Join Jonathan Fernandes for an in-depth discussion in this video Next steps, part of Apache PySpark by Example.
- [Jonathan] So what next?…Well, if you want a couple more exercises to practice on,…you can always head over to the city of Chicago's…data portal dashboard and recreate some of the insights…and check you're getting the same results as displayed.…Now, remember that Apache Spark has an entire ecosystem…and we've only looked at a part of it.…You can delve deeper into Spark streaming,…the machine learning library.…There are also a couple of Apache Spark summits…throughout the year, and that's a great place…to find out what's the latest and greatest with Spark.…
I hope you found this course helpful.…Thanks for watching, and I'd love to hear back from you…and to connect via LinkedIn.…Enjoy, and Soli Deo Gloria.…
Author
Jonathan Fernandes
Released
1/31/2019- Benefits of the Apache Spark ecosystem
- Working with the DataFrame API
- Working with columns and rows
- Leveraging built-in Spark functions
- Creating your own functions in Spark
- Working with Resilient Distributed Datasets (RDDs)
Skill Level Intermediate
Duration
Views
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Introduction
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Apache PySpark1m 5s
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What you should know1m 4s
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1. Introduction to Apache Spark
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The Apache Spark ecosystem4m 38s
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Why Spark?4m 53s
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Spark origins and Databricks2m 48s
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Spark components2m 32s
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2. Technical Setup
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Set up the lab environment4m 53s
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Importing1m 34s
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3. Working with the DataFrame API
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The DataFrame API2m 9s
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Working with DataFrames2m 44s
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Schemas8m 29s
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Working with columns5m 11s
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Working with rows5m 42s
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Challenge31s
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Solution3m 6s
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4. Functions
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Built-in functions8m 24s
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Working with dates10m 10s
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User-defined functions2m 54s
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Working with joins10m 59s
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Challenge29s
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Solution15m 3s
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5. Resilient Distributed Datasets (RDDs)
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RDDs4m 6s
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Working with RDDs7m 45s
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Conclusion
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Next steps40s
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Video: Next steps