ClickHouse Simple Queries (WHERE Clause, IN Clause, ORDER BY, etc.)
.clickhouse Basic Concepts of Simple Queries
.clickhouse is an open-source columnar storage engine primarily used for large-scale data processing and analysis.
WHERE Clause
The WHERE clause filters a subset of the table's data based on any condition.
Syntax: SELECT column_name FROM table_name WHERE condition;
Example:
SELECT * FROM customers WHERE country='USA';IN Clause
The IN clause filters a subset of the table's data based on one or more values.
Syntax: SELECT column_name FROM table_name WHERE column_name IN (value1, value2, ...);
Example:
SELECT * FROM customers WHERE country IN ('USA', 'Canada');ORDER BY Clause
The ORDER BY clause sorts the data in a table.
Syntax: SELECT column_name FROM table_name ORDER BY column_name ASC|DESC;
Example:
SELECT * FROM customers ORDER BY last_name ASC;LIMIT Clause
The LIMIT clause limits the number of rows returned from a table.
Syntax: SELECT column_name FROM table_name LIMIT n;
Example:
SELECT * FROM customers LIMIT 10;.clickhouse Unique Features
.clickhouse has unique query capabilities, such as full-table scans, Range Scan, and Interval Scan. These features can improve performance in certain scenarios but may also increase resource pressure.
.clickhouse Functions
.clickhouse provides a series of functions for calculating and comparing data, including SUM, AVG, MAX, MIN, COUNT, DATE_FORMAT, NOW(), etc. These functions are invoked by providing the function name along with necessary parameters.
Syntax: SELECT function_name(value1, value2, ...) FROM table_name;
Example:
SELECT SUM(column_name) FROM customers;.clickhouse Combined Queries
.clickhouse supports combined queries including joins and subqueries. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 JOIN table2 ON condition UNION SELECT column_name FROM table3 WHERE condition;
Example:
SELECT * FROM customers JOIN orders ON customers.customer_id = orders.customer_id;.clickhouse Grouping and Aggregation
.clickhouse supports SQL-standard grouping and aggregation, including GROUP BY, HAVING, SUM, AVG, MAX, MIN, etc.
Syntax: SELECT column_name, aggregation_function(column_name) FROM table_name GROUP BY column_name HAVING condition;
Example:
SELECT country, SUM(income) FROM customers GROUP BY country;.clickhouse Aggregation Functions
.clickhouse provides a series of aggregation functions including SUM, AVG, MAX, MIN, etc. These functions are invoked by providing the function name along with necessary parameters.
Syntax: SELECT aggregation_function(column_name) FROM table_name;
Example:
SELECT SUM(income) FROM customers;.clickhouse Subquery Joins
.clickhouse supports SQL-standard subqueries including INNER JOIN, LEFT JOIN, RIGHT JOIN and FULL OUTER JOIN etc. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 INNER JOIN table2 ON condition;
Example:
SELECT * FROM customers INNER JOIN orders ON customers.customer_id = orders.customer_id;.clickhouse Subqueries
.clickhouse supports SQL-standard subqueries including single-column and multi-column subqueries. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 WHERE condition;
Example:
SELECT * FROM customers WHERE country IN (SELECT country FROM orders);.clickhouse Full Table Scan
.clickhouse supports full-table scans including filtering and sorting the entire table. These features help handle large-scale data analysis tasks.
Syntax: SELECT column_name FROM table_name;
Example:
SELECT * FROM customers;.clickhouse Range Scan
.clickhouse supports range scanning, including single-column and multi-column range scans. These features help handle large-scale data analysis tasks.
Syntax: SELECT column_name FROM table1 WHERE condition;
Example:
SELECT * FROM customers WHERE income BETWEEN 10000 AND 50000;.clickhouse Interval Scan
.clickhouse supports interval scanning, including single-column and multi-column interval scans. These features help handle large-scale data analysis tasks.
Syntax: SELECT column_name FROM table1 WHERE condition;
Example:
SELECT * FROM customers WHERE created_at BETWEEN '2020-01-01' AND '2020-12-31';.clickhouse Pagination Queries
.clickhouse supports pagination queries, including single-column and multi-column pagination. These features help handle large-scale data analysis tasks.
Syntax: SELECT column_name FROM table_name LIMIT n;
Example:
SELECT * FROM customers LIMIT 10;.clickhouse Computed Subqueries
.clickhouse supports computed subqueries, including single-column and multi-column computed subqueries. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 WHERE condition;
Example:
SELECT * FROM customers WHERE income > (SELECT AVG(income) FROM orders);.clickhouse Conditional Functions
.clickhouse supports conditional functions including IF, CASE etc. These features help handle complex data analysis tasks.
Syntax: SELECT IF(condition, value_if_true, value_if_false);
Example:
SELECT IF(country='USA', 'American', 'Not American');.clickhouse Aggregation Functions
.clickhouse supports aggregation functions including SUM, AVG, MAX, MIN etc. These functions are invoked by providing the function name along with necessary parameters.
Syntax: SELECT aggregation_function(column_name) FROM table_name;
Example:
SELECT SUM(income) FROM customers;.clickhouse Subquery Joins
.clickhouse supports subqueries including INNER JOIN, LEFT JOIN, RIGHT JOIN and FULL OUTER JOIN etc. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 INNER JOIN table2 ON condition;
Example:
SELECT * FROM customers INNER JOIN orders ON customers.customer_id = orders.customer_id;.clickhouse Subqueries
.clickhouse supports subqueries including single-column and multi-column subqueries. These features help handle complex data analysis tasks.
Syntax: SELECT column_name FROM table1 WHERE condition;
Example:
SELECT * FROM customers WHERE country IN (SELECT country FROM orders);