Lindorm uses storage of the Capacity type to store cold data that is infrequently accessed. This way, the storage cost of historical data is reduced. This topic describes the benefits of Capacity storage and provides sample performance testing results for the feature.

Benefits

  • The cold storage feature provides cost-effective storage.

    The costs of Capacity storage are 20% of the costs of Standard storage.

  • The cold storage feature supports data write operations and ensures that you can read data at each point in time.
  • The cold storage feature is easy to use.

    To use Capacity storage to store cold data, set Purchase Capacity Storage to Yes and specify a value for Capacity Storage when you purchase a Lindorm instance. Then, specify that cold data is stored in Capacity storage when you use CREATE TABLE statements to create tables.

  • The cold storage feature supports the tiered storage of hot data and cold data in a single table.

    If you enable the hot and cold data separation feature for a table, Lindorm stores data that is frequently accessed in hot storage with higher data read and write performance, and stores historical data that is infrequently accessed in Capacity storage to reduce storage costs. To separately store hot and cold data in your business, see Overview.

Enable Capacity storage

For more information about how to enable Capacity storage for a Lindorm instance, see Enable cold storage.

Performance testing

Testing environment: In this test, a master node of the ecs.c5.xlarge specification is required. The master node has 4 CPU cores and 8 GB of memory. Four region servers of the ecs.c5.xlarge specification are required. Each region server has 4 CPU cores and 8 GB of memory.

The following table shows the write performance of cold storage.
Storage typeavg rtp99 rt
Hot storage1736 us4811 us
Capacity storage1748 us5243 us
Note Each data row has 10 columns and has 100 bytes of data stored in each column. This means that each row stores 1 KB of data. The system uses 16 parallel threads to write data.
The following table shows the random read performance of Capacity storage.
Storage typeavg rtp99 rt
Hot storage1704 us5923 us
Capacity storage14738 us31519 us
Note During the performance testing, BlockCache is disabled and the system reads data in disks. Each data row has 10 columns and has 100 bytes of data stored in each column. This means that each row stores 1 KB of data. The system uses 8 threads to read 1 KB of data for each request.
The following table shows the range scanning performance of Capacity storage.
Storage typeavg rtp99 rt
Hot storage6222 us20975 us
Capacity storage51134 us115967 us
Note During the performance testing, BlockCache is disabled and the system reads data in disks. Each data row has 10 columns and has 100 bytes of data stored in each column. This means that each row stores 1 KB of data. The system uses 8 threads to read 1 KB of data for each request. The Caching parameter is set to 30.

Usage notes

  • Capacity storage is suitable for scenarios in which data is not frequently queried because the IOPS of Capacity storage is low.
  • The write throughput of Capacity storage is close to that of standard storage.
  • Capacity storage is not suitable for processing a large number of concurrent read requests. An error may occur if Capacity storage is used to process a large number of concurrent read requests.
  • If you purchase a large capacity of Capacity storage for your Lindorm instance, you can adjust the read IOPS based on your business requirements. For more information, contact the Technical support.
  • We recommend that you store no more than 30 TB of cold data on each node. To store more cold data in Capacity storage, contact the Technical support.
  • If more than 95% of the Capacity storage of an instance is used, data can no longer be written to Capacity storage. Monitor the utilization of the Capacity storage of your instance. For more information, see View the cold storage size.