[SPARK-19610][SQL] Support parsing multiline CSV files #16976
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| Joe,20,"Hi, | ||
| I am Jeo" | ||
| Tom,30,"My name is Tom" | ||
| Hyukjin,25,"I am Hyukjin | ||
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| I love Spark!" | ||
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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. | ||
| */ | ||
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| package org.apache.spark.sql.execution.datasources.csv | ||
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| import java.io.InputStream | ||
| import java.nio.charset.{Charset, StandardCharsets} | ||
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| import com.univocity.parsers.csv.{CsvParser, CsvParserSettings} | ||
| import org.apache.hadoop.conf.Configuration | ||
| import org.apache.hadoop.fs.{FileStatus, Path} | ||
| import org.apache.hadoop.io.{LongWritable, Text} | ||
| import org.apache.hadoop.mapred.TextInputFormat | ||
| import org.apache.hadoop.mapreduce.Job | ||
| import org.apache.hadoop.mapreduce.lib.input.FileInputFormat | ||
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| import org.apache.spark.TaskContext | ||
| import org.apache.spark.input.{PortableDataStream, StreamInputFormat} | ||
| import org.apache.spark.rdd.{BinaryFileRDD, RDD} | ||
| import org.apache.spark.sql.{Dataset, Encoders, SparkSession} | ||
| import org.apache.spark.sql.catalyst.InternalRow | ||
| import org.apache.spark.sql.execution.datasources._ | ||
| import org.apache.spark.sql.execution.datasources.text.TextFileFormat | ||
| import org.apache.spark.sql.types.StructType | ||
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| /** | ||
| * Common functions for parsing CSV files | ||
| */ | ||
| abstract class CSVDataSource extends Serializable { | ||
| def isSplitable: Boolean | ||
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| /** | ||
| * Parse a [[PartitionedFile]] into [[InternalRow]] instances. | ||
| */ | ||
| def readFile( | ||
| conf: Configuration, | ||
| file: PartitionedFile, | ||
| parser: UnivocityParser, | ||
| parsedOptions: CSVOptions): Iterator[InternalRow] | ||
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| /** | ||
| * Infers the schema from `inputPaths` files. | ||
| */ | ||
| def infer( | ||
| sparkSession: SparkSession, | ||
| inputPaths: Seq[FileStatus], | ||
| parsedOptions: CSVOptions): Option[StructType] | ||
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| /** | ||
| * Generates a header from the given row which is null-safe and duplicate-safe. | ||
| */ | ||
| protected def makeSafeHeader( | ||
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| row: Array[String], | ||
| caseSensitive: Boolean, | ||
| options: CSVOptions): Array[String] = { | ||
| if (options.headerFlag) { | ||
| val duplicates = { | ||
| val headerNames = row.filter(_ != null) | ||
| .map(name => if (caseSensitive) name else name.toLowerCase) | ||
| headerNames.diff(headerNames.distinct).distinct | ||
| } | ||
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| row.zipWithIndex.map { case (value, index) => | ||
| if (value == null || value.isEmpty || value == options.nullValue) { | ||
| // When there are empty strings or the values set in `nullValue`, put the | ||
| // index as the suffix. | ||
| s"_c$index" | ||
| } else if (!caseSensitive && duplicates.contains(value.toLowerCase)) { | ||
| // When there are case-insensitive duplicates, put the index as the suffix. | ||
| s"$value$index" | ||
| } else if (duplicates.contains(value)) { | ||
| // When there are duplicates, put the index as the suffix. | ||
| s"$value$index" | ||
| } else { | ||
| value | ||
| } | ||
| } | ||
| } else { | ||
| row.zipWithIndex.map { case (_, index) => | ||
| // Uses default column names, "_c#" where # is its position of fields | ||
| // when header option is disabled. | ||
| s"_c$index" | ||
| } | ||
| } | ||
| } | ||
| } | ||
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| object CSVDataSource { | ||
| def apply(options: CSVOptions): CSVDataSource = { | ||
| if (options.wholeFile) { | ||
| WholeFileCSVDataSource | ||
| } else { | ||
| TextInputCSVDataSource | ||
| } | ||
| } | ||
| } | ||
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| object TextInputCSVDataSource extends CSVDataSource { | ||
| override val isSplitable: Boolean = true | ||
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| override def readFile( | ||
| conf: Configuration, | ||
| file: PartitionedFile, | ||
| parser: UnivocityParser, | ||
| parsedOptions: CSVOptions): Iterator[InternalRow] = { | ||
| val lines = { | ||
| val linesReader = new HadoopFileLinesReader(file, conf) | ||
| Option(TaskContext.get()).foreach(_.addTaskCompletionListener(_ => linesReader.close())) | ||
| linesReader.map { line => | ||
| new String(line.getBytes, 0, line.getLength, parsedOptions.charset) | ||
| } | ||
| } | ||
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| val shouldDropHeader = parsedOptions.headerFlag && file.start == 0 | ||
| UnivocityParser.parseIterator(lines, shouldDropHeader, parser) | ||
| } | ||
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| override def infer( | ||
| sparkSession: SparkSession, | ||
| inputPaths: Seq[FileStatus], | ||
| parsedOptions: CSVOptions): Option[StructType] = { | ||
| val csv: Dataset[String] = createBaseDataset(sparkSession, inputPaths, parsedOptions) | ||
| val firstLine: String = CSVUtils.filterCommentAndEmpty(csv, parsedOptions).first() | ||
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| val firstRow = new CsvParser(parsedOptions.asParserSettings).parseLine(firstLine) | ||
| val caseSensitive = sparkSession.sessionState.conf.caseSensitiveAnalysis | ||
| val header = makeSafeHeader(firstRow, caseSensitive, parsedOptions) | ||
| val tokenRDD = csv.rdd.mapPartitions { iter => | ||
| val filteredLines = CSVUtils.filterCommentAndEmpty(iter, parsedOptions) | ||
| val linesWithoutHeader = | ||
| CSVUtils.filterHeaderLine(filteredLines, firstLine, parsedOptions) | ||
| val parser = new CsvParser(parsedOptions.asParserSettings) | ||
| linesWithoutHeader.map(parser.parseLine) | ||
| } | ||
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| Some(CSVInferSchema.infer(tokenRDD, header, parsedOptions)) | ||
| } | ||
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| private def createBaseDataset( | ||
| sparkSession: SparkSession, | ||
| inputPaths: Seq[FileStatus], | ||
| options: CSVOptions): Dataset[String] = { | ||
| val paths = inputPaths.map(_.getPath.toString) | ||
| if (Charset.forName(options.charset) == StandardCharsets.UTF_8) { | ||
| sparkSession.baseRelationToDataFrame( | ||
| DataSource.apply( | ||
| sparkSession, | ||
| paths = paths, | ||
| className = classOf[TextFileFormat].getName | ||
| ).resolveRelation(checkFilesExist = false)) | ||
| .select("value").as[String](Encoders.STRING) | ||
| } else { | ||
| val charset = options.charset | ||
| val rdd = sparkSession.sparkContext | ||
| .hadoopFile[LongWritable, Text, TextInputFormat](paths.mkString(",")) | ||
| .mapPartitions(_.map(pair => new String(pair._2.getBytes, 0, pair._2.getLength, charset))) | ||
| sparkSession.createDataset(rdd)(Encoders.STRING) | ||
| } | ||
| } | ||
| } | ||
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| object WholeFileCSVDataSource extends CSVDataSource { | ||
| override val isSplitable: Boolean = false | ||
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| override def readFile( | ||
| conf: Configuration, | ||
| file: PartitionedFile, | ||
| parser: UnivocityParser, | ||
| parsedOptions: CSVOptions): Iterator[InternalRow] = { | ||
| UnivocityParser.parseStream( | ||
| CodecStreams.createInputStreamWithCloseResource(conf, file.filePath), | ||
| parsedOptions.headerFlag, | ||
| parser) | ||
| } | ||
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| override def infer( | ||
| sparkSession: SparkSession, | ||
| inputPaths: Seq[FileStatus], | ||
| parsedOptions: CSVOptions): Option[StructType] = { | ||
| val csv: RDD[PortableDataStream] = createBaseRdd(sparkSession, inputPaths, parsedOptions) | ||
| val maybeFirstRow: Option[Array[String]] = csv.flatMap { lines => | ||
| UnivocityParser.tokenizeStream( | ||
| CodecStreams.createInputStreamWithCloseResource(lines.getConfiguration, lines.getPath()), | ||
| false, | ||
| new CsvParser(parsedOptions.asParserSettings)) | ||
| }.take(1).headOption | ||
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| if (maybeFirstRow.isDefined) { | ||
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| val firstRow = maybeFirstRow.get | ||
| val caseSensitive = sparkSession.sessionState.conf.caseSensitiveAnalysis | ||
| val header = makeSafeHeader(firstRow, caseSensitive, parsedOptions) | ||
| val tokenRDD = csv.flatMap { lines => | ||
| UnivocityParser.tokenizeStream( | ||
| CodecStreams.createInputStreamWithCloseResource(lines.getConfiguration, lines.getPath()), | ||
| parsedOptions.headerFlag, | ||
| new CsvParser(parsedOptions.asParserSettings)) | ||
| } | ||
| Some(CSVInferSchema.infer(tokenRDD, header, parsedOptions)) | ||
| } else { | ||
| // If the first row could not be read, just return the empty schema. | ||
| Some(StructType(Nil)) | ||
| } | ||
| } | ||
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| private def createBaseRdd( | ||
| sparkSession: SparkSession, | ||
| inputPaths: Seq[FileStatus], | ||
| options: CSVOptions): RDD[PortableDataStream] = { | ||
| val paths = inputPaths.map(_.getPath) | ||
| val name = paths.mkString(",") | ||
| val job = Job.getInstance(sparkSession.sessionState.newHadoopConf()) | ||
| FileInputFormat.setInputPaths(job, paths: _*) | ||
| val conf = job.getConfiguration | ||
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| val rdd = new BinaryFileRDD( | ||
| sparkSession.sparkContext, | ||
| classOf[StreamInputFormat], | ||
| classOf[String], | ||
| classOf[PortableDataStream], | ||
| conf, | ||
| sparkSession.sparkContext.defaultMinPartitions) | ||
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| // Only returns `PortableDataStream`s without paths. | ||
| rdd.setName(s"CSVFile: $name").values | ||
| } | ||
| } | ||
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The same here.