Past Meetup

Patrick McFadin talks Cassandra, Spark, tips and tricks

Hosted by Netherlands Cassandra Users - by DataStax -

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This Meetup is past

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Details

Patrick McFadin is with us again at this meetup in Amsterdam. As always, we are very happy to have him here and places usually fill up very quickly for this one so please RSVP asap to avoid disappointment.

Schedule:

17:30 – Reception (with drinks and snacks)
18:30 – Apache Cassandra & Apache Spark for Time Series Data
19:15 – Break
19:30 – Cassandra application performance tips and trick
20:15 – Networking

Speaker:
Patrick McFadin ( http://goo.gl/9498ts )

Patrick McFadin is regarded as one of the experts of Apache Cassandra and data modeling techniques. As the Chief Evangelist for Apache Cassandra and consultant for DataStax, he has helped build some of the largest deployments in the world. Previous to DataStax, he was Chief Architect at Hobsons, an education services company. There, he spoke often on Web Application design and performance.

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Apache Cassandra & Apache Spark for Time Series Data

Apache Cassandra has proven to be one of the best solutions for storing and retrieving time series data at high velocity and high volume. This talk will discuss how the storage model of Cassandra is ideal for time series use cases and go over examples of how to best build data models. We will also cover pairing Apache Spark with Apache Cassandra to create a real time data analytics platform. Attendees will leave this session knowing how to build their own real time data analytics platform, and will be shocked at how easy it is!

Cassandra application performance tips and tricks

Cassandra is built to be a fast application database. This talk is all about getting the most performance. Simple changes can make a big difference. We will go over patterns and anti-patterns.

- Data models for performance- Connection settings- Application API usage- Tradeoffs for speed vs efficiency

Don’t let inefficient bottlenecks get in the way of making your application fast. We’ll do a quick intro for those of you not familiar with Cassandra but dive right into the details.