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| author | Reynold Xin <rxin@databricks.com> | 2015-01-13 17:16:41 -0800 |
|---|---|---|
| committer | Reynold Xin <rxin@databricks.com> | 2015-01-13 17:16:41 -0800 |
| commit | f9969098c8cb15e36c718b80c6cf5b534a6cf7c3 (patch) | |
| tree | f7335abaafcd8e044d09565f6f1f21f24d5bc544 /project/MimaExcludes.scala | |
| parent | 14e3f114efb906937b2d7b7ac04484b2814a3b48 (diff) | |
| download | spark-f9969098c8cb15e36c718b80c6cf5b534a6cf7c3.tar.gz spark-f9969098c8cb15e36c718b80c6cf5b534a6cf7c3.tar.bz2 spark-f9969098c8cb15e36c718b80c6cf5b534a6cf7c3.zip | |
[SPARK-5123][SQL] Reconcile Java/Scala API for data types.
Having two versions of the data type APIs (one for Java, one for Scala) requires downstream libraries to also have two versions of the APIs if the library wants to support both Java and Scala. I took a look at the Scala version of the data type APIs - it can actually work out pretty well for Java out of the box.
As part of the PR, I created a sql.types package and moved all type definitions there. I then removed the Java specific data type API along with a lot of the conversion code.
This subsumes https://github.com/apache/spark/pull/3925
Author: Reynold Xin <rxin@databricks.com>
Closes #3958 from rxin/SPARK-5123-datatype-2 and squashes the following commits:
66505cc [Reynold Xin] [SPARK-5123] Expose only one version of the data type APIs (i.e. remove the Java-specific API).
Diffstat (limited to 'project/MimaExcludes.scala')
| -rw-r--r-- | project/MimaExcludes.scala | 12 |
1 files changed, 12 insertions, 0 deletions
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 51e8bd4cf6..f6f9f491f4 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -60,6 +60,18 @@ object MimaExcludes { ProblemFilters.exclude[IncompatibleResultTypeProblem]( "org.apache.spark.streaming.flume.sink.SparkAvroCallbackHandler." + "removeAndGetProcessor") + ) ++ Seq( + // SPARK-5123 (SparkSQL data type change) - alpha component only + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.ml.feature.HashingTF.outputDataType"), + ProblemFilters.exclude[IncompatibleResultTypeProblem]( + "org.apache.spark.ml.feature.Tokenizer.outputDataType"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.feature.Tokenizer.validateInputType"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.classification.LogisticRegressionModel.validateAndTransformSchema"), + ProblemFilters.exclude[IncompatibleMethTypeProblem]( + "org.apache.spark.ml.classification.LogisticRegression.validateAndTransformSchema") ) case v if v.startsWith("1.2") => |