This might help: http://www.cloudera.com/documentation/enterprise/latest/topics/impala_performance.html
On Tue, Oct 18, 2016 at 12:30 AM, Buntu Dev <buntu...@gmail.com> wrote: > I got table of user purchases and subscriptions with various product skus > along with user attributes in a single table (~1g and 20M rows). > > Due to the number of combinations for slicing and dicing the data, it takes > a while to query for churn, retention, etc. on the dataset for various time > periods and product skus selected and makes it not ideal the frontend. > Generating a precomputed table with all the combinations is pretty > exhausting, so I'm look to see if there are any best practices in designing > a schema to overcome these issues. > > > Thanks!
