Analyzing Log Data with Spark and Looker

May 18, 2016

Machines are constantly generating data. Unlocking the value of log files has historically lived in the realm of batch processing. However, emerging technologies have dramatically reduced the latency of event pipelines and have improved interactive analysis and querying.

In this webinar, Scott Hoover, Looker Data Scientist, and Daniel Mintz, Chief Data Evangelist at Looker, discuss the specifics of setting up a modern pipeline that collects, processes, and analyzes high-volume, machine-generated data.

Topics covered include:

- Popular collection mechanisms

- Hands-on log-parsing example in Spark

- How to utilize Looker to glean insights from event data

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Analyzing Log Data with Spark and Looker
Analyzing Log Data with Spark and Looker

Machines are constantly generating data. Unlocking the value of log files has historically lived in the rea...

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