How Swoole implements high-performance data backup
In recent years, data backup has become an indispensable part of enterprise information construction. As the business volume and data volume of enterprises increase, traditional backup solutions can no longer meet the needs, so some new backup tools have emerged. Swoole is a high-performance network communication framework based on the PHP language, which is mainly used to implement server applications. This article will introduce how to use Swoole to achieve high-performance data backup.
1. Back up data
First, we need to back up the data. Database software such as MySQL has provided us with relevant tools. We only need to call the corresponding commands to back up the data. The following is a simple backup function:
function backupDatabase($db, $user, $password, $host, $port, $output) { $exec = "mysqldump --opt --skip-lock-tables --extended-insert --user={$user} --password={$password} --host={$host} --port={$port} {$db}"; if($output) { $exec .= " > {$output}"; } exec($exec); }
This function receives the following parameters:
$db: the name of the database that needs to be backed up;
$user: the database user name;
$password: database password;
$host: database host name;
$port: database port number;
$output: backup file path, Can be null.
This function backs up the database to a file, which can be a sql script file used when restoring data. Of course, other backup methods can also be used, such as copying database files, etc.
2. Concurrent backup
If the data is large, the backup process may take some time. Using the traditional backup method, you can only back up one by one according to the specified backup order, and cannot perform multiple backup tasks at the same time. Swoole provides coroutine support, which can implement asynchronous and concurrent backup tasks.
The following is a concurrent backup function implemented using Swoole:
function concurrentBackup($max, $databases) { $num = count($databases); $max = min($max, $num); $chan = new chan($max); for($i = 0; $i < $max; $i++) { $chan->push($i); } $results = []; $i = 0; $executor = new SwooleCoroutineMysql(); while($i < $num) { if($result = $chan->pop()) { $database = $databases[$i]; go(function() use($database, $executor, $chan, &$results) { $executor->connect([ 'host' => $database['host'], 'user' => $database['user'], 'password' => $database['password'], 'database' => $database['schema'] ]); $filename = "/tmp/{$database['schema']}.sql"; backupDatabase($database['schema'], $database['user'], $database['password'], $database['host'], $database['port'], $filename); $executor->query('DROP TABLE IF EXISTS test'); $result = $executor->query("source {$filename}"); if($result === false) { $results[$database['schema']] = 'error'; } else { $results[$database['schema']] = 'ok'; } $executor->close(); $chan->push(1); }); $i++; if($i == $num) break; } } while(count($results) < $num) { Co::sleep(0.01); } return $results; }
This function receives two parameters:
$max: the maximum number of concurrent backups;
$databases: Databases that need to be backed up, including connection information for each database.
This function starts multiple concurrent backup tasks through coroutine. First create a channel with a size of $max to control the number of concurrencies. Then the backup task is executed in a loop, each time taking an available position from the channel and starting a coroutine. Back up the specified database in the coroutine, and then restore the contents of the backup file to the target database. Finally, the results are stored in the $results array.
Because coroutines are lightweight threads that can process multiple tasks simultaneously in one thread, efficient concurrent backup can be achieved.
3. Compress backup files
When backing up data, in order to save storage space, it is usually necessary to compress the backup files. Swoole provides two compression methods, gzip and zlib, which can easily compress backup files.
The following is a function for compressing backup files:
function compressBackupFile($filename, $level = 6, $mode = SWOOLE_ZLIB) { $output = $filename . '.gz'; $ouputFile = gzopen($output, 'wb' . $level); $inFile = fopen($filename, 'rb'); if ($ouputFile && $inFile) { if($mode == SWOOLE_ZLIB) { $z = new SwooleZlib(SW_ZLIB_DEFLATE, $level, SW_ZLIB_ENCODING_GZIP); while(!feof($inFile)) { $data = fread($inFile, 1024 * 4); if(!$data) break; if($z->deflate($data)) { gzwrite($ouputFile, $z->output); } } $z->flush(true); gzwrite($ouputFile, $z->output); } else { while(!feof($inFile)) { $data = fread($inFile, 1024 * 4); if(!$data) break; gzwrite($ouputFile, $data); } } fclose($inFile); gzclose($ouputFile); unlink($filename); return true; } else { return false; } }
This function receives three parameters:
$filename: the name of the backup file that needs to be compressed;
$level: compression level, value range is 1-9, default is 6;
$mode: compression mode, value is SWOOLE_ZLIB or SWOOLE_GZIP, default is SWOOLE_ZLIB.
Using this function, the backup file can be compressed into gz or zlib format.
4. Achieve high-performance backup
By combining the above three functions, we can achieve high-performance data backup. The following is a sample program:
$databases = [ [ 'host' => '127.0.0.1', 'port' => 3306, 'user' => 'root', 'password' => '', 'schema' => 'db1', ], [ 'host' => '127.0.0.1', 'port' => 3306, 'user' => 'root', 'password' => '', 'schema' => 'db2', ], [ 'host' => '127.0.0.1', 'port' => 3306, 'user' => 'root', 'password' => '', 'schema' => 'db3', ], [ 'host' => '127.0.0.1', 'port' => 3306, 'user' => 'root', 'password' => '', 'schema' => 'db4', ], ]; $max = 4; $s1 = microtime(true); $results = concurrentBackup($max, $databases); foreach($results as $schema => $result) { echo "{$schema} backup: {$result} "; } $s2 = microtime(true); echo "time consumed: " . round($s2 - $s1, 3) . "s "; foreach($databases as $database) { $filename = "/tmp/{$database['schema']}.sql.gz"; compressBackupFile($filename, 6, SWOOLE_GZIP); }
This program defines four databases that need to be backed up, and sets the maximum number of concurrencies to 4. First call the concurrentBackup function to back up data in parallel, and then output the backup results and the execution time of the backup process. Finally, compress the backup file.
Using Swoole to achieve high-performance data backup can greatly improve backup efficiency compared with traditional backup methods. However, when using Swoole for data backup, you need to pay attention to the tuning of performance parameters such as thread pool size to take advantage of Swoole.
The above is the detailed content of How Swoole implements high-performance data backup. For more information, please follow other related articles on the PHP Chinese website!

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