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SkillsCast

Make Your Data FABulous

4th July 2019 in London at CodeNode

There are 15 other SkillsCasts available from Infiniteconf 2019 - A one-day community celebration of Big Data, Machine Learning and AI

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The CAP theorem is widely known for distributed systems, but it's not the only tradeoff you should be aware of. For datastores there is also the FAB theory and just like with the CAP theorem you can only pick two:

Fast: Results are real-time or near real-time instead of batch oriented Accurate: Answers are exact and don't have a margin of error. Big: You require horizontal scaling and need to distribute your data.

While Fast and Big are relatively easy to understand, Accurate is a bit harder to picture. This talk shows some concrete examples of accuracy tradeoffs Elasticsearch can take for terms aggregations, cardinality aggregations with HyperLogLog++, and the IDF part of full-text search. Or how to trade some speed or the distribution for more accuracy.

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Make Your Data FABulous

Philipp Krenn

Research assistant, Vienna University of Technology Philipp Krenn is currently writing his thesis on NoSQL and is employed as a research assistant at the Vienna University of Technology for a commercial product (ERPEL) which is based on MongoDB and

SkillsCast

Please log in to watch this conference skillscast.

Https s3.amazonaws.com prod.tracker2 resource 41088130 skillsmatter conference skillscast o9nohu

The CAP theorem is widely known for distributed systems, but it's not the only tradeoff you should be aware of. For datastores there is also the FAB theory and just like with the CAP theorem you can only pick two:

Fast: Results are real-time or near real-time instead of batch oriented Accurate: Answers are exact and don't have a margin of error. Big: You require horizontal scaling and need to distribute your data.

While Fast and Big are relatively easy to understand, Accurate is a bit harder to picture. This talk shows some concrete examples of accuracy tradeoffs Elasticsearch can take for terms aggregations, cardinality aggregations with HyperLogLog++, and the IDF part of full-text search. Or how to trade some speed or the distribution for more accuracy.

YOU MAY ALSO LIKE:

Thanks to our sponsors

About the Speaker

Make Your Data FABulous

Philipp Krenn

Research assistant, Vienna University of Technology Philipp Krenn is currently writing his thesis on NoSQL and is employed as a research assistant at the Vienna University of Technology for a commercial product (ERPEL) which is based on MongoDB and

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