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Cassandra as the Central Nervous System of Your Distributed Systems with Joe Stein - Powered by NoSQL
In the 4th week of the DataStax’s Cassandra NYC 2011 video series, we have Joe Stein from Medialets talking about the architecture
Before diving into the video here are some interesting data points:
- Medialets serves rich media ads
- they handle 3-4TB of daily data
- microsecond-level response times
- Cassandra is used for time series and aggregate metrics
- all MapReduce jobs written in Python. This reminded me of the recent post about the performance impact of operations in Hadoop Map phase
Major components of the Medialets’s architecture:
- Cassandra: 6 node cluster, 100k requests, single DC
- ZooKeeper: coordinates all the services on the platform
- some of the data in MySQL is replicated in Cassandra (and coordinated with ZooKeeper)
- data is fed back to MySQL
- Kafka for collecting analytics data:
- aggregates go into Cassandra
- events in Hadoop
- GROUP BY with Cassandra
- for real-time systems aggregations must be done upfront
- the way data is segmented is critical
- aggregation leads to data explosion
For today’s Powered by Cassandra video from the Cassandra NYC 2011 event organized by DataStax, I chose Chris Burroughs’s presentation about Clearspring’s usage of Cassandra. Just in case you wonder what Clearspring is doing, the sharing buttons you see here on myNoSQL are powered by AddThis product from Clearspring.
While today was supposed to be a new educational video from the Cassandra NYC 2011 video series, I thought that learning from the lessons of operating Cassandra at Outbrain to serve over 30 billion impressions monthly will be quite educational.
One of the best presentations I’ve seen: concise, covering the topic from different angles, providing useful information, pitching a product and company in non-obtrusive ways.
The slidedeck by Matthew F. Dennis talks about realtime data and analytics from the perspective of Cassandra and DataStax. It starts by presenting the most important features of Cassandra:
- true multi DC support
- no SPOF
- linear scalability
- great read and write performance
- tunable consistency access
- integrated caching
and a series of use cases for Cassandra:
- time series
- sensor data
- ad tracking
- financial market data
- user activity streams
- fraud detection
- risk analysis
It then summarizes three major Cassandra case studies with quotes emphasizing why Cassandra plays a critical role in each of them:
Enjoy it after the break.
To keep with last week’s model—an educational video about Cassandra, followed by a Cassandra case study—today’s video in the Cassandra NYC 2011 video series from DataStax, is Ilya Maykov describe how Cassandra is used at Ooyala for computing multi-dimensional video analytics reports for 100M+ monthly unique users in near-real-time.
Continuing the Cassandra NYC 2011 video series, made available by the folks from DataStax, this week we have Matthew F. Dennis which covers a couple of different Cassandra data modeling use cases.
The fine folks from DataStax have made available the presentations from their Cassandra NYC 2011 event.
The first video to post here is Eric Evans’s presentation on Cassandra Query Language.