从mysql查一万条数据存入Redis mysql查询一万条数据时间

测试MySQL千万条数据插入速度

使用多线程，每条线程处理数据100万条，每次插入携带数据7万条进行提交

数据库基数为0，插入1000万条数据，时间为311957毫秒，也就是311.957秒，约为5.2分钟

数据库基础数据为2000万条数据，插入1000万条数据，时间为302545毫秒，也就是502.545秒。约5.1分钟

数据库基础数据为3000万条数据，插入1000万条数据，时间为286377毫秒，也就是286.377秒。约4.7分

1000万条数据日志

===================>>>>>DefaultManagedAwareThreadFactory-1
===================>>>>>DefaultManagedAwareThreadFactory-2
===================>>>>>DefaultManagedAwareThreadFactory-3
===================>>>>>DefaultManagedAwareThreadFactory-4
===================>>>>>DefaultManagedAwareThreadFactory-5
===================>>>>>DefaultManagedAwareThreadFactory-6
===================>>>>>DefaultManagedAwareThreadFactory-7
===================>>>>>DefaultManagedAwareThreadFactory-8
===================>>>>>DefaultManagedAwareThreadFactory-9
===================>>>>>DefaultManagedAwareThreadFactory-10
DefaultManagedAwareThreadFactory-2======结束=====>>>>285025
DefaultManagedAwareThreadFactory-7======结束=====>>>>286669
DefaultManagedAwareThreadFactory-3======结束=====>>>>296607
DefaultManagedAwareThreadFactory-6======结束=====>>>>298840
DefaultManagedAwareThreadFactory-10======结束=====>>>>296657
DefaultManagedAwareThreadFactory-4======结束=====>>>>301761
DefaultManagedAwareThreadFactory-5======结束=====>>>>302579
DefaultManagedAwareThreadFactory-8======结束=====>>>>301438
DefaultManagedAwareThreadFactory-1======结束=====>>>>311957
DefaultManagedAwareThreadFactory-9======结束=====>>>>304187

基础数据2000万，插入1000万条数据日志：

===================>>>>>DefaultManagedAwareThreadFactory-1
===================>>>>>DefaultManagedAwareThreadFactory-2
===================>>>>>DefaultManagedAwareThreadFactory-3
===================>>>>>DefaultManagedAwareThreadFactory-4
===================>>>>>DefaultManagedAwareThreadFactory-5
===================>>>>>DefaultManagedAwareThreadFactory-6
===================>>>>>DefaultManagedAwareThreadFactory-7
===================>>>>>DefaultManagedAwareThreadFactory-8
===================>>>>>DefaultManagedAwareThreadFactory-9
===================>>>>>DefaultManagedAwareThreadFactory-10
DefaultManagedAwareThreadFactory-8======结束=====>>>>276787
DefaultManagedAwareThreadFactory-3======结束=====>>>>284162
DefaultManagedAwareThreadFactory-4======结束=====>>>>284252
DefaultManagedAwareThreadFactory-2======结束=====>>>>291498
DefaultManagedAwareThreadFactory-1======结束=====>>>>297639
DefaultManagedAwareThreadFactory-7======结束=====>>>>292803
DefaultManagedAwareThreadFactory-5======结束=====>>>>297715
DefaultManagedAwareThreadFactory-9======结束=====>>>>297572
DefaultManagedAwareThreadFactory-10======结束=====>>>>296322
DefaultManagedAwareThreadFactory-6======结束=====>>>>302545

基础数据3000万，插入1000万条数据日志：

===================>>>>>DefaultManagedAwareThreadFactory-1
===================>>>>>DefaultManagedAwareThreadFactory-2
===================>>>>>DefaultManagedAwareThreadFactory-3
===================>>>>>DefaultManagedAwareThreadFactory-4
===================>>>>>DefaultManagedAwareThreadFactory-5
===================>>>>>DefaultManagedAwareThreadFactory-6
===================>>>>>DefaultManagedAwareThreadFactory-7
===================>>>>>DefaultManagedAwareThreadFactory-8
===================>>>>>DefaultManagedAwareThreadFactory-9
===================>>>>>DefaultManagedAwareThreadFactory-10
DefaultManagedAwareThreadFactory-6======结束=====>>>>259247
DefaultManagedAwareThreadFactory-2======结束=====>>>>264036
DefaultManagedAwareThreadFactory-3======结束=====>>>>265275
DefaultManagedAwareThreadFactory-7======结束=====>>>>264781
DefaultManagedAwareThreadFactory-10======结束=====>>>>265781
DefaultManagedAwareThreadFactory-9======结束=====>>>>271145
DefaultManagedAwareThreadFactory-5======结束=====>>>>281170
DefaultManagedAwareThreadFactory-1======结束=====>>>>286377
DefaultManagedAwareThreadFactory-4======结束=====>>>>283481
DefaultManagedAwareThreadFactory-8======结束=====>>>>279556

模拟数据测试：

模拟随机产生手机号码：

/**
     * 返回手机号码
     */
    private static String[] telFirst = "134,135,136,137,138,139,150,151,152,157,158,159,130,131,132,155,156,133,153".split(",");

    public static int getNum(int start, int end) {
        return (int) (Math.random() * (end - start + 1) + start);
    }

    public static String getTel() {
        int index = getNum(0, telFirst.length - 1);
        String first = telFirst[index];
        String second = String.valueOf(getNum(1, 888) + 10000).substring(1);
        String third = String.valueOf(getNum(1, 9100) + 10000).substring(1);
        return first + second + third;
    }

模拟随机产生出生日期：

/**
     * 随机出生日期
     *
     * @return
     */
    public static String randomBirthday() {
        Calendar birthday = Calendar.getInstance();
        birthday.set(Calendar.YEAR, (int) (Math.random() * 60) + 1950);
        birthday.set(Calendar.MONTH, (int) (Math.random() * 12));
        birthday.set(Calendar.DATE, (int) (Math.random() * 31));

        StringBuilder builder = new StringBuilder();
        builder.append(birthday.get(Calendar.YEAR));
        long month = birthday.get(Calendar.MONTH) + 1;
        if (month < 10) {
            builder.append("0");
        }
        builder.append(month);
        long date = birthday.get(Calendar.DATE);
        if (date < 10) {
            builder.append("0");
        }
        builder.append(date);
        return builder.toString();
    }

模拟产生姓名：

private static final String[] Surname= {"赵","钱","孙","李","周","吴","郑","王","冯","陈","褚","卫","蒋","沈","韩","杨","朱","秦","尤","许",
            "何","吕","施","张","孔","曹","严","华","金","魏","陶","姜","戚","谢","邹","喻","柏","水","窦","章","云","苏","潘","葛","奚","范","彭","郎",
            "鲁","韦","昌","马","苗","凤","花","方","俞","任","袁","柳","酆","鲍","史","唐","费","廉","岑","薛","雷","贺","倪","汤","滕","殷",
            "罗","毕","郝","邬","安","常","乐","于","时","傅","皮","卞","齐","康","伍","余","元","卜","顾","孟","平","黄","和",
            "穆","萧","尹","姚","邵","湛","汪","祁","毛","禹","狄","米","贝","明","臧","计","伏","成","戴","谈","宋","茅","庞","熊","纪","舒",
            "屈","项","祝","董","梁","杜","阮","蓝","闵","席","季","麻","强","贾","路","娄","危","江","童","颜","郭","梅","盛","林","刁","钟",
            "徐","邱","骆","高","夏","蔡","田","樊","胡","凌","霍","虞","万","支","柯","昝","管","卢","莫","经","房","裘","缪","干","解","应",
            "宗","丁","宣","贲","邓","郁","单","杭","洪","包","诸","左","石","崔","吉","钮","龚","程","嵇","邢","滑","裴","陆","荣","翁","荀",
            "羊","于","惠","甄","曲","家","封","芮","羿","储","靳","汲","邴","糜","松","井","段","富","巫","乌","焦","巴","弓","牧","隗","山",
            "谷","车","侯","宓","蓬","全","郗","班","仰","秋","仲","伊","宫","宁","仇","栾","暴","甘","钭","厉","戎","祖","武","符","刘","景",
            "詹","束","龙","叶","幸","司","韶","郜","黎","蓟","溥","印","宿","白","怀","蒲","邰","从","鄂","索","咸","籍","赖","卓","蔺","屠",
            "蒙","池","乔","阴","郁","胥","能","苍","双","闻","莘","党","翟","谭","贡","劳","逄","姬","申","扶","堵","冉","宰","郦","雍","却",
            "璩","桑","桂","濮","牛","寿","通","边","扈","燕","冀","浦","尚","农","温","别","庄","晏","柴","瞿","阎","充","慕","连","茹","习",
            "宦","艾","鱼","容","向","古","易","慎","戈","廖","庾","终","暨","居","衡","步","都","耿","满","弘","匡","国","文","寇","广","禄",
            "阙","东","欧","殳","沃","利","蔚","越","夔","隆","师","巩","厍","聂","晁","勾","敖","融","冷","訾","辛","阚","那","简","饶","空",
            "曾","毋","沙","乜","养","鞠","须","丰","巢","关","蒯","相","查","后","荆","红","游","郏","竺","权","逯","盖","益","桓","公","仉",
            "督","岳","帅","缑","亢","况","郈","有","琴","归","海","晋","楚","闫","法","汝","鄢","涂","钦","商","牟","佘","佴","伯","赏","墨",
            "哈","谯","篁","年","爱","阳","佟","言","福","南","火","铁","迟","漆","官","冼","真","展","繁","檀","祭","密","敬","揭","舜","楼",
            "疏","冒","浑","挚","胶","随","高","皋","原","种","练","弥","仓","眭","蹇","覃","阿","门","恽","来","綦","召","仪","风","介","巨",
            "木","京","狐","郇","虎","枚","抗","达","杞","苌","折","麦","庆","过","竹","端","鲜","皇","亓","老","是","秘","畅","邝","还","宾",
            "闾","辜","纵","侴","万俟","司马","上官","欧阳","夏侯","诸葛","闻人","东方","赫连","皇甫","羊舌","尉迟","公羊","澹台","公冶","宗正",
            "濮阳","淳于","单于","太叔","申屠","公孙","仲孙","轩辕","令狐","钟离","宇文","长孙","慕容","鲜于","闾丘","司徒","司空","兀官","司寇",
            "南门","呼延","子车","颛孙","端木","巫马","公西","漆雕","车正","壤驷","公良","拓跋","夹谷","宰父","谷梁","段干","百里","东郭","微生",
            "梁丘","左丘","东门","西门","南宫","第五","公仪","公乘","太史","仲长","叔孙","屈突","尔朱","东乡","相里","胡母","司城","张廖","雍门",
            "毋丘","贺兰","綦毋","屋庐","独孤","南郭","北宫","王孙"};
    public static String getChineseName() {
        String str = null;
        String name = null;
        int highPos, lowPos;
        Random random = new Random();
        //区码，0xA0打头，从第16区开始，即0xB0=11*16=176,16~55一级汉字，56~87二级汉字
        highPos = (176 + Math.abs(random.nextInt(72)));
        random=new Random();
        //位码，0xA0打头，范围第1~94列
        lowPos = 161 + Math.abs(random.nextInt(94));

        byte[] bArr = new byte[2];
        bArr[0] = (new Integer(highPos)).byteValue();
        bArr[1] = (new Integer(lowPos)).byteValue();
        try {
            //区位码组合成汉字
            str = new String(bArr, "GB2312");
            int index=random.nextInt(Surname.length-1);
            //获得一个随机的姓氏
            name = Surname[index] +str;

        } catch (UnsupportedEncodingException e) {
            e.printStackTrace();
        }
        return name;
    }

模拟产生创建时间：

public static Date getTime() {
        Random   rand   =   new   Random();
        Calendar   cal   =   Calendar.getInstance();
        cal.set(1900,   0,   1);
        long   start   =   cal.getTimeInMillis();
        cal.set(2020,   0,   1);
        long   end   =   cal.getTimeInMillis();
        Date   d   =   new   Date(start   +   (long)(rand.nextDouble()   *   (end   -   start)));
        return d;
    }

 

优化点：

1：尽量使用MySQL自增ID，InnoDB引擎表是基于B+树的索引组织表，数据记录本身被存于主索引（一颗B+Tree）的叶子节点上。这就要求同一个叶子节点内（大小为一个内存页或磁盘页）的各条数据记录按主键顺序存放，因此每当有一条新的记录插入时，MySQL会根据其主键将其插入适当的节点和位置，如果页面达到装载因子（InnoDB默认为15/16），则开辟一个新的页（节点），如果表使用自增主键，那么每次插入新的记录，记录就会顺序添加到当前索引节点的后续位置，当一页写满，就会自动开辟一个新的页。如果使用非自增主键（如果身份证号或学号等），由于每次插入主键的值近似于随机，因此每次新纪录都要被插到现有索引页得中间某个位置，此时MySQL不得不为了将新记录插到合适位置而移动数据，甚至目标页面可能已经被回写到磁盘上而从缓存中清掉，此时又要从磁盘上读回来，这增加了很多开销，同时频繁的移动、分页操作造成了大量的碎片，得到了不够紧凑的索引结构，后续不得不通过OPTIMIZE TABLE来重建表并优化填充页面。

2：取消所有的索引，尤其是唯一索引。（同上）每当有一条新的记录插入时，MySQL会根据其插入适当的节点和位置，会导致移动数据，造成大量碎片

3：批量插入可以使SQL日志量（MySQL的binlog和innodb的事务让日志）减少了，降低日志刷盘的数据量和频率，从而提高效率。通过批量插入减少SQL语句解析的次数，减少网络传输的IO。

4：使用事务可以提高数据的插入效率，这是因为进行一个INSERT操作时，MySQL内部会建立一个事务，在事务内才进行真正插入处理操作。通过使用事务可以减少创建事务的消耗，所有插入都在执行后才进行提交操作。

5：多线程处理，这个就不要多说了。