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      <title>[EN] Building a CI/CD pipeline for a Spark project using Github Actions, SBT and AWS S3 — Part 2</title>
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      <pubDate>Wed, 29 Apr 2020 13:01:24 +0200</pubDate>
      <guid>/post/en-building-a-ci/cd-pipeline-for-a-spark-project-using-github-actions-sbt-and-aws-s3-part-2/</guid>
      <description>&lt;p&gt;In the &lt;a href=&#34;https://medium.com/alterway/building-a-ci-cd-pipeline-for-a-spark-project-using-github-actions-sbt-and-aws-s3-part-1-c7d43658832d&#34;&gt;first article&lt;/a&gt; of this series, we talked about how we can set up a CI/CD pipeline for a Spark project using Github Actions, SBT as a build tool and S3 for deployment. Our code once pushed to the [master] branch of our project on Github, triggered an SBT Build command to generate a fat jar, then pushed it to S3 to the chosen bucket.&lt;/p&gt;
&lt;p&gt;However, this pipeline still lacks a way to add a logic since it does not allow us to check whether the jar’s version we’re putting to S3 already exists for instance.&lt;/p&gt;</description>
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