toString,
serializableConf): ReadTask[Row]
+ }.toList.asJava
+ } else {
+ Collections.emptyList()
+ }
+ }
+ }
+
+ class Writer(path: String, conf: Configuration) extends
DataSourceV2Writer {
+ // We can't get the real spark job id here, so we use a timestamp and
random UUID to simulate
+ // a unique job id.
+ protected val jobId = new SimpleDateFormat("yyyyMMddHHmmss",
Locale.US).format(new Date()) +
+ "-" + UUID.randomUUID()
+
+ override def createWriterFactory(): DataWriterFactory[Row] = {
+ new SimpleCSVDataWriterFactory(path, jobId, new
SerializableConfiguration(conf))
+ }
+
+ override def commit(messages: Array[WriterCommitMessage]): Unit = {
+ val finalPath = new Path(path)
+ val jobPath = new Path(new Path(finalPath, "_temporary"), jobId)
+ val fs = jobPath.getFileSystem(conf)
+ try {
+ for (file <- fs.listStatus(jobPath).map(_.getPath)) {
+ val dest = new Path(finalPath, file.getName)
+ if(!fs.rename(file, dest)) {
+ throw new IOException(s"failed to rename($file, $dest)")
+ }
+ }
+ } finally {
+ fs.delete(jobPath, true)
+ }
+ }
+
+ override def abort(messages: Array[WriterCommitMessage]): Unit = {
+ val jobPath = new Path(new Path(path, "_temporary"), jobId)
+ val fs = jobPath.getFileSystem(conf)
+ fs.delete(jobPath, true)
+ }
+ }
+
+ class InternalRowWriter(path: String, conf: Configuration)
+ extends Writer(path, conf) with SupportsWriteInternalRow {
+
+ override def createWriterFactory(): DataWriterFactory[Row] = {
+ throw new IllegalArgumentException("not expected!")
+ }
+
+ override def createInternalRowWriterFactory():
DataWriterFactory[InternalRow] = {
+ new InternalRowCSVDataWriterFactory(path, jobId, new
SerializableConfiguration(conf))
+ }
+ }
+
+ override def createReader(options: DataSourceV2Options):
DataSourceV2Reader = {
+ val path = new Path(options.get("path").get())
+ val conf = SparkContext.getActive.get.hadoopConfiguration
+ new Reader(path.toUri.toString, conf)
+ }
+
+ override def createWriter(
+ schema: StructType,
+ mode: SaveMode,
+ options: DataSourceV2Options): Optional[DataSourceV2Writer] = {
+ assert(DataType.equalsStructurally(schema.asNullable,
this.schema.asNullable))
+
assert(!SparkContext.getActive.get.conf.getBoolean("spark.speculation", false))
+
+ val path = new Path(options.get("path").get())
+ val internal = options.get("internal").isPresent
+ val conf = SparkContext.getActive.get.hadoopConfiguration
+ val fs = path.getFileSystem(conf)
+
+ if (mode == SaveMode.ErrorIfExists) {
+ if (fs.exists(path)) {
+ throw new RuntimeException("data already exists.")
+ }
+ }
+ if (mode == SaveMode.Ignore) {
+ if (fs.exists(path)) {
+ return Optional.empty()
+ }
+ }
+ if (mode == SaveMode.Overwrite) {
+ if (fs.exists(path)) {
+ fs.delete(path, true)
--- End diff --
cc @steveloughran , overwrite needs this check, because we need to delete
the root dir here. The writers always create file with unique name, so we can't
delete old files while overwriting.
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