Preamble
In this post you will learn how to get the number of MySQL lines in a database.
Getting the number of MySQL rows in one table
To get the number of rows per table, you use the COUNT(*) operator in SELECT as follows:
SELECT
COUNT(*)
FROM
table_name;
For example, to get the number of rows in the andreyex table in a database example, use the following operator:
SELECT
COUNT(*)
FROM
andrex;
+ ---------- +
| COUNT(*) |
+ ---------- +
| 35 |
+ ---------- +
1 row in set (0.01 sec)
Getting the number of MySQL rows in two or more tables
To get the number of rows in several tables, you use the UNION operator to combine sets of results returned by each individual SELECT operator.
For example, to get the number of rows in a table and the number of rows in a single query, use the following instructions.
SELECT
'andrex' tablename,
COUNT(*) rows
FROM
andrex
UNION
SELECT
"trainings" tablename,
COUNT(*) rows
FROM
I'm sorry;
| tablename | rows |
| andrex | 34 |
| | 451 |
2 rows in set (0.01 sec)
Getting the number of MySQL rows of all tables in a particular database
To get the number of rows of all tables in a particular database, such as classicmodels, you use the following steps:
- First, get all table names in the database
- Second, create a SQL statement that includes all SELECT COUNT(*) FROM table_name operators for all tables separated by UNION.
- Third, execute a SQL statement using the prepared statement
First, to get all the names of the database tables, you query the following from the information_schema database:
SELECT
table_name
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
AND table_type = 'BASE TABLE';
+ -------------- +
| TABLE_NAME |
+ -------------- +
| andrex |
|
| sites |
+ -------------- +
3 rows in set (0.02 sec)
Second, to build the SQL operator, we use GROUP_CONCAT and CONCAT functions as follows:
SELECT
CONCAT(GROUP_CONCAT(CONCAT('SELECT ''',
table_name,
'' table_name,COUNT(*) rows FROM ',
table_name)
' UNION '),
' ORDER BY table_name')
INTO @sql
FROM
table_list;
This query contains a list of table_list table names, which is the result of the query at the first stage.
The next query uses the first query as a derived table and returns the SQL instruction as a string.
SELECT
CONCAT(GROUP_CONCAT(CONCAT('SELECT ''',
table_name,
'' table_name,COUNT(*) rows FROM ',
table_name)
' UNION '),
' ORDER BY table_name')
INTO @sql
FROM
(SELECT
table_name
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
AND table_type = 'BASE TABLE') table_list
If you use MySQL 8.0+, you can use MySQL CTE (generic table expression) instead of a derived table:
WITH table_list AS (
SELECT
table_name
FROM information_schema.tables
WHERE table_schema = 'classicmodels' AND
table_type = 'BASE TABLE'
)
SELECT CONCAT(
GROUP_CONCAT(CONCAT("SELECT '",table_name," table_name,COUNT(*) rows FROM ",table_name) SEPARATOR " UNION "),
' ORDER BY table_name'.
)
INTO @sql
FROM table_list;
Third, you execute the @sql operator using the prepared operator as follows:
PREPARE s FROM @sql;
EXECUTE s;
DEALLOCATE PREPARE s;
Getting the number of MySQL rows of all tables in a database by one query
A quick way to get the number of rows of all tables in the database is to query data from the information_schema database directly:
SELECT
table_name,
table_rows
FROM
information_schema.tables
WHERE
table_schema = 'classicmodels'
ORDER BY table_name;
This method is sometimes not accurate because the number of rows in information_schema and the actual number of rows in tables are not synchronized. To avoid this, you must follow the ANALYZE TABLE instruction before requesting the number of rows in the information_schema database.
ANALYZE TABLE table_name,...;
In this article you learned about different ways to get the number of rows of one or more tables in a MySQL database.
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of clouds, RDBMS, NoSQL, and machine learning database platforms.
The views expressed on this blog are those of the author and do not necessarily reflect the opinions of Enteros Inc. This blog may contain links to the content of third-party sites. By providing such links, Enteros Inc. does not adopt, guarantee, approve, or endorse the information, views, or products available on such sites.
Are you interested in writing for Enteros’ Blog? Please send us a pitch!
RELATED POSTS
Microfinance platforms scaling to millions
- 15 September 2025
- Software Engineering
Introduction Microfinance has transformed financial inclusion, giving underserved communities access to credit and opportunity. But as platforms scale from thousands to millions of borrowers, the very systems enabling this mission can become bottlenecks. The Challenge Peak-hour overload: thousands apply at once, slowing approvals. Read moreMongoDB profiler and database performance problem diagnosis and identificationDelays in scoring: … Continue reading “Microfinance platforms scaling to millions”
Breaking news under load
When traffic spikes become breaking points Election nights. Natural disasters. Global events. In those moments, audiences turn to news sites in record numbers. But just when the newsroom needs to move fastest, the CMS and databases often slow to a crawl. The result: missed updates, frustrated readers, and credibility at risk. When breaking news slows, … Continue reading “Breaking news under load”
Unlocking RevOps Efficiency in the Banking World with AIOps-Powered Database Technology and Root Cause Analysis—Driven by Enteros
Introduction The banking sector has long been a pioneer in adopting cutting-edge technologies to maintain security, efficiency, and customer trust. From mobile banking apps and real-time payments to fraud detection systems and risk management models, financial institutions operate on massive volumes of data and complex database infrastructures. But with this dependency comes a unique set … Continue reading “Unlocking RevOps Efficiency in the Banking World with AIOps-Powered Database Technology and Root Cause Analysis—Driven by Enteros”
Driving Technology Sector Growth with Enteros: AI-Powered Database Performance, Cloud FinOps, and Next-Gen Database Software
Introduction The technology sector is at the heart of global digital transformation. From software-as-a-service (SaaS) providers to enterprise IT vendors, cloud-native startups, and global hyperscalers, the industry is both the builder and consumer of massive-scale digital infrastructure. To remain competitive, technology companies must ensure optimal database performance, leverage the power of artificial intelligence (AI), adopt … Continue reading “Driving Technology Sector Growth with Enteros: AI-Powered Database Performance, Cloud FinOps, and Next-Gen Database Software”