Data architecture for event log metrics?
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elliot42
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Published on 2012-07-19T18:21:19Z
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2012/09/17
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My service has a large ongoing number of user events, and we would like to do things like "count occurrence of event type T since date D."
We are trying to make two basic decisions:
What to store? Storing every event vs. only storing aggregates
- (Event log style) log every event and count them later, vs.
- (Time-series style) store a single aggregated "count of event E for date D" for every day
Where to store the data
- In a relational database (particularly MySQL)
- In a non-relational (NoSQL) database
- In flat log files (collected centrally over the network via
syslog-ng
)
What is standard practice / where can I read more about comparing the different types of systems?
Additional details:
- The total event stream is large, potentially hundreds of thousands of entries per day
- But our current need is only to count certain types of events within it
- We don't necessarily need real-time access to the raw data or aggregation results
IMHO, "log all events to files, crawl them at a later time to filter and aggregate the stream" is a pretty standard UNIX Way, but my Rails-y compatriots seem to think that nothing is real unless it's in MySQL.
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