GitHub user HyukjinKwon opened a pull request:
https://github.com/apache/spark/pull/14215
[SPARK-16544][SQL][WIP] Support for conversion from compatible schema for
Parquet data source when data types are not matched
## What changes were proposed in this pull request?
This PR adds schema compatibility for Parquet.
Currently if user-given schema is different with the Parquet schema, it
throws an exception even when the user-given schema is compatible with Parquet
schema.
For example, executing the codes below:
```scala
val path = "/tmp/test.parquet"
val data = (1 to 4).map(Tuple1(_))
spark.createDataFrame(data).toDF("a").write.parquet(path)
val schema = StructType(StructField("a", LongType, true) :: Nil)
spark.read.schema(schema).parquet(path).show()
```
throws an exception as below:
```
org.apache.parquet.io.ParquetDecodingException: Can not read value at 1 in
block 0
...
```
This PR lets Parqet supports this schema compatibility.
- [x] Schema compatibility for `NumericType` except `DecimalType`.
- [ ] Schema compatibility for other `AtomicType`.
- [ ] Schema compatibility for vectorized reader.
## How was this patch tested?
Unit tests in `ParquetIOSuite`.
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/HyukjinKwon/spark SPARK-16544
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/14215.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 #14215
----
commit b45f2eae8417d9fdf1ecb8de7dd0a43a3d4c0fa8
Author: hyukjinkwon <gurwls...@gmail.com>
Date: 2016-07-15T03:37:45Z
Support for conversion from compatible schema for Parquet data source when
data types are not matched
----
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