Github user zero323 commented on a diff in the pull request:
https://github.com/apache/spark/pull/17938#discussion_r116029940
--- Diff: docs/sql-programming-guide.md ---
@@ -581,6 +581,46 @@ Starting from Spark 2.1, persistent datasource tables
have per-partition metadat
Note that partition information is not gathered by default when creating
external datasource tables (those with a `path` option). To sync the partition
information in the metastore, you can invoke `MSCK REPAIR TABLE`.
+### Bucketing, Sorting and Partitioning
--- End diff --
@tejasapatil
> There could be multiple possible orderings of `partitionBy,` `bucketBy`
and `sortBy` calls. Not all of them are supported, not all of them would
produce correct outputs.
Shouldn't the output be the same no matter the order? `sortBy` is not
applicable for `partitionBy` and takes precedence over `bucketBy`, if both are
present. This is Hive's behaviour if I am not mistaken, and at first glance
Spark is doing the same thing. It there any gotcha here?
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