db sharding

) of the correct shards and send them a query, called a targeted query (targeted), because it only targets shards that might contain the data we're looking for. If it knows we're looking for {"foo": "Bar"}, then it doesn't make sense to query the Shard with the slice key value greater than bar.If the query does not contain a slice key, MONGOs must send the query to all shards, which may be less efficient than the true query, but not necessarily, if a broad query accesses only a small number of d

The first partBefore we build MongoDB, we need to consider a few minor issues:1. What is the purpose of building a cluster? Do multiple backups improve fault tolerance and system availability or scale-out storage of large-scale data or both?If it is for multi-backup then choose Replication Cluster Build, if it is to deal with big data need to build sharding cluster, if both need to create replica for each shardsvr.2. What is

Tags: png recover title cut ROS Development ext Cat TarThis article describes a simple SQL script that implements the ability to shrink all non-system db file sizes across Microsoft SQL Server instances. As a program that deals with SQL every day, apes often encounter db files that are too large to fill the space: For the development tester, if the DB data is n

1. database/table sharding Obviously, the unlimited growth of a primary table (that is, a very important table, such as a user table) will inevitably seriously affect performance. Database sharding and table sharding are a good solution, this is also the way to optimize performance. In this case, we have a more than 10 million-record user table members, which is

Example of ThinkPHP (million-level) data sharding technology Let's talk about the example of using the built-in table sharding algorithm of ThinkPHP to process millions of data. if you need it, let's take a look.Code extracted from thinkphp to see how big data table Sharding is implemented.Data table: house_member_0house_member_1house_member_2house_membe

, there must be a lot more unpopular sections than popular ones. These unpopular sections usually only have a few posts, which is too wasteful to open tables for them; at the same time, the number and access volume of popular sections are much larger than those of unpopular sections, which is very characteristic.The unite table can also be extended into a hash table. Using the md5 code of the entry, it can be divided into n tables. I forget it. The first digit of md5 can be divided into 16 table

Before that, if you do not understand the IP sharding technology, refer to here. The IP sharding technology is simple and violent, and it is not as complicated as the TCP window protocol. Basically, the code is basically in ip_defragment.c. Let's talk about it in general. First, each IP address (host) will have an IP segment package (note that it is an IP address, not an IP address pair ). Therefore, each I

ArticleDirectory Solution 3 1. Process of splitting file batches In a recent project, because the amount of data calculated every day is too large, databases need to be stored in sub-databases. When the data is distributed to various databases, the data update operation will have a consistency and integrity problem. The following is a typical scenario: Assume that there are currently three physical databases, and there is a file containing pieces of data. According to the da

MongoDB sharding algorithm, mongodbsharding There are two main types: range division by numerical values and hash, which are somewhat similar to the memcached cluster mechanism. The following table compares the advantages and disadvantages Sharding Algorithm Range Query Performance Data Distribution Ranged based Strong, easy to concentrate on

30000000-60000000 data is stored in the part_02 partition table. This achieves the goal of horizontal table sharding. 1.2 table creation by date Partition Create table test2 ( ID NUMBERNotNull, JQBH VARCHAR2 (20 ), FJH VARCHAR2 (20 ), KPRQDATE ) PartitionByRange (KPRQ) ( Partition part_01ValuesLess than (TO_DATE ('2017-01-01 00:00:00','Syyyy-MM-DD HH24: MI: ss','Nls _ CALENDAR = GREGORIAN') Tablespace WLKP_FP_DATA_2011, Partition part_02Va

1. database/table sharding Obviously, the unlimited growth of a primary table (that is, a very important table, such as a user table) will inevitably seriously affect performance. Database sharding and table sharding are a good solution, this is also the way to optimize performance. In this case, we have a more than 10 million-record user table members, which i

For Python sharding, Just in the Forum python version http://bbs.byr.cn /#! Article/Python/1693 solves a python sharding problem. Problem: UesrList = ['1', '2', '3', '4', '5', '6'] subList1 = uesrList [2: 5] subList2 = uesrList [-3: -1] subList3 = uesrList [0:-2] subList4 = uesrList [0:-3] subList5 = uesrList [-3:0] print (subList1) print (subList2) print (subList3) print (subList4) print (subList5) # out

Forest An open-source framework for distributed services and data sharding is released with the following features: Simple Application Lightweight Framework Easy to expand Source code, Detailed introduction documents and examples: https://github.com/wtt2012/forest Architecture Forest-core Core APIs and basic implementations. However, to create a distributed service, such as a redis/memecached cluster, you can also creat

The two most prone areas of error– Incrementing the Sharding key– Random sharding KeySharding Key SelectionIncrementing the Sharding key– Fewer data files (advantages)– Because the data file is incremented, the insert write Io is permanently placed on the last piece, resulting in the last write hotspot– At the same time, as the last piece of data increases, it wi

CSS webpage layout example: horizontal column sharding CSS horizontal column layout example. In the content display area, because the element has no height defined, you must add the content to better display the position of the element. That is to say, there is more room for the text display area, so that the content determines the height of the square, because the layout instance is horizontally unchanged and vertically changed to meet different layo

|+ --------- + ------------ + ------------------ + -------------- + ------------- + ----------- + ------------- + ---------- + -------- + ------------ + ----------- +| T_group | 0 | PRIMARY | 1 | id | A | 10388608 | NULL | BTREE || T_group | 1 | idx_user_name | 1 | user_name | A | 8 | NULL | BTREE || T_group | 1 | idx_combination1 | 1 | user_name | A | 8 | NULL | BTREE || T_group | 1 | idx_combination1 | 2 | money | A | 3776 | NULL | BTREE |+ --------- + ------------ + ------------------ + ----

Mysql Master/Slave database, database/table sharding, and other notes 1. mysql Directory:/var/lib/mysql default directory during rpm or yum installation: /usr/local/mysql 2. MySQL installed with the rpm package will not install/etc/my. the cnf file, as to why MySQL can still start and work normally without this file, there are two statements at the point. The first one is my. cnf is only a parameter file during MySQL startup. It can be left empty. MyS

Mycat zookeeper norm zookeeper sharding-by-monthSharding-by-month has been used when calling Dynamic Route1. rule. xml Please wait until (then again) until then again before again until then Class = "io. mycat. route. function. PartitionByMonth"> DateFormat: How many threads are there? SBeginDate? Br/> 2. schema. xml Please wait until (then again) until then again before again until then

used as the value, scatter all keywords in a dictionary Code that implements keyword Filtering90Multiple rows. No!The efficiency is also good. The keywords and content to be filtered are more than 10 thousand characters, and the time is only 10 milliseconds. The two groups of data are read from the notepad. public string Filter(string str) { if (string.IsNullOrEmpty(str)) { return string.Empty; } int len = str.Length - 1;

;+ ---- + ---------- +| Id | name |+ ---- + ---------- +| 3 | beijing4 |+ ---- + ---------- +1 row in set (0.00 sec) OK. In general, MRG_MYISAM table sharding has the following advantages:(1) tables for log applications. for example, you can put the monthly data in a separate table, compress these tables with myisampack, and create a MERGE table to treat them as a table.(2) The query speed should be better. For some tables, large read-only tables can