Simple SELECT Clause
The simple SELECT
clause is the main SQL syntax to read and processexisting data.
When used as a stand-alone statement, the simple SELECT
clause isalso called "the SELECT
statement". However, it is also aselection clause that can be combinedwith other constructs to form more complex selection queries.
Synopsis
Tip:
The simple SELECT
clause also has other applications not covered here, such as executing functions like SELECT current_timestamp();
.
Required privileges
The user must have the SELECT
privilege on the tables used as operands.
Parameters
Parameter | Description |
---|---|
DISTINCT or ALL | See Eliminate Duplicate Rows. |
DISTINCT ON ( a_expr [, …] ) | DISTINCT ON followed by a list of scalar expressions within parentheses. See Eliminate Duplicate Rows. |
target_elem | A scalar expression to compute a column in each result row, or to automatically retrieve all columns from the FROM clause.If target_elem contains an aggregate function, a GROUP BY clause can be used to further control the aggregation. |
table_ref | The table expression you want to retrieve data from.Using two or more table expressions in the FROM sub-clause, separated with a comma, is equivalent to a CROSS JOIN expression. |
AS OF SYSTEM TIME timestamp | Retrieve data as it existed as of timestamp . *Note: Because AS OF SYSTEM TIME returns historical data, your reads might be stale. |
WHERE a_expr | Only retrieve rows that return TRUE for a_expr , which must be a scalar expression that returns Boolean values using columns (e.g., <column> = <value> ). |
GROUP BY a_expr | When using aggregate functions in target_elem or HAVING , list the column groupings after GROUP BY . |
HAVING a_expr | Only retrieve aggregate function groups that return TRUE for a_expr , which must be a scalar expression that returns Boolean values using an aggregate function (e.g., <aggregate function> = <value> ). HAVING works like the WHERE clause, but for aggregate functions. |
WINDOW window_definition_list | A list of window functions definitions. |
Eliminate duplicate rows
The DISTINCT
subclause specifies to remove duplicate rows.
By default, or when ALL
is specified, SELECT
returns all the rowsselected, without removing duplicates. When DISTINCT
is specified,duplicate rows are eliminated.
Without ON
, two rows are considered duplicates if they are equal onall the results computed by SELECT
.
With ON
, two rows are considered duplicates if they are equal onlyusing the scalar expressions listed with ON
. When two rows are considered duplicates according to DISTINCT ON
, the values from the first FROM
row in the order specified by ORDER BY
are used to compute the remaining target expressions. If ORDER BY
is not specified, CockroachDB will pick any one of the duplicate rows as first row, non-deterministically.
Examples
Choose columns
Retrieve specific columns
Retrieve specific columns by naming them in a comma-separated list:
> SELECT id, name, balance
FROM accounts;
+----+-----------------------+---------+
| id | name | balance |
+----+-----------------------+---------+
| 1 | Bjorn Fairclough | 1200 |
| 2 | Bjorn Fairclough | 2500 |
| 3 | Arturo Nevin | 250 |
[ truncated ]
+----+-----------------------+---------+
Retrieve all columns
Retrieve all columns by using *
:
> SELECT *
FROM accounts;
+----+-----------------------+---------+----------+--------------+
| id | name | balance | type | state_opened |
+----+-----------------------+---------+----------+--------------+
| 1 | Bjorn Fairclough | 1200 | checking | AL |
| 2 | Bjorn Fairclough | 2500 | savings | AL |
| 3 | Arturo Nevin | 250 | checking | AK |
[ truncated ]
+----+-----------------------+---------+----------+--------------+
Filter rows
Filter on a single condition
Filter rows with expressions that use columns and return Boolean values in the WHERE
clause:
> SELECT name, balance
FROM accounts
WHERE balance < 300;
+------------------+---------+
| name | balance |
+------------------+---------+
| Arturo Nevin | 250 |
| Akbar Jinks | 250 |
| Andrea Maas | 250 |
+------------------+---------+
Filter on multiple conditions
To use multiple WHERE
filters join them with AND
or OR
. You can also create negative filters with NOT
:
> SELECT *
FROM accounts
WHERE balance > 2500 AND NOT type = 'checking';
+----+-------------------+---------+---------+--------------+
| id | name | balance | type | state_opened |
+----+-------------------+---------+---------+--------------+
| 4 | Tullia Romijnders | 3000 | savings | AK |
| 62 | Ruarc Mathews | 3000 | savings | OK |
+----+-------------------+---------+---------+--------------+
Select distinct rows
Columns without the Primary Key or Unique constraints can have multiple instances of the same value:
> SELECT name
FROM accounts
WHERE state_opened = 'VT';
+----------------+
| name |
+----------------+
| Sibylla Malone |
| Sibylla Malone |
+----------------+
Using DISTINCT
, you can remove all but one instance of duplicate values from your retrieved data:
> SELECT DISTINCT name
FROM accounts
WHERE state_opened = 'VT';
+----------------+
| name |
+----------------+
| Sibylla Malone |
+----------------+
Filter values with a list
Using WHERE <column> IN (<comma separated list of values>)
performs an OR
search for listed values in the specified column:
> SELECT name, balance, state_opened
FROM accounts
WHERE state_opened IN ('AZ', 'NY', 'WA');
+-----------------+---------+--------------+
| name | balance | state_opened |
+-----------------+---------+--------------+
| Naseem Joossens | 300 | AZ |
| Aygün Sanna | 900 | NY |
| Carola Dahl | 800 | NY |
| Edna Barath | 750 | WA |
| Edna Barath | 2200 | WA |
+-----------------+---------+--------------+
Rename columns in output
Instead of outputting a column's name in the retrieved table, you can change its label using AS
:
> SELECT name AS NY_accounts, balance
FROM accounts
WHERE state_opened = 'NY';
+-------------+---------+
| NY_accounts | balance |
+-------------+---------+
| Aygün Sanna | 900 |
| Carola Dahl | 800 |
+-------------+---------+
This does not change the name of the column in the table. To do that, use RENAME COLUMN
.
Search for string values
Search for partial string matches in columns using LIKE
, which supports the following wildcard operators:
%
matches 0 or more characters._
matches exactly 1 character.
For example:
> SELECT id, name, type
FROM accounts
WHERE name LIKE 'Anni%';
+----+----------------+----------+
| id | name | type |
+----+----------------+----------+
| 58 | Annibale Karga | checking |
| 59 | Annibale Karga | savings |
+----+----------------+----------+
Aggregate functions
Aggregate functions perform calculations on retrieved rows.
Perform aggregate function on entire column
By using an aggregate function as a target_elem
, you can perform the calculation on the entire column.
> SELECT MIN(balance)
FROM accounts;
+--------------+
| MIN(balance) |
+--------------+
| 250 |
+--------------+
You can also use the retrieved value as part of an expression. For example, you can use the result in the WHERE
clause to select additional rows that were not part of the aggregate function itself:
> SELECT id, name, balance
FROM accounts
WHERE balance = (
SELECT
MIN(balance)
FROM accounts
);
+----+------------------+---------+
| id | name | balance |
+----+------------------+---------+
| 3 | Arturo Nevin | 250 |
| 10 | Henrik Brankovic | 250 |
| 26 | Odalys Ziemniak | 250 |
| 35 | Vayu Soun | 250 |
+----+------------------+---------+
Perform aggregate function on retrieved rows
By filtering the statement, you can perform the calculation only on retrieved rows:
> SELECT SUM(balance)
FROM accounts
WHERE state_opened IN ('AZ', 'NY', 'WA');
+--------------+
| SUM(balance) |
+--------------+
| 4950 |
+--------------+
Filter columns fed into aggregate functions
You can use FILTER (WHERE <Boolean expression>)
in the target_elem
to filter which rows are processed by an aggregate function; those that return FALSE
or NULL
for the FILTER
clause's Boolean expression are not fed into the aggregate function:
> SELECT count(*) AS unfiltered, count(*) FILTER (WHERE balance > 1500) AS filtered FROM accounts;
+------------+----------+
| unfiltered | filtered |
+------------+----------+
| 84 | 14 |
+------------+----------+
Create aggregate groups
Instead of performing aggregate functions on an the entire set of retrieved rows, you can split the rows into groups and then perform the aggregate function on each of them.
When creating aggregate groups, each column used as a target_elem
must be included in GROUP BY
.
For example:
> SELECT state_opened AS state, SUM(balance) AS state_balance
FROM accounts
WHERE state_opened IN ('AZ', 'NY', 'WA')
GROUP BY state_opened;
+-------+---------------+
| state | state_balance |
+-------+---------------+
| AZ | 300 |
| NY | 1700 |
| WA | 2950 |
+-------+---------------+
Filter aggregate groups
To filter aggregate groups, use HAVING
, which is the equivalent of the WHERE
clause for aggregate groups, which must evaluate to a Boolean value.
For example:
> SELECT state_opened, AVG(balance) as avg
FROM accounts
GROUP BY state_opened
HAVING AVG(balance) BETWEEN 1700 AND 50000;
+--------------+---------+
| state_opened | avg |
+--------------+---------+
| AR | 3700.00 |
| UT | 1750.00 |
| OH | 2500.00 |
| AL | 1850.00 |
+--------------+---------+
Use aggregate functions in having clause
Aggregate functions can also be used in the HAVING
clause without needing to be included as a target_elem
.
For example:
> SELECT name, state_opened
FROM accounts
WHERE state_opened in ('LA', 'MO')
GROUP BY name, state_opened
HAVING COUNT(name) > 1;
+----------------+--------------+
| name | state_opened |
+----------------+--------------+
| Yehoshua Kleid | MO |
+----------------+--------------+
Select from a specific index
By using the explicit index annotation, you can override CockroachDB's index selection and use a specific index when reading from a named table.
Note:
Index selection can impact performance, but does not change the result of a query.
The syntax to force a scan of a specific index is:
> SELECT * FROM table@my_idx;
This is equivalent to the longer expression:
> SELECT * FROM table@{FORCE_INDEX=my_idx};
New in v19.1: The syntax to force a reverse scan of a specific index is:
> SELECT * FROM table@{FORCE_INDEX=my_idx,DESC};
Forcing a reverse can is sometimes useful during performance tuning. For reference, the full syntax for choosing an index and its scan direction is
SELECT * FROM table@{FORCE_INDEX=idx[,DIRECTION]}
where the optional DIRECTION
is either ASC
(ascending) or DESC
(descending).
When a direction is specified, that scan direction is forced; otherwise the cost-based optimizer is free to choose the direction it calculates will result in the best performance.
You can verify that the optimizer is choosing your desired scan direction using EXPLAIN (OPT)
. For example, given the table
> CREATE TABLE kv (K INT PRIMARY KEY, v INT);
you can check the scan direction with:
> EXPLAIN (opt) SELECT * FROM kv@{FORCE_INDEX=primary,DESC};
text
text
scan kv,rev
└── flags: force-index=primary,rev
(2 rows)
To see all indexes available on a table, use SHOW INDEXES
.
Select historical data (time-travel)
CockroachDB lets you find data as it was stored at a given point intime using AS OF SYSTEM TIME
with various supportedformats. This can be also advantageous forperformance. For more details, see AS OF SYSTEM
.
TIME
Advanced uses of SELECT clauses
CockroachDB supports numerous ways to combine results from SELECT
clauses together.
See Selection Queries fordetails. A few examples follow.
Sorting and limiting query results
To order the results of a SELECT
clause or limit the number of rowsin the result, you can combine it with ORDER BY
or LIMIT
/OFFSET
to form a selection query orsubquery.
See Ordering Query Results and Limiting QueryResults for more details.
Note:
When ORDER BY
is not included in a query, rows are not sorted by any consistent criteria. Instead, CockroachDB returns them as the coordinating node receives them.Also, CockroachDB sorts NULL
values first with ASC
and last with DESC
. This differs from PostgreSQL, which sorts NULL
values last with ASC
and first with DESC
.
Combining results from multiple queries
Results from two or more queries can be combined together as follows:
- Using join expressions to combine rowsaccording to conditions on specific columns.
- Using set operations to combine rowsusing inclusion/exclusion rules.