MySQL千万级数据进行插入,基础数据3千万,插入1千万数据时间约为4.7分钟,10个线程同时插入

🏷️ s365app下载 📅 2025-08-31 06:40:32 ✍️ admin 👀 9365 ❤️ 339
MySQL千万级数据进行插入,基础数据3千万,插入1千万数据时间约为4.7分钟,10个线程同时插入

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","***","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。

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