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https://issues.apache.org/jira/browse/SPARK-23271?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16345228#comment-16345228
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Pavlo Z. commented on SPARK-23271:
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In example schema is provided, and this schema have to be written to output,
with no data.
if use such empty dataframe instead of CSV:
{code:java}
val inputDF = List.empty[String].toDF()
{code}
in output directory present "parquet" file, and output is read without errors;
for me it looks correct.
Behaviour for CSV file is different.
Looks like it is bug - empty DataFrame cannot be written differently, depending
on source.
> 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.
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