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需求背景： 有一些xls大文件数据。使用spark-excel（spark-excel）来读取时，文件太大会oom；工具提供的流式读取参数：maxRowsInMemory 也只支持xlsx类型文件。搜索了poi流式读取xls的方案，HSSFEventFactory提供了HSSFListener进行逐条处理数据。所以编写了spark读取xls的简易source。代码如下：

spark.read.format(“xls”).option(“path”, logPath).load()能够跑通。但是对应xls大文件还是会oom。具体了解后得到原因：SSTRecord存储了整个excel中所有字符串去重后结果，LabelSSTRecord只是存储了该字符串值在SSTRecord中的索引位置。所以在逐条处理xls文件数据的时候遇到SSTRecord还是会oom。

结论：没实现成功，失败；找不到其它实习方案，只能python脚本提前将xls文件转为csv。

package cn.keytop.source.xlsimport org.apache.hadoop.fs.{FileSystem, Path}
import org.apache.poi.hssf.eventusermodel._
import org.apache.poi.hssf.eventusermodel.dummyrecord.LastCellOfRowDummyRecord
import org.apache.poi.hssf.record._
import org.apache.poi.hssf.usermodel.HSSFDataFormatter
import org.apache.poi.poifs.filesystem.POIFSFileSystem
import org.apache.spark.sql.types._
import org.apache.spark.sql.{DataFrame, Row, SQLContext}import scala.collection.mutable.ArrayBuffer/*** @author: 王建成* @since: 2025/4/18 13:46* @description: coding需求和地址 编写一个spark source plugin来读取xls大文件数据*/              
class XLSReader {def read(pathStr: String, sqlContext: SQLContext): org.apache.spark.sql.DataFrame = {val hadoopConf = sqlContext.sparkContext.hadoopConfigurationval fsPath = new Path(pathStr)val fs = fsPath.getFileSystem(hadoopConf)// 获取所有 .xls 文件val allFiles: Array[Path] = {if (fs.isDirectory(fsPath)) {fs.listStatus(fsPath).filter(f => f.isFile && f.getPath.getName.toLowerCase.endsWith(".xls")).map(_.getPath)} else {Array(fsPath)}}// 每个文件读取出一个 DataFrame，然后合并val dfs = allFiles.map { filePath =>println(s"Reading XLS file: $filePath")readSingleXLS(filePath, fs, sqlContext)}dfs.reduceOption(_.union(_)).getOrElse {// 如果目录下没有任何 xls 文件sqlContext.createDataFrame(sqlContext.sparkContext.emptyRDD[Row], StructType(Nil))}}private def readSingleXLS(path: Path, fs: FileSystem, sqlContext: SQLContext): DataFrame = {val inputStream = fs.open(path)val fsPOI = new POIFSFileSystem(inputStream)val rowsBuffer = ArrayBuffer[ArrayBuffer[String]]()var sstRecord: SSTRecord = nullvar headers: ArrayBuffer[String] = ArrayBuffer()var currentRow = ArrayBuffer[String]()var currentRowNum = -1val listener = new HSSFListener {val formatter = new HSSFDataFormatter()override def processRecord(record: Record): Unit = {record match {case sst: SSTRecord =>sstRecord = sstcase label: LabelSSTRecord =>val value = sstRecord.getString(label.getSSTIndex).toStringensureSize(currentRow, label.getColumn + 1, "")currentRow(label.getColumn) = valuecurrentRowNum = label.getRowcase number: NumberRecord =>val value = number.getValue.toStringensureSize(currentRow, number.getColumn + 1, "")currentRow(number.getColumn) = valuecurrentRowNum = number.getRowcase _: LastCellOfRowDummyRecord =>if (currentRow.nonEmpty) {if (currentRowNum == 0 && headers.isEmpty) {headers = currentRow.clone()} else {rowsBuffer += currentRow.clone()}}currentRow.clear()currentRowNum = -1case _ =>}}def ensureSize(buffer: ArrayBuffer[String], size: Int, default: String): Unit = {while (buffer.size < size) {buffer += default}}}val factory = new HSSFEventFactory()val request = new HSSFRequest()val listener1 = new MissingRecordAwareHSSFListener(listener)val listener2 = new FormatTrackingHSSFListener(listener1)request.addListenerForAllRecords(listener2)factory.processWorkbookEvents(request, fsPOI)val schema = StructType(headers.map(name => StructField(name, StringType, nullable = true)))val rows = rowsBuffer.map(Row.fromSeq)sqlContext.createDataFrame(sqlContext.sparkContext.parallelize(rows), schema)}}

package cn.keytop.source.xlsimport org.apache.spark.rdd.RDD
import org.apache.spark.sql.sources.{BaseRelation, DataSourceRegister, RelationProvider, TableScan}
import org.apache.spark.sql.types.StructType
import org.apache.spark.sql.{Row, SQLContext}import java.io.Serializable
/*** @author: 王建成* @since: 2025/4/18 13:46* @description: coding需求和地址 编写一个spark source plugin来读取xls大文件数据*/
class DefaultSource extends RelationProvider with DataSourceRegister with Serializable{override def shortName(): String = "xls"override def createRelation(sqlContext: SQLContext, parameters: Map[String, String]): BaseRelation = {val path = parameters.getOrElse("path", throw new IllegalArgumentException("Missing path"))val reader = new XLSReader()val df = reader.read(path, sqlContext)new BaseRelation with TableScan {override def sqlContext: SQLContext = sqlContextoverride def schema: StructType = df.schemaoverride def buildScan(): RDD[Row] = df.rdd}}
}