always

Type of operation: Filter

Description

When the verb input is a Resource dataset, always selects all resources that matched the predicate at all times. always may also be applied to a non-Resource dataset if it has a primary key. In that case, the primary key identifies groups of rows. always selects all groups where every row in the group matches the predicate.

Usage

always predicate, [ frame ]

Argument	Type	Optional	Repeatable	Restrictions
predicate	bool	no	no	none
frame	frame	yes	no	constant

Accelerable

always is accelerable if there is a frame() argument. A dataset that only uses accelerable verbs can be accelerated, making queries on the dataset respond faster.

Examples

always string(status_code) ~ /^2.*/

Select only resources where the status_code column, converted to string, always started with 2, at all points of the query time window. This formulation is not accelerable.

always string(status_code) ~ /^2.*/, frame(back: 30m)

Select only resources where the status_code column, converted to string, started with 2, at all times in the last half hour. This formulation is accelerable because the frame(back:30m) argument specifies a relative time range to check.

always bytesUsed > 20000000

Assume the verb input is an Event dataset representing memory usage metrics. The input dataset has a Valid From field “timestamp”, a primary key (“deviceId”), and an additional column “bytesUsed”. The OPAL selects the “deviceId”s for which bytesUsed is above 20000000 at all times, and returns all rows for the selected “deviceId”s.