Myths about Spark, or Can an Ordinary Java Developer Use Spark?
summary
Presentation introduces Apache Spark for Java developers, explaining how Spark works, what tasks it can handle (batch, streaming, integrating with various databases) and how to use its functional programming APIs instead of scripts or SQL. The talk covers common beginner problems and solutions, Spark syntax and tips, with extensive live coding so attendees can start using Spark themselves.
AI-written summary · about
chapters (16)
- 0:00Spark myths introduction
- 1:25Conceptual myths
- 3:52Spark vs Hadoop and locality
- 8:03Spark history and versions
- 13:59RDD basics and API
- 20:40RDD performance issues
- 24:09Java vs Scala for Spark
- 27:18Scala advantages in Spark
- 30:51Java API demo
- 41:27Broadcast variables
- 47:03Spark and Spring
- 51:59DataFrames basics
- 57:19DataFrames from unstructured data
- 59:03Custom functions in Spark
- 1:01:09Pop music analysis
- 1:05:29Conclusion and Q&A
related talks
01h 12mBig Data in Java World: Apache Spark and Scala. Arch and live coding
01h 00mGetting Started with Spark
46mSpark: One Tool for Everything?
56mThe Magic of Spark: How High-Level Pipelines Become Distributed Hardcore
50mIntroduction to Real-Time Big Data with Apache Spark
50mA Java Implementer's Guide to Better Apache Spark Performance
52mSolving Analytical Problems using Apache Spark
53mLord of the Spark
