Important

You are viewing the documentation of an older version of the TiDB database (TiDB v5.0). It is recommended that you use the latest LTS version of the TiDB database.

Read Historical Data

This document describes how TiDB reads data from the history versions, how TiDB manages the data versions, as well as an example to show how to use the feature.

Feature description

TiDB implements a feature to read history data using the standard SQL interface directly without special clients or drivers. By using this feature:

Even when data is updated or removed, its history versions can be read using the SQL interface.
Even if the table structure changes after the data is updated, TiDB can use the old structure to read the history data.

How TiDB reads data from history versions

The tidb_snapshot system variable is introduced to support reading history data. About the tidb_snapshot variable:

The variable is valid in the SESSION scope.
Its value can be modified using the SET statement.
The data type for the variable is text.
The variable accepts TSO (Timestamp Oracle) and datetime. TSO is a globally unique time service, which is obtained from PD. The acceptable datetime format is "2016-10-08 16:45:26.999". Generally, the datetime can be set using second precision, for example "2016-10-08 16:45:26".
When the variable is set, TiDB creates a Snapshot using its value as the timestamp, just for the data structure and there is no any overhead. After that, all the SELECT operations will read data from this Snapshot.

Note

Because the timestamp in TiDB transactions is allocated by Placement Driver (PD), the version of the stored data is also marked based on the timestamp allocated by PD. When a Snapshot is created, the version number is based on the value of the tidb_snapshot variable. If there is a large difference between the local time of the TiDB server and the PD server, use the time of the PD server.

After reading data from history versions, you can read data from the latest version by ending the current Session or using the SET statement to set the value of the tidb_snapshot variable to "" (empty string).

How TiDB manages the data versions

TiDB implements Multi-Version Concurrency Control (MVCC) to manage data versions. The history versions of data are kept because each update/removal creates a new version of the data object instead of updating/removing the data object in-place. But not all the versions are kept. If the versions are older than a specific time, they will be removed completely to reduce the storage occupancy and the performance overhead caused by too many history versions.

In TiDB, Garbage Collection (GC) runs periodically to remove the obsolete data versions. For GC details, see TiDB Garbage Collection (GC)

Pay special attention to the following:

tidb_gc_life_time: This system variable is used to configure the retention time of earlier modifications (default: 10m0s).
The output of SELECT * FROM mysql.tidb WHERE variable_name = 'tikv_gc_safe_point'. This is the current safePoint where you can read historical data up to. It is updated every time the garbage collection process is run.

Example

At the initial stage, create a table and insert several rows of data:

mysql> create table t (c int);
Query OK, 0 rows affected (0.01 sec)

mysql> insert into t values (1), (2), (3);
Query OK, 3 rows affected (0.00 sec)

View the data in the table:

mysql> select * from t;
+------+
| c    |
+------+
|    1 |
|    2 |
|    3 |
+------+
3 rows in set (0.00 sec)

View the timestamp of the table:

mysql> select now();
+---------------------+
| now()               |
+---------------------+
| 2016-10-08 16:45:26 |
+---------------------+
1 row in set (0.00 sec)

Update the data in one row:

mysql> update t set c=22 where c=2;
Query OK, 1 row affected (0.00 sec)

Make sure the data is updated:

mysql> select * from t;
+------+
| c    |
+------+
|    1 |
|   22 |
|    3 |
+------+
3 rows in set (0.00 sec)

Set the tidb_snapshot variable whose scope is Session. The variable is set so that the latest version before the value can be read.
Note
In this example, the value is set to be the time before the update operation.
```
mysql> set @@tidb_snapshot="2016-10-08 16:45:26";
Query OK, 0 rows affected (0.00 sec)
```
Note
You should use @@ instead of @ before tidb_snapshot because @@ is used to denote the system variable while @ is used to denote the user variable.
Result: The read from the following statement is the data before the update operation, which is the history data.
```
mysql> select * from t;
+------+
| c    |
+------+
|    1 |
|    2 |
|    3 |
+------+
3 rows in set (0.00 sec)
```
Set the tidb_snapshot variable to be "" (empty string) and you can read the data from the latest version:
```
mysql> set @@tidb_snapshot="";
Query OK, 0 rows affected (0.00 sec)
```
```
mysql> select * from t;
+------+
| c    |
+------+
|    1 |
|   22 |
|    3 |
+------+
3 rows in set (0.00 sec)
```
Note
You should use @@ instead of @ before tidb_snapshot because @@ is used to denote the system variable while @ is used to denote the user variable.

How to restore historical data

Before you restore data from an older version, make sure that Garbage Collection (GC) does not clear the history data while you are working on it. This can be done by setting the tidb_gc_life_time variable as the following example shows. Do not forget to set the variable back to the previous value after the restore.

SET GLOBAL tidb_gc_life_time="60m";

Note

Increasing the GC life time from the default 10 minutes to half an hour or more will result in additional versions of rows being retained, which might require more disk space. This might also affect the performance of certain operations such as scans when TiDB needs to skip these additional versions of the same rows during data reads.

To restore data from an older version, you can use one of the following methods:

For simple cases, use SELECT after setting the tidb_snapshot variable and copy-paste the output, or use SELECT ... INTO LOCAL OUTFLE and use LOAD DATA to import the data later on.
Use Dumpling to export a historical snapshot. Dumpling performs well in exporting larger sets of data.