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 <[email protected]>
Date: 2016-08-25T07:13:20Z
Pass path as basePath for partitionSpec creation if path is not globbing.
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