Type of operation: Filter
Exclude rows from the input dataset that do not match the given predicate expression.
filter_last behaves identically to the verb
filter except when the input is a Resource dataset.
See the documentation of
filter for more details.
When the input is a Resource dataset, cell values may change over time for a given row. In this case,
filter the rows based on their last value. When the input is a Resource dataset and the filter predicate refers to a column
which is time-mutable, then
filter_last is not accelerable. See verb
for more information on time-mutable and time-immutable columns. To make
filter_last accelerable on a Resource dataset,
consider instead using
ever with a frame or first using
set_col_immutable. Consider also first converting the Resource
to an Event or Interval dataset using
make_interval, upon which
filter_last is accelerable.
filter_last is sometimes accelerable, depending on options used. A dataset that only uses accelerable verbs can be accelerated, making queries on the dataset respond faster.
filter_last string(status_code) ~ /^5.*/
Keep only rows where the
status_code column, converted to string, starts with “5”.
For more simple examples, see the
Where the input is a Resource dataset with a time-mutable column “status”, select the Resources whose last status during the query window was “ON”. This example is not accelerable.
Suppose the input is a Resource dataset describing many servers and how their statuses change over time. In this example, the primary key of the
input Resource is the column “server_id”, and this column is time-immutable. This example would select the servers whose
server_id is greater
than 100. This example is accelerable because for a given server, its
server_id cannot change over time.