Github user tejasapatil commented on a diff in the pull request:
https://github.com/apache/spark/pull/16898#discussion_r100696521
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/datasources/FileFormatWriter.scala
---
@@ -108,8 +108,15 @@ object FileFormatWriter extends Logging {
job.setOutputValueClass(classOf[InternalRow])
FileOutputFormat.setOutputPath(job, new Path(outputSpec.outputPath))
+ val allColumns = queryExecution.logical.output
val partitionSet = AttributeSet(partitionColumns)
val dataColumns =
queryExecution.logical.output.filterNot(partitionSet.contains)
+ val bucketColumns = bucketSpec.toSeq.flatMap {
+ spec => spec.bucketColumnNames.map(c => allColumns.find(_.name ==
c).get)
--- End diff --
nit: `allColumns` -> `dataColumns` ?
No need to look at all columns since Spark doesn't allow bucketing over
partition columns.
```
scala> df1.write.format("orc").partitionBy("i").bucketBy(8,
"i").sortBy("k").saveAsTable("table70")
org.apache.spark.sql.AnalysisException: bucketBy columns 'i' should not be
part of partitionBy columns 'i';
```
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