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https://issues.apache.org/jira/browse/SPARK-23372?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16360252#comment-16360252
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Harleen Singh Mann commented on SPARK-23372:
--------------------------------------------
Perhaps a dumb question: Why are you edition
[OrcUtils.scala|https://github.com/apache/spark/pull/20579/files#diff-3fb8426b690ab771c4f67f9cad336498]
?
> Writing empty struct in parquet fails during execution. It should fail
> earlier during analysis.
> -----------------------------------------------------------------------------------------------
>
> Key: SPARK-23372
> URL: https://issues.apache.org/jira/browse/SPARK-23372
> Project: Spark
> Issue Type: Improvement
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Dilip Biswal
> Priority: Minor
>
> *Running*
> spark.emptyDataFrame.write.format("parquet").mode("overwrite").save(path)
> *Results in*
> {code:java}
> org.apache.parquet.schema.InvalidSchemaException: Cannot write a schema with
> an empty group: message spark_schema {
> }
> at org.apache.parquet.schema.TypeUtil$1.visit(TypeUtil.java:27)
> at org.apache.parquet.schema.TypeUtil$1.visit(TypeUtil.java:37)
> at org.apache.parquet.schema.MessageType.accept(MessageType.java:58)
> at org.apache.parquet.schema.TypeUtil.checkValidWriteSchema(TypeUtil.java:23)
> at
> org.apache.parquet.hadoop.ParquetFileWriter.<init>(ParquetFileWriter.java:225)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:342)
> at
> org.apache.parquet.hadoop.ParquetOutputFormat.getRecordWriter(ParquetOutputFormat.java:302)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetOutputWriter.<init>(ParquetOutputWriter.scala:37)
> at
> org.apache.spark.sql.execution.datasources.parquet.ParquetFileFormat$$anon$1.newInstance(ParquetFileFormat.scala:151)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.newOutputWriter(FileFormatWriter.scala:376)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$SingleDirectoryWriteTask.execute(FileFormatWriter.scala:387)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:278)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask$3.apply(FileFormatWriter.scala:276)
> at
> org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1411)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$.org$apache$spark$sql$execution$datasources$FileFormatWriter$$executeTask(FileFormatWriter.scala:281)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:206)
> at
> org.apache.spark.sql.execution.datasources.FileFormatWriter$$anonfun$write$1.apply(FileFormatWriter.scala:205)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
> at org.apache.spark.scheduler.Task.run(Task.scala:109)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
> at
> java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
> at
> java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
> at java.lang.Thread.run(Thread.
> {code}
> We should detect this earlier in the processing and raise the error.
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