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author | Joseph K. Bradley <joseph@databricks.com> | 2016-04-21 16:50:09 -0700 |
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committer | DB Tsai <dbt@netflix.com> | 2016-04-21 16:50:09 -0700 |
commit | f25a3ea8d3ee6972efb925826981918549deacaa (patch) | |
tree | 5365b5f162b41fba8e1786634ccc2c8d585fd47c /project | |
parent | e2b5647ab92eb478b3f7b36a0ce6faf83e24c0e5 (diff) | |
download | spark-f25a3ea8d3ee6972efb925826981918549deacaa.tar.gz spark-f25a3ea8d3ee6972efb925826981918549deacaa.tar.bz2 spark-f25a3ea8d3ee6972efb925826981918549deacaa.zip |
[SPARK-14734][ML][MLLIB] Added asML, fromML methods for all spark.mllib Vector, Matrix types
## What changes were proposed in this pull request?
For maintaining wrappers around spark.mllib algorithms in spark.ml, it will be useful to have ```private[spark]``` methods for converting from one linear algebra representation to another.
This PR adds toNew, fromNew methods for all spark.mllib Vector and Matrix types.
## How was this patch tested?
Unit tests for all conversions
Author: Joseph K. Bradley <joseph@databricks.com>
Closes #12504 from jkbradley/linalg-conversions.
Diffstat (limited to 'project')
-rw-r--r-- | project/MimaExcludes.scala | 4 |
1 files changed, 4 insertions, 0 deletions
diff --git a/project/MimaExcludes.scala b/project/MimaExcludes.scala index 9b2a966aaf..c98a39dc0c 100644 --- a/project/MimaExcludes.scala +++ b/project/MimaExcludes.scala @@ -660,6 +660,10 @@ object MimaExcludes { ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.OutputWriter"), ProblemFilters.exclude[MissingClassProblem]("org.apache.spark.sql.sources.OutputWriterFactory") ) ++ Seq( + // SPARK-14734: Add conversions between mllib and ml Vector, Matrix types + ProblemFilters.exclude[ReversedMissingMethodProblem]("org.apache.spark.mllib.linalg.Vector.asML"), + ProblemFilters.exclude[ReversedMissingMethodProblem]("org.apache.spark.mllib.linalg.Matrix.asML") + ) ++ Seq( // SPARK-14704: Create accumulators in TaskMetrics ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.executor.InputMetrics.this"), ProblemFilters.exclude[DirectMissingMethodProblem]("org.apache.spark.executor.OutputMetrics.this") |