Github user HyukjinKwon commented on the pull request:
https://github.com/apache/spark/pull/13181#issuecomment-220522607
@marmbrus I tested and could produce the exceptions for reading in
https://issues.apache.org/jira/browse/SPARK-15393 but it seems this might not
be the reason.
I tested the codes below on
https://github.com/apache/spark/commit/c0c3ec35476c756e569a1f34c4b258eb0490585c
(right before this PR) and master branch.
```scala
test("SPARK-15393: create empty file") {
withSQLConf(SQLConf.SHUFFLE_PARTITIONS.key -> "10") {
withTempPath { path =>
val schema = StructType(
StructField("k", StringType, true) ::
StructField("v", IntegerType, false) :: Nil)
val emptyDf =
spark.createDataFrame(spark.sparkContext.emptyRDD[Row], schema)
emptyDf.write
.format("parquet")
.save(path.getCanonicalPath)
val copyEmptyDf = spark.read
.format("parquet")
.load(path.getCanonicalPath)
copyEmptyDf.show()
}
}
}
```
and it seems both produce the exceptions below:
```scala
Unable to infer schema for ParquetFormat at
/private/var/folders/9j/gf_c342d7d150mwrxvkqnc180000gn/T/spark-98dfbe86-afca-413e-9be7-46ff18bac443.
It must be specified manually;
org.apache.spark.sql.AnalysisException: Unable to infer schema for
ParquetFormat at
/private/var/folders/9j/gf_c342d7d150mwrxvkqnc180000gn/T/spark-98dfbe86-afca-413e-9be7-46ff18bac443.
It must be specified manually;
at
org.apache.spark.sql.execution.datasources.DataSource$$anonfun$16.apply(DataSource.scala:324)
at
org.apache.spark.sql.execution.datasources.DataSource$$anonfun$16.apply(DataSource.scala:324)
at scala.Option.getOrElse(Option.scala:121)
at
org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:323)
```
I will try to figure out why but please feel free to revert this if you
think my PR is problematic. I will fix the both issues together anyway later.
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