I kinda agree it is confusing when a parameter is not used... ________________________________ From: Ryan Blue <rb...@netflix.com.INVALID> Sent: Thursday, April 11, 2019 11:07:25 AM To: Bruce Robbins Cc: Dávid Szakállas; Spark Dev List Subject: Re: Dataset schema incompatibility bug when reading column partitioned data
I think the confusion is that the schema passed to spark.read is not a projection schema. I don’t think it is even used in this case because the Parquet dataset has its own schema. You’re getting the schema of the table. I think the correct behavior is to reject a user-specified schema in this case. On Thu, Apr 11, 2019 at 11:04 AM Bruce Robbins <bersprock...@gmail.com<mailto:bersprock...@gmail.com>> wrote: I see a Jira: https://issues.apache.org/jira/browse/SPARK-21021 On Thu, Apr 11, 2019 at 9:08 AM Dávid Szakállas <david.szakal...@gmail.com<mailto:david.szakal...@gmail.com>> wrote: +dev for more visibility. Is this a known issue? Is there a plan for a fix? Thanks, David Begin forwarded message: From: Dávid Szakállas <david.szakal...@gmail.com<mailto:david.szakal...@gmail.com>> Subject: Dataset schema incompatibility bug when reading column partitioned data Date: 2019. March 29. 14:15:27 CET To: u...@spark.apache.org<mailto:u...@spark.apache.org> We observed the following bug on Spark 2.4.0: scala> spark.createDataset(Seq((1,2))).write.partitionBy("_1").parquet("foo.parquet") scala> val schema = StructType(Seq(StructField("_1", IntegerType),StructField("_2", IntegerType))) scala> spark.read.schema(schema).parquet("foo.parquet").as[(Int, Int)].show +---+---+ | _2| _1| +---+---+ | 2| 1| +---+- --+ That is, when reading column partitioned Parquet files the explicitly specified schema is not adhered to, instead the partitioning columns are appended the end of the column list. This is a quite severe issue as some operations, such as union, fails if columns are in a different order in two datasets. Thus we have to work around the issue with a select: val columnNames = schema.fields.map(_.name) ds.select(columnNames.head, columnNames.tail: _*) Thanks, David Szakallas Data Engineer | Whitepages, Inc. -- Ryan Blue Software Engineer Netflix