PySpark:PicklingError:无法序列化对象:TypeError:无法腌制CompiledFFI对象 [英] PySpark: PicklingError: Could not serialize object: TypeError: can't pickle CompiledFFI objects

问题描述

我是PySpark环境的新手，在尝试使用加密模块在RDD中加密数据时遇到错误.这是代码:

I'm new to the PySpark environment and came across an error while trying to encrypt data in an RDD with the cryptography module. Here's the code:

from pyspark.sql import SparkSession
spark = SparkSession.builder.appName('encrypt').getOrCreate()

df = spark.read.csv('test.csv', inferSchema = True, header = True)
df.show()
df.printSchema()

from cryptography.fernet import Fernet
key = Fernet.generate_key()
f = Fernet(key)

dfRDD = df.rdd
print(dfRDD)
mappedRDD = dfRDD.map(lambda value: (value[0], str(f.encrypt(str.encode(value[1]))), value[2] * 100))
data = mappedRDD.toDF()
data.show()

在我尝试将value[1]与str(f.encrypt(str.encode(value[1])))映射之前，一切正常.我收到以下错误:

Everything works fine of course until I try mapping the value[1] with str(f.encrypt(str.encode(value[1]))). I receive the following error:

PicklingError:无法序列化对象:TypeError:无法使CompiledFFI对象腌制

PicklingError: Could not serialize object: TypeError: can't pickle CompiledFFI objects

我没有看到太多有关此错误的资源，而是想看看是否有人遇到过该错误(或者如果通过PySpark，您有推荐的列加密方法).

I have not seen too many resources referring to this error and wanted to see if anyone else has encountered it (or if via PySpark you have a recommended approach to column encryption).

推荐答案

推荐的列加密方法

recommended approach to column encryption

您可以考虑使用Hive内置加密功能( HIVE-5207 ， HIVE-6329 )，但目前此功能相当有限( HIVE-7934 ).

You may consider Hive built-in encryption (HIVE-5207, HIVE-6329) but it is fairly limited at this moment (HIVE-7934).

您的当前代码不起作用，因为Fernet对象不可序列化.您可以通过仅分发密钥来使其工作:

Your current code doesn't work because Fernet objects are not serializable. You can make it work by distributing only keys:

def f(value, key=key): 
    return value[0], str(Fernet(key).encrypt(str.encode(value[1]))), value[2] * 100

mappedRDD = dfRDD.map(f)

或

def g(values, key=key):
    f = Fernet(key)
    for value in values:
        yield value[0], str(f.encrypt(str.encode(value[1]))), value[2] * 100

mappedRDD = dfRDD.mapPartitions(g)

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