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

This article will explain in detail about the special data types in Redis. The editor thinks it is very practical, so I share it with you as a reference. I hope you can get something after reading this article.

In addition to the five basic data types, Redis also has three special data types, namely HyperLogLogs (cardinality statistics), Bitmaps (bitmap) and geospatial (geographic location).

HyperLogLogs (cardinality statistics)

Redis version 2.8.9 updates the Hyperloglog data structure!

What is the cardinality?

For example, A = {1, 2, 3, 4, 5}, B = {3, 5, 6, 7, 9}; then the cardinality (non-repeating elements) = 1, 2, 4, 6, 7, 9; (fault tolerance is allowed, that is, a certain error is acceptable)

What problems are solved by HyperLogLogs cardinality statistics?

This structure can save memory to count all kinds of counts, such as the number of registered IP, the number of daily visits to IP, the real-time UV of pages, the number of online users, the number of common friends, and so on.

What are its advantages?

A large website, for example, has 1 million IP per day. Roughly speaking, an IP consumes 15 bytes, then 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 estimated cardinality is not necessarily accurate, it is an approximate value with 0.81% standard error (for business scenarios that can accept certain fault tolerance, such as IP statistics, UV, etc., it is negligible).

Use of related commands

127.0.0.1 pfadd key1 a b c d e f g h i # create the first set of elements (integer) 1127.0.0.1 pfcount key1 # the cardinality number of statistical elements (integer) 9127.0.0.1 pfcount key1 # create the second set of elements (integer) 1127.0.0.1 : 6379 > pfcount key2 (integer) 8127.0.1 pfmerge key3 key1 key2 # merge two groups: key1 key2-> key3 union OK127.0.0.1:6379 > pfcount key3 (integer) 13Bitmap (bit storage)

Bitmap, that is, the bitmap data structure, all operate binary bits to record, with only 0 and 1 states.

To solve what problem?

For example: statistical user information, active, inactive! Login, not logged in! Clock in, don't clock in! For both states, you can use Bitmaps!

How much memory does it take to store an one-year sign-in status? 365 days = 365 bit 1 byte = 8bit about 46 bytes!

Use of related commands

Use bitmap to record sign-in from Monday to Sunday! Monday: 1 Tuesday: 0 Wednesday: 0 Thursday: 1.

127.0.0.1 setbit sign 01 (integer) 0127.0.0.1 setbit sign 1 (integer) 0127.0.0.1 setbit sign 6379 > setbit sign 2 0 (integer) 0127.0.1 setbit sign 6379 > setbit sign 4 0 (integer) 0127.0.1 0.1 integer > setbit sign 50 (integer) 0127.0.1 > setbit sign 6 1 (integer) 0

Check to see if there is a sign-in one day!

127.0.0.1 getbit sign 6379 > getbit sign 3 (integer) 1127.0.0.1 getbit sign 5 (integer) 0

Statistical operation, count the number of days of clocking in!

127.0.0.1 bitcount sign 6379 > count this week's sign-in records, you can see if there is a full attendance! (integer) 3geospatial (geographic location)

Redis's Geo is available in Redis version 3.2! This function can calculate the geographical location information: the distance between the two places, the people within a few miles.

Geoadd

Add geolocation

127.0.1 geoadd china:city manjing 112.55 37.86 taiyuan 123.43 41.80 shenyang (integer) 3127.0.1 shenyang > geoadd china:city 144.05 22.52 shengzhen 120.16 30.24 hangzhou 108.96 34.26 xian (integer) 3

Rules

The two levels cannot be added directly. We usually download city data (this URL can be queried GEO: http://www.jsons.cn/lngcode)!

Valid longitude ranges from-180 degrees to 180 degrees.

Valid latitudes range from-85.05112878 to 85.05112878 degrees.

# when the coordinate location is outside the specified range, the command will return an error. 127.0.0.1 beijin 6379 > geoadd china:city 39.90 116.40 beijin (error) ERR invalid longitude,latitude pair 39.900000116.400000

Geopos

Gets the longitude and latitude of the specified member

1) "112.54999905824661255" 1) "37.86000073876942196" 2) 1) "118.759957323074341" 1) "32.03999960287850968"

To get the current location, it must be a coordinate value!

Geodist

If it does not exist, return empty

The units are as follows

M

Km

Mi miles

Ft feet

127.0.0.1 6379 > geodist china:city taiyuan shenyang m "1026439.1070" 127.0.1 VR 6379 > geodist china:city taiyuan shenyang km "1026.4391"

Georadius

People in the neighborhood = > get the addresses and locations of all the people in the neighborhood, and query through the radius.

Get a specified number of people

127.0.0.1 georadius china:city 6379 > 1000.30 1000 km centered on the coordinates of 1000.30 Looking for cities with a radius of 1000km 1) "xian" 2) "hangzhou" 3) "manjing" 4) "taiyuan" 127.0.0.1 georadius china:city 6379 > georadius china:city 11030 500 km1) "xian" 127.0.0.1 xian 500 km withdist1) 1) "xian" 2) "483.8340" 127.0.1 1 georadius china:city 30 1000km withcoord withdist count 21) 1) "xian" 2 ) "483.8340" 3) 1) "108.96000176668167114" 2) "34.25999964418929977" 2) 1) "manjing" 2) "864.9816" 3) 1) "118.759957323074341" 2) "32.03999960287850968"

Parameter key longitude and latitude radius unit [longitude and latitude of display result] [distance of display result] [number of results displayed]

Georadiusbymember

Displays other members within a certain radius of the specified member

127.0.0.1 georadiusbymember china:city taiyuan 1000 km1) "manjing" 2) "taiyuan" 3) "xian" 127.0.0.1 xian > georadiusbymember china:city taiyuan 1000 km withcoord withdist count 21) 1) "taiyuan" 2) "0.0000" 3) 1) "112.54999905824661255" 2) "37.86000073876942196" 2) "xian" 2) "514.2264" 3) 1) "108.96000176668167114" 2) "34.259999644929977"

Parameters are the same as georadius

Geohash (less used)

This command returns an 11-character hash string

127.0.0.1 wxrvb9qyxk0 6379 > geohash china:city taiyuan shenyang1) "ww8p3hhqmp0" 2) "wxrvb9qyxk0"

Convert a two-dimensional latitude and longitude into an one-dimensional string. The closer the two strings are, the closer they are.

Bottom layer

The underlying implementation principle of geo is actually Zset. We can operate geo through the Zset command.

127.0.0.1 purl 6379 > type china:cityzset

View all elements delete the specified element

127.0.0.1 withscores 6379 > zrange china:city 0-1 withscores 1) "xian" 2) "4040115445396757" 3) "hangzhou" 4) "4054133997236782" 5) "manjing" 6) "4066006694128997" 7) "taiyuan" 8) "4068216047500484" 9) "shenyang" 1) "4072519231994779" 2) "shengzhen" 3) "4154606886655324" 127.0.1RH 6379 > zrem china:city manjing (integer) 1127.0.1RH 6379 > zrange china:city 0 -11) "xian" 2) "hangzhou" 3) "taiyuan" 4) "shenyang" 5) "shengzhen" about "what are the special data types in Redis"? Hope that the above content can be helpful to you, so that you can learn more knowledge, if you think the article is good, please share it for more people to see.

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