Sharing data has become easier today, so protecting sensitive and confidential information is a good way to avoid data leaks. One of the best practices we can follow is to apply data encryption during processing and storage. In PySpark, we can achieve that by using theaes_encrypt()andaes_dec...
# -*- coding: utf-8 -*-importosfrompyspark.sqlimportSparkSessiondefnoop(x):importsocketimportsys host = socket.gethostname() +' '.join(sys.path) +' '.join(os.environ)print('host: '+ host)print('PYTHONPATH: '+ os.environ['PYTHONPATH'])print('PWD: '+ os.environ['PWD'])print(...
With PySpark, the APIs are simpler and more consistent, so the need for helper tools is reduced. Of course the modern way to do data science is via notebooks, and the Databricks notebook does a great job at doing away with coding for tasks that should be point and click, like graph...
you will read the instruction for the exercise together with Florian and he will give you tips on how to best solve the exercise. Then, you will solve the exercises on your own in an interactive coding environment in your browser. When you submit code that is not (yet) solving the exerci...
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# -*- coding: utf-8 -*- import os from pyspark.sql import SparkSession def noop(x): import socket import sys host = socket.gethostname() + ' '.join(sys.path) + ' '.join(os.environ) print('host: ' + host) print('PYTHONPATH: ' + os.environ['PYTHONPATH']) print('PWD...
# -*- coding: utf-8 -*- import os from pyspark.sql import SparkSession def noop(x): import socket import sys host = socket.gethostname() + ' '.join(sys.path) + ' '.join(os.environ) print('host: ' + host) print('PYTHONPATH: ' + os.environ['PYTHONPATH']) print('PWD:...