[GitHub] [spark] huaxingao commented on a change in pull request #28104: [SPARK-31331][SQL][DOCS] Document Spark integration with Hive UDFs/UDAFs/UDTFs

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huaxingao commented on a change in pull request #28104: [SPARK-31331][SQL][DOCS] Document Spark integration with Hive UDFs/UDAFs/UDTFs
URL: https://github.com/apache/spark/pull/28104#discussion_r406001569
 
 

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 File path: docs/sql-ref-functions-udf-hive.md
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 @@ -19,4 +19,94 @@ license: |
   limitations under the License.
 ---
 
-Integration with Hive UDFs/UDAFs/UDTFs
\ No newline at end of file
+### Description
+
+Spark SQL supports integration of Hive UDFs, UDAFs and UDTFs. Similar to Spark UDFs and UDAFs, Hive UDFs work on a single row as input and generate a single row as output, while Hive UDAFs operate on multiple rows and return a single aggregated row as a result. In addition, Hive also supports UDTFs (User Defined Tabular Functions) that act on one row as input and return multiple rows as output. To use Hive UDFs/UDAFs/UTFs, the user should register them in Spark, and then use them in Spark SQL queries.
+
+### Examples
+
+Hive has two UDF interfaces: [UDF](https://github.com/apache/hive/blob/master/udf/src/java/org/apache/hadoop/hive/ql/exec/UDF.java) and [GenericUDF](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDF.java).
+An example below uses [GenericUDFAbs](https://github.com/apache/hive/blob/master/ql/src/java/org/apache/hadoop/hive/ql/udf/generic/GenericUDFAbs.java) derived from `GenericUDF`.
+
+<pre><code>
+// Register `GenericUDFAbs` and use it in Spark SQL.
+// Note that, if you use your own programmed one, you need to add a JAR containig it into a classpath,
+// e.g., `spark.sql("ADD JAR yourHiveUDF.jar")`.
+spark.sql("CREATE TEMPORARY FUNCTION testUDF AS 'org.apache.hadoop.hive.ql.udf.generic.GenericUDFAbs'")
+
+spark.sql("SELECT * FROM hiveUDFTestTable").show()
 
 Review comment:
   OK. Will convert to SQL
   

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