Why redis so fast

When it exceeds the maximum time that 24bit can express, it will start from scratch. In this case, the lru of the object may be larger than that of server. If this happens, two keys will be added rather than subtracted to find the longest key. Need additional data structure, consume resources.

As shown in the figure, suppose A is visited five times in 10 seconds, and B is visited three times in 10 seconds. Because B was last visited later than A, in the same case, A was recycled first. Counter is implemented with probability based logarithm counter, 8 bits can represent millions of access frequency. If the counter only increases, it will not decrease, and it will not reflect the heat of the object.

How does the counter decrement when it is not accessed? The reduced value is controlled by the attenuation factor LFU deck time minutes. If the value is 1, N minutes will be reduced if there is no access. Keywords: Programming Redis Database Linux socket. Why is Redis so fast? Single thread What are the benefits of a single thread? Isn't it a waste of CPU resources to use a single thread? Why is single thread so fast? Because Redis is a memory based operation, let's start with memory.

Virtual memory virtual memory Main memory: memory; auxiliary memory: disk hard disk The main memory of a computer can be regarded as an array of M consecutive byte sized units. There are several drawbacks to this approach: 1. What is context? File descriptor FD Linux system treats all devices as files, and Linux uses file descriptors to identify each file object. There are three standard file descriptors in Linux system. In order to solve the problem of blocking, we have several ideas.

Reuse: refers to reusing one or more threads. Expiration Policies To achieve key expiration, we have several ideas. Timed expiration active elimination Each key setting expiration time needs to create a timer, which will be cleared immediately after expiration time. Inertia expiration passive elimination Only when a key is accessed will it be judged whether the key has expired. For example, String will call expireifneed in getCommand db.

The database number is the 'id' field in the structure. If it doesn't expire, what if Redis is full of memory? Write prompt OOM error information without affecting reading. Elimination strategy Redis's memory elimination strategy refers to that when the memory usage reaches the maximum memory limit, the elimination algorithm needs to be used to decide which data is cleaned up to ensure the storage of new data. LFU, least frequently used, added in version 4.

If there is no key object to delete, fallback to the noeviction policy. If not, go back to the noeviction policy. At this time, Redis only responds to read operations.

Additional data structure storage is required, which consumes memory. How to find the lowest heat data? Source code: server. Will there be no delay? OK, when there is LRU field value in the object, you can evaluate the heat of the object. Source evict.

In addition to consuming resources, what are the problems with traditional LRU s? LFU server. When the object is read and written, the lfu value is updated. According to the LRU algorithm, delete the key with the timeout attribute set until enough memory is freed up.

According to the LRU algorithm, delete the key, no matter whether the data has set the timeout attribute or not, until enough memory is freed up. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Should I use Redis? Since redis is rather a memory oriented it's really good for frequently updated real-time data, such as session store, state database, statistics, caching and it's advanced data structures offers versatility to many other scenarios.

Is Redis faster than MongoDB? MongoDB is easier if you need to spread your data across several servers automatically. How many keys can Redis handle? Why is Redis faster than SQL? In Redis, Read and Write operations are extremely fast because of storing data in primary memory.

Primary memory is in lesser in size and much expensive than secondary so, Redis cannot store large files or binary data. Is Redis faster than Postgres? Is Redis in memory only? Redis is an in-memory but persistent on disk database, so it represents a different trade off where very high write and read speed is achieved with the limitation of data sets that can't be larger than memory. Does Redis keep all data in memory? Redis is an in-memory database because it keeps the whole data set in memory, and answers all queries from memory.

Because RAM is faster than disks, this means Redis always has very fast reads. They always keep the whole data set including indices on disk in a format that allows random access. Does Redis support SQL? Redis supports pipelining , so it is possible to send multiple commands at once, a feature often exploited by real world applications.

Redis pipelining is able to dramatically improve the number of operations per second a server is able do deliver. This is an example of running the benchmark in a MacBook Air 11" using a pipelining of 16 commands:.

The first point is obvious: the golden rule of a useful benchmark is to only compare apples and apples. Different versions of Redis can be compared on the same workload for instance. Or the same version of Redis, but with different options. If you plan to compare Redis to something else, then it is important to evaluate the functional and technical differences, and take them in account.

A common misconception is that redis-benchmark is designed to make Redis performances look stellar, the throughput achieved by redis-benchmark being somewhat artificial, and not achievable by a real application. This is actually not true. The redis-benchmark program is a quick and useful way to get some figures and evaluate the performance of a Redis instance on a given hardware.

However, by default, it does not represent the maximum throughput a Redis instance can sustain. Actually, by using pipelining and a fast client hiredis , it is fairly easy to write a program generating more throughput than redis-benchmark. The default behavior of redis-benchmark is to achieve throughput by exploiting concurrency only i. It does not use pipelining or any parallelism at all one pending query per connection at most, and no multi-threading , if not explicitly enabled via the -P parameter.

So in some way using redis-benchmark and, triggering, for example, a BGSAVE operation in the background at the same time, will provide the user with numbers more near to the worst case than to the best case. To run a benchmark using pipelining mode and achieve higher throughput , you need to explicitly use the -P option. Please note that it is still a realistic behavior since a lot of Redis based applications actively use pipelining to improve performance.

However you should use a pipeline size that is more or less the average pipeline length you'll be able to use in your application in order to get realistic numbers. Finally, the benchmark should apply the same operations, and work in the same way with the multiple data stores you want to compare. It is absolutely pointless to compare the result of redis-benchmark to the result of another benchmark program and extrapolate.

Both are in-memory data stores, working mostly in the same way at the protocol level. Provided their respective benchmark application is aggregating queries in the same way pipelining and use a similar number of connections, the comparison is actually meaningful.

This perfect example is illustrated by the dialog between Redis antirez and memcached dormando developers. You can see that in the end, the difference between the two solutions is not so staggering, once all technical aspects are considered. Please note both Redis and memcached have been optimized further after these benchmarks.

Finally, when very efficient servers are benchmarked and stores like Redis or memcached definitely fall in this category , it may be difficult to saturate the server. Sometimes, the performance bottleneck is on client side, and not server-side. In that case, the client i. There are multiple factors having direct consequences on Redis performance. We mention them here, since they can alter the result of any benchmarks.

Please note however, that a typical Redis instance running on a low end, untuned box usually provides good enough performance for most applications.

One important goal of any benchmark is to get reproducible results, so they can be compared to the results of other tests. WARNING: Note that most of the following benchmarks are a few years old and are obtained using old hardware compared to today's standards. This page should be updated, but in many cases you can expect twice the numbers you are seeing here using state of hard hardware.

Moreover Redis 4. Notes: changing the payload from to or bytes does not change the numbers significantly but reply packets are glued together up to bytes so GETs may be slower with big payloads. The same for the number of clients, from 50 to clients I got the same numbers.

With only 10 clients it starts to get a bit slower.