Create a Secondary Index

This document describes how to create a secondary index using SQL and various programming languages and lists the rules of index creation. In this document, the Bookshop application is taken as an example to walk you through the steps of secondary index creation.

Before you start

Before creating a secondary index, do the following:

• Build a TiDB Cluster in TiDB Cloud (Developer Tier).
• Read Schema Design Overview.
• Create a Database.
• Create a Table.

What is secondary index

A secondary index is a logical object in a TiDB cluster. You can simply regard it as a sorting type of data that TiDB uses to improve the query performance. In TiDB, creating a secondary index is an online operation, which does not block any data read and write operations on a table. For each index, TiDB creates references for each row in a table and sorts the references by selected columns instead of by data directly.

For more information about secondary indexes, see Secondary Indexes.

For more information about secondary indexes, see Secondary Indexes.

In TiDB, you can either add a secondary index to an existing table or create a secondary index when creating a new table.

Add a secondary index to an existing table

To add a secondary index to an existing table, you can use the CREATE INDEX statement as follows:

CREATE INDEX {index_name} ON {table_name} ({column_names});

Parameter description:

• {index_name}: the name of a secondary index.
• {table_name}: the table name.
• {column_names}: the names of the columns to be indexed, separated by semi-colon commas.

Create a secondary index when creating a new table

To create a secondary index at the same time as table creation, you can add a clause containing the KEY keyword to the end of the CREATE TABLE statement:

KEY `{index_name}` (`{column_names}`)

Parameter description:

• {index_name}: the name of a secondary index.
• {column_names}: the names of the columns to be indexed, separated by semi-colon commas.

Rules in secondary index creation

See Best Practices for Indexing.

Example

Suppose you want the bookshop application to support searching for all books published in a given year.

The fields in the books table are as follows:

The books table is created using the following SQL statement:

CREATE TABLE `bookshop`.`books` (
  `id` bigint(20) AUTO_RANDOM NOT NULL,
  `title` varchar(100) NOT NULL,
  `type` enum('Magazine', 'Novel', 'Life', 'Arts', 'Comics', 'Education & Reference', 'Humanities & Social Sciences', 'Science & Technology', 'Kids', 'Sports') NOT NULL,
  `published_at` datetime NOT NULL,
  `stock` int(11) DEFAULT '0',
  `price` decimal(15,2) DEFAULT '0.0',
  PRIMARY KEY (`id`) CLUSTERED
) DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_bin;

To support the searching by year feature, you need to write a SQL statement to search for all books published in a given year. Taking 2022 as an example, write a SQL statement as follows:

SELECT * FROM `bookshop`.`books` WHERE `published_at` >= '2022-01-01 00:00:00' AND `published_at` < '2023-01-01 00:00:00';

To check the execution plan of the SQL statement, you can use the EXPLAIN statement.

EXPLAIN SELECT * FROM `bookshop`.`books` WHERE `published_at` >= '2022-01-01 00:00:00' AND `published_at` < '2023-01-01 00:00:00';

The following is an example output of the execution plan:

+-------------------------+----------+-----------+---------------+--------------------------------------------------------------------------------------------------------------------------+
| id                      | estRows  | task      | access object | operator info                                                                                                            |
+-------------------------+----------+-----------+---------------+--------------------------------------------------------------------------------------------------------------------------+
| TableReader_7           | 346.32   | root      |               | data:Selection_6                                                                                                         |
| └─Selection_6           | 346.32   | cop[tikv] |               | ge(bookshop.books.published_at, 2022-01-01 00:00:00.000000), lt(bookshop.books.published_at, 2023-01-01 00:00:00.000000) |
|   └─TableFullScan_5     | 20000.00 | cop[tikv] | table:books   | keep order:false                                                                                                         |
+-------------------------+----------+-----------+---------------+--------------------------------------------------------------------------------------------------------------------------+
3 rows in set (0.61 sec)

In the example output, TableFullScan is displayed in the id column, which means that TiDB is ready to do a full table scan on the books table in this query. In the case of a large amount of data, however, a full table scan might be quite slow and cause a fatal impact.

To avoid such impact, you can add an index for the published_at column to the books table as follows:

CREATE INDEX `idx_book_published_at` ON `bookshop`.`books` (`bookshop`.`books`.`published_at`);

After adding the index, execute the EXPLAIN statement again to check the execution plan.

The following is an example output.

+-------------------------------+---------+-----------+--------------------------------------------------------+-------------------------------------------------------------------+
| id                            | estRows | task      | access object                                          | operator info                                                     |
+-------------------------------+---------+-----------+--------------------------------------------------------+-------------------------------------------------------------------+
| IndexLookUp_10                | 146.01  | root      |                                                        |                                                                   |
| ├─IndexRangeScan_8(Build)     | 146.01  | cop[tikv] | table:books, index:idx_book_published_at(published_at) | range:[2022-01-01 00:00:00,2023-01-01 00:00:00), keep order:false |
| └─TableRowIDScan_9(Probe)     | 146.01  | cop[tikv] | table:books                                            | keep order:false                                                  |
+-------------------------------+---------+-----------+--------------------------------------------------------+-------------------------------------------------------------------+
3 rows in set (0.18 sec)

In the output, IndexRangeScan is displayed instead of TableFullScan, which means that TiDB is ready to use indexes to do this query.

The words such as TableFullScan and IndexRangeScan in the execution plan are operators in TiDB. For more information about execution plans and operators, see TiDB Query Execution Plan Overview.

The execution plan does not return the same operator every time. This is because TiDB uses a Cost-Based Optimization (CBO) approach, in which an execution plan depends on both rules and data distribution. For more information about TiDB SQL performance, see SQL Tuning Overview.

The execution plan does not return the same operator every time. This is because TiDB uses a Cost-Based Optimization (CBO) approach, in which an execution plan depends on both rules and data distribution. For more information about TiDB SQL performance, see SQL Tuning Overview.

To query the indexes on a table, you can use the SHOW INDEXES statement:

SHOW INDEXES FROM `bookshop`.`books`;

The following is an example output:

+-------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+-----------+
| Table | Non_unique | Key_name              | Seq_in_index | Column_name  | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment | Index_comment | Visible | Expression | Clustered |
+-------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+-----------+
| books |          0 | PRIMARY               |            1 | id           | A         |           0 |     NULL | NULL   |      | BTREE      |         |               | YES     | NULL       | YES       |
| books |          1 | idx_book_published_at |            1 | published_at | A         |           0 |     NULL | NULL   |      | BTREE      |         |               | YES     | NULL       | NO        |
+-------+------------+-----------------------+--------------+--------------+-----------+-------------+----------+--------+------+------------+---------+---------------+---------+------------+-----------+
2 rows in set (1.63 sec)

Next step

After creating a database and adding tables and secondary indexes to it, you can start adding the data write and read features to your application.