10.5.5 Bulk Data Loading for InnoDB Tables

These performance tips supplement the general guidelines for fast inserts in Section 10.2.5.1, “Optimizing INSERT Statements”.

When importing data into InnoDB, turn off autocommit mode, because it performs a log flush to disk for every insert. To disable autocommit during your import operation, surround it with SET autocommit and COMMIT statements:
```
SET autocommit=0;
... SQL import statements ...
COMMIT;
```
The mysqldump option --opt creates dump files that are fast to import into an InnoDB table, even without wrapping them with the SET autocommit and COMMIT statements.
If you have UNIQUE constraints on secondary keys, you can speed up table imports by temporarily turning off the uniqueness checks during the import session:
```
SET unique_checks=0;
... SQL import statements ...
SET unique_checks=1;
```
For big tables, this saves a lot of disk I/O because InnoDB can use its change buffer to write secondary index records in a batch. Be certain that the data contains no duplicate keys.
If you have FOREIGN KEY constraints in your tables, you can speed up table imports by turning off the foreign key checks for the duration of the import session:
```
SET foreign_key_checks=0;
... SQL import statements ...
SET foreign_key_checks=1;
```
For big tables, this can save a lot of disk I/O.
Use the multiple-row INSERT syntax to reduce communication overhead between the client and the server if you need to insert many rows:
```
INSERT INTO yourtable VALUES (1,2), (5,5), ...;
```
This tip is valid for inserts into any table, not just InnoDB tables.
When doing bulk inserts into tables with auto-increment columns, set innodb_autoinc_lock_mode to 2 (interleaved) instead of 1 (consecutive). See Section 17.6.1.6, “AUTO_INCREMENT Handling in InnoDB” for details.
When performing bulk inserts, it is faster to insert rows in PRIMARY KEY order. InnoDB tables use a clustered index, which makes it relatively fast to use data in the order of the PRIMARY KEY. Performing bulk inserts in PRIMARY KEY order is particularly important for tables that do not fit entirely within the buffer pool.
For optimal performance when loading data into an InnoDB FULLTEXT index, follow this set of steps:
1. Define a column FTS_DOC_ID at table creation time, of type BIGINT UNSIGNED NOT NULL, with a unique index named FTS_DOC_ID_INDEX. For example:
```
CREATE TABLE t1 (
FTS_DOC_ID BIGINT unsigned NOT NULL AUTO_INCREMENT,
title varchar(255) NOT NULL DEFAULT '',
text mediumtext NOT NULL,
PRIMARY KEY (`FTS_DOC_ID`)
) ENGINE=InnoDB;
CREATE UNIQUE INDEX FTS_DOC_ID_INDEX on t1(FTS_DOC_ID);
```
2. Load the data into the table.
3. Create the FULLTEXT index after the data is loaded.
Note
When adding FTS_DOC_ID column at table creation time, ensure that the FTS_DOC_ID column is updated when the FULLTEXT indexed column is updated, as the FTS_DOC_ID must increase monotonically with each INSERT or UPDATE. If you choose not to add the FTS_DOC_ID at table creation time and have InnoDB manage DOC IDs for you, InnoDB adds the FTS_DOC_ID as a hidden column with the next CREATE FULLTEXT INDEX call. This approach, however, requires a table rebuild which can impact performance.
If loading data into a new MySQL instance, consider disabling redo logging using ALTER INSTANCE {ENABLE|DISABLE} INNODB REDO_LOG syntax. Disabling redo logging helps speed up data loading by avoiding redo log writes. For more information, see Disabling Redo Logging.
Warning
This feature is intended only for loading data into a new MySQL instance. Do not disable redo logging on a production system. It is permitted to shutdown and restart the server while redo logging is disabled, but an unexpected server stoppage while redo logging is disabled can cause data loss and instance corruption.
Use MySQL Shell to import data. MySQL Shell's parallel table import utility util.importTable() provides rapid data import to a MySQL relational table for large data files. MySQL Shell's dump loading utility util.loadDump() also offers parallel load capabilities. See MySQL Shell Utilities.