max_n() functions give the same results as the regular SQL query SELECT ... ORDER BY ... LIMIT n. But unlike the SQL query, they can be composed and
combined like other aggregate hyperfunctions.
To get the N smallest values, use min_n(). To get the N largest
values with accompanying data, use max_n_by().
This function group uses the two-step aggregation
pattern. In addition to the usual aggregate function max_n, it also
includes accessors and rollup functions.
Two-step aggregation
This group of functions uses the two-step aggregation pattern. Rather than calculating the final result in one step, you first create an intermediate aggregate by using the aggregate function. Then, use any of the accessors on the intermediate aggregate to calculate a final result. You can also roll up multiple intermediate aggregates with the rollup functions. The two-step aggregation pattern has several advantages:- More efficient because multiple accessors can reuse the same aggregate
- Easier to reason about performance, because aggregation is separate from final computation
- Easier to understand when calculations can be rolled up into larger intervals, especially in window functions and continuous aggregates
- Perform retrospective analysis even when underlying data is dropped, because the intermediate aggregate stores extra information not available in the final result
Samples
Get the 10 largest transactions from a table of stock trades
This example assumes that you have a table of stock trades in this format:Available functions
Aggregate
max_n(): construct an aggregate that keeps track of the largest values passed through it
Accessors
into_values(): return the N highest values seen by the aggregateinto_array(): return the N highest values seen by the aggregate as an array
Rollup
rollup(): combine multiple MaxN aggregates