try_reflect
This is a special version of reflect that performs the same operation, but returns a NULL value instead of raising an error if the invoke method thrown exception.
Syntax
Python
from pyspark.sql import functions as sf
sf.try_reflect(*cols)
Parameters
Parameter | Type | Description |
|---|---|---|
|
| The first element should be a Column representing literal string for the class name, and the second element should be a Column representing literal string for the method name, and the remaining are input arguments (Columns or column names) to the Java method. |
Examples
Example 1: Reflecting a method call with arguments
Python
from pyspark.sql import functions as sf
df = spark.createDataFrame([("a5cf6c42-0c85-418f-af6c-3e4e5b1328f2",)], ["a"])
df.select(
sf.try_reflect(sf.lit("java.util.UUID"), sf.lit("fromString"), "a")
).show(truncate=False)
Output
+------------------------------------------+
|try_reflect(java.util.UUID, fromString, a)|
+------------------------------------------+
|a5cf6c42-0c85-418f-af6c-3e4e5b1328f2 |
+------------------------------------------+
Example 2: Exception in the reflection call, resulting in null
Python
from pyspark.sql import functions as sf
spark.range(1).select(
sf.try_reflect(sf.lit("scala.Predef"), sf.lit("require"), sf.lit(False))
).show(truncate=False)
Output
+-----------------------------------------+
|try_reflect(scala.Predef, require, false)|
+-----------------------------------------+
|NULL |
+-----------------------------------------+