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[SPARK-26673][SQL] File source V2 writes: create framework and migrat…
…e ORC ## What changes were proposed in this pull request? Create a framework for write path of File Source V2. Also, migrate write path of ORC to V2. Supported: * Write to file as Dataframe Not Supported: * Partitioning, which is still under development in the data source V2 project. * Bucketing, which is still under development in the data source V2 project. * Catalog. ## How was this patch tested? Unit test Closes #23601 from gengliangwang/orc_write. Authored-by: Gengliang Wang <[email protected]> Signed-off-by: Wenchen Fan <[email protected]>
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sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/FileBatchWrite.scala
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| /* | ||
| * 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.execution.datasources.v2 | ||
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| import org.apache.hadoop.mapreduce.Job | ||
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| import org.apache.spark.internal.Logging | ||
| import org.apache.spark.internal.io.FileCommitProtocol | ||
| import org.apache.spark.sql.execution.datasources.{WriteJobDescription, WriteTaskResult} | ||
| import org.apache.spark.sql.execution.datasources.FileFormatWriter.processStats | ||
| import org.apache.spark.sql.sources.v2.writer._ | ||
| import org.apache.spark.util.SerializableConfiguration | ||
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| class FileBatchWrite( | ||
| job: Job, | ||
| description: WriteJobDescription, | ||
| committer: FileCommitProtocol) | ||
| extends BatchWrite with Logging { | ||
| override def commit(messages: Array[WriterCommitMessage]): Unit = { | ||
| val results = messages.map(_.asInstanceOf[WriteTaskResult]) | ||
| committer.commitJob(job, results.map(_.commitMsg)) | ||
| logInfo(s"Write Job ${description.uuid} committed.") | ||
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| processStats(description.statsTrackers, results.map(_.summary.stats)) | ||
| logInfo(s"Finished processing stats for write job ${description.uuid}.") | ||
| } | ||
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| override def useCommitCoordinator(): Boolean = false | ||
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| override def abort(messages: Array[WriterCommitMessage]): Unit = { | ||
| committer.abortJob(job) | ||
| } | ||
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| override def createBatchWriterFactory(): DataWriterFactory = { | ||
| val conf = new SerializableConfiguration(job.getConfiguration) | ||
| FileWriterFactory(description, committer, conf) | ||
| } | ||
| } | ||
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158 changes: 158 additions & 0 deletions
158
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/v2/FileWriteBuilder.scala
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| /* | ||
| * 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.execution.datasources.v2 | ||
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| import java.util.UUID | ||
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| import scala.collection.JavaConverters._ | ||
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| import org.apache.hadoop.conf.Configuration | ||
| import org.apache.hadoop.fs.Path | ||
| import org.apache.hadoop.mapreduce.Job | ||
| import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat | ||
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| import org.apache.spark.internal.io.FileCommitProtocol | ||
| import org.apache.spark.sql.{AnalysisException, SaveMode, SparkSession} | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.catalyst.util.{CaseInsensitiveMap, DateTimeUtils} | ||
| import org.apache.spark.sql.execution.datasources.{BasicWriteJobStatsTracker, DataSource, OutputWriterFactory, WriteJobDescription} | ||
| import org.apache.spark.sql.execution.metric.SQLMetric | ||
| import org.apache.spark.sql.internal.SQLConf | ||
| import org.apache.spark.sql.sources.v2.DataSourceOptions | ||
| import org.apache.spark.sql.sources.v2.writer.{BatchWrite, SupportsSaveMode, WriteBuilder} | ||
| import org.apache.spark.sql.types.StructType | ||
| import org.apache.spark.util.SerializableConfiguration | ||
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| abstract class FileWriteBuilder(options: DataSourceOptions) | ||
| extends WriteBuilder with SupportsSaveMode { | ||
| private var schema: StructType = _ | ||
| private var queryId: String = _ | ||
| private var mode: SaveMode = _ | ||
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| override def withInputDataSchema(schema: StructType): WriteBuilder = { | ||
| this.schema = schema | ||
| this | ||
| } | ||
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| override def withQueryId(queryId: String): WriteBuilder = { | ||
| this.queryId = queryId | ||
| this | ||
| } | ||
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| override def mode(mode: SaveMode): WriteBuilder = { | ||
| this.mode = mode | ||
| this | ||
| } | ||
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| override def buildForBatch(): BatchWrite = { | ||
| validateInputs() | ||
| val pathName = options.paths().head | ||
| val path = new Path(pathName) | ||
| val sparkSession = SparkSession.active | ||
| val optionsAsScala = options.asMap().asScala.toMap | ||
| val hadoopConf = sparkSession.sessionState.newHadoopConfWithOptions(optionsAsScala) | ||
| val job = getJobInstance(hadoopConf, path) | ||
| val committer = FileCommitProtocol.instantiate( | ||
| sparkSession.sessionState.conf.fileCommitProtocolClass, | ||
| jobId = java.util.UUID.randomUUID().toString, | ||
| outputPath = pathName) | ||
| lazy val description = | ||
| createWriteJobDescription(sparkSession, hadoopConf, job, pathName, optionsAsScala) | ||
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| val fs = path.getFileSystem(hadoopConf) | ||
| mode match { | ||
| case SaveMode.ErrorIfExists if fs.exists(path) => | ||
| val qualifiedOutputPath = path.makeQualified(fs.getUri, fs.getWorkingDirectory) | ||
| throw new AnalysisException(s"path $qualifiedOutputPath already exists.") | ||
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| case SaveMode.Ignore if fs.exists(path) => | ||
| null | ||
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| case SaveMode.Overwrite => | ||
| committer.deleteWithJob(fs, path, true) | ||
| committer.setupJob(job) | ||
| new FileBatchWrite(job, description, committer) | ||
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| case _ => | ||
| committer.setupJob(job) | ||
| new FileBatchWrite(job, description, committer) | ||
| } | ||
| } | ||
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| /** | ||
| * Prepares a write job and returns an [[OutputWriterFactory]]. Client side job preparation can | ||
| * be put here. For example, user defined output committer can be configured here | ||
| * by setting the output committer class in the conf of spark.sql.sources.outputCommitterClass. | ||
| */ | ||
| def prepareWrite( | ||
| sqlConf: SQLConf, | ||
| job: Job, | ||
| options: Map[String, String], | ||
| dataSchema: StructType): OutputWriterFactory | ||
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| private def validateInputs(): Unit = { | ||
| assert(schema != null, "Missing input data schema") | ||
| assert(queryId != null, "Missing query ID") | ||
| assert(mode != null, "Missing save mode") | ||
| assert(options.paths().length == 1) | ||
| DataSource.validateSchema(schema) | ||
| } | ||
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| private def getJobInstance(hadoopConf: Configuration, path: Path): Job = { | ||
| val job = Job.getInstance(hadoopConf) | ||
| job.setOutputKeyClass(classOf[Void]) | ||
| job.setOutputValueClass(classOf[InternalRow]) | ||
| FileOutputFormat.setOutputPath(job, path) | ||
| job | ||
| } | ||
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| private def createWriteJobDescription( | ||
| sparkSession: SparkSession, | ||
| hadoopConf: Configuration, | ||
| job: Job, | ||
| pathName: String, | ||
| options: Map[String, String]): WriteJobDescription = { | ||
| val caseInsensitiveOptions = CaseInsensitiveMap(options) | ||
| // Note: prepareWrite has side effect. It sets "job". | ||
| val outputWriterFactory = | ||
| prepareWrite(sparkSession.sessionState.conf, job, caseInsensitiveOptions, schema) | ||
| val allColumns = schema.toAttributes | ||
| val metrics: Map[String, SQLMetric] = BasicWriteJobStatsTracker.metrics | ||
| val serializableHadoopConf = new SerializableConfiguration(hadoopConf) | ||
| val statsTracker = new BasicWriteJobStatsTracker(serializableHadoopConf, metrics) | ||
| // TODO: after partitioning is supported in V2: | ||
| // 1. filter out partition columns in `dataColumns`. | ||
| // 2. Don't use Seq.empty for `partitionColumns`. | ||
| new WriteJobDescription( | ||
| uuid = UUID.randomUUID().toString, | ||
| serializableHadoopConf = new SerializableConfiguration(job.getConfiguration), | ||
| outputWriterFactory = outputWriterFactory, | ||
| allColumns = allColumns, | ||
| dataColumns = allColumns, | ||
| partitionColumns = Seq.empty, | ||
| bucketIdExpression = None, | ||
| path = pathName, | ||
| customPartitionLocations = Map.empty, | ||
| maxRecordsPerFile = caseInsensitiveOptions.get("maxRecordsPerFile").map(_.toLong) | ||
| .getOrElse(sparkSession.sessionState.conf.maxRecordsPerFile), | ||
| timeZoneId = caseInsensitiveOptions.get(DateTimeUtils.TIMEZONE_OPTION) | ||
| .getOrElse(sparkSession.sessionState.conf.sessionLocalTimeZone), | ||
| statsTrackers = Seq(statsTracker) | ||
| ) | ||
| } | ||
| } | ||
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