by Nicole Tache | Released June 2016 | ISBN: 9781491965801

Learn about the very latest in real-time data processing tools, architectures, and applications with this video collection of select talks from the five Strata + Hadoop World conferences in 2016. You'll see world-class experts like Jay Kreps (Confluent) and Michael Armbrust (Databricks) discuss advances in tools such as Kafka and Spark, and leaders in the field explain how they design real-time platforms at scale, address common challenges, and implement streaming architectures across industries.With The Real-time Video Collection: 2016, you get the full year of real-time talks, no matter when you purchase during 2016.Here's how it works: After each conference wraps up, we'll update the video with an additional batch of talks. This year's conferences are being held in June, August, September and December. Content from Strata + Hadoop World San Jose, held in March 2016, is already available, and includes 11 talks from experts in real-time data processing. Show and hide more Publisher resources View/Submit Errata

1. San Jose 2016: Real-Time Tools
   • Distributed stream processing with Apache Kafka - Jay Kreps (Confluent) 00:39:54
   • Apache Spark and real-time analytics: From interactive queries to streaming - Michael Armbrust (Databricks) 00:39:24
   • Fast data made easy with Apache Kafka and Apache Kudu (incubating) - Ted Malaska (Cloudera), Jeff Holoman (Cloudera) 00:38:54
   • Apache Flink: Streaming done right - Kostas Tzoumas (data Artisans) 00:35:40
   • Real-time Hadoop: What an ideal messaging system should bring to Hadoop - Ted Dunning (MapR Technologies) 00:42:16
   • Designing a scalable real-time data platform using Akka, Spark Streaming, and Kafka - Alex Silva (Pluralsight) 00:39:32
   • Pulsar: Real-time analytics at scale leveraging Kafka, Kylin, and Druid - Tony Ng (eBay, Inc.) 00:36:38
   • Lessons learned building a scalable self-serve, real-time, multitenant monitoring service at Yahoo - Sumeet Singh (Yahoo), Mridul Jain (Yahoo) 00:41:36
2. San Jose 2016: Real-Time Applications
   • Taking Spark Streaming to the next level with DataFrames - Tathagata Das (Databricks) 00:33:33
   • Real-time fraud detection using process mining with Spark Streaming - Hylke Hendriksen (ING) 00:37:15
   • Uber, your Hadoop has arrived: Powering intelligence for Uber’s real-time marketplace - Vinoth Chandar (Uber) 00:50:15
3. London 2016: Real-time Tools
   • Triggers in Apache Beam (incubating): User-controlled balance of completeness, latency, and cost in streaming big data pipelines - Kenneth Knowles (Google) 00:44:32
   • The evolution of massive-scale data processing - Tyler Akidau (Google) 00:41:36
4. London 2016: Real-time Architectures
   • Analytics for large-scale time series and event data - Ira Cohen (Anodot) 00:29:31
   • Streaming analytics at 300 billion events per day with Kafka, Samza, and Druid - Xavier Léauté (Metamarkets) 00:43:50
5. London 2016: Real-time Applications
   • Real-time epilepsy monitoring with smart clothing: A case study in time series, open source technology, and connected devices - Eric Kramer (Dataiku) 00:37:58
   • Kappa architecture in the telecom industry - Ignacio Manuel Mulas Viela (Ericsson) and Nicolas Seyvet (Ericsson AB) 00:33:51
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