mask

Masks the given string value. This can be useful for creating copies of tables with sensitive information removed.

For the corresponding Databricks SQL function, see mask function.

Syntax

Python

from pyspark.databricks.sql import functions as dbf

dbf.mask(col=<col>, upperChar=<upperChar>, lowerChar=<lowerChar>, digitChar=<digitChar>, otherChar=<otherChar>)

Parameters

Parameter	Type	Description
col	pyspark.sql.Column or str	target column to compute on.
upperChar	pyspark.sql.Column or str, optional	character to replace upper-case characters with. Specify NULL to retain original character.
lowerChar	pyspark.sql.Column or str, optional	character to replace lower-case characters with. Specify NULL to retain original character.
digitChar	pyspark.sql.Column or str, optional	character to replace digit characters with. Specify NULL to retain original character.
otherChar	pyspark.sql.Column or str, optional	character to replace all other characters with. Specify NULL to retain original character.

Returns

pyspark.sql.Column:

Examples

Python

df = spark.createDataFrame([("AbCD123-@$#",), ("abcd-EFGH-8765-4321",)], ['data'])
df.select(mask(df.data).alias('r')).collect()
df.select(mask(df.data, lit('Y')).alias('r')).collect()
df.select(mask(df.data, lit('Y'), lit('y')).alias('r')).collect()
df.select(mask(df.data, lit('Y'), lit('y'), lit('d')).alias('r')).collect()
df.select(mask(df.data, lit('Y'), lit('y'), lit('d'), lit('*')).alias('r')).collect()