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https://issues.apache.org/jira/browse/SPARK-49812?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17885297#comment-17885297
]
Martin Andersson commented on SPARK-49812:
------------------------------------------
Changing the schema to a single column results in a single row data frame with
a null value for zstd compressed files.
{code}
+--------+
|some_col|
+--------+
| NULL|
+--------+
{code}
> NPE when reading empty zstd compressed csv file
> -----------------------------------------------
>
> Key: SPARK-49812
> URL: https://issues.apache.org/jira/browse/SPARK-49812
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.5.3
> Environment: Ubuntu 22.04
> Java 17
> spark 3.5.3
> Reporter: Martin Andersson
> Priority: Minor
>
> Reading an empty zstd compressed csv file results in a NPE. The same file
> works fine when not compressed.
> {code:sh}
> $touch empty.csv
> $zstd < empty.csv > empty.csv.zst
> {code}
> This works as expected - resulting in an empty DataFrame.
> {code:java}
> spark.read()
> .option("header", "false")
> .option("lineSep", "|")
> .option("multiLine", "true")
> .option("quote", "")
> .schema("some_col string, other_col string")
> .csv("empty.csv")
> .show();
> {code}
> Changing the path to "empty.csv.zst" triggers an exception. The exception is
> only trigger for zstd files when both properties "multiLine" and "quote" are
> set.
> {code:java}
> INFO DAGScheduler: ResultStage 0 (show at Main.java:24) failed in 0.408 s due
> to Job aborted due to stage failure: Task 0 in stage 0.0 failed 1 times, most
> recent failure: Lost task 0.0 in stage 0.0 (TID 0) (192.168.32.18 executor
> driver): org.apache.spark.SparkException: Encountered error while reading
> file file:///tmp/empty.csv.zst. Details:
> at
> org.apache.spark.sql.errors.QueryExecutionErrors$.cannotReadFilesError(QueryExecutionErrors.scala:864)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:293)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:129)
> at scala.collection.Iterator$$anon$9.hasNext(Iterator.scala:576)
> at
> org.apache.spark.sql.catalyst.expressions.GeneratedClass$GeneratedIteratorForCodegenStage1.processNext(Unknown
> Source)
> at
> org.apache.spark.sql.execution.BufferedRowIterator.hasNext(BufferedRowIterator.java:43)
> at
> org.apache.spark.sql.execution.WholeStageCodegenEvaluatorFactory$WholeStageCodegenPartitionEvaluator$$anon$1.hasNext(WholeStageCodegenEvaluatorFactory.scala:43)
> at
> org.apache.spark.sql.execution.SparkPlan.$anonfun$getByteArrayRdd$1(SparkPlan.scala:388)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2(RDD.scala:893)
> at
> org.apache.spark.rdd.RDD.$anonfun$mapPartitionsInternal$2$adapted(RDD.scala:893)
> at
> org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:52)
> at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:367)
> at org.apache.spark.rdd.RDD.iterator(RDD.scala:331)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:93)
> at
> org.apache.spark.TaskContext.runTaskWithListeners(TaskContext.scala:166)
> at org.apache.spark.scheduler.Task.run(Task.scala:141)
> at
> org.apache.spark.executor.Executor$TaskRunner.$anonfun$run$4(Executor.scala:620)
> at
> org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally(SparkErrorUtils.scala:64)
> at
> org.apache.spark.util.SparkErrorUtils.tryWithSafeFinally$(SparkErrorUtils.scala:61)
> at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:94)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:623)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1136)
> at
> java.base/java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:635)
> at java.base/java.lang.Thread.run(Thread.java:840)
> Caused by: java.lang.NullPointerException: Cannot invoke
> "org.apache.spark.unsafe.types.UTF8String.toString()" because "currentInput"
> is null
> at
> org.apache.spark.sql.catalyst.csv.UnivocityParser.org$apache$spark$sql$catalyst$csv$UnivocityParser$$convert(UnivocityParser.scala:333)
> at
> org.apache.spark.sql.catalyst.csv.UnivocityParser$.$anonfun$parseStream$1(UnivocityParser.scala:400)
> at
> org.apache.spark.sql.catalyst.util.FailureSafeParser.parse(FailureSafeParser.scala:60)
> at
> org.apache.spark.sql.catalyst.csv.UnivocityParser$.$anonfun$parseStream$3(UnivocityParser.scala:409)
> at
> org.apache.spark.sql.catalyst.csv.UnivocityParser$$anon$1.next(UnivocityParser.scala:432)
> at scala.collection.Iterator$$anon$10.nextCur(Iterator.scala:587)
> at scala.collection.Iterator$$anon$10.hasNext(Iterator.scala:601)
> at scala.collection.Iterator$$anon$9.hasNext(Iterator.scala:576)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.hasNext(FileScanRDD.scala:129)
> at
> org.apache.spark.sql.execution.datasources.FileScanRDD$$anon$1.nextIterator(FileScanRDD.scala:283)
> ... 22 more
> {code}
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