使用MSExcelLowFootprintParser读取指定XLSX工作表时遇NullPointerException

尝试使用org.zuinnote.spark.office.excel读取包含3个工作表的XLSX文件中指定工作表**"Most Runs Over - 2010"**为Spark DataFrame，采用MSExcelLowFootprintParser解析器时抛出空指针异常，但读取所有工作表或不使用低内存解析器时程序可正常运行。

使用的版本信息：

• org.apache.poi 4.1.2
• spark-hadoopoffice-ds 1.3.9
• Spark 3.1.2

代码实现 #

val hadoopConf = new Configuration()
val spark = SparkSession.builder()
  .appName("ExcelReadingExample")
  .master("local[*]")
  .getOrCreate()


spark.sparkContext.hadoopConfiguration.set("hadoopoffice.read.lowFootprint", "true")
spark.sparkContext.hadoopConfiguration.set("hadoopoffice.read.header.read","true")
spark.sparkContext.hadoopConfiguration.set("hadoopoffice.read.sheets", "Most Runs Over - 2010")

spark.sparkContext.setLogLevel("INFO")
val schema = StructType(Seq(
    StructField("col", IntegerType, nullable = true),
    StructField("col1", StringType, nullable = true),
    StructField("Runs", IntegerType, nullable = true),
    StructField("BF", IntegerType, nullable = true),
    StructField("SR", DoubleType, nullable = true),
    StructField("s4", IntegerType, nullable = true),
    StructField("s6", IntegerType, nullable = true),
    StructField("Against", StringType, nullable = true),
    StructField("Venue", StringType, nullable = true),
    StructField("Match Date", StringType, nullable = true),
    StructField("Match Time", StringType, nullable = true),
    StructField("Match Partition Time", StringType, nullable = true)
))

val df: Dataset[Row] = spark.read
  .format("org.zuinnote.spark.office.excel")
  .option("hadoopoffice.read.sheets", "Most Runs Over - 2010")
  .option("read.spark.simpleMode","true")
  .option("read.lowFootprint", "true")
  .option("multiLine", "true")
  .option("read.spark.simpleMode.maxInferRows","1000")
  .option("read.header.read","true")
  .schema(schema)
  .load("D:\\excel\\spark-hadoopoffice-ds-s2-ho-1.3.9\\spark-hadoopoffice-ds-s2-ho-1.3.9\\src\\resources\\MostRuns_Over2008.xlsx")

df.show();

抛出的异常 #

java.lang.NullPointerException
at org.apache.poi.xssf.eventusermodel.XSSFReader$SheetIterator.getSheetName(XSSFReader.java:325)
at org.zuinnote.hadoop.office.format.common.parser.msexcel.MSExcelLowFootprintParser.processOPCPackage(MSExcelLowFootprintParser.java:374)
at org.zuinnote.hadoop.office.format.common.parser.msexcel.MSExcelLowFootprintParser.parse(MSExcelLowFootprintParser.java:267)
at org.zuinnote.hadoop.office.format.common.OfficeReader.parse(OfficeReader.java:92)
at org.zuinnote.hadoop.office.format.mapreduce.AbstractSpreadSheetDocumentRecordReader.initialize(AbstractSpreadSheetDocumentRecordReader.java:138)
at org.zuinnote.spark.office.excel.HadoopFileExcelReader.<init>(HadoopFileExcelReader.scala:55)
at org.zuinnote.spark.office.excel.DefaultSource.$anonfun$buildReader$4(DefaultSource.scala:322)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:148)
at org.apache.spark.sql.execution.datasources.FileFormat$$anon$1.apply(FileFormat.scala:133)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.org$apache$spark$sql$execution$datasources$FileScanRDD$$anon$$readCurrentFile(FileScanRDD.scala:185)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:240)
at org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:159)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown Source)
at org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:35)
at org.apache.spark.sql.execution.WholeStageCodegenExec$$anon$1.hasNext(WholeStageCodegenExec.scala:832)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:458)
at scala.collection.Iterator$SliceIterator.hasNext(Iterator.scala:266)
at scala.collection.Iterator.foreach(Iterator.scala:941)
at scala.collection.Iterator.foreach$(Iterator.scala:941)
at scala.collection.AbstractIterator.foreach(Iterator.scala:1429)
at scala.collection.generic.Growable.$plus$plus$eq(Growable.scala:62)
at scala.collection.generic.Growable.$plus$plus$eq$(Growable.scala:53)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:105)
at scala.collection.mutable.ArrayBuffer.$plus$plus$eq(ArrayBuffer.scala:49)
at scala.collection.TraversableOnce.to(TraversableOnce.scala:315)
at scala.collection.TraversableOnce.to$(TraversableOnce.scala:313)
at scala.collection.AbstractIterator.to(Iterator.scala:1429)
at scala.collection.TraversableOnce.toBuffer(TraversableOnce.scala:307)
at scala.collection.TraversableOnce.toBuffer$(TraversableOnce.scala:307)
at scala.collection.AbstractIterator.toBuffer(Iterator.scala:1429)
at scala.collection.TraversableOnce.toArray(TraversableOnce.scala:294)
at scala.collection.TraversableOnce.toArray$(TraversableOnce.scala:288)
at scala.collection.AbstractIterator.toArray(Iterator.scala:1429)
at org.apache.spark.rdd.RDD.$anonfun$take$2(RDD.scala:1449)
at org.apache.spark.SparkContext.$anonfun$runJob$5(SparkContext.scala:2281)
at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:90)
at org.apache.spark.scheduler.Task.run(Task.scala:131)
at org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$3(Executor.scala:497)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1439)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:500)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:750)

内容的提问来源于stack exchange，提问作者Ashish Mishra