Starting to develop in PySpark with Jupyter installed in a Big Data Cluster
Is not a secret that Data Science tools like Jupyter, Apache Zeppelin or the more recently launched Cloud Data Lab and Jupyter Lab are a must be known for the day by day work so How could be combined the power of easily developing models and the capacity of computation of a Big Data Cluster? Well in this article I will share very simple step to start using Jupyter notebooks for PySpark in a Data Proc Cluster in GCP. I'm going to set basic specs: In this article, I tried to deploy Jupyter in a Data Proc Cluster making more friendly to use PySpark in a real cluster. Please feel free if you have questions or suggestions for next articles. See you in the next article!
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