数据仓库:Mysql大量数据快速导出

背景

写这篇文章主要是介绍一下我做数据仓库ETL同步的过程中遇到的一些有意思的内容和提升程序运行效率的过程。

关系型数据库:

  项目初期:游戏的运营数据比较轻量,相关的运营数据是通过Java后台程序聚合查询关系型数据库MySQL完全可以应付,系统通过定时任务每日统计相关数据,等待运营人员查询即可。

  项目中后期:随着开服数量增多,玩家数量越来越多,数据库的数据量越来越大,运营后台查询效率越来越低。对于普通的关系型来说,如MySQL,当单表存储记录数超过500万条后,数据库查询性能将变得极为缓慢,而往往我们都不会只做单表查询,还有多表join。这里假如有100个游戏服,每个服有20张表,而每个表有500W数据,那么:

  总数据量 = 100 * 20 * 500W = 10亿  按当时的库表结构,换算成磁盘空间,约为100G左右

我的天呐,现在没有单机的内存能同一时间载入100G的数据

https://www.zhihu.com/question/19719997

  所以,考虑到这一点,Hive被提出来解决难题!

 

数据仓库

Hive适合做海量数据的数据仓库工具, 因为数据仓库中的数据有这两个特点:最全的历史数据(海量)、相对稳定的;所谓相对稳定,指的是数据仓库不同于业务系统数据库,数据经常会被更新,数据一旦进入数据仓库,很少会被更新和删除,只会被大量查询。而Hive,也是具备这两个特点

二、项目架构设计

 在这里先说下初期项目架构的探索,因为数据流向,其实最终就是从MYSQL--------->Hive中,我使用的是Jdbc方式。为什么不使用下列工具呢?

  • Sqoop, 因为该游戏每个服有将近80张表,然后又有很多服,以后还会更多,而每个服的库表数据结构其实是完全一样的,只是IP地址不一样,使用Sqoop的话,将会需要维护越来越多的脚本,再者Sqoop没法处理原始数据中一些带有Hive表定义的行列分隔符
  • DataX 阿里开源的数据同步中间件,没做过详细研究

1、全局缓存队列

使用生产者消费者模型,中间使用内存,数据落地成txt

 

 

首先生产者通过Jdbc获取源数据内容,放入固定大小的缓存队列,同时消费者不断的从缓存读取数据,根据不同的数据类型分别读取出来,并逐条写入相应的txt文件。

速度每秒约8000条。

这样做表面上看起来非常美好,流水式的处理,来一条处理一下,可是发现消费的速度远远赶不上生产的速度,生产出来的数据会堆积在缓存队列里面,假如队列不固定长度的话,这时候还会大量消耗内存,所以为了提升写入的速度,决定采用下一种方案

 

2、每一张表一个缓存队列及writer接口

每张表各自起一个生产者消费者模型,消费者启动时初始化相应的writer接口,架构设计如下:

 

table1的生产者通过Jdbc获取源数据内容,放入table自带的固定大小的缓存队列,同时table1相应的消费者不断的从缓存读取数据,根据不同的数据类型分别读取出来,并逐条写入相应的txt文件。

速度每秒约2W条。

 这样生产者线程可以并发的进行,通过控制生产者线程的数量,可以大大提高处理的效率, 项目关键代码如下:

1)线程池

/***
 * 
 * 
 * @描述 任务线程池
 */
public class DumpExecuteService {

    private static ExecutorService dumpServerWorkerService; // 游戏服任务
    private static ExecutorService dumpTableWorkerService; // 表数据任务
    private static ExecutorService dumpReaderWorkerService; // 读取数据任务
    private static ExecutorService dumpWriterWorkerService; // 写数据结果任务

    /***
     * 初始化任务线程池
     * @param concurrencyDBCount 并发数量
     */
    public synchronized static void startup(int concurrencyDBCount) {

        if (dumpServerWorkerService != null)
            return;

        if (concurrencyDBCount > 2)
            concurrencyDBCount = 2; // 最多支持两个数据库任务并发执行

        if (concurrencyDBCount < 1)
            concurrencyDBCount = 1;

        dumpServerWorkerService = Executors.newFixedThreadPool(concurrencyDBCount, new NamedThreadFactory(
                "DumpExecuteService.dumpServerWorkerService" + System.currentTimeMillis()));
        dumpTableWorkerService = Executors.newFixedThreadPool(2, new NamedThreadFactory("DumpExecuteService.dumpTableWorkerService"
                + System.currentTimeMillis()));
        dumpWriterWorkerService = Executors.newFixedThreadPool(8, new NamedThreadFactory("DumpExecuteService.dumpWriterWorkerService"
                + System.currentTimeMillis()));
        dumpReaderWorkerService = Executors.newFixedThreadPool(2, new NamedThreadFactory("DumpExecuteService.dumpReaderWorkerService"
                + System.currentTimeMillis()));
    }

    public static Future<Integer> submitDumpServerWorker(DumpServerWorkerLogic worker) {
        return dumpServerWorkerService.submit(worker);
    }

    public static Future<Integer> submitDumpWriteWorker(DumpWriteWorkerLogic worker) {
        return dumpWriterWorkerService.submit(worker);
    }

    public static Future<Integer> submitDumpReadWorker(DumpReadWorkerLogic worker) {
        return dumpReaderWorkerService.submit(worker);
    }

    public static Future<Integer> submitDumpTableWorker(DumpTableWorkerLogic worker) {
        return dumpTableWorkerService.submit(worker);
    }

    /***
     * 关闭线程池
     */
    public synchronized static void shutdown() {

        //执行线程池关闭...
    }
}

说明:该类定义4个线程池,分别用于执行不同的任务

2)游戏服任务线程池

/**
 * 1) 获取 游戏服log库数据库连接 
2) 依次处理单张表
*/ public class DumpServerWorkerLogic extends AbstractLogic implements Callable<Integer> { private static Logger logger = LoggerFactory.getLogger(DumpServerWorkerLogic.class); private final ServerPO server;// 数据库 private final String startDate;// 开始时间 private SourceType sourceType;// 数据来源类型 private Map<String, Integer> resultDBMap;// 表记录计数 private GameType gameType; public DumpServerWorkerLogic(ServerPO server, String startDate, SourceType sourceType, Map<String, Integer> resultDBMap, GameType gameType) { CheckUtil.checkNotNull("DumpServerWorkerLogic.server", server); CheckUtil.checkNotNull("DumpServerWorkerLogic.startDate", startDate); CheckUtil.checkNotNull("DumpServerWorkerLogic.sourceType", sourceType); CheckUtil.checkNotNull("DumpServerWorkerLogic.resultDBMap", resultDBMap); CheckUtil.checkNotNull("DumpServerWorkerLogic.gameType", gameType); this.server = server; this.startDate = startDate; this.sourceType = sourceType; this.resultDBMap = resultDBMap; this.gameType = gameType; } @Override public Integer call() { // 获取连接, 并取得该库的所有表 Connection conn = null; try { conn = JdbcUtils.getDbConnection(server); } catch (Exception e) { throw new GameRuntimeException(e.getMessage(), e); } List<String> tableNames = null; DumpDbInfoBO dumpDbInfoBO = DumpConfig.getDumpDbInfoBO(); int totalRecordCount = 0; try { switch (this.sourceType) { case GAME_LOG: tableNames = JdbcUtils.getAllTableNames(conn); break; case INFOCENTER: tableNames = dumpDbInfoBO.getIncludeInfoTables(); tableNames.add("pay_action"); break; case EVENT_LOG: tableNames = new ArrayList<String>(); Date date = DateTimeUtil.string2Date(startDate, "yyyy-MM-dd"); String sdate = DateTimeUtil.date2String(date, "yyyyMMdd"); String smonth = DateTimeUtil.date2String(date, "yyyyMM"); tableNames.add("log_device_startup" + "_" + smonth); tableNames.add("log_device" + "_" + sdate); break; } // 遍历table for (String tableName : tableNames) { // 过滤 if (dumpDbInfoBO.getExcludeTables().contains(tableName)) continue; DumpTableWorkerLogic tableTask = new DumpTableWorkerLogic(conn, server, tableName, startDate, resultDBMap, gameType, sourceType); Future<Integer> tableFuture = DumpExecuteService.submitDumpTableWorker(tableTask); int count = tableFuture.get(); totalRecordCount += count; logger.info(String.format("DumpServerWorkerLogic %s-%s.%s be done", startDate, server.getLogDbName(), tableName)); } return totalRecordCount; } catch (Exception e) { throw new GameRuntimeException(e, "DumpTableWorkerLogic fail. server={%s}, errorMsg={%s} ",server.getId(), e.getMessage()); } finally { JdbcUtils.closeConnection(conn); } } }

 

 3)表处理任务,一个表一个

 

/***
 * 
 * 
 * @描述 创建一个表查询结果写任务 (一个表一个)
 */
public class DumpTableWorkerLogic implements Callable<Integer> {
    private static Logger logger = LoggerFactory.getLogger(DumpTableWorkerLogic.class);

    private final String tableName;
    private final Connection conn;

    private ServerPO server;

    private String startDate;

    private Map<String, Integer> resultDBMap;// 表记录计数

    private GameType gameType;

    private SourceType sourceType;// 数据来源类型

    public DumpTableWorkerLogic(Connection conn, ServerPO server, String tableName, String startDate, Map<String, Integer> resultDBMap,
            GameType gameType, SourceType sourceType) {
        CheckUtil.checkNotNull("DumpTableWorkerLogic.conn", conn);
        CheckUtil.checkNotNull("DumpTableWorkerLogic.tableName", tableName);
        CheckUtil.checkNotNull("DumpTableWorkerLogic.server", server);
        CheckUtil.checkNotNull("DumpTableWorkerLogic.startDate", startDate);
        CheckUtil.checkNotNull("DumpTableWorkerLogic.resultDBMap", resultDBMap);
        CheckUtil.checkNotNull("DumpTableWorkerLogic.gameType", gameType);
        CheckUtil.checkNotNull("DumpServerWorkerLogic.sourceType", sourceType);

        this.conn = conn;
        this.tableName = tableName;
        this.server = server;
        this.startDate = startDate;
        this.resultDBMap = resultDBMap;
        this.gameType = gameType;
        this.sourceType = sourceType;

        logger.info("DumpTableWorkerLogic[{}] Reg", tableName);
    }

    @Override
    public Integer call() {
        logger.info("DumpTableWorkerLogic[{}] Start", tableName);

        // 写检查结果任务
        DumpWriteWorkerLogic writerWorker = new DumpWriteWorkerLogic(server, tableName, startDate, resultDBMap, gameType,
                sourceType);
        Future<Integer> writeFuture = DumpExecuteService.submitDumpWriteWorker(writerWorker);
        logger.info("DumpTableWorkerLogic[{}] writer={}", tableName);

        // 数据查询任务
        DumpReadWorkerLogic readerWorker = new DumpReadWorkerLogic(conn, tableName, writerWorker, startDate);
        DumpExecuteService.submitDumpReadWorker(readerWorker);
        logger.info("DumpTableWorkerLogic[{}] reader={}", tableName);

        try {
            int writeCount = writeFuture.get();
            logger.info("DumpTableWorkerLogic[{}] ---" + startDate + "---" + server.getId() + "---" + tableName + "---导出数据条数---"
                    + writeCount);
            return writeCount;
        }  catch (Exception e) {
            throw new GameRuntimeException(e, "DumpTableWorkerLogic fail. tableName={%s}, errorMsg={%s} ",tableName, e.getMessage());
        }
    }

}

 

 

4)单表读取任务线程

/***
 * mysql读取数据任务
 * 
 */
public class DumpReadWorkerLogic implements Callable<Integer> {

    private static Logger logger = LoggerFactory.getLogger(DumpReadWorkerLogic.class);

    private String tableName;

    private final Connection conn;

    private DumpWriteWorkerLogic writerWorker; // 写结果数据任务

    private String startDate;// 开始导出日期

    private static final int LIMIT = 50000;// 限制sql一次读出条数

    public DumpReadWorkerLogic(Connection conn, String tableName, DumpWriteWorkerLogic writerWorker, String startDate) {
        CheckUtil.checkNotNull("MysqlDataReadWorker.conn", conn);
        CheckUtil.checkNotNull("MysqlDataReadWorker.tableName", tableName);
        CheckUtil.checkNotNull("MysqlDataReadWorker.startDate", startDate);

        this.conn = conn;
        this.tableName = tableName;
        this.writerWorker = writerWorker;
        this.startDate = startDate;

        logger.info("DumpReadWorkerLogic Reg. tableName={}", this.tableName);
    }

    @Override
    public Integer call() {
        try {
            List<Map<String, Object>> result = JdbcUtils.queryForList(conn, "show full fields from " + tableName);

            int index = 0;
            String querySql = "";

            int totalCount = 0;
            while (true) {
                int offset = index * LIMIT;
                querySql = DumpLogic.getTableQuerySql(result, tableName, true, startDate) + " limit " + offset + "," + LIMIT;
                int row = DumpLogic.query(conn, querySql, writerWorker);
                totalCount += row;
                logger.info("tableName=" + tableName + ", offset=" + offset + ", index=" + index + ", row=" + row + ", limit=" + LIMIT);
                if (row < LIMIT)
                    break;
                index++;
            }
            writerWorker.prepareClose();
            logger.info(startDate + "---" + tableName + "---Read.End");
            return totalCount;
        }
        catch (Exception e) {
            throw new GameRuntimeException(e, "MysqlDataReadWorker fail. tableName={%s}, errorMsg={%s} ",tableName, e.getMessage());
        }
    }

}

 

5)单表写入任务线程

/***
 * 
 * 
 * @描述 mysql数据导出任务
 */
public class DumpWriteWorkerLogic implements Callable<Integer> {

    private static final Logger logger = LoggerFactory.getLogger(DumpWriteWorkerLogic.class);
    private String tableName;// 表名

    private AtomicBoolean alive; // 线程是否活着

    private BufferedWriter writer;

    private ArrayBlockingQueue<String> queue; // 消息队列

    private ServerPO server;// 服务器

    private String startDate;// 开始时间

    private Map<String, Integer> resultDBMap;// 当天某服某表数量记录

    private GameType gameType;

    private SourceType sourceType;// 数据来源类型

    public DumpWriteWorkerLogic(ServerPO server, String tableName, String startDate, Map<String, Integer> resultDBMap, GameType gameType,
            SourceType sourceType) {
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.tableName", tableName);
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.server", server);
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.startDate", startDate);
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.resultDBMap", resultDBMap);
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.gameType", gameType);
        CheckUtil.checkNotNull("DumpWriteWorkerLogic.sourceType", sourceType);

        this.tableName = tableName;
        this.server = server;
        this.startDate = startDate;
        this.queue = new ArrayBlockingQueue<>(65536);
        this.alive = new AtomicBoolean(true);
        this.gameType = gameType;
        this.sourceType = sourceType;
        this.writer = createWriter();
        this.resultDBMap = resultDBMap;

        logger.info("DumpWriteWorkerLogic Reg. tableName={}", this.tableName);
    }

    /***
     * 创建writer, 若文件不存在,会新建文件
     * 
     * @param serverId
     * @return
     */
    private BufferedWriter createWriter() {
        try {
            File toFile = FileUtils.getFilenameOfDumpTable(sourceType, tableName, startDate, gameType, ".txt");
            if (!toFile.exists()) {
                FileUtils.createFile(sourceType, tableName, startDate, gameType);
            }
            return new BufferedWriter(new OutputStreamWriter(new FileOutputStream(toFile, true), Charsets.UTF_8), 5 * 1024 * 1024);
        } catch (Exception e) {
            throw new GameRuntimeException(e, "DumpWriteWorkerLogic createWriter fail. server={%s}, errorMsg={%s} ",server.getId(), e.getMessage());
        }
    }

    /***
     * 写入文件
     * 
     * @param line
     *            一条记录
     */
    private void writeToFile(String line) {
        try {
            this.writer.write(line + "\n");
        } catch (Exception e) {
            throw new GameRuntimeException(e, "DumpWriteWorkerLogic writeToFile fail. errorMsg={%s} ", e.getMessage());
        }
    }

    /**
     * 记录数据到消息队列; 如果消息队列满了, 会阻塞直到可以put为止
     * 
     * @param result
     */
    public void putToWriterQueue(String line) {

        CheckUtil.checkNotNull("DumpWriteWorkerLogic putToWriterQueue", line);

        try {
            queue.put(line);
        } catch (InterruptedException e) {
            throw new GameRuntimeException(e, "DumpWriteWorkerLogic putToWriterQueue fail. errorMsg={%s} ", e.getMessage());
        }
    }

    /**
     * 准备关闭 (通知一下"需要处理的用户数据都处理完毕了"; task 写完数据, 就可以完毕了)
     */
    public void prepareClose() {
        alive.set(false);
    }

    @Override
    public Integer call() {
        logger.info("DumpWriteWorkerLogic Start. tableName={}", this.tableName);
        try {
            int totalCount = 0;
            while (alive.get() || !queue.isEmpty()) {
                List<String> dataList = new ArrayList<String>();
                queue.drainTo(dataList);
                int count = processDataList(dataList);
                totalCount += count;
            }
            logger.info("DumpWriteWorkerLogic ---" + startDate + "---" + tableName + "---Writer.End");
            return totalCount;
        } catch (Exception exp) {
            throw new GameRuntimeException(exp, "DumpWriteWorkerLogic call() fail. errorMsg={%s} ", exp.getMessage());
        } finally {
            FileUtil.close(this.writer);
        }
    }

    /***
     * 处理数据:写入本地文件及map
     * 
     * @param dataList
     *            数据集合
     * @return
     */
    private int processDataList(List<String> dataList) {
        int totalCount = 0;

        // 所有记录
        String key = server.getId() + "#" + tableName + "#" + sourceType.getIndex();
        if (dataList != null && dataList.size() > 0) {

            for (String line : dataList) {

                // 按行写入文件
                writeToFile(line);

                // 记录到result_data_record_count
                if (resultDBMap.get(key) != null) {
                    resultDBMap.put(key, resultDBMap.get(key) + 1);
                }
                else {
                    resultDBMap.put(key, 1);
                }

                totalCount++;
            }
        }

        return totalCount;
    }

}

内存优化

1、使用Jdbc方式获取数据,如果这个数据表比较大,那么获取数据的速度特别慢;

2、这个进程还会占用非常大的内存,并且GC不掉。分析原因,Jdbc获取数据的时候,会一次将所有数据放入到内存,如果同步的数据表非常大,那么甚至会将内存撑爆。

那么优化的方法是让Jdbc不是一次全部将数据拿到内存,而是分页获取,每次最大limit数设置为50000,请参考read线程。

 

经过这种架构优化后,5000W数据大约花费40min可完成导出

 

说明:

因为本文只是记录项目的设计过程,详细的代码后面会开源。

posted @ 2017-09-29 18:14 ^_TONY_^ 阅读(...) 评论(...) 编辑 收藏