Merk
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Registers a Java user-defined function as a SQL function.
In addition to a name and the function itself, the return type can be optionally specified. When the return type is not specified, it is inferred via reflection.
Syntax
registerJavaFunction(name, javaClassName, returnType=None)
Parameters
| Parameter | Type | Description |
|---|---|---|
name |
str | Name of the user-defined function. |
javaClassName |
str | Fully qualified name of the Java class. |
returnType |
DataType or str, optional | The return type of the registered Java function. The value can be either a DataType object or a DDL-formatted type string. |
Returns
None
Notes
Use spark.udf.register in a Scala notebook cell to register a Scala UDF; it will be accessible from Python in the same session.
Examples
Register with an explicit DataType return type.
from pyspark.sql.types import IntegerType
spark.udf.registerJavaFunction(
"javaStringLength", "test.org.apache.spark.sql.JavaStringLength", IntegerType())
spark.sql("SELECT javaStringLength('test')").collect()
# [Row(javaStringLength(test)=4)]
Register without specifying a return type (inferred via reflection).
spark.udf.registerJavaFunction(
"javaStringLength2", "test.org.apache.spark.sql.JavaStringLength")
spark.sql("SELECT javaStringLength2('test')").collect()
# [Row(javaStringLength2(test)=4)]
Register with a DDL-formatted return type string.
spark.udf.registerJavaFunction(
"javaStringLength3", "test.org.apache.spark.sql.JavaStringLength", "integer")
spark.sql("SELECT javaStringLength3('test')").collect()
# [Row(javaStringLength3(test)=4)]