generated-columns.md

title	summary	aliases
Generated Columns	Learn how to use generated columns.	/docs/dev/generated-columns/ /docs/dev/reference/sql/generated-columns/

Generated Columns

Warning:

This is still an experimental feature. It is NOT recommended that you use it in the production environment.

This document introduces the concept and usage of generated columns.

Basic concepts

Unlike general columns, the value of the generated column is calculated by the expression in the column definition. When inserting or updating a generated column, you cannot assign a value, but only use DEFAULT.

There are two kinds of generated columns: virtual and stored. A virtual generated column occupies no storage and is computed when it is read. A stored generated column is computed when it is written (inserted or updated) and occupies storage. Compared with the virtual generated columns, the stored generated columns have better read performance, but take up more disk space.

You can create an index on a generated column whether it is virtual or stored.

Usage

One of the main usage of generated columns is to extract data from the JSON data type and indexing the data.

In both MySQL 5.7 and TiDB, columns of type JSON can not be indexed directly. That is, the following table schema is not supported:

{{< copyable "sql" >}}

CREATE TABLE person (
    id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    address_info JSON,
    KEY (address_info)
);

To index a JSON column, you must extract it as a generated column first.

Using the city field in address_info as an example, you can create a virtual generated column and add an index for it:

{{< copyable "sql" >}}

CREATE TABLE person (
    id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    address_info JSON,
    city VARCHAR(64) AS (JSON_UNQUOTE(JSON_EXTRACT(address_info, '$.city'))),
    KEY (city)
);

In this table, the city column is a virtual generated column and has an index. The following query can use the index to speed up the execution:

{{< copyable "sql" >}}

SELECT name, id FROM person WHERE city = 'Beijing';

{{< copyable "sql" >}}

EXPLAIN SELECT name, id FROM person WHERE city = 'Beijing';

+---------------------------------+---------+-----------+--------------------------------+-------------------------------------------------------------+
| id                              | estRows | task      | access object                  | operator info                                               |
+---------------------------------+---------+-----------+--------------------------------+-------------------------------------------------------------+
| Projection_4                    | 10.00   | root      |                                | test.person.name, test.person.id                            |
| └─IndexLookUp_10                | 10.00   | root      |                                |                                                             |
|   ├─IndexRangeScan_8(Build)     | 10.00   | cop[tikv] | table:person, index:city(city) | range:["Beijing","Beijing"], keep order:false, stats:pseudo |
|   └─TableRowIDScan_9(Probe)     | 10.00   | cop[tikv] | table:person                   | keep order:false, stats:pseudo                              |
+---------------------------------+---------+-----------+--------------------------------+-------------------------------------------------------------+

From the query execution plan, it can be seen that the city index is used to read the HANDLE of the row that meets the condition city ='Beijing', and then it uses this HANDLE to read the data of the row.

If no data exists at path $.city, JSON_EXTRACT returns NULL. If you want to enforce a constraint that city must be NOT NULL, you can define the virtual generated column as follows:

{{< copyable "sql" >}}

CREATE TABLE person (
    id INT NOT NULL AUTO_INCREMENT PRIMARY KEY,
    name VARCHAR(255) NOT NULL,
    address_info JSON,
    city VARCHAR(64) AS (JSON_UNQUOTE(JSON_EXTRACT(address_info, '$.city'))) NOT NULL,
    KEY (city)
);

Validation of generated columns

Both INSERT and UPDATE statements check virtual column definitions. Rows that do not pass validation return errors:

{{< copyable "sql" >}}

mysql> INSERT INTO person (name, address_info) VALUES ('Morgan', JSON_OBJECT('Country', 'Canada'));
ERROR 1048 (23000): Column 'city' cannot be null

Generated columns index replacement rule

When an expression in a query is equivalent to a generated column with an index, TiDB replaces the expression with the corresponding generated column, so that the optimizer can take that index into account during execution plan construction.

For example, the following example creates a generated column for the expression a+1 and adds an index:

create table t(a int);
desc select a+1 from t where a+1=3;
+---------------------------+----------+-----------+---------------+--------------------------------+
| id                        | estRows  | task      | access object | operator info                  |
+---------------------------+----------+-----------+---------------+--------------------------------+
| Projection_4              | 8000.00  | root      |               | plus(test.t.a, 1)->Column#3    |
| └─TableReader_7           | 8000.00  | root      |               | data:Selection_6               |
|   └─Selection_6           | 8000.00  | cop[tikv] |               | eq(plus(test.t.a, 1), 3)       |
|     └─TableFullScan_5     | 10000.00 | cop[tikv] | table:t       | keep order:false, stats:pseudo |
+---------------------------+----------+-----------+---------------+--------------------------------+
4 rows in set (0.00 sec)

alter table t add column b bigint as (a+1) virtual;
alter table t add index idx_b(b);
desc select a+1 from t where a+1=3;
+------------------------+---------+-----------+-------------------------+---------------------------------------------+
| id                     | estRows | task      | access object           | operator info                               |
+------------------------+---------+-----------+-------------------------+---------------------------------------------+
| IndexReader_6          | 10.00   | root      |                         | index:IndexRangeScan_5                      |
| └─IndexRangeScan_5     | 10.00   | cop[tikv] | table:t, index:idx_b(b) | range:[3,3], keep order:false, stats:pseudo |
+------------------------+---------+-----------+-------------------------+---------------------------------------------+
2 rows in set (0.01 sec)

Note:

Only when the expression type and the generated column type are strictly equal, the replacement is performed.

In the above example, the column type of a is int and the column type of a+1 is bigint. If the type of the generated column is set to int, the replacement will not occur.

For type conversion rules, see [Type Conversion of Expression Evaluation] (/functions-and-operators/type-conversion-in-expression-evaluation.md).

Limitations

The current limitations of JSON and generated columns are as follows:

• You cannot add a stored generated column through ALTER TABLE.
• You can neither convert a stored generated column to a normal column through the ALTER TABLE statement nor convert a normal column to a stored generated column.
• You cannot modify the expression of a stored generated column through the ALTER TABLE statement.
• Not all JSON functions are supported;
• Currently, the generated column index replacement rule is valid only when the generated column is a virtual generated column. It is not valid on the stored generated column, but the index can still be used by directly using the generated column itself.