Big Data made easy with a Spark (3.0)
summary
Hands-on labs that actually load CSVs, infer schemas and run locally with Spark 3.0 and Java 8 (Eclipse or equivalent required), including a data‑quality step implemented as user‑defined functions and a simple linear regression ML demo that predicts about $218 revenue for a 40‑guest party. Code runs on a laptop (Java‑11 warnings appear but examples complete), and the session introduces an open‑source ETL tool from Advance Auto Parts called data in the fast lane. Watch if runnable examples and concrete results matter.
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chapters (12)
- 0:00Start
- 4:00Caution
- 6:32Who are thou?
- 9:17But most importantly...
- 13:41An analytics operating system?
- 17:37What a typical app looks like?
- 19:42We Can Do It!
- 21:54Get all the STUFF
- 22:36Download some tools
- 40:40Lab #1 - ingestion
- 49:50If it was in a relational database
- 50:23Basic analytics
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