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Docker Dev Workflow for Apache Spark

Written by @jstephan | Published on 2020/12/19

TL;DR
The benefits that come with using Docker containers are well known: they provide consistent and isolated environments so that applications can be deployed anywhere - locally, in dev / testing / prod environments, across all cloud providers, and on-premise - in a repeatable way. 

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Written by
@jstephan
Co-Founder @ Data Mechanics (www.datamechanics.co). Previously software engineer @ Databricks.

Topics and
tags
apache-spark|docker|kubernetes|data-engineering|big-data|data-science|spark|programming
This story on HackerNoon has a decentralized backup on Sia.
Transaction ID: 0teB8TGetALj_afkZ40T677Ti3q7TdyG9kdZqnwE39M