# CryptographicHash 클래스
<a name="aws-glue-api-pyspark-transforms-CryptographicHash"></a>

 `CryptographicHash` 변환은 열에서 값을 해시하는 데 알고리즘을 적용합니다.

## 예제
<a name="pyspark-CryptographicHash-examples"></a>

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

secret = "${SECRET}"
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_output = pii.CryptographicHash.apply(
        data_frame=input_df,
        spark_context=sc,
        source_columns=["id", "phone"],
        secret_id=secret,
        algorithm="HMAC_SHA256",
        output_format="BASE64",
    )
    df_output.show()
except:
    print("Unexpected Error happened ")
    raise
```

## 출력
<a name="pyspark-CryptographicHash-output"></a>

출력은 다음과 같습니다.

```
```
+---+------------+-------------------+-------------------+
| id| phone | id_hashed | phone_hashed |
+---+------------+-------------------+-------------------+
| 1| 1234560000 | QUI1zXTJiXmfIb... | juDBAmiRnnO3g... |
| 2| 1234560001 | ZAUWiZ3dVTzCo... | vC8lgUqBVDMNQ... |
| 3| 1234560002 | ZP4VvZWkqYifu... | Kl3QAkgswYpzB... |
| 4| 1234560003 | 3u8vO3wQ8EQfj... | CPBzK1P8PZZkV... |
| 5| 1234560004 | eWkQJk4zAOIzx... | aLf7+mHcXqbLs... |
| 6| 1234560005 | xtI9fZCJZCvsa... | dy2DFgdYWmr0p... |
| 7| 1234560006 | iW9hew7jnHuOf... | wwfGMCOEv6oOv... |
| 8| 1234560007 | H9V1pqvgkFhfS... | g9WKhagIXy9ht... |
| 9| 1234560008 | xDhEuHaxAUbU5... | b3uQLKPY+Q5vU... |
| 10| 1234560009 | GRN6nFXkxk349... | VJdsKt8VbxBbt... |
+---+------------+-------------------+-------------------+
```
```

 변환은 지정된 알고리즘과 시크릿 키를 사용하여 `id` 및 `phone` 열 값의 암호화 해시를 계산하고 Base64 형식으로 해시를 인코딩합니다. 결과 `df\$1output` DataFrame에는 원래 `input\$1df` DataFrame의 모든 열과 계산된 해시가 포함된 추가 `id\$1hashed` 및 `phone\$1hashed` 열이 있습니다.

## 메서드
<a name="aws-glue-api-pyspark-transforms-CryptographicHash-_methods"></a>
+ [\$1\$1call\$1\$1](#aws-glue-api-pyspark-transforms-CryptographicHash-__call__)
+ [apply](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-apply)
+ [이름](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-name)
+ [describeArgs](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeArgs)
+ [describeReturn](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeReturn)
+ [describeTransform](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeTransform)
+ [describeErrors](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeErrors)
+ [describe](#aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describe)

## \$1\$1call\$1\$1(spark\$1context, data\$1frame, source\$1columns, secret\$1id, algorithm=None, secret\$1version=None, create\$1secret\$1if\$1missing=False, output\$1format=None, entity\$1type\$1filter=None)
<a name="aws-glue-api-pyspark-transforms-CryptographicHash-__call__"></a>

 `CryptographicHash` 변환은 열에서 값을 해시하는 데 알고리즘을 적용합니다.
+ `source_columns` - 기존 열의 배열.
+ `secret_id` – Secrets Manager 시크릿 키의 ARN. 소스 열을 해시하기 위해 해시 기반 메시지 인증 코드(HMAC) 접두사 알고리즘에 사용되는 키.
+ `secret_version` – 선택 사항입니다. 기본적으로 최신 시크릴 버전으로 설정됩니다.
+ `entity_type_filter` - 엔터티 유형의 선택적 배열. 자유 텍스트 열에서 탐지된 PII만 암호화하는 데 사용할 수 있습니다.
+ `create_secret_if_missing` - 선택적 부울. true인 경우 호출자를 대신하여 시크릿을 생성하려고 시도합니다.
+ `algorithm` – 데이터를 해시하는 데 사용되는 알고리즘. 유효한 열거형 값: MD5, SHA1, SHA256, SHA512, HMAC\$1MD5, HMAC\$1SHA1, HMAC\$1SHA256, HMAC\$1SHA512.

## apply(cls, \$1args, \$1\$1kwargs)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-apply"></a>

`GlueTransform` [apply](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-apply)에서 상속됩니다.

## name(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-name"></a>

`GlueTransform` [name](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-name)에서 상속됩니다.

## describeArgs(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeArgs"></a>

`GlueTransform` [describeArgs](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeArgs)에서 상속됩니다.

## describeReturn(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeReturn"></a>

`GlueTransform` [describeReturn](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeReturn)에서 상속됩니다.

## describeTransform(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeTransform"></a>

`GlueTransform` [describeTransform](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeTransform)에서 상속됩니다.

## describeErrors(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describeErrors"></a>

`GlueTransform` [describeErrors](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describeErrors)에서 상속됩니다.

## describe(cls)
<a name="aws-glue-api-crawler-pyspark-transforms-CryptographicHash-describe"></a>

`GlueTransform` [describe](aws-glue-api-crawler-pyspark-transforms-GlueTransform.md#aws-glue-api-crawler-pyspark-transforms-GlueTransform-describe)에서 상속됩니다.