Github user brkyvz commented on a diff in the pull request:
https://github.com/apache/spark/pull/15951#discussion_r88934128
--- Diff:
sql/core/src/test/scala/org/apache/spark/sql/test/DataFrameReaderWriterSuite.scala
---
@@ -573,4 +573,39 @@ class DataFrameReaderWriterSuite extends QueryTest
with SharedSQLContext with Be
}
}
}
+
+ test("SPARK-18510: Data corruption from user specified partition column
schemas") {
+ import org.apache.spark.sql.functions.udf
+ import testImplicits._
+ withTempDir { src =>
+ val createArray = udf { (length: Long) =>
+ for (i <- 1 to length.toInt) yield i.toString
+ }
+ spark.range(4).select(createArray('id + 1) as 'ex, 'id, 'id % 4 as
'part).coalesce(1).write
+ .partitionBy("part", "id")
+ .mode("overwrite")
+ .parquet(src.toString)
+ // make sure to specify the schema in the wrong order. Partition
column in the middle, etc.
--- End diff --
with the fix, it still does not matter. The comment is outdated, I thought
something else was the problem. In terms of schema though, the output from
Spark is always consistent, i.e. partition columns go last.
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