Database Development
Databases providing the most efficient means of data management, storage and access are essential to the successful operation of today’s world. One of most widely used database management systems today is MySQL and it is widely employed in web-based services, SaaS applications, e-commerce and enterprise systems. MySQL is a highly scalable and robust relational database management system however, it can be difficult to work with if not properly optimized for large datasets.
In this blog we will go into detail about indexing and how indexing can be used to improve speed of queries and overall performance of the MySQL database. We’ll review the various types of indexes available and what best usage practices exist for developers in utilizing indexes in the MySQL database.
How Does Indexing Work in MySQL?
Using an index in MySQL can be defined as a data structure method for improving/querying speed of database tables. You might consider an index similar to the way a book has a table of contents; the index helps your query quickly identify the location of relevant rows in the table without performing a full table scan of all the records in the table.
In the absence of an index, MySQL would perform a full table scan for each record in the table to find rows matching a condition specified in the query. This process becomes very time-consuming as the number of records increases. However, with an index, the database can quickly retrieve matching rows as specified by the query without needing to scan every record; this results in dramatically reduced retrieval times and increased overall performance.
The Benefits of Indexing to Query Performance
The following are just a few of the performance benefits provided by indexing:
- Faster Retrieval of Data – When queries reference columns that have been indexed, the amount of time to obtain a response is generally much shorter than when referencing non-indexed columns.
- Less Load on the Server – Since the number of rows that MySQL has to examine when executing a query decreases as the number of indexed rows increases, this decreases the amount of CPU and memory consumed by MySQL.
- Optimized Sorting and Filtering of Data – The time required to execute ordering (ORDER BY) and/or filtering (WHERE) statements can be reduced by using indexes to access sorted and/or filtered data more quickly.
- Improved Performance When Joining Tables – When you use foreign key references when executing complex queries that utilize multiple joins, the performance of your query will be enhanced significantly by having foreign keys indexed.
While indexing improves the performance of read operations, indexes will add an additional burden on the performance of write operations (INSERT, UPDATE, DELETE). Understanding when and how to leverage indexes is an important part of improving overall performance in using indexes.
Types of Indexes in MySQL
A variety of index types are available when using MySQL for a range of applications:
1. Primary Key Indexes
The primary key is a unique column identifier for data entries within a table. A table’s primary key will always generate a unique index (or key) automatically for that column. It allows for quick lookups in addition to ensuring all records will have a unique set of values for that column.
2. Unique Index
The unique index allows you to enforce distinctness on the values stored in the indexed column(s). It commonly applies to user tables, such as email, user name, etc. in order to ensure that the record contains only one instance of the same email address.
3. Non-unique Regular Index
The regular index can allow for duplicates within the indexed column(s). It allows for efficient performance improvement of queries utilizing this index type in order to search, sort, and filter.
4. Fulltext Indexes
Fulltext indexes provide greater performance for text search operations. For example, many people use fulltext indexes when performing keyword searches through articles, blogs, or product descriptions.
5. Composite Index
A composite index can consist of multiple columns. It is useful when querying with more than one column condition. The order of the columns included in a composite index has a direct impact on the query performance.
6. Spatial Index
The spatial Indexed columns support the geospatial data type. They improve query performance when dealing with geolocation-based data. Such as (mapping), calculations of distance, etc.
How to Identify Queries That Need Indexing
Not every query benefits from indexing. Indexes are most useful for:
- Columns used in WHERE clauses frequently.
- Columns used in JOIN operations.
- Columns used in ORDER BY and GROUP BY.
- Columns that are searched for uniqueness (like usernames or IDs).
You can identify slow queries using tools like MySQL EXPLAIN, which shows how the query executes and whether indexes are being used.
Best Practices for MySQL Indexing
If you want to maximize the benefits of indexing while minimizing the drawbacks of using lots of indexes, you should follow these best practices for indexing.
1. Index Columns that are Selective
The most selective columns (i.e. those with lots of unique values and very few duplicates) normally give you the greatest benefit from an index. Columns that are low cardinality (e.g. boolean columns) will not give you any performance improvements.
2. Do not Over-Index
Having too many indexes means that there is more data to store, which makes writing to the database slower. Instead, focus on indexing those columns that are queried most often.
3. Use Composite Indexes Correctly
Composite indexes (indexes on more than one column) can provide significant benefits; however, they must follow the order of the columns used in the WHERE clause of your queries. For instance, if you have an index defined on (col1, col2) and you use the following query or similar: WHERE COl1 = ? AND CL2 = ?, then your composite index will significantly help with performance.
4. Regularly Check Indexes
Using SHOW INDEX and EXPLAIN to monitor index usage will allow you to find indexes that are not being used and free up resources.
5. Index Only What is Necessary
Unless absolutely necessary, do not index large text columns. Consider using a prefix index (i.e. indexing the first N characters of a VARCHAR column) if you must index long VARCHAR columns.
6. Index for Joins
You should always create an index for any columns that are part of a foreign key relationship. This will help you achieve the greatest performance improvement for joins.
Mistakes Developers Make
- Relying exclusively on primary keys – Not all queries will use the primary key to look records up and it may be necessary to have other indexes to improve the performance of these other queries.
- Indexing Columns that are Rarely Used – Indexing rarely used columns creates additional overhead with no gain in performance.
- Ignoring Query Analysis – If you fail to analyze which queries will benefit from an index when you create the indexes, then you can create inefficient databases.
- Failing to Update Indexes After Changes to the Schema – If you make changes to the schema (e.g. adding new indexes) you should also update the existing indexes on the affected tables.
Measuring the Impact of Indexing
Indexing has a significant impact on your ability to measure the effects of indexes on query performance.
To assess the indexing process:
- Use EXPLAIN to determine the execution plan of the query.
- Monitor query execution time prior to adding an index and again after adding it.
- Monitor server load and other related resource utilization.
- Use performance monitoring tools, such as MySQL Performance Schema and Percona Monitoring and Management to monitor live usage of indexes and database usage.
By adding an index, you may reduce the execution time of a query from seconds to milliseconds, thus improving user experience and creating a more scalable application.
In conclusion
Indexing is a very important method of improving MySQL query performance. By applying the concepts of primary, unique, composite, fulltext, and spatial type indexes, developers can significantly improve the speed of retrieving data from the database, minimize load on the server, and make their application scalable.
Although the benefits of the indexes in read-heavy systems are indisputable, developers need to take care in planning how to implement indexes in order to minimize other types of overhead associated with writing data to the database. The effective implementation of best practices in monitoring query performance and periodically reviewing the strategy for indexing are necessary to establish a MySQL database with optimal performance.
To be able to create efficient, fast, and scalable applications, developers need to know how to understand and utilize MySQL indexing properly.
Contact Us Today
