GitHub user viirya opened a pull request: https://github.com/apache/spark/pull/14803
[SPARK-17153][SQL] Should read partition data when reading new files in filestream without globbing ## What changes were proposed in this pull request? When reading file stream with non-globbing path, the results return data with all `null`s for the partitioned columns. E.g., case class A(id: Int, value: Int) val data = spark.createDataset(Seq( A(1, 1), A(2, 2), A(2, 3)) ) val url = "/tmp/test" data.write.partitionBy("id").parquet(url) spark.read.parquet(url).show +-----+---+ |value| id| +-----+---+ | 2| 2| | 3| 2| | 1| 1| +-----+---+ val s = spark.readStream.schema(spark.read.load(url).schema).parquet(url) s.writeStream.queryName("test").format("memory").start() sql("SELECT * FROM test").show +-----+----+ |value| id| +-----+----+ | 2|null| | 3|null| | 1|null| +-----+----+ ## How was this patch tested? Jenkins tests. You can merge this pull request into a Git repository by running: $ git pull https://github.com/viirya/spark-1 filestreamsource-option Alternatively you can review and apply these changes as the patch at: https://github.com/apache/spark/pull/14803.patch To close this pull request, make a commit to your master/trunk branch with (at least) the following in the commit message: This closes #14803 ---- commit 2771d71898f187d479cdb0996c96494c0b53a344 Author: Liang-Chi Hsieh <sim...@tw.ibm.com> Date: 2016-08-25T07:13:20Z Pass path as basePath for partitionSpec creation if path is not globbing. ---- --- If your project is set up for it, you can reply to this email and have your reply appear on GitHub as well. If your project does not have this feature enabled and wishes so, or if the feature is enabled but not working, please contact infrastructure at infrastruct...@apache.org or file a JIRA ticket with INFRA. --- --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org