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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

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

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()