Providing master keys

To provide master keys:

1. Pass the explicit master keys, in the following format:

   parameter name: "encryption.key.list"
   parameter value: "<master key ID>:<master key (base64)> , <master key ID>:<master key (base64)>.."
   

   For example:

   sc.hadoopConfiguration.set("encryption.key.list" , "k1:iKwfmI5rDf7HwVBcqeNE6w== , k2:LjxH/aXxMduX6IQcwQgOlw== , k3:rnZHCxhUHr79Y6zvQnxSEQ==")
   

   The length of master keys before base64 encoding can be 16, 24 or 32 bytes (128, 192 or 256 bits).

Writing encrypted data

To write encrypted data:

1. Specify which columns to encrypt, and which master keys to use:

   parameter name:  "encryption.column.keys"
   parameter value: "<master key ID>:<column>,<column>;<master key ID>:<column> .."
   

2. Specify the footer key:

   parameter name:  "encryption.footer.key"
   parameter value:  "<master key ID>"
   

   For example:

   dataFrame.write
   .option("encryption.footer.key" , "k1")
   .option("encryption.column.keys" , "k2:SSN,Address;k3:CreditCard")
   .parquet("<path to encrypted files>")
   

   Note: `" "` must contain the string `.encrypted` in the URL, for example `/path/to/my_table.parquet.encrypted`. If either the `"encryption.column.keys"` parameter or the `"encryption.footer.key"` parameter is not set, an exception will be thrown.

Reading encrypted data

The required metadata is stored in the encrypted Parquet files.

To read the encrypted data:

1. Provide the encryption keys:

   sc.hadoopConfiguration.set("encryption.key.list" , "k1:iKwfmI5rDf7HwVBcqeNE6w== , k2:LjxH/aXxMduX6IQcwQgOlw== , k3:rnZHCxhUHr79Y6zvQnxSEQ==")
   

2. Call the regular parquet read commands, such as:

   val dataFrame = spark.read.parquet("<path to encrypted files>")
   

   Note: `" "` must contain the string `.encrypted` in the URL, for example `/path/to/my_table.parquet.encrypted`.

Parent topic: Parquet encryption