Calculates the average for the given entry.

from p in Payment, select: avg(p.value)

Counts the entries in the table.

from p in Post, select: count()

Counts the given entry.

from p in Post, select: count(p.id)

Returns relative rank of the current row: (number of rows preceding or peer with current row) / (total rows).

from p in Post,
     select: cume_dist() |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns rank of the current row without gaps; this function counts peer groups.

from p in Post,
     select: dense_rank() |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Applies the given expression as a FILTER clause against an aggregate. This is currently only supported by Postgres.

from p in Post,
     select: avg(p.value)
             |> filter(p.value > 0 and p.value < 100)
             |> over(partition_by: p.category_id, order_by: p.date)

Returns value evaluated at the row that is the first row of the window frame.

from p in Post,
     select: first_value(p.id) |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns value evaluated at the row that is offset rows before the current row within the partition.

If there is no such row, instead return default (which must be of the same type as value). Both offset and default are evaluated with respect to the current row. If omitted, offset defaults to 1 and default to nil.

from e in Events,
     windows: [w: [partition_by: e.name, order_by: e.tick]],
     select: {
       e.tick,
       e.action,
       e.name,
       lag(e.action) |> over(:w), # previous_action
       lead(e.action) |> over(:w) # next_action
     }

Note that this function must be invoked using window function syntax.

Returns value evaluated at the row that is the last row of the window frame.

from p in Post,
     select: last_value(p.id) |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns value evaluated at the row that is offset rows after the current row within the partition.

If there is no such row, instead return default (which must be of the same type as value). Both offset and default are evaluated with respect to the current row. If omitted, offset defaults to 1 and default to nil.

from e in Events,
     windows: [w: [partition_by: e.name, order_by: e.tick],
     select: {
       e.tick,
       e.action,
       e.name,
       lag(e.action) |> over(:w), # previous_action
       lead(e.action) |> over(:w) # next_action
     }

Note that this function must be invoked using window function syntax.

Calculates the maximum for the given entry.

from p in Payment, select: max(p.value)

Calculates the minimum for the given entry.

from p in Payment, select: min(p.value)

Returns value evaluated at the row that is the nth row of the window frame (counting from 1); nil if no such row.

from p in Post,
     select: nth_value(p.id, 4) |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns integer ranging from 1 to the argument value, dividing the partition as equally as possible.

from p in Post,
     select: ntile(10) |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns relative rank of the current row: (rank - 1) / (total rows - 1).

from p in Post,
     select: percent_rank() |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns rank of the current row with gaps; same as row_number/0 of its first peer.

from p in Post,
     select: rank() |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Returns number of the current row within its partition, counting from 1.

from p in Post,
     select: row_number() |> over(partition_by: p.category_id, order_by: p.date)

Note that this function must be invoked using window function syntax.

Calculates the sum for the given entry.

from p in Payment, select: sum(p.value)