All OPAL verbs

Opal verbs process sets of rows of columns.

Verb	Description
add_key	Add a candidate key to the output.
aggregate	Aggregates metrics across tag dimensions.
align	Align raw metrics onto a time grid (defined by the input period) by aggregating nearby data points together.
always	When the verb input is a Resource dataset, always selects all resources that matched the predicate at all times.
bottomk	Selects all data for each of the bottom k ranked groups.
dedup	dedup collapses all rows in a dataset with the same timestamp and identical values in specified columns to one row.
drop_col	Exclude one or more columns from the input dataset to the output dataset.
drop_interface	Removes one or more interface implementations from the current dataset.
ever	When the verb input is a Resource dataset, ever selects all resources that at some point matched the predicate.
exists	Return the rows from the default dataset that have a match anywhere in the query time window.
extract_regex	Add one or more columns by matching capture names in a regular expression against a given source expression.
filter	Exclude rows from the input dataset that do not match the given predicate expression.
filter_last	Exclude rows from the input dataset that do not match the given predicate expression.
flatten	Given an object or array input, recursively flatten all child elements into key-value columns, with null intermediates.
flatten_all	Given an object or array input, recursively flatten all child and intermediate elements into key-value columns.
flatten_leaves	Given an object or array input, recursively flatten all child elements into key-value columns, returning only leaf values.
flatten_single	Given an object or array input, flatten the first level of child elements into key-value columns.
follow	Return the rows from the additional joined dataset that have a match anywhere in the query time window.
follow_not	Return the rows from the joined dataset that do not have a match anywhere in the query time window.
fulljoin	Temporal full join, adding new columns in the output dataset.
histogram	Generate an approximated equi-width histogram for the selected expression.
interface	Map fields of this dataset to a pre-defined interface.
join	Temporal inner join, adding new columns in the output dataset.
leftjoin	Temporal left join, adding new columns in the output dataset.
limit	Select the first count rows based on the current ordering of the input and filter out the rest.
lookup	Find matching rows in a dataset, retrieving fields and adding them to the output dataset as new columns.
lookup_ip_info	Using a value or column of type IPv4, look up corresponding fields associated with the IP address.
make_col	Add one or more new columns from the input dataset to the output dataset.
make_event	Creates an Event dataset from an input Table, Interval, or Resource dataset.
make_interval	Creates an Interval dataset from an input Table, Event, or Resource dataset.
make_metric	Creates a metric dataset from dataset with precomputed time grid.
make_resource	Creates a Resource dataset from an input Event or Interval dataset.
make_session	Group events or intervals that are close to each other into sessions, and calculate aggregations over each session.
make_table	Creates a Table dataset from an input Event, Interval, or Resource dataset.
merge_events	Merge consecutive events into new events based on merge conditions.
never	When the verb input is a Resource dataset, never selects all resources that at no point matched the predicate.
not_exists	Return the rows from the default dataset that do not have a match anywhere in the query time window.
pick_col	Exclude all columns except the specified columns from the input dataset to the output dataset.
pivot	The pivot verb rotates a table by transforming rows into columns.
rename_col	Renames a column.
rollup	Rollup raw metrics into aligned metrics.
set_col_enum	Mark specified columns as enumerations, or not, so that the user interface can present them appropriately.
set_col_immutable	Mark resource columns as time immutable (time-invariant), or not.
set_col_searchable	Include or exclude columns from any future full-text search operation.
set_col_visible	Show or hide columns by name.
set_label	Declare the ‘label’ of the output to be the designated column.
set_link	Add a foreign key to the output, which identifies the target dataset and columns used to find a target resource.
set_metric	Register a metric, with its metadata defined in an options object.
set_metric_metadata	Specify the dataset that stores the metadata of the metrics defined in the current dataset.
set_primary_key	Declare the primary key of the output as consisting of one or more named columns.
set_valid_from	Declare the valid from of the output to be the named column, which must be a timestamp column.
set_valid_to	Declare the valid to of the output to be the named column, which must be a timestamp column.
sort	Sort rows in the dataset based on ordering functions applied to column fields or column name provided as arguments.
statsby	Calculate statistics of columns with aggregate functions, based on (optional) grouping columns.
surrounding	Outer joins datasets by matching row time to a specified frame as well as column values.
timechart	Bin (in time) and aggregate point or interval table columns through time, based on (optional) grouping columns.
timeshift	Shifts the timestamps of rows ahead in time by the specified interval.
timestats	Aggregate columns at every point in time, based on (optional) grouping columns.
topk	Selects all data for each of the top k ranked groups.
union	Create a new dataset consisting of the rows from the main input and each of the arguments.
unpivot	The unpivot verb rotates a table by transforming a list of columns into rows.
unset_all_links	Drop all outbound links without having to specify the individual labels.
unset_keys	Remove the primary and candidate key declarations from the dataset.
unset_link	Drop a foreign key by specifying the foreign keys label.
unsort	Remove all column sort ordering metadata that may have been inserted by the sort verb.
update_resource	Augments the input Resource dataset using events from another dataset.

Aliases

Aliases work as alternative names for their main verb. Users of certain other query languages may be more comfortable with these alternative names. Alias names on this list can always be used whenever the main name can be used.

Alias Name	Main Name
distinct	dedup
set_pk	set_primary_key
bucketize	timechart