The Spark Video Collection: 2016

Table of contents

1. San Jose 2016: Spark 2.0
   1. The state of Spark and where it is going in 2016 - Reynold Xin (Databricks)
2. San Jose 2016: Spark Streaming
   1. Apache Spark and real-time analytics: From interactive queries to streaming - Michael Armbrust (Databricks)
3. San Jose 2016: Spark and Machine Learning
   1. Fast big data analytics and machine learning using Alluxio and Spark in Baidu - Bin Fan (Alluxio), Haojun Wang (Baidu)
   2. SparkNet: Training deep networks in Spark - Robert Nishihara (UC Berkeley)
4. San Jose 2016: Spark in Production
   1. Scala and the JVM as a big data platform: Lessons from Apache Spark - Dean Wampler (Lightbend)
   2. Not your father's database: How to use Apache Spark properly in your big data architecture - Vida Ha (Databricks)
5. London 2016: Spark Streaming
   1. The future of streaming in Spark: Structured streaming - Tathagata Das (Databricks)
   2. So you think you can stream: Use cases and design patterns for Spark Streaming - Vida Ha (Databricks) and Prakash Chockalingam (Databricks)
   3. Anomaly detection in telecom with Spark - Ted Dunning (MapR Technologies)
6. London 2016: Spark in Production
   1. Securing Apache Spark on production Hadoop clusters - Kostas Sakellis (Cloudera)
   2. Beyond shuffling: Tips and tricks for scaling Spark jobs - Holden Karau (IBM)
   3. Adding complex data to the Spark stack - Neeraja Rentachintala (MapR Technologies)