This topic describes the specifications of data migration instances and provides the results of performance testing.
Precautions
The performance metrics provided in this topic are used only for reference and are not used as criteria for product SLA evaluation.
Terms
Term | Description |
---|---|
specification | DTS provides data migration instances that have different specifications. The performance of these instances depends on the performance of incremental data migration. |
table quantity | The total number of tables in the test model. |
record size | The size of each record that is migrated during incremental data migration. |
RPS | The number of records per second (RPS) that are changed by INSERT, UPDATE, and DELETE operations in the source database. |
Note
- If an SQL statement contains operations on multiple rows of data, DTS identifies the operations as multiple data changes. If you perform INSERT, UPDATE, and DELETE operations on a data record multiple times, DTS also identifies the operations as multiple data changes.
- DTS identifies each COMMIT operation as a data change.
Specifications
DTS provide the following four specifications based on the maximum performance of
data migration instances: small, medium, large, and 2xlarge. The data migration instance
of each specification can reach the maximum performance if the following conditions
are met:
- The pressure on the source instance must be greater than or equal to the maximum performance that corresponds to each specification.
- The destination instance does not have bottlenecks in write performance and supports the performance pressure that corresponds to each specification.
- The network latency between the DTS server and the source or destination instance does not exceed 2 milliseconds.
Specification | Maximum performance (RPS) |
---|---|
small | 200 to 2,000 |
medium | 2,000 to 5,000 |
large | Unlimited
Note The online running performance of the large specification depends on the network environment
and the performance of the source and destination instances.
|
2xlarge |
Test model
Test procedure: Create an incremental migration task between two ApsaraDB RDS for MySQL instances. Then, perform a stress test on the source ApsaraDB RDS for MySQL instance to view the performance of incremental data migration.
Instance | RDS instance configuration | Maximum performance |
---|---|---|
Source instance |
|
|
Destination instance |
|
|
Test model:
- The number of test tables is 20.
- Each test table has a primary key.
- The record size is 1 KB.
- Each transaction has an average of two DML operations and one COMMIT operation. The ratio of INSERT, UPDATE, and DELETE operations is 3:1:2.
Test results
Source instance region | Destination instance region | Network latency between instances (milliseconds) | Specification | RPS |
---|---|---|---|---|
China (Hangzhou) | China (Hangzhou) | 0.26 | small | 2,566 |
China (Hangzhou) | China (Hangzhou) | 0.26 | medium | 4,726 |
China (Hangzhou) | China (Hangzhou) | 0.26 | large | 6,378 |
China (Hangzhou) | China (Qingdao) | 26 | small | 2,469 |
China (Hangzhou) | China (Qingdao) | 26 | medium | 4,856 |
China (Hangzhou) | China (Qingdao) | 26 | large | 5,439 |
China (Hangzhou) | China (Beijing) | 26 | small | 2,533 |
China (Hangzhou) | China (Beijing) | 26 | medium | 5,038 |
China (Hangzhou) | China (Beijing) | 26 | large | 6,829 |
China (Hangzhou) | US (Silicon Valley) | 175 | small | 1,753 |
China (Hangzhou) | US (Silicon Valley) | 175 | medium | 2,837 |
China (Hangzhou) | US (Silicon Valley) | 175 | large | 3,884 |
Singapore (Singapore) | US (Silicon Valley) | 198 | small | 1,104 |
Singapore (Singapore) | US (Silicon Valley) | 198 | medium | 1,724 |
Singapore (Singapore) | US (Silicon Valley) | 198 | large | 2,256 |
Note The preceding test results show the maximum performance of data migration instances
that are configured with different specifications. The performance of incremental
data migration cannot be guaranteed in the following cases: The table to be migrated
does not have a primary key, the network latency is high, an update hotspot exists,
or the source and destination instances have performance bottlenecks.