Why is redis single threaded

There must be more than one thread when a formal Redis Server is running. Here you need to pay attention to it! For example, when Redis is persisted, it will be executed in the form of a sub-process or a sub-thread specifically whether the sub-thread or sub-process is for readers to study in depth ; for example, I check the Redis process on the test server and then find the thread under the process: The "-T" parameter of the ps command indicates the display threads Show threads, possibly with SPID column.

So whether the article is still single-threaded in future versions requires readers to verify! We know that Redis uses the "single-threaded multiplexed IO model" to achieve high-performance in-memory data services.

This mechanism avoids the use of locks, but at the same time this mechanism is more time-consuming in the sun and the like The command will make the concurrency of redis drop. Because it is a single thread, only one operation is in progress at the same time.

Therefore, time-consuming commands will lead to a decrease in concurrency, not only read concurrency, but also write concurrency. And a single thread can only use one CPU core, so you can start multiple instances in the same multi-core server to form a master-master or master-slave form.

Time-consuming read commands can be performed entirely in the slave. CPU is an important influencing factor. The most obvious impact is that redis-benchmark will randomly use CPU cores. In order to obtain accurate results, you need to use a fixed processor tool you can use taskset on Linux. The most effective way is to separate the client and server into two different CPUs to use the third-level cache in colleges. Multi-process model: Oracle Linux version ; 3.

Nginx has two types of processes, one is called Master process equivalent to management process , and the other is called Worker process actual work process. There are two ways to start: 1 Single process start: At this time, there is only one process in the system, which acts as both the role of Master process and the role of Worker process.

Why is Redis single-threaded and why is Redis so fast! ApsaraDB for Redis Redis. This article is an English version of an article which is originally in the Chinese language on aliyun. It can be exploited by the user to implement optimistic locking and other patterns without paying for the synchronization overhead.

It's single-threaded, runs on one core, at user level , so I would not refer to this as concurrent. Others differ.. They may get more belief if they said 'can scale better than one-thread-per-client, providing the clients don't ask for much', though they may then feel obliged to add 'blown away on heavy loading by other async solutions that use all cores at user level'.

Python Javascript Linux Cheat sheet Contact. A typical example would be: redis-benchmark -q -n Using this tool is quite easy, and you can also write your own benchmark, but as with any benchmarking activity, there are some pitfalls to avoid.

Redis is a server: all commands involve network or IPC round trips. Redis commands return an acknowledgment for all usual commands. Some other data stores do not. Comparing Redis to stores involving one-way queries is only mildly useful. Naively iterating on synchronous Redis commands does not benchmark Redis itself, but rather measure your network or IPC latency and the client library intrinsic latency.

Redis is an in-memory data store with some optional persistence options. Redis is, mostly, a single-threaded server from the POV of commands execution actually modern versions of Redis use threads for different things.

It is not designed to benefit from multiple CPU cores. People are supposed to launch several Redis instances to scale out on several cores if needed.

It is not really fair to compare one single Redis instance to a multi-threaded data store. Network bandwidth and latency usually have a direct impact on the performance.

It is a good practice to use the ping program to quickly check the latency between the client and server hosts is normal before launching the benchmark. In many real world scenarios, Redis throughput is limited by the network well before being limited by the CPU. CPU is another very important factor. Being single-threaded, Redis favors fast CPUs with large caches and not many cores.

At this game, Intel CPUs are currently the winners. When client and server run on the same box, the CPU is the limiting factor with redis-benchmark. Speed of RAM and memory bandwidth seem less critical for global performance especially for small objects. Usually, it is not really cost-effective to buy expensive fast memory modules to optimize Redis. Redis runs slower on a VM compared to running without virtualization using the same hardware.

If you have the chance to run Redis on a physical machine this is preferred. However this does not mean that Redis is slow in virtualized environments, the delivered performances are still very good and most of the serious performance issues you may incur in virtualized environments are due to over-provisioning, non-local disks with high latency, or old hypervisor software that have slow fork syscall implementation.

When an ethernet network is used to access Redis, aggregating commands using pipelining is especially efficient when the size of the data is kept under the ethernet packet size about bytes.

Actually, processing 10 bytes, bytes, or bytes queries almost result in the same throughput. See the graph below. The most visible effect is that redis-benchmark results seem non-deterministic because client and server processes are distributed randomly on the cores.

To get deterministic results, it is required to use process placement tools on Linux: taskset or numactl. Based on the above characteristics ,Redis Single thread has achieved enough performance , therefore Redis There is no multithreading model.

The biggest drawback of single threaded processing is , If the previous request takes a long time , So the whole Redis Will be blocked , No other requests can come in , Until this time-consuming operation is completed and returned , Other requests can only be processed to.

We usually meet Redis Problems with slow response or long-term blocking , Most of it is because Redis Processing requests is caused by a single thread. And in the Redis 4. Delete big key when , Freeing memory is often time consuming , therefore Redis Provides a way to release memory asynchronously , Let these time-consuming operations be processed asynchronously in another thread , Thus, the execution of the main thread is not affected , Improve performance.

It is mainly to solve the problem of high concurrency scenarios , The pressure of single thread parsing request data protocol. After the protocol parsing of request data is completed by multithreading , The subsequent request processing phase is still single thread queuing. Redis The author is very clear about the use scenarios of single thread and multi thread , Optimize targeted. Home 6. Why is redis single thread so fast? Pure memory operation Redis It's a memory database , Its data is stored in memory , This means that we read and write data in memory , It's very fast.

Advantages of single thread Based on the above characteristics ,Redis Single thread has achieved enough performance , therefore Redis There is no multithreading model.