How to Use SELECT Statement in ClickHouse

Galaxy Glossary

How do I use the ClickHouse SELECT statement to query data efficiently?

SELECT retrieves, filters, aggregates, and transforms rows stored in ClickHouse tables.

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Description

Example H2

Example H3

What does the SELECT statement do in ClickHouse?

SELECT reads data from one or more tables, applies filters, joins, aggregations, and functions, and returns the resulting rows to the client. Because ClickHouse is column-oriented, SELECT is optimized for fast analytical queries.

How do I list all columns or only specific ones?

Use SELECT * to return every column, or list columns explicitly to reduce network and CPU usage. Example: SELECT id, name, price FROM Products.

How can I filter rows efficiently?

Add a WHERE clause. ClickHouse skips entire data parts when the condition matches table indexes. Example: SELECT * FROM Orders WHERE order_date >='2024-01-01'.

How do aggregations work in ClickHouse?

GROUP BY aggregates huge datasets quickly. Always pair aggregate functions with GROUP BY or use WITH TOTALS for grand totals. Example: SELECT customer_id, sum(total_amount) FROM Orders GROUP BY customer_id.

Can I join tables in ClickHouse?

Yes. ClickHouse supports INNER, LEFT, RIGHT, and ANY joins. Keep join keys small and low-cardinality for performance. Example below joins Orders with Customers.

How do I order and limit results?

Use ORDER BY and LIMIT to sort and cut result size. ClickHouse streams results, so LIMIT reduces memory usage. Example: SELECT * FROM Products ORDER BY price DESC LIMIT 10.

When should I use ARRAY JOIN or GLOBAL JOIN?

ARRAY JOIN explodes array columns into multiple rows; GLOBAL JOIN forces distributing a small table to every node in a cluster. Use them only when necessary to avoid large shuffles.

Best practices for SELECT in production?

• Always project only needed columns.
• Filter early with WHERE.
• Prefer pre-aggregated materialized views for heavy dashboards.
• Check system.query_log for slow queries and add indexes.

Why How to Use SELECT Statement in ClickHouse is important

How to Use SELECT Statement in ClickHouse Example Usage


-- Top 5 customers by lifetime spend
SELECT c.id, c.name, sum(o.total_amount) AS lifetime_spend
FROM Customers c
JOIN Orders o ON o.customer_id = c.id
WHERE o.order_date BETWEEN '2023-01-01' AND '2024-12-31'
GROUP BY c.id, c.name
ORDER BY lifetime_spend DESC
LIMIT 5;

How to Use SELECT Statement in ClickHouse Syntax


SELECT [DISTINCT] <column_expr_list>
FROM <table_expression>
[WHERE <filter_condition>]
[GROUP BY <expr_list> [WITH TOTALS]]
[HAVING <condition>]
[ORDER BY <expr_list> [ASC|DESC] [NULLS {FIRST|LAST}]]
[LIMIT <n> [OFFSET m]]
[JOIN|ANY JOIN|GLOBAL JOIN <table> USING|ON <keys>]

-- Example 1: get latest orders per customer
SELECT DISTINCT ON (customer_id) *
FROM Orders
ORDER BY customer_id, order_date DESC;

-- Example 2: revenue by product with filtering
SELECT p.id, p.name, sum(oi.quantity * p.price) AS revenue
FROM OrderItems oi
JOIN Products p ON p.id = oi.product_id
WHERE p.stock > 0
GROUP BY p.id, p.name
ORDER BY revenue DESC;

Common Mistakes

Selecting * in production dashboards. It transfers unnecessary columns, increases CPU usage, and slows clients. Fix by listing only required columns.
Forgetting to add a WHERE clause on partition key. ClickHouse scans full partitions, causing slow queries. Always filter by partition or add a data-skipping index.