Encrypt class - Amazon Glue
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Encrypt class

The Encrypt transform encrypts source columns using the Amazon Key Management Service key. The Encrypt transform can encrypt up to 128 MiB per cell. It will attempt to preserve the format on decryption. To preserve the data type, the data type metadata must serialize to less than 1KB. Otherwise, you must set the preserve_data_type parameter to false. The data type metadata will be stored in plaintext in the encryption context.

Example

from pyspark.context import SparkContext
from pyspark.sql import SparkSession
from awsgluedi.transforms import *

kms = "${KMS}"
sc = SparkContext()
spark = SparkSession(sc)

input_df = spark.createDataFrame(
    [
        (1, "1234560000"),
        (2, "1234560001"),
        (3, "1234560002"),
        (4, "1234560003"),
        (5, "1234560004"),
        (6, "1234560005"),
        (7, "1234560006"),
        (8, "1234560007"),
        (9, "1234560008"),
        (10, "1234560009"),
    ],
    ["id", "phone"],
)

try:
    df_encrypt = pii.Encrypt.apply(
        data_frame=input_df,
        spark_context=sc,
        source_columns=["phone"],
        kms_key_arn=kms
    )
except:
    print("Unexpected Error happened ")
    raise

Output

The output will be a PySpark DataFrame with the original `id` column and an additional column containing the encrypted values of the `phone` column. 

```
+---+------------+-------------------------+
| id| phone | phone_encrypted |
+---+------------+-------------------------+
| 1| 1234560000| EncryptedData1234...abc |
| 2| 1234560001| EncryptedData5678...def |
| 3| 1234560002| EncryptedData9012...ghi |
| 4| 1234560003| EncryptedData3456...jkl |
| 5| 1234560004| EncryptedData7890...mno |
| 6| 1234560005| EncryptedData1234...pqr |
| 7| 1234560006| EncryptedData5678...stu |
| 8| 1234560007| EncryptedData9012...vwx |
| 9| 1234560008| EncryptedData3456...yz0 |
| 10| 1234560009| EncryptedData7890...123 |
+---+------------+-------------------------+
```

The Encrypt transform takes the `source_columns` as `["phone"]` and the `kms_key_arn` as the value of the `${KMS}` environment variable. The transformation encrypts the values in the `phone` column using the specified KMS key. The resulting `df_encrypt` DataFrame contains the original `id` column, the original `phone` column, and an additional column named `phone_encrypted` containing the encrypted values of the `phone` column.

Methods

__call__(spark_context, data_frame, source_columns, kms_key_arn, entity_type_filter=None, preserve_data_type=None)

The Encrypt transform encrypts source columns using the Amazon Key Management Service key.

  • source_columns – An array of existing columns.

  • kms_key_arn – The key ARN of the Amazon Key Management Service key to use to Encrypt the source columns.

  • entity_type_filter – Optional array of entity types. Can be used to encrypt only detected PII in free-text column.

  • preserve_data_type – Optional boolean. Defaults to true. If false, the data type will not be stored.

apply(cls, *args, **kwargs)

Inherited from GlueTransform apply.

name(cls)

Inherited from GlueTransform name.

describeArgs(cls)

Inherited from GlueTransform describeArgs.

describeReturn(cls)

Inherited from GlueTransform describeReturn.

describeTransform(cls)

Inherited from GlueTransform describeTransform.

describeErrors(cls)

Inherited from GlueTransform describeErrors.

describe(cls)

Inherited from GlueTransform describe.