SELECT

The SELECT statement reads data from tables, allowing you to query and process your data based on one or more parameters.

Syntax Summary

This code block is a quick reference with all the parameters that you can use with the SELECT statement.

See some practical examples.

SELECT [ DISTINCT ] [ * | expression [ [ AS ] expression_alias ] [, ...] ]
FROM from_item [, ...]
[JOIN from_item [ ON join_condition | USING ( join_column [, ...] ) ]]
[ WHERE condition ]
[ GROUP BY { expression | expression_index } [, ...] ]
[ HAVING condition [, ...] ]
[ ORDER BY { column_name | column_position |expression } [, ...] ]

Parameters

The SELECT statement accepts the following parameters.

Most of these parameters are optional, but you must provide an expression parameter and a from_item parameter.

Parameter Description Example

DISTINCT

The SELECT DISTINCT statement returns only unique rows, ignoring any duplicates.

expression

The columns to select such as names of columns or the * wildcard.

from_item

A table expression that can be one of the following:

  • [schema_name.]table_name [ [ AS ] table_alias]

  • (SELECT …​ ) AS table_alias

  • TABLE(function_name([ argument [, …​] ] ))

  • (VALUES (expression, [, …​]) [, …​] )

JOIN

An optional clause that, if given, combines the results of two or more table expressions based on the values of particular columns. JOIN expressions (also called joins) define a data source in the FROM sub-clause.

WHERE condition

An optional clause that, if given, indicates the conditions that rows must satisfy to be selected. condition is an expression that is evaluated for each row. If the expression is true, the row is selected. This expression is evaluated before grouping.

GROUP BY expression

An optional clause that allows you to group results in a column by the given expression.

HAVING condition

An optional filter that selects only group rows that satisfy the condition. Unlike WHERE filters, the HAVING filter is applied to group rows created by a GROUP BY subquery or aggregate functions such as SUM().

Examples

This section lists some example SQL queries that show you how to use the SELECT statement.

Get Columns by Name

You can get columns by name, by adding them as a comma-separated list after the SELECT statement.

SELECT name, likes FROM csv_likes;
+--------------------+------------+
|name                |       likes|
+--------------------+------------+
|Jerry               |          13|
|Greg                |         108|
|Mary                |          73|
|Jerry               |          88|
+--------------------+------------+

To get all columns from a table, use the * character.

SELECT * FROM csv_likes;
+------------+--------------------+------------+
|          id|name                |       likes|
+------------+--------------------+------------+
|           1|Jerry               |          13|
|           2|Greg                |         108|
|           3|Mary                |          73|
|           4|Jerry               |          88|
+------------+--------------------+------------+

Filter Rows by Condition

You can filter rows by using a WHERE clause to find columns according to a certain condition.

SELECT name FROM csv_likes WHERE likes > 20;
+--------------------+
|name                |
+--------------------+
|Greg                |
|Mary                |
|Jerry               |
+--------------------+

To filter rows on more than one condition, you can join conditions with the AND, OR, and NOT operators.

SELECT *
FROM csv_likes
WHERE likes > 20 AND name = 'Mary';
+------------+--------------------+------------+
|          id|name                |       likes|
+------------+--------------------+------------+
|           3|Mary                |          73|
+------------+--------------------+------------+

Sort and Limit Results

You can use the standard SQL clauses ORDER BY, LIMIT, and OFFSET to sort and limit the result set of a query.

To use these clauses on map entries, the map entries must be indexed. See Indexing Maps.
You cannot use these clauses in subqueries.

The following statement gets the top five employees ordered by the first_name field and skips the first three results:

SELECT
    employee_id, first_name, last_name
FROM
    employees
ORDER BY first_name
LIMIT 5 OFFSET 3;

The following statement gets the top five employees with the highest salaries.

SELECT
    employee_id, first_name, last_name, salary
FROM
    employees
ORDER BY salary DESC
LIMIT 5;

Join Tables

You can use the standard SQL JOIN clause to combines rows from two or more tables, based on a related column among them.

This clause has the following limitatons:

  • At the moment, Hazelcast supports only LEFT JOIN, which returns all records from the left table as well as the matching records from the right table.

  • You cannot reorder the results of a join. Tables are always joined in the order they appear in the FROM clause.

  • On the right side of the join, you can use only a map. For example, you can do FROM my_kafka_topic JOIN my_map, but not FROM my_map JOIN my_kafka_topic even though these queries are equivalent.

The following query gets the names of all employees that are managers and their departments.

SELECT
    managers.department, employees.name
FROM
    managers
JOIN employees
ON managers.manager_id = employees.employee_id

The following query is equivalent.

SELECT
    managers.department, employees.name
FROM
    managers, employees
WHERE managers.manager_id = employees.employee_id
In these examples, the employee table must be a map because it’s on the right side of the join.

Alias Columns in the Query Results

If you are returning query results to a client, you may want to give the returned columns a new name.

To alias a column in your query results, use the AS clause.

This clause does not rename the column in the table.
SELECT name AS popular_users, likes
FROM csv_likes
WHERE likes > 20;
+--------------------+------------+
|popular_users       |       likes|
+--------------------+------------+
|Greg                |         108|
|Mary                |          73|
|Jerry               |          88|
+--------------------+------------+

Aggregate Data

To perform calculations on rows, use aggregate functions.

For a complete list of available aggregate functions, see Functions and Operators.

You cannot aggregate data that comes a streaming query.

To calculate the total number of likes for all names, use the SUM() function.

SELECT SUM(likes) AS total_likes FROM csv_likes;
+--------------------+
|         total_likes|
+--------------------+
|                 282|
+--------------------+

To filter for the names that have more than 100 likes, use the HAVING clause, which is equivalent to the WHERE clause but for aggregate groups.

SELECT name AS most_liked
FROM csv_likes
GROUP BY name HAVING SUM(likes) > 100;
+--------------------+
|most_liked          |
+--------------------+
|Jerry               |
|Greg                |
+--------------------+

To pass a function only unique values, use the DISTINCT operator.

This operator is ignored in MIN/MAX functions.

This query calculates the number of distinct colors of cars in a table.

SELECT COUNT(DISTINCT color)
FROM cars

Generate Data

To generate data and make it available as a table that you can use in your own statements, use table-valued functions.

To generate a table with numbers 1 to 3, use the TABLE(generate_series()) table expression.

SELECT * FROM TABLE(generate_series(1,3));
+------------+
|           v|
+------------+
|           1|
|           2|
|           3|
+------------+

To generate a stream of data, use the TABLE(generate_stream()) table expression. This example generates 100 numbers per second, starting from 0 and displays only multiples of 10 in the results.

SELECT * FROM TABLE(generate_stream(100))
WHERE v / 10 * 10 = v;