pyspark.sql.functions.aes_decrypt#
- pyspark.sql.functions.aes_decrypt(input, key, mode=None, padding=None, aad=None)[source]#
Returns a decrypted value of input using AES in mode with padding. Key lengths of 16, 24 and 32 bits are supported. Supported combinations of (mode, padding) are (‘ECB’, ‘PKCS’), (‘GCM’, ‘NONE’) and (‘CBC’, ‘PKCS’). Optional additional authenticated data (AAD) is only supported for GCM. If provided for encryption, the identical AAD value must be provided for decryption. The default mode is GCM.
New in version 3.5.0.
- Parameters
- input
Column
or str The binary value to decrypt.
- key
Column
or str The passphrase to use to decrypt the data.
- mode
Column
or str, optional Specifies which block cipher mode should be used to decrypt messages. Valid modes: ECB, GCM, CBC.
- padding
Column
or str, optional Specifies how to pad messages whose length is not a multiple of the block size. Valid values: PKCS, NONE, DEFAULT. The DEFAULT padding means PKCS for ECB, NONE for GCM and PKCS for CBC.
- aad
Column
or str, optional Optional additional authenticated data. Only supported for GCM mode. This can be any free-form input and must be provided for both encryption and decryption.
- input
- Returns
Column
A new column that contains an decrypted value.
Examples
Example 1: Decrypt data with key, mode, padding and aad.
>>> import pyspark.sql.functions as sf >>> df = spark.createDataFrame([( ... "AAAAAAAAAAAAAAAAQiYi+sTLm7KD9UcZ2nlRdYDe/PX4", ... "abcdefghijklmnop12345678ABCDEFGH", "GCM", "DEFAULT", ... "This is an AAD mixed into the input",)], ... ["input", "key", "mode", "padding", "aad"] ... ) >>> df.select(sf.aes_decrypt( ... sf.unbase64(df.input), df.key, df.mode, df.padding, df.aad ... ).cast("STRING")).show(truncate=False) +---------------------------------------------------------------------+ |CAST(aes_decrypt(unbase64(input), key, mode, padding, aad) AS STRING)| +---------------------------------------------------------------------+ |Spark | +---------------------------------------------------------------------+
Example 2: Decrypt data with key, mode and padding.
>>> import pyspark.sql.functions as sf >>> df = spark.createDataFrame([( ... "AAAAAAAAAAAAAAAAAAAAAPSd4mWyMZ5mhvjiAPQJnfg=", ... "abcdefghijklmnop12345678ABCDEFGH", "CBC", "DEFAULT",)], ... ["input", "key", "mode", "padding"] ... ) >>> df.select(sf.aes_decrypt( ... sf.unbase64(df.input), df.key, df.mode, df.padding ... ).cast("STRING")).show(truncate=False) +------------------------------------------------------------------+ |CAST(aes_decrypt(unbase64(input), key, mode, padding, ) AS STRING)| +------------------------------------------------------------------+ |Spark | +------------------------------------------------------------------+
Example 3: Decrypt data with key and mode.
>>> import pyspark.sql.functions as sf >>> df = spark.createDataFrame([( ... "AAAAAAAAAAAAAAAAAAAAAPSd4mWyMZ5mhvjiAPQJnfg=", ... "abcdefghijklmnop12345678ABCDEFGH", "CBC", "DEFAULT",)], ... ["input", "key", "mode", "padding"] ... ) >>> df.select(sf.aes_decrypt( ... sf.unbase64(df.input), df.key, df.mode ... ).cast("STRING")).show(truncate=False) +------------------------------------------------------------------+ |CAST(aes_decrypt(unbase64(input), key, mode, DEFAULT, ) AS STRING)| +------------------------------------------------------------------+ |Spark | +------------------------------------------------------------------+
Example 4: Decrypt data with key.
>>> import pyspark.sql.functions as sf >>> df = spark.createDataFrame([( ... "83F16B2AA704794132802D248E6BFD4E380078182D1544813898AC97E709B28A94", ... "0000111122223333",)], ... ["input", "key"] ... ) >>> df.select(sf.aes_decrypt( ... sf.unhex(df.input), df.key ... ).cast("STRING")).show(truncate=False) +--------------------------------------------------------------+ |CAST(aes_decrypt(unhex(input), key, GCM, DEFAULT, ) AS STRING)| +--------------------------------------------------------------+ |Spark | +--------------------------------------------------------------+