GROUP BY clause
Group by one or more columns.
Condenses the selected rows that share the same values for a set of columns or values returned by a function into a group.
Either one or more primary key columns or a deterministic function or aggregate can be used in the GROUP BY clause.
SELECT race_date, race_time FROM cycling.race_times_summary
GROUP BY race_date;Results
race_date | race_time
------------+--------------------
2019-03-21 | 10:01:18.000000000
2018-07-26 | 10:01:18.000000000
2017-04-14 | 10:01:18.000000000
(3 rows)
Warnings :
Aggregation query used without partition keyEach set of rows with the same race_date column value are grouped together into one row in the query output.
Three rows are returned because there are three groups of rows with the same race_date column value.
The value returned is the first value that is found for the group.
ORDER BY clause
You can fine-tune the display order using the ORDER BY clause.
The partition key must be defined in the WHERE clause and then the ORDER BY clause defines one or more clustering columns to use for ordering.
The order of the specified columns must match the order of the clustering columns in the PRIMARY KEY definition.
The options for ordering are ASC (ascending) and DESC (descending).
If no order is specified, the results are returned in the stored order.
|
Note that using both |
SELECT * FROM cycling.calendar WHERE race_id IN (100, 101, 102)
ORDER BY race_start_date ASC;Results
race_id | race_start_date | race_end_date | race_name
---------+---------------------------------+---------------------------------+-----------------------
100 | 2013-05-07 00:00:00.000000+0000 | 2014-05-29 00:00:00.000000+0000 | Giro d'Italia
101 | 2013-06-05 00:00:00.000000+0000 | 2013-06-12 00:00:00.000000+0000 | Criterium du Dauphine
102 | 2013-06-11 00:00:00.000000+0000 | 2013-06-19 00:00:00.000000+0000 | Tour de Suisse
100 | 2014-05-08 00:00:00.000000+0000 | 2014-05-30 00:00:00.000000+0000 | Giro d'Italia
101 | 2014-06-06 00:00:00.000000+0000 | 2014-06-13 00:00:00.000000+0000 | Criterium du Dauphine
102 | 2014-06-12 00:00:00.000000+0000 | 2014-06-20 00:00:00.000000+0000 | Tour de Suisse
100 | 2015-05-09 00:00:00.000000+0000 | 2015-05-31 00:00:00.000000+0000 | Giro d'Italia
101 | 2015-06-07 00:00:00.000000+0000 | 2015-06-14 00:00:00.000000+0000 | Criterium du Dauphine
102 | 2015-06-13 00:00:00.000000+0000 | 2015-06-21 00:00:00.000000+0000 | Tour de Suisse
(9 rows)The ORDER BY clause also supports vector searches of the vector column.
The result set is sorted using the Approximate Nearest Neighbor (ANN) algorithm with the supplied array values.
LIMIT clause
If a query returns a large number of rows, you can limit the number of rows returned, to limit the amount of data returned.
The default limit is set to 10,000 rows, the number of rows cqlsh allows.
This examples limits the rows to 3:
SELECT * FROM cycling.comments_vs
ORDER BY comment_vector ANN OF [0.15, 0.1, 0.1, 0.35, 0.55]
LIMIT 3;Results
id | created_at | comment | comment_vector | commenter | record_id
--------------------------------------+---------------------------------+----------------------------------------+------------------------------+-----------+--------------------------------------
e8ae5cf3-d358-4d99-b900-85902fda9bb0 | 2017-04-01 14:33:02.160000+0000 | rain, rain,rain, go away! | [0.9, 0.54, 0.12, 0.1, 0.95] | John | 70157590-4084-11ef-893f-0fd142cea825
e7ae5cf3-d358-4d99-b900-85902fda9bb0 | 2017-04-01 14:33:02.160000+0000 | LATE RIDERS SHOULD NOT DELAY THE START | [0.9, 0.54, 0.12, 0.1, 0.95] | Alex | 700ebed0-4084-11ef-893f-0fd142cea825
e8ae5df3-d358-4d99-b900-85902fda9bb0 | 2017-04-01 14:33:02.160000+0000 | Rain like a monsoon | [0.9, 0.54, 0.12, 0.1, 0.95] | Jane | 701611d0-4084-11ef-893f-0fd142cea825
(3 rows)PER PARTITION LIMIT clause
The PER PARTITION LIMIT option sets the maximum number of rows that the query returns from each partition.
This will only apply to tables that spread across more than one partition.
An example of such a table is defined here:
USE cycling;
CREATE TABLE rank_by_year_and_name (
race_year int,
race_name text,
cyclist_name text,
rank int,
PRIMARY KEY ((race_year, race_name), rank)
);where the partition key is a composite of race_year and race_name.
The following query returns the top two cyclists from each partition stored:
SELECT rank, cyclist_name AS name FROM cycling.rank_by_year_and_name
PER PARTITION LIMIT 2;Results
ALLOW FILTERING
The ALLOW FILTERING clause allows you to perform queries that require scanning all partitions, with no primary key columns specified.
It should not be used in production as it can cause severe performance issues!
When initially modeling your data, you should avoid using ALLOW FILTERING and instead model your data to avoid it.
However, for a small dataset or for testing purposes, it can be useful.
It may even help you identify where you need to add indexes to your data model.
For more information, see Allow Filtering explained.
The following query selects the birthday and nationality columns from the cyclist_alt_stats table, with the ALLOW FILTERING clause:
SELECT lastname, birthday, nationality FROM cycling.cyclist_alt_stats
WHERE birthday = '1991-08-25' AND nationality = 'Ethiopia'
ALLOW FILTERING;Results
