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https://issues.apache.org/jira/browse/SPARK-33940?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-33940:
------------------------------------
Assignee: (was: Apache Spark)
> allow configuring the max column name length in csv writer
> ----------------------------------------------------------
>
> Key: SPARK-33940
> URL: https://issues.apache.org/jira/browse/SPARK-33940
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.1.0
> Reporter: Nan Zhu
> Priority: Major
>
> csv writer actually has an implicit limit on column name length due to
> univocity-parser,
>
> when we initialize a writer
> [https://github.com/uniVocity/univocity-parsers/blob/e09114c6879fa6c2c15e7365abc02cda3e193ff7/src/main/java/com/univocity/parsers/common/AbstractWriter.java#L211,]
> it calls toIdentifierGroupArray which calls valueOf in NormalizedString.java
> eventually
> ([https://github.com/uniVocity/univocity-parsers/blob/e09114c6879fa6c2c15e7365abc02cda3e193ff7/src/main/java/com/univocity/parsers/common/NormalizedString.java#L205-L209)]
>
> in that stringCache.get, it has a maxStringLength cap
> [https://github.com/uniVocity/univocity-parsers/blob/e09114c6879fa6c2c15e7365abc02cda3e193ff7/src/main/java/com/univocity/parsers/common/StringCache.java#L104]
> which is 1024 by default
>
> we do not expose this as configurable option, leading to NPE when we have a
> column name larger than 1024,
>
> ```
> [info] Cause: java.lang.NullPointerException:
> [info] at
> com.univocity.parsers.common.AbstractWriter.submitRow(AbstractWriter.java:349)
> [info] at
> com.univocity.parsers.common.AbstractWriter.writeHeaders(AbstractWriter.java:444)
> [info] at
> com.univocity.parsers.common.AbstractWriter.writeHeaders(AbstractWriter.java:410)
> [info] at
> org.apache.spark.sql.catalyst.csv.UnivocityGenerator.writeHeaders(UnivocityGenerator.scala:87)
> [info] at
> org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter$.writeHeaders(CsvOutputWriter.scala:58)
> [info] at
> org.apache.spark.sql.execution.datasources.csv.CsvOutputWriter.<init>(CsvOutputWriter.scala:44)
> [info] at
> org.apache.spark.sql.execution.datasources.csv.CSVFileFormat$$anon$1.newInstance(CSVFileFormat.scala:86)
> [info] at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.newOutputWriter(FileFormatDataWriter.scala:126)
> [info] at
> org.apache.spark.sql.execution.datasources.SingleDirectoryDataWriter.<init>(FileFormatDataWriter.scala:111)
> [info] at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.executeTask(FileFormatWriter.scala:269)
> [info] at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.$anonfun$write$15(FileFormatWriter.scala:210)
> ```
>
> it could be reproduced by a simple unit test
>
> ```
> val row1 = Row("a")
> val superLongHeader = (0 until 1025).map(_ => "c").mkString("")
> val df = Seq(s"${row1.getString(0)}").toDF(superLongHeader)
> df.repartition(1)
> .write
> .option("header", "true")
> .option("maxColumnNameLength", 1025)
> .csv(dataPath)
> ```
>
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