0.1 billion pieces of data are split into 100 Mysql Databases and Mysql Databases in PHP.

0.1 billion pieces of data are split into 100 Mysql Databases and Mysql Databases in PHP.

When the amount of data increases, you will choose database/table hash to optimize the data read/write speed. I made a simple attempt to divide 0.1 billion pieces of data into 100 tables. The specific implementation process is as follows:

First, create 100 tables:

 1 $i=0; 2 while($i<=99){ 3 echo "$newNumber \r\n"; 4 $sql="CREATE TABLE `code_".$i."` ( 5  `full_code` char(10) NOT NULL, 6  `create_time` int(10) unsigned NOT NULL, 7  PRIMARY KEY  (`full_code`), 8 ) ENGINE=MyISAM DEFAULT CHARSET=utf8"; 9 mysql_query($sql);10 $i++; 

Next, let's talk about my table sharding rule. full_code is used as the primary key, and we do hash on full_code.

The function is as follows:

1 $table_name=get_hash_table('code',$full_code);2 function get_hash_table($table,$code,$s=100){3 $hash = sprintf("%u", crc32($code));4 echo $hash;5 $hash1 = intval(fmod($hash, $s));6  return $table."_".$hash1;7 } 

In this way, get_hash_table is used to obtain the name of the table where data is stored before data is inserted.

Finally, we use the merge storage engine to implement a complete code table.

1 CREATE TABLE IF NOT EXISTS `code` (  2 `full_code` char(10) NOT NULL,3 `create_time` int(10) unsigned NOT NULL,4 INDEX(full_code)  5 ) TYPE=MERGE UNION=(code_0,code_1,code_2.......) INSERT_METHOD=LAST ; 

In this way, we can use select * from code to obtain all the full_code data.