Shulou(Shulou.com)05/31 Report--

In this issue, the editor will bring you about the special data types in Redis. The article is rich in content and analyzes and narrates it from a professional point of view. I hope you can get something after reading this article.

Preface

Reids is widely used in the development of Web applications, and almost all back-end technologies involve the use of Redis. In addition to the common string String, dictionary Hash, list List, collection Set, ordered collection SortedSet, and so on, there are also some less commonly used data types, which are highlighted here. There is no more to say below, let's take a look at the detailed introduction.

BitMap

BitMap is to use a bit bit to represent the corresponding value or state of an element, where the key is the corresponding element itself. In fact, the underlying layer is also achieved through string manipulation. Redis has added several bitmap-related commands such as setbit, getbit, bitcount and so on since version 2.2. Although it is a new command, it is an operation on a string, so let's take a look at the syntax:

SETBIT key offset value

Offset must be a number, and value can only be 0 or 1. At first glance, it doesn't feel useful. Let's take a look at the specific expression of bitmap. When we use the command setbit key (0mem2re5, 5heli9) 1, it is expressed as follows:

Bytebit0bit1bit2bit3bit4bit5bit6bit7byte010100100byte101001000

You can see that the default value of bit is 0, so what about the use of BitMap in actual development? Here's an example: store the user's online status. All you need here is a key, and then the user ID is set as the offset, set to 1 if online and 0 if not online. Example code:

/ / set online status $redis- > setBit ('online', $uid, 1); / / set offline status $redis- > setBit (' online', $uid, 0); / / get status $isOnline = $redis- > getBit ('online', $uid); / / get online number $isOnline = $redis- > bitCount (' online')

Geo

Redis's GEO feature is available in version 3.2 of Redis, which stores and manipulates geolocation information given by the user. The data structure of GEO has a total of six commands: geoadd, geopos, geodist, georadius, georadiusbymember, gethash, a few of which are emphasized here.

1.GEOADD

GEOADD key longitude latitude member [longitude latitude member...]

Adds the given spatial element (latitude, longitude, name) to the specified key. This data is stored in the key in an ordered collection, allowing commands such as GEORADIUS and GEORADIUSBYMEMBER to retrieve these elements later through a location query. Example:

Redis > GEOADD Sicily 13.361389 38.115556 "Palermo" 15.087269 37.502669 "Catania" (integer) 2

2.GEOPOS

GEOPOS key member [member...]

Returns the position (longitude and latitude) of all given location elements from the key, for example:

Redis > GEOPOS Sicily Palermo Catania NonExisting1) 1) "13.361389338970184" 2) "38.115556395496299"

3.GEODIST

GEODIST key member1 member2 [unit]

Returns the distance between two given positions. If one of the two locations does not exist, the command returns a null value. The parameter unit for the specified unit must be one of the following units: (default is m)

M represents the unit in meters.

Km means the unit is kilometer.

Mi stands for miles.

Ft means the unit is feet.

Redis > GEODIST Sicily Palermo Catania "166274.15156960039"

4.GEORADIUS

GEORADIUS key longitude latitude radius m | km | ft | mi [WITHCOORD] [WITHDIST] [WITHHASH] [ASC | DESC] [COUNT count]

With a given latitude and longitude as the center, the return key contains all location elements whose distance from the center does not exceed the given maximum distance. The distance unit is the same as the one above, with the following options:

WITHDIST: returns the distance between the location element and the center as well as the location element. The unit of distance is consistent with the range unit given by the user.

WITHCOORD: returns the longitude and dimension of the location element as well.

WITHHASH: returns the ordered set score of the position element encoded by the original geohash as a 52-bit signed integer. This option is mainly used for underlying applications or debugging, but it is not very useful in practice.

Redis > GEORADIUS Sicily 15 37 200 km WITHDIST1) 1) "Palermo" 2) "190.4424" 2) 1) "Catania" 2) "56.4413"

HyperLogLog

Redis cardinality statistics, this structure can save memory to count a variety of counts, such as the number of registered IP, daily visit IP, page real-time UV), the number of online users and so on. But it also has limitations, that is, it can only count the quantity, but there is no way to know what the specific content is.

Of course, using sets can also solve this problem. But a large website, for example, has 1 million IP per day. Roughly speaking, an IP consumes 15 bytes, so 1 million IP is 15m. On the other hand, HyperLogLog occupies 12K for each key in Redis, and the theoretical storage is close to 2 ^ 64 values. no matter what the stored content is, an algorithm based on cardinality estimation can only accurately estimate the cardinality, and a small amount of fixed memory can be used to store and identify the unique elements in the collection. And the cardinality of this estimate is not necessarily accurate, it is an approximate value with 0.81% standard error.

There are three commands for this data structure: PFADD, PFCOUNT, and PFMERGE

1.PFADD

Redis > PFADD databases "Redis"MongoDB"MySQL" (integer) 1redis > PFADD databases "Redis" # Redis already exists, it is not necessary to update the estimated quantity (integer) 0

2.PFCOUNT

Redis > PFCOUNT databases (integer) 3

3.PFMERGE

PFMERGE destkey sourcekey [sourcekey...]

Merge multiple HyperLogLog into a single HyperLogLog, and the cardinality of the merged HyperLogLog is close to the union of all visible sets of input HyperLogLog. The merged HyperLogLog is stored in the destkey key, and if the key does not exist, an empty HyperLogLog is created for the key before the command is executed.

Redis > PFADD nosql "Redis"MongoDB"Memcached" (integer) 1redis > PFADD RDBMS "MySQL"MSSQL"PostgreSQL" (integer) 1redis > PFMERGE databases nosql RDBMSOKredis > PFCOUNT databases (integer) 6 these are the special data types of Redis shared by Xiaobian. If you happen to have similar doubts, please refer to the above analysis to understand. If you want to know more about it, you are welcome to follow the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.