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| author | Xiangrui Meng <meng@databricks.com> | 2014-11-03 19:29:11 -0800 |
|---|---|---|
| committer | Xiangrui Meng <meng@databricks.com> | 2014-11-03 19:30:32 -0800 |
| commit | 42d02db86cd973cf31ceeede0c5a723238bbe746 (patch) | |
| tree | 4d773eec8740849bdbca1007f7a0b0af03a1e1bc /sql/catalyst | |
| parent | 0826eed9c84a73544e3d8289834c8b5ebac47e03 (diff) | |
| download | spark-42d02db86cd973cf31ceeede0c5a723238bbe746.tar.gz spark-42d02db86cd973cf31ceeede0c5a723238bbe746.tar.bz2 spark-42d02db86cd973cf31ceeede0c5a723238bbe746.zip | |
[SPARK-4192][SQL] Internal API for Python UDT
Following #2919, this PR adds Python UDT (for internal use only) with tests under "pyspark.tests". Before `SQLContext.applySchema`, we check whether we need to convert user-type instances into SQL recognizable data. In the current implementation, a Python UDT must be paired with a Scala UDT for serialization on the JVM side. A following PR will add VectorUDT in MLlib for both Scala and Python.
marmbrus jkbradley davies
Author: Xiangrui Meng <meng@databricks.com>
Closes #3068 from mengxr/SPARK-4192-sql and squashes the following commits:
acff637 [Xiangrui Meng] merge master
dba5ea7 [Xiangrui Meng] only use pyClass for Python UDT output sqlType as well
2c9d7e4 [Xiangrui Meng] move import to global setup; update needsConversion
7c4a6a9 [Xiangrui Meng] address comments
75223db [Xiangrui Meng] minor update
f740379 [Xiangrui Meng] remove UDT from default imports
e98d9d0 [Xiangrui Meng] fix py style
4e84fce [Xiangrui Meng] remove local hive tests and add more tests
39f19e0 [Xiangrui Meng] add tests
b7f666d [Xiangrui Meng] add Python UDT
(cherry picked from commit 04450d11548cfb25d4fb77d4a33e3a7cd4254183)
Signed-off-by: Xiangrui Meng <meng@databricks.com>
Diffstat (limited to 'sql/catalyst')
| -rw-r--r-- | sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala | 9 |
1 files changed, 8 insertions, 1 deletions
diff --git a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala index e1b5992a36..5dd19dd12d 100644 --- a/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala +++ b/sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/types/dataTypes.scala @@ -71,6 +71,8 @@ object DataType { case JSortedObject( ("class", JString(udtClass)), + ("pyClass", _), + ("sqlType", _), ("type", JString("udt"))) => Class.forName(udtClass).newInstance().asInstanceOf[UserDefinedType[_]] } @@ -593,6 +595,9 @@ abstract class UserDefinedType[UserType] extends DataType with Serializable { /** Underlying storage type for this UDT */ def sqlType: DataType + /** Paired Python UDT class, if exists. */ + def pyUDT: String = null + /** * Convert the user type to a SQL datum * @@ -606,7 +611,9 @@ abstract class UserDefinedType[UserType] extends DataType with Serializable { override private[sql] def jsonValue: JValue = { ("type" -> "udt") ~ - ("class" -> this.getClass.getName) + ("class" -> this.getClass.getName) ~ + ("pyClass" -> pyUDT) ~ + ("sqlType" -> sqlType.jsonValue) } /** |