Github user gatorsmile commented on a diff in the pull request:
https://github.com/apache/spark/pull/14883#discussion_r77290382
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/catalog/ExternalCatalog.scala
---
@@ -184,4 +184,17 @@ abstract class ExternalCatalog {
def listFunctions(db: String, pattern: String): Seq[String]
+ //
--------------------------------------------------------------------------
+ // Resources
+ //
--------------------------------------------------------------------------
+
+ /**
+ * Add a JAR resource to the underlying external catalog for DDL (e.g.
CREATE TABLE) and DML
+ * (e.g., LOAD TABLE) operations.
+ *
+ * For example, when users create a Hive serde table, they can specify a
custom
+ * Serializer-Deserializer (SerDe) class. When Hive metastore is unable
to access the custom SerDe
+ * JAR (e.g., not on the Hive classpath), the JAR file must be added at
runtime using this API.
+ */
+ def addJar(path: String): Unit
--- End diff --
Yeah, we still need it after hive and data source tables are consolidated.
The major reason is for supporting custom Hive Serde, custom Hive file format,
and custom UDF/UDAF. They are major features for the existing Hive users. These
supports might be critical for migration from Hive to Spark.
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