alibabacloud Improving Redis Performance through Multi-Thread Processing
Redis is generally known as a single-process, single-thread model. This is not true. Redis also runs multiple backend threads to perform backend cleaning works, such as cleansing the dirty data and closing file descriptors.
NOTE:
"multiple backend threads"指的是background IO thread，即
bio，参见Background-IO-thread章节
In Redis, the main thread is responsible for the major tasks, including but not limited to:
1、receiving the connections from clients,
2、processing the connection read/write events,
3、parsing requests, processing commands,
4、processing timer events, and
5、synchronizing data.
Only one CPU core runs a single process and single thread. For small packets, a Redis server can process 80,000 to 100,000 QPS. A larger QPS is beyond the processing capacity of a Redis server. A common solution is to partition the data and adopt multiple servers in distributed architecture. However, this solution also has many drawbacks. For example, too many Redis servers to manage; some commands that are applicable to a single Redis server do not work on the data partitions; data partitions cannot solve the hot spot read/write problem; and data skew(数据倾斜), redistribution, and scale-up/down become more complex. Due to restrictions of the single process and single thread, we hope that the multi-thread can be reconstructed to fully utilize the advantages of the SMP multi-core architecture, thus increasing the throughput of a single Redis server. To make Redis multi-threaded, the simplest way to think of is that every thread performs both I/O and command processing. However, as the data structure processed by Redis is complex, the multi-thread needs to use the locks to ensure the thread security. Improper handling of the lock granularity may deteriorate(破坏、恶化) the performance.
We suggest that the number of I/O threads should be increased to enable an independent I/O thread to read/write data in the connections, parse commands, and reply data packets, and still let a single thread process the commands and execute the timer events. In this way, the throughput of a single Redis server can be increased.
NOTE:
这是目前Redis所采用的
Single Process and Single Thread Model
Advantages
1、Due to restrictions of the single-process and single-thread model, time-consuming operations (such as dict rehash and expired key deletion) are broken into multiple steps and executed one by one in Redis implementation. This prevents execution of an operation for a long time and therefore avoids long time blocking of the system by an operation. The single-process and single-thread code is easy to compile, which reduces the context switching and lock seizure(争夺) caused by multi-process and multi-thread.
Disadvantages
1、Only one CPU core can be used, and the multi-core advantages cannot be utilized.
2、For heavy I/O applications, a large amount of CPU capacity is consumed by the network I/O operations. Applications that use Redis as cache are often heavy I/O applications. These applications basically have a high QPS, use relatively simple commands (such as get, set, and incr), but are RT sensitive. They often have a high bandwidth usage, which may even reach hundreds of megabits. Thanks to popularization of the 10-GB and 25-GB network adapters, the network bandwidth is no longer a bottleneck. Therefore, what we need to think about is how to utilize the advantages of multi-core and performance of the network adapter.
NOTE:
"RT sensitive" 中 "RT" 应该是 realtime的意思
Multi-Thread Model and Implementation
Thread Model
There are three thread types, namely:
- Main thread
- I/O thread
- Worker thread
1、Main thread: Receives connections, creates clients, and forwards connections to the I/O thread.
2、I/O thread: Processes the connection read/write events, parses commands, forwards the complete parsed commands to the worker thread for processing, sends the response packets, and deletes connections.
3、Worker thread: Processes commands, generates the client response packets, and executes the timer events.
4、The main thread, I/O thread, and worker thread are driven by events separately.
5、Threads exchange data through the lock-free queue and send notifications through tunnels.
Benefits of Multi Thread Model
Increased Read/Write Performance
The stress test result indicates that the read/write performance can be improved by about three folds in the small packet scenario.
Increased Master/Slave Synchronization Speed
When the master sends the synchronization data to the slave, data is sent in the I/O thread. When reading data from the master, the slave reads the full data from the worker thread, and the incremental data from the I/O thread. This can efficiently increase the synchronization speed.
Subsequent Tasks
The first task is to increase the number of I/O threads and optimize the I/O read/write capability. Next, we can break down the worker thread so that each thread completes I/O reading, as well as the work of the worker thread.
Setting of the Number of I/O threads
1、Test results indicate that the number of I/O threads should not exceed 6. Otherwise, the worker thread will become a bottleneck for simple operations.
2、Upon startup of a process, the number of I/O threads must be set. When the process is running, the number of I/O threads cannot be modified. Based on the current connection allocation policy, modification of the number of I/O threads involves re-allocation of connections, which is quite complex.
Considerations
1、With popularization of the 10-GB and 25-GB network adapters, how to fully utilize the hardware performance must be carefully considered. We can use technologies, such as multiple threads for networkI/O and the kernel bypass user-mode protocol stack.
2、The I/O thread can be used to implement blocking-free data migration. The I/O thread encodes the data process or forwards commands, whereas the target node decodes data or executes commands.
To learn more about Alibaba Cloud ApsaraDB for Redis, visit www.alibabacloud.com/product/apsaradb-for-redis