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Right now the datasette logs produced by the ELT pipeline live in a flat denormalized table. This result in some duplicate information and could result in a very wide table if we continue to add columns.
We could use star schemas to model the datasette logs. Each transaction is a log with an http request, timestamp and size. We could create a dimension table for the ip address information. This is where most of the duplicate information is because ip addresses make multiple requests.
The text was updated successfully, but these errors were encountered:
Right now the datasette logs produced by the ELT pipeline live in a flat denormalized table. This result in some duplicate information and could result in a very wide table if we continue to add columns.
We could use star schemas to model the datasette logs. Each transaction is a log with an http request, timestamp and size. We could create a dimension table for the ip address information. This is where most of the duplicate information is because ip addresses make multiple requests.
The text was updated successfully, but these errors were encountered: