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Lessons from the Field:Applying Best Practices to Your Apache Spark Applications with Silvio Fiorito
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Apache Spark is an excellent tool to accelerate your analytics, whether you’re doing ETL, Machine Learning, or Data Warehousing. However, to really make the most of Spark it pays to understand best practices for data storage, file formats, and query optimization.
As a follow-up of last year’s “Lessons From The Field”, this session will review some common anti-patterns I’ve seen in the field that could introduce performance or stability issues to your Spark jobs. We’ll look at ways of better understanding your Spark jobs and identifying solutions to these anti-patterns to help you write better performing and more stable applications.
About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
Connect with us:
As a follow-up of last year’s “Lessons From The Field”, this session will review some common anti-patterns I’ve seen in the field that could introduce performance or stability issues to your Spark jobs. We’ll look at ways of better understanding your Spark jobs and identifying solutions to these anti-patterns to help you write better performing and more stable applications.
About: Databricks provides a unified data analytics platform, powered by Apache Spark™, that accelerates innovation by unifying data science, engineering and business.
Connect with us:
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