This topic describes how X-Engine of ApsaraDB for RDS helps reduce the costs of DingTalk and implement online collaborative offices.
DingTalk is a leading enterprise-grade instant messaging (IM) tool in China. It serves hundreds of millions of users across China. Its basic functions include video conferences and daily reports. DingTalk Open Platform also provides various office automation (OA) applications to facilitate communication between co-workers.
In 2020, COVID-19 is a serious problem. To avoid the risk of infection caused by work in centralized offices, a large number of employees have opted to work from home. The demand for collaborative office tools suddenly increases. In this situation, DingTalk is quickly elevated to the top of the App Store download list. This results in a sharp increase in DingTalk access. DingTalk is based on the elastic infrastructure provided by Alibaba Cloud. This ensures that all the traffic peaks are smoothly handled.
To serve a large number of users, DingTalk must ensure the timely and correct delivery of messages, and provide specific functions, such as read and unread messages. Unlike user-level IM tools such as WeChat, enterprise-grade IM tools must include the permanent storage of chat records and provide the multi-terminal roaming function. This function allows users to receive messages from multiple terminals. As the number of users sharply increases, DingTalk faces challenges in the costs incurred by the permanent storage of chat records while ensuring the performance of read and write operations on the chat records.
To address these challenges, DingTalk uses X-Engine as the storage engine for messages. This achieves a balance between the costs and performance. X-Engine has the following advantages:
- The storage space required by X-Engine is about 62% less than that required by the InnoDB storage engine.
- Specific database functions such as transactions and secondary indexes are supported.
- Service code can be migrated to RDS instances that are powered by X-Engine without changes.
- X-Engine separates hot and cold data to accelerate the processing of current messages. It also implements the most efficient compression algorithm for historical messages.
X-Engine storage efficiency is tested on two datasets: Link-Bench and Alibaba internal transaction business. In the test, X-Engine requires 2-fold less storage space than the InnoDB storage engine with compression enabled, and 3- to 5-fold less storage space than the InnoDB engine with compression disabled.
Low costs achieved by X-Engine
X-Engine adopts the following technologies to ensure low costs:
- Compact pages
X-Engine uses the Copy-on-write technology to write new data to new pages without updating the original pages. The new pages are read-only and cannot be directly updated. These pages are stored in a compact manner, and the data is compressed by using specific algorithms, such as prefix encoding. This improves the storage efficiency. You can use the compaction operation to clear invalid records. This ensures a compact arrangement of valid records. X-Engine requires only 10% to 50% of the storage space compared with conventional storage engines, such as InnoDB.
- Data compression and cleaning of invalid records
Pages after encoding can be compressed by using general compression algorithms, such as zlib, zstd, and snappy. Data at a low level of a log-structured merge-tree (LSM tree) is compressed by default.
Data compression sacrifices computing resources for storage space. We recommend that you select compression algorithms that provide a low compression ratio and a high speed of compression and decompression. After a large number of comparative tests, X-Engine selects zstd as the default compression algorithm with additional support for other compression algorithms.
In addition, the compaction operation is introduced to delete invalid records. This way, only valid records are retained. The more frequently the compaction operation is performed, the lower the proportion of invalid records, and the higher the storage efficiency. Therefore, you must perform the compaction operation at a suitable frequency.
The X-Engine team also develops the field-programmable gate array (FPGA) compaction technology to reduce the computing resource consumption of the compaction operation. This technology uses heterogeneous computing hardware to accelerate the compaction process. It streamlines compaction and compression operations by using FPGA hardware. On a host without FPGA hardware, X-Engine can use a suitable scheduling algorithm to save storage space at a lower performance cost.
- Intelligent separation between hot and cold data
In normal access to a storage system, most access requests direct to a small portion of data. This is why the cache works. In an LSM tree structure, frequently accessed data is stored at a high level to a fast storage device, such as NVM and DRAM. Infrequently accessed data is stored at a low level to a slow storage device. This is the hot and cold data separation in X-Engine.
The separation algorithm completes the following tasks:
- In the compaction operation, the pages and records that are least likely to be accessed are selected and moved to the bottom of the LSM tree.
- Current hot data is selected and backfilled to memory (BlockCache and RowCache) in the compaction or dump process. This prevents compromised performance from jitters in cache hit rates.
- The AI algorithm recognizes data that may be accessed in the future and pre-reads it into memory. This increases the hit rates for accessing cache at the first time.
Hot data and cold data are accurately identified to avoid computing resource waste due to invalid compression or decompression. This improves system throughput.
For more information, see X-Engine overview.