[
https://issues.apache.org/jira/browse/SPARK-23271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16349649#comment-16349649
]
Dilip Biswal commented on SPARK-23271:
--------------------------------------
[~hyukjin.kwon]
I took a look at this. To the best of my knowledge, the difference in the
behaviour between these two cases is because of the following :
case 1
{code:java}
scala> List.empty[String].toDF().rdd.partitions.length
res18: Int = 1
{code}
Case 2
{code:java}
scala> val anySchema = StructType(StructField("anyName", StringType, nullable =
false) :: Nil)
anySchema: org.apache.spark.sql.types.StructType =
StructType(StructField(anyName,StringType,false))
scala>
spark.read.schema(anySchema).csv("/tmp/empty_folder").rdd.partitions.length
res22: Int = 0
{code}
For the 2nd case, since number of partitions = 0, we don't call the write task
(the task has logic to create the empty parquet file).
I tried to repartition the input RDD after
[here|https://github.com/apache/spark/blob/master/sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala#L180]
if input number of partitions = 0, before setting up the write job and things
seem to work well.
Would this be a reasonable way to fix this ? Appreciate your feedback.
> Parquet output contains only "_SUCCESS" file after empty DataFrame saving
> --------------------------------------------------------------------------
>
> Key: SPARK-23271
> URL: https://issues.apache.org/jira/browse/SPARK-23271
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.2.0
> Reporter: Pavlo Z.
> Priority: Minor
> Attachments: parquet-empty-output.zip
>
>
> Sophisticated case, reproduced only if read empty CSV file without header
> with assigned schema.
> Steps for reproduce (Scala):
> {code:java}
> val anySchema = StructType(StructField("anyName", StringType, nullable =
> false) :: Nil)
> val inputDF = spark.read.schema(anySchema).csv(inputFolderWithEmptyCSVFile)
> inputDF.write.parquet(outputFolderName)
> // Exception: org.apache.spark.sql.AnalysisException: Unable to infer schema
> for Parquet. It must be specified manually.;
> val actualDF = spark.read.parquet(outputFolderName)
>
> {code}
> *Actual:* Only "_SUCCESS" file in output directory
> *Expected*: at least one Parquet file with schema.
> Project for reproduce is attached.
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
