SELECT
Synopsis
Use the SELECT
statement to retrieve (part of) rows of specified columns that meet a given condition from a table. It specifies the columns to be retrieved, the name of the table, and the condition each selected row must satisfy.
Syntax
Diagram
select
order_expression
Grammar
select ::= SELECT [ DISTINCT ] { * | column_name [ , column_name ... ] }
FROM table_name
[ WHERE where_expression ]
[ IF where_expression ]
[ ORDER BY order_expression ]
[ LIMIT limit_expression ] [ OFFSET offset_expression ]
order_expression ::= ( { column_name [ ASC | DESC ] } [ , ... ] )
Where
table_name
andcolumn_name
are identifiers (table_name
may be qualified with a keyspace name).limit_expression
is an integer literal (or a bind variable marker for prepared statements).- Restrictions for
where_expression
are discussed in the Semantics section. - See Expressions for more information on syntax rules.
Semantics
- An error is raised if the specified
table_name
does not exist. SELECT DISTINCT
can only be used for partition columns or static columns.*
means all columns of the table will be retrieved.LIMIT
clause sets the maximum number of results (rows) to be returned.OFFSET
clause sets the number of rows to be skipped before returning results.ALLOW FILTERING
is provided for syntax compatibility with Cassandra. You can always filter on all columns.- Reads default to
QUORUM
and read from the tablet-leader. - To read from followers use
ONE
consistency level. - To benefit from local reads, in addition to specifying the consistency level of
ONE
, set theregion
also in the client driver to indicate where the request is coming from, and it should match the--placement_region
argument for the yb-tservers in that region.
ORDER BY
clause
- The
ORDER BY
clause sets the order for the returned results. - Only clustering columns are allowed in the
order_expression
. - For a given column,
DESC
means descending order andASC
or omitted means ascending order. - Currently, only two overall orderings are allowed, the clustering order from the
CREATE TABLE
statement (forward scan) or its opposite (reverse scan).
WHERE
clause
-
The
where_expression
must evaluate to boolean values. -
The
where_expression
can specify conditions on any columns including partition, clustering, and regular columns. -
The
where_expression
has a restricted list of operators.- Only
=
,!=
,IN
andNOT IN
operators can be used for conditions on partition columns. - Only operators
=
,!=
,<
,<=
,>
,>=
,IN
andNOT IN
can be used for conditions on clustering and regular columns. - Only
IN
operator can be used for conditions on tuples of clustering columns.
- Only
IF
clause
- The
if_expression
must evaluate to boolean values. - The
if_expression
supports any combinations of all available boolean and logical operators. - The
if_expression
can only specify conditions for non-primary-key columns although it can used on a key column of a secondary index. - While WHERE condition is used to generate efficient query plan, the IF condition is not. ALL rows that satisfy WHERE condition will be read from the database before the IF condition is used to filter unwanted data. In the following example, although the two queries yield the same result set, SELECT with WHERE clause will use INDEX-SCAN while SELECT with IF clause will use FULL-SCAN.
SELECT * FROM a_table WHERE key = 'my_key';
SELECT * FROM a_table IF key = 'my_key';
Note
While the where clause allows a wide range of operators, the exact conditions used in the where clause have significant performance considerations (especially for large datasets). Some best practices are:
- Use equality conditions on all partition columns (to fix the value of the partition key).
- Use comparison operators on the clustering columns (tighter restrictions are more valuable for left-most clustering columns).
- Generally, the closer a column is to the beginning of the primary key, the higher the performance gain for setting tighter restrictions on it.
Ideally, these performance considerations should be taken into account when creating the table schema.
Examples
Select all rows from a table
ycqlsh:example> CREATE TABLE employees(department_id INT,
employee_id INT,
dept_name TEXT STATIC,
employee_name TEXT,
PRIMARY KEY(department_id, employee_id));
ycqlsh:example> INSERT INTO employees(department_id, employee_id, dept_name, employee_name)
VALUES (1, 1, 'Accounting', 'John');
ycqlsh:example> INSERT INTO employees(department_id, employee_id, dept_name, employee_name)
VALUES (1, 2, 'Accounting', 'Jane');
ycqlsh:example> INSERT INTO employees(department_id, employee_id, dept_name, employee_name)
VALUES (1, 3, 'Accounting', 'John');
ycqlsh:example> INSERT INTO employees(department_id, employee_id, dept_name, employee_name)
VALUES (2, 1, 'Marketing', 'Joe');
ycqlsh:example> SELECT * FROM employees;
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 1 | Accounting | John
1 | 2 | Accounting | Jane
1 | 3 | Accounting | John
2 | 1 | Marketing | Joe
Select with limit
ycqlsh:example> SELECT * FROM employees LIMIT 2;
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 1 | Accounting | John
1 | 2 | Accounting | Jane
Select with offset
ycqlsh:example> SELECT * FROM employees LIMIT 2 OFFSET 1;
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 2 | Accounting | Jane
1 | 3 | Accounting | John
Select distinct values
ycqlsh:example> SELECT DISTINCT dept_name FROM employees;
dept_name
------------
Accounting
Marketing
Select with a condition on the partitioning column
ycqlsh:example> SELECT * FROM employees WHERE department_id = 2;
department_id | employee_id | dept_name | employee_name
---------------+-------------+-----------+---------------
2 | 1 | Marketing | Joe
Select with condition on the clustering column
ycqlsh:example> SELECT * FROM employees WHERE department_id = 1 AND employee_id <= 2;
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 1 | Accounting | John
1 | 2 | Accounting | Jane
Select with condition on a regular column, using WHERE clause
ycqlsh:example> SELECT * FROM employees WHERE employee_name = 'John';
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 1 | Accounting | John
1 | 3 | Accounting | John
Select with condition on a regular column, using IF clause
ycqlsh:example> SELECT * FROM employees WHERE department_id = 1 IF employee_name != 'John';
department_id | employee_id | dept_name | employee_name
---------------+-------------+------------+---------------
1 | 2 | Accounting | Jane
Select with ORDER BY
clause
ycqlsh:example> CREATE TABLE sensor_data(device_id INT,
sensor_id INT,
ts TIMESTAMP,
value TEXT,
PRIMARY KEY((device_id), sensor_id, ts)) WITH CLUSTERING ORDER BY (sensor_id ASC, ts DESC);
ycqlsh:example> INSERT INTO sensor_data(device_id, sensor_id, ts, value)
VALUES (1, 1, '2018-1-1 12:30:30 UTC', 'a');
ycqlsh:example> INSERT INTO sensor_data(device_id, sensor_id, ts, value)
VALUES (1, 1, '2018-1-1 12:30:31 UTC', 'b');
ycqlsh:example> INSERT INTO sensor_data(device_id, sensor_id, ts, value)
VALUES (1, 2, '2018-1-1 12:30:30 UTC', 'x');
ycqlsh:example> INSERT INTO sensor_data(device_id, sensor_id, ts, value)
VALUES (1, 2, '2018-1-1 12:30:31 UTC', 'y');
Reverse scan, opposite of the table's clustering order.
ycqlsh:example> SELECT * FROM sensor_data WHERE device_id = 1 ORDER BY sensor_id DESC, ts ASC;
device_id | sensor_id | ts | value
-----------+-----------+---------------------------------+-------
1 | 2 | 2018-01-01 12:30:30.000000+0000 | x
1 | 2 | 2018-01-01 12:30:31.000000+0000 | y
1 | 1 | 2018-01-01 12:30:30.000000+0000 | a
1 | 1 | 2018-01-01 12:30:31.000000+0000 | b
Forward scan, same as a SELECT without an ORDER BY clause.
ycqlsh:example> SELECT * FROM sensor_data WHERE device_id = 1 ORDER BY sensor_id ASC, ts DESC;
device_id | sensor_id | ts | value
-----------+-----------+---------------------------------+-------
1 | 1 | 2018-01-01 12:30:31.000000+0000 | b
1 | 1 | 2018-01-01 12:30:30.000000+0000 | a
1 | 2 | 2018-01-01 12:30:31.000000+0000 | y
1 | 2 | 2018-01-01 12:30:30.000000+0000 | x
Other orderings are not allowed.
ycqlsh:example> SELECT * FROM sensor_data WHERE device_id = 1 ORDER BY sensor_id ASC, ts ASC;
InvalidRequest: Unsupported order by relation
SELECT * FROM sensor_data WHERE device_id = 1 ORDER BY sensor_id ASC, ts ASC;
^^^^^^^^^^^^^^^^^^^^^