This is going to talk a little bit about how to identify situations that a bot could help you, possible ways to build them, the challenges and the some things that may go wrong.

We hear a lot about lambda architectures and how Cassandra and Spark can help us crunch our data both in batch and real-time. After a year in the trenches, I'll share how we at The Weather Company built a general purpose, weather-scale event processing pipeline to make sense of billions of events each day. If you want to avoid much of the pain learning how to get it right, this talk is for you.

In this talk, we’ll explore Spark and see how it works together with Cassandra to deliver a powerful open-source big data analytic solution.

The audience will participate in a live, interactive demo that generates high-quality recommendations using the latest Spark-Cassandra integration for real time, approximate, and advanced analytics including machine learning, graph processing, and text processing.

We will present our Office 365 use case scenarios, why we chose Cassandra + Spark, and walk through the architecture we chose for running DSE on Azure.

You’ve heard all of the hype, but how can SMACK work for you? In this all-star lineup, you will learn how to create a reactive, scaling, resilient and performant data processing powerhouse. Bringing Akka, Kafka and Mesos together provides a foundation to develop and operate an elastically scalable actor system. We will go through the basics of Akka, Kafka and Mesos and then deep dive into putting them together in an end2end (and back again) distrubuted transaction. Distributed transactions mean producers waiting for one or more of consumers to respond. We'll also go through automated ways to failure induce these systems (using LinkedIn Simoorg) and trace them from start to stop through each component (using Twitters Zipkin). Finally, you will see how Apache Cassandra and Spark can be combined to add the incredibly scaling storage and data analysis needed in fast data pipelines. With these technologies as a foundation, you have the assurance that scale is never a problem and uptime is default.

This case study concerns how Open Source Connections moved large amounts of US Patent and Trademark Office patent data from Cassandra to Solr. How we approached the problem, the introduction of Spark as a solution, and how to optimize Spark jobs

It has been 2 years and 20 million+ consoles sold since the Playstation 4 launch, and Cassandra is still alive and well within our infrastructure. We will cover various aspects of running Cassandra at large scale, share our findings, and discuss some tricks that can make your lives easier. We will share how we handle varying use cases such as batch analytics using Spark to how we provide real-time personalized search.