GitHub user kiszk opened a pull request:
https://github.com/apache/spark/pull/17293
[SPARK-19950][SQL] Fix to ignore nullable when df.load() is executed for
file-based data source
## What changes were proposed in this pull request?
This PR fixes a problem that was reported in [Databricks
forum](https://forums.databricks.com/questions/7123/nullable-seemingly-ignored-when-reading-parquet.html).
When the following code is executed, a schema for ``id`` has ``nullable =
true`` while `read.schema()` specifies ``nullable = false``.
I realized this is because current Spark sets `true` into ``nullable`` in
its schema for file-based data source. I fixed this conservative setting.
```java
val field = "id"
val df = spark.range(0, 5, 1, 1).toDF(field)
val fmt = "parquet"
val path = "/tmp/parquet"
val schema = StructType(Seq(StructField(field, LongType, false)))
df.write.format(fmt).mode("overwrite").save(path)
val dfRead = spark.read.format(fmt).schema(schema).load(path)
dfRead.printSchema
```
## How was this patch tested?
added new test in `DataFrameSuite`
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/kiszk/spark SPARK-19950
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/17293.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 #17293
----
commit e36bb0bb8b19d9951f81c431969732ec3f79fd51
Author: Kazuaki Ishizaki <[email protected]>
Date: 2017-03-14T16:14:49Z
initial commit
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