一些概念
分区表在oracle和sqlserver中都上存在的,当数据表的数据量过大时,上千万,上亿的数据,在进行数据查询时需要显得比较慢,性能很差,这时是时候引入分区表了,分区表顾名思义,就是把物理表用一些文件NDF进行分块存储,以缓减IO的压力,因为当你的SQL文件过大的,这其实对系统的IO影响是最大的,这种分区表我感觉类似于数据的分片(mongodb),它将有效的利用服务器的CPU多核资源,并行去处理你的请求,所以在大数据情况下,分区表是很好的一种选择!
我们通常也把电脑的磁盘分成若干的区,其中一种考虑也是为了性能,安全等
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" 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sql的分区表于若干的文件组组成,它们可以被理解成依照某个条件(分区函数)来进行划分的文件块,当你进行curd操作时,SQL会把它同时响应到对应的块上去,文件组里至少包含一个文件,当然可以是多个,它们也可以在不同的磁盘上。
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" alt="" />
说干就干
下面来一步一步的实现一下分区表的建立逻辑
--建立两个文件组
ALTER DATABASE Test ADD FILEGROUP BEFORE2000
ALTER DATABASE Test ADD FILEGROUP AFTER2000
ALTER DATABASE Test ADD FILEGROUP AFTER2010 --创建文件
ALTER DATABASE Test ADD FILE
(Name=N'Before2000',filename='c:\Program Files\Microsoft SQL Server\MSSQL10.MSSQLSERVER\MSSQL\DATA\Before2000.ndf',size=5mb,maxsize=100Mb,filegrowth=5mb)
TO FILEGROUP Before2000
ALTER DATABASE Test ADD FILE
(Name=N'After2000',filename='c:\Program Files\Microsoft SQL Server\MSSQL10.MSSQLSERVER\MSSQL\DATA\After2000.ndf',size=5mb,maxsize=100Mb,filegrowth=5mb)
TO FILEGROUP After2000
ALTER DATABASE Test ADD FILE
(Name=N'After2010',filename='c:\Program Files\Microsoft SQL Server\MSSQL10.MSSQLSERVER\MSSQL\DATA\After2010.ndf',size=5mb,maxsize=100Mb,filegrowth=5mb)
TO FILEGROUP After2010
上面代码在磁盘上建立了两个文件组,用来存储2000年以前,2000-2010年,以2010年以后的数据,而ndf是分区表文件的类型,一个分区表文件组可以由多个ndf文件构成
--编写分区函数
CREATE PARTITION FUNCTION RangeTime (DATETIME) AS RANGE LEFT FOR VALUES ('2000-01-01','2010-01-01')
--编写分区方案, 分区方案也就是将分区函数与文件组进行一个关联
CREATE PARTITION SCHEME RangeSchema_CreateTime
AS PARTITION RangeTime
TO (BEFORE2000,AFTER2000,AFTER2010)
上面分区函数说明以哪里依据进行分区,而分区方案是将它与分区文件组进行接合,或者和数据表进行打通,以后我们用的时候,直接用分区函数(表名)即可。
--创建分区表,先建表,再设主键,否则会出错
CREATE TABLE Order
(
ID VARCHAR(50) ,
UserId VARCHAR(50) ,
CreateTime DATETIME
)
ON RangeSchema_CreateTime(CreateTime)
上面代码建立一张表,并进行分区的配置,注意,在建立表后,再建立主键,我们填充一些数据就可以测试了,下面介绍几个常用的命令
返回2001-2-2日这条数据会被分配到哪个分区了
--测试某个对象放在哪个分区里
SELECT $PARTITION.RangeTime('2001-2-2')
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZ8AAAB8CAIAAAA5JypbAAAPnUlEQVR4nO1dPWsbSRjeWr/D7R0BVU4R/BN8kKvTLdh9dK2aqy+Gw2YxGBchVdyYYNQIhKsQbSGCsQshNSkMuhRR526umP2Y753Zb42ehwex3p2deeedmUfv7KzGwcPiayFJxwhSAgAA2CLouboF4zHUDQCAEui7ulEjLdVtcHDaBC1zpsl0ieXzTtnWbrl9tsqULRhfb+u0b5iTMUAT6Lu6OcVuFYeHLjchZ11BbD42w8nS4NL1Mpvq5MAWjFcaU842m5SunjE4yilxlUIBV/Rd3aiRTcduRAq7dMeGsUEkdXOqpKVhJeplKQdOpdgktkzDVl84kM9X8Q+RVKmiE2yydXICUC/6rm4txG7KQcKekXNWlmU2wDITXQJdYrMTlIXau1F31d6YwlKIRsV051394+p/cz42txQ2QUW/AfboQN2W9xfBeByMx8HFPXv+7mYcjMev7/+TjWxI3YiqI+o+XTtludFVOr1QBaU9yuqY/9SdKVFfs8HCXYX+dyrR0IKGM5ZFVO+WhTkA5dC2ut3d5KK2vL/ItGx5fxHcPJLHG0Hdmo7diNSbdZ9OWVn24Oqj0ZxAmV6usv2AtyzCNVn2KThH538n/xS2i+Wf5Wpq03kKOzZQDl3OTFl1SyCpGzWyJ+pmLstsgHxVl544jhbWPMvR7uRG+arstIqVlauQnS/MytVdNn3AYGH19irRIkA5dKJuj6FqZkqIQt3af+6m+1SmtzdAl4ncy0skI0aNMA8q+8GvzLZ0LWwsl686+Ue40dBeZo/ZuLFKtyzMASiHLmO3uxvpKVvV2O1qIp5bnByc6s9XUrcSUiIZXNDvC7PVJdNZLsuEsi7KnG1uEfymbykHdTM7wdI/OlMLczN7soo9QnMAtaPbNdPHUAjfuojdiGpEyZ+6Hqw7rqv3W6YnepWRB5Iyma4gopIY5S3KlOZaZPkoW9OQYQl/6qy1TFOuISxvAZpA2+r24WIcPibHdzfj4OaRu9zuczfhRlK3ujl5psposbFTWXf52GCAXFPdXfaWKJtAzr+if3StY05jWYvq3dKpnwD2aD92Sx+68c/d6OsggXSpzdjNvk8TjfaZbdDd5WSeOY1NXQRfZX/qCrLP3MmHsk/kg0Lb7D1paZKusiXawp7WYwdwQ9/f5qVGtqZuxDjhErqj0DUNORgGcPXRIttveW9mtsEkXea6atrkY1MXNv/CWpRzo/LG0r2oSg7lRgVQiL6rW8uxG1GNczlnwj8tUl4S+q6uuEKzzQnKXTWbpKuOpXMMHnNtCNe7nNLYn3RiiRzKDAzAAn1XN2pkm6sK8iVDzspLmTFKq5RnXIuwrBSRpEooy5BsoFEx+xq5NhZbaKHn7f0j185wl43lQvvapzdYCDSBvqtbO++7mbt7jbmVyLB0vSxvdMrf0kslbCZ2Supqv/Jqxa5SOxsYNwAh/Vc3amS3+7uBYKNsYQjtJ/qubq3FbiAIdssgqHn/7b6rGzUS6gaC3nPv1A2xGwjuCfdO3aiR+6Zuby6fl5d/d24GCLZJH9RNt3vlh4vkhwrsj7FKxG5n6/Tv6WKyngwOTt9cPotJ15PBwelgtGBO5b+r16Y/OB0cnJ5M85NvLp8nI1V68nx2XLKN8/wJmYxOxUoRQghJtY/ZHYCxkK9XfslgJ1soIYRMr0qkl/3DnqE253myBgvU2N80C9vxZEpq/NY5Wwud5GqiqmzW9ELRubWM8w3n2VawM09drnt6Vb2OJ0uppjuvbrrdK5n9Qh7Dcf5bVGqkvbqxUc/JlBvYudN5z55MFUqkS38yzTsN7UZU3Wjik2miR1LHteZokeWf5ZZ2kVx/ufyPJ8v1RKiF4IdMWcx2CjGja3qFf3K/PS/Xqf2qnm3wf72aYlNoDe3o0tAZz9aiCjB1v5ow33aD0YL98ig8/+bymUyvBqOFpSe15ZZKL9dLNPvgdOCBurFQ7F6Zns/UzTV2083p0vNXE4WXDerGpz+eLKUeaW4wV9JgUHWJUzc2WXLMd1xRnaWvcWUpOu/ZppdkK7vxZPp8dpmOZ0d14+xnwrosQfI1M80usdtbZeHt89nlIr/reLLMMrIYeFlAxFlFCFk/T2iJiWGMguvzHxycnq0VLj1biwGXrm9wnZbxj+585r0S3xP6PmmbXl0vqRv4oW763SvpVfF82Zkp4zvDhEinbor0RZ2jurqlo1E2SRu7na3TPez4+mamygOpIXVT3J56jDo5cbWjunH2j64YJ/CxSeof9b3HkyWjTawD2RjTzT/HkyWNU0YLWno2sM35C63JlqvvYFz7iirGxMjK80JzuFARELim19TrasL3cz/ULYFi98r/7l/z09Iqa6Zsr6ondmtD3fJhQ4gwM82Rm6GZybKPkGSbu1K3ZLzZqZvafjYmIkQMYIVm4gvKzeMzIYQIu5k6x6ppKyRmFOU/OJ4sVepm7g+sSTWpW8GurlK5rukLKHzveqVuQpi2vL8IxhcfFFPV0mum+TekYRWS7RDZIFGnLxqW1dWN651cX9R+23Ngnnkl96ZhhY2dzc5Mj1MPX7rEbpz93Le9Ynou+E2wJ/dnQTxSVd0K4x0XdXtz+SzH8pyF3MxUfV7Vo8qUW2P6gX/qptu9kl1t4Oxzi934WJdpXaFfnq3zvmWjbll6PsYWH6DWoW5shYTnR/J4EEdRZidrf/JEWTc2+A5aSd2Mqwqpk+UVtKuJWFmN/axa8WGCWt3EKXzeduaVisrqVrgSov6uUvcHpVAeTyZMXVhFU5+XPFOy3JrSp07wbWaq2r3yv/vXY273yrJrpkLknMcLUtrFyYH05gEhJF0DVadPBwmbOB+BqsTlqH4uy1eKmf7QM+Ljc0LyDpctWunsNMSATum5S/wbISSbYzLremkv5502srH/eTLN16zz5kjvlSehy7XwjcVWIP9WUNVXNSPLcp5e0UKXl39ny+i6/NnSi78IpRkuewvz5tOVkLOpUXjHlii3hvTZXT6uKrjYt5e/VXBdpQItvdqjd6RVb4TsFT1/I8TeyH1TN7BGKtfQ+8AGX6brP718m9fZvr2M3UBwD7l36kaNhLqBoPdsW92Ojo5s5A8EQbBvNInleDym6lavoAIAALQAU+zGqlvnMgyCIOhEqBsIgn4yV7cgEJUO6gaC4O4yUbQgCKBuIAj6xOAhlTaoGwiCPjFgIVyDuoEguLtE7AaCoJ/EczcQBP0k1kxBEPSTeN8NBEE/CXUDQdBPQt1AEPSTwdgIqm7mNAAAAD1EcAQAAOAjgq7lFQAAoBFY7c0LgiC4c4S6gSDoJ6FuIAj6SagbCIJ+suZ/QtMEOvcRCIK7yB2I3Y7wf7lAEHTnDqjbeDzuOny0QueOAkGQ5W6o206EbzthJAjuD3N1C6NYyWEosmUTleo2m81ms9ktj+vrjx26ksaY3TYnCIIZOXWLYpIwIqGGZnUTNomT94wrQaW6RVEsTAw3m00YRR26cldiTBDcE5piNzlqG4bxcFhJ3QI9dHma1W273cY/SfyTfPr2KwyhbiAIJsw1hY2G5vN5djybzejBy8tLFMXDYajNK1Uog3ixKqY7FmhQt6enpziO5/P5p2+/oiiuqG4GG2yCUKgbCPaKanXLFI0Qcnt7S6Vtu91GUXx4eKjOqEi/sjN1xW5RHN/e3kZRfH39kdJJ3WSDlQf21kLdQLBXzEfp9fXHp6en+Xw+40EVhD6zN6ubPOyV6lZ4LNDyudunb7+SIC6OozherVbFlefljP00WwV1A8H+k1M3ZewWRfF2u6WPt66vP+rULclOE/WwCeqK3X78+LHZbDabTRyTT99+ffr2i7V5OAxtBE5pfDlroW4g2CsWzExfXl5ub2+zJ/dmdTMoVJX0OnVbrVZcgBnHVNhIFEZRPJ/PDQJXKLhmC6FuINh/5qP0/Pw8jmMqFtkjLfqZPduKoqhwZprN75RiYYYyZ8uZaaJuhBBCVqvVMAyHw9ByDcRwCbEbCO4oOXVjZ3Z0GWG73V5ff4x/Ejr7Oz8/N+gFl2/R2sKD6jmXkgZ1o0HlZrOJf6bqFoUkDAkhYTSMongYFluL2A0EvaRa3ehsNHvWlj3YKlQ3NnZjTwppdAdKmtWNSlv8k7DR3Ha7Xa1WUWx6f0Vn3gNiNxD0gpy6ZSuk7GyULpWep9DphTDmdaGQTvXKzUwzaYvjVN3CkITDHz9+hNGwUN0C1SRaZ0m5GBMEwa7Iqdvh4eFwGAqf7AGFVb5l36uQWaxuMQnjYbbmu9lsnp6eZrOZ/bvH5kuWwSbUDQR7xV3dI4SuitJ3eikTdQuHJBzO5/NhODSom81jwQdJ3QwndXaCINgVd1jdhmH47t27YRhSUnVL3uZNZ9YlnrvpHh0K81aoGwj2nLuqbjKplsnsm50gCLZDf9Stc+6KnSC4J9wZdSMAAAAu2AF1A0EQLMFgDAAA4COCIwAAAB/R4H9rPtq1h2U7ZzAAAAYEpJl/4zRmlgI6n367GgwAgAeAukHdAMBP7LC6GX5BBXUDAKATdfvnz+CPC4v9hcxbd1irW1Ic1A0A9godqNvd+9/+/Lc4ENNd0m3UYdrI6N8/grf/QN0AYK/QvrqpI6mK6la0I9vnv34vCN+gbgDgGVpXN00YZVY35eYcNvsUZbx4G8gBI9QNADxG2+p29/63V+8/PxgfugmP3gTB0s1M2QTypaxcqBsA7Ak6UzelKpnP26ibLgaEugHAvqHX6qZMoAvrzDEg1A0A9g3dP3czxGLmZMI81LywgOduALBv6HjNVLfuaV4icE+DNVMA2Dt0+b6bQZ4K3/ZQ3q6dmeJ9NwDYP3T2WwVdqGVYM5WTGcSOOYnfKgDAPmKHf2fanMEAAHiAgBDS0MaYmVg0lH/tgLoBgE8IKu5+aQYhpNH8a0fXzQEAQG1o/L/GyK+q9fmz6+YAAKA2NDikj46OHhZfv+8OgqDBfdgBAGgZibo19JCexkRdq5YtELsBgE9oXN26liwHIHYDAJ+A2C0HYjcA8AkGdbN6CbZ07Hb+Nn0l9+15mxJmAGI3APAJSnX7/NfvVHhqUDdl7PZl9CoVNeawayB2AwCf0FnsluHL6NWr0ZcWxKsQiN0AwCc0rm5Fz90QuwEA0Ag6jt2+jF4FPYncELsBgF/oMnbrlbR9R+wGAH6hs9itb9L2HbEbAPiFjmK387c9ehMkBWI3APAJ3cRu+ctuQRAEfYnhELsBgE/AbxVyIHYDAJ+A35nmQOwGAD4BsVsOxG4A4BMSdWtoI2/EbgAAdIXgYfG1uY28EbsBANAVGt95/KHrzcSdPrtuDgAAagPGMwAAfgLqBgCAn4C6AQDgJ6BuAAD4CagbAAB+4n/VjViO6YoHQAAAAABJRU5ErkJggg==" alt="" />
查看指定分区内的数据
--查看某个分区表里存放的数据
SELECT *
FROM shop
WHERE $PARTITION.RangeTime(CreateTime) = 1
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAARcAAAA+CAIAAACOZcjJAAAGsUlEQVR4nO2dPZLiPBCGdSEoYqLvClTBFcgJWNK5AQRTyyXI2PIZJqSmJvNh/AUWtqw/d1s/lnv6ra4to2nJEtZDS8a9iJ/X18/r6+Pj4z8WizVJQqWoSaaIjSftZ2ZRGgsxoS6NTlH7Mq6piJbT1OxGaSzEDBtUmKIiLtXsnWFTjSlajFEaCzFbFEXP02Z9qtoD0evwiW9q2MjhU2kca8/TRqwuT6OT2d6W11d1XkHejQl23wtd+2uKi75oWyxF/Ux9XNbOqeOeeddDN/Wfp43Y3YMoEqKrm52i6rzqz/66HrAggTp8PYjdPfEAl2sEKPJd1/GmAI2M2PO0WZ8u+/fczU3R47JWIuHU/iMoYvNemsVS5L7G7lj0uKzF5vzQGr/sh+uiftW3u0uf3WGtlHSdMfqmroXeK0ZZd3O+XuTBY3gWHw/2sVgZ6M+1uxuNDzv2aHsi9KWy1hMjFgUPh5LRoMj5eezdkb8nUHuxn6eN0OJJv1asziuxv6pbIFnyGmBj3191064/0ftAnkVZW7rDAo4i2U9v4xr/PmcbRWHDoWQ0KJoQixT73InBZDKnl6OkD1Bt4fWgBaXuM98WrJTpqMr5+Y2MRZbbMOrnhb1jzp5YY1HQcCgZCYom7IsGdj1odxeAFBmdqc6rzX63WZ8q7e7FyLQDbTkQ+6IBGFrj3o45e4Ki6NftoAhQNOUeXb8ee7ljkX1FJ6eIuaL7eX21t8iEpOg9mbT29QOl/94piLhHd1YXaVrj7o75egKmCDwcSrZYipRFw7Tvi5RNtrYws52onyirQYlWUZnT6nc4Xoq+JHtj6x/E90Um2ErjesekQzvdXT2BUwQdDiVbFEWzNvXzmnm7zM8uFGtMEcaYIjabMUWLMUpjIWahFH2kUdenopqaXZTGQkzTKUqqpmkKbGp2URoLMU2kKHWgFEJE/JeNLalNpwheE6W28e9IStfP/KI0FkoKpSg6013jQogoFAkhkr17ucUUlalyKYqC0DfHIlZ6lUtRhlgk3NLcPC9ziikqUykoCkrqgsWiv3ux/wujyDNCFw9quelTMEXVURwr5UWrrghS0hjVu7+hnM3+QFo23ed19lRXFZeiLmknAkWOWPTvj3yUDUpRSCwaLYS/d1Hkvlr1bWtc/+2tlkfHCliitif/9D5COZv98Thbqpfh7Kk+FMciX7kwgpJZklPwWKRe9vq2PVagEltL8hDlbPmDx9lZfW5nT/WhyqXIEYvQFPljkb9cY0bMvUFCrOj60FHftmJ7q0Elb2nMoJ3N/ridbdVlxQTOiG54qmsql6I8sWh0Rac6uw6yadK+aHs8yhkAKWllnUAoZ7M/LufAuZ7OmQJFGWLRYGw2NytajW11l0coitRSbQa4SiQnx8o/gcDOTJFF1GLRYGwOijzHC6Govm3NuwFjJb4tAdyZ90UWkYpFnuVcF3n89xJKpqif6dVRvLcNoyW9jNtTKGezPz5nvkf3O2ORp0pSTdoXLfH7or7irM7zfF8UweZ6js5FkRadRqskFepqsbKpXIqiIPSdbF+UH6GGKSpV5VKUORYtQkxRmQqlKFH+bf5YtAhRGgslBVEUkGA7Io5FVjFFZSqIotQmOF2cbSE2nSI8tCDFbTxdP/OL0lgoKZSi6ExHR5TSzKM0FkpiipYkSmOhJKZoRMKtWD2EiykqU5Ep6n+LYeqPUQMpMp9Kxo7Qg4cKiYuWIikaeQKoS0Dt3rp0D/WgnDljvAdA+V0g388KRaCovm1FKEX62PAPrUKajSv3WOrxjPHB86Tv9DbNR21PfxDTOEUsZ34a1QVDdV4Nfn44JkX1basninnkaQpCiIcuyNnjCh6LtNwYLRc0eRI4ypkzIxwwpIxF1VHLDPPLTxHq2FU3mxArOkuCt5q0eqzsPlKBiXcoZ1t1zhjXfyYxLkWWt8yv8Fi0hBVdq5GM8fc6q3/nEiWBo5w519VCUQhCoxSp6+48scjlP4tQFKmlMs/OvcqfkATOGeOdIlMUiNAYRd2eVQoCUmAs0vyB71QiTaJI3lXwzok6chI4ypn3RQMGPnch/58jdF/UNE3iWKQW+gXpQETBKarNBO/hLqjlKlUSOMqZ79GpACg/3C2EEMnu0QGGBR6hGPteyOo8lybtiyz54RmSwFHOnDEeFHkmUwTXaFPwqFI8Rax59Hsp0lZlkNUaU8Sy6vdStERRGgslhVKULmN8lhEWLkpjoaQgigJSwkfEFFlFaSyUFEQRGxvbD/KjbUARElcWi9U0TBGLFS6miMUKFVPEYoXqf5CJr6wNfzJyAAAAAElFTkSuQmCC" alt="" />
查看某个分区里,记录的个数
--查看某个分区表的个数
SELECT $PARTITION.RangeTime(CreateTime) AS 分区编号 ,
COUNT(id) AS 记录数
FROM shop
GROUP BY $PARTITION.RangeTime(CreateTime)
aaarticlea/png;base64,iVBORw0KGgoAAAANSUhEUgAAAJoAAABQCAIAAABu7vuSAAAEPElEQVR4nO2dQW7jMAxFdaEEWWeVKxRIr5B9F5lsc4NmEbSXyK4Dn2GWg0F2OYxnkdp1Y4miKNKmVH4IRTrIyF98Ih0rHIzbmCqS22w2rZhEJxeVTudRV584r3//sI/j8dhfXmJ+uaHT+dCV4SzeuXaczjnva/wY/y3vPM4nmnOMT+/lQsbwM5eNMxSUYWiGL4DwIakjnYcuGmU8/nX8s1Sc0RAnBQiejRcnktbPyk4kTuBtD1sbzk5McBlxRsmNzUS96cUZcuzdraEtPFx5NJoszjF55t06wCYDFlsGTjifAIrjpcJBTAouxjl8Ue9U8J+PiZaHM7Tah5XAvwK8vXEBwpSDM2lRoVwEbNeJM0ToYY+H4pLEMh/n0MO46sDrLRgnMh0xYOBCmlRpkTjhGa5gznlt/AicSZsaWbXgnYHBGa3noboKvCHqWTVOJCeYh3drT4ATMDwuDF7DoXcWmZ3eSuilhayT3mqG2QcEnIBJ5IXgGhvyphen8qHTeQLOo4z6ywvNLyedzlE4RdW2rfQlhKTTeRyndJWAP3xq/qlwoHDCbyLrPvm/MuWcEwoLWQk42ffRvdbfd/rcaCiS2+VkqcA5NxeiLDstO2WVifP12T29y2bn29Zt3yYClCYgO5tdd3Cwa5iJgSLjvByWd78MOAPZ+fvX6n4JpThDsbud1h3FwctJZNlJF+beeTut16cbDyuEVOAE7516cSLunZadj9KLM5qdt9PaTZmbSnBWmZ3Ts2yV4ASDphcnkJ2zsGyV4KwtO5vd1A8onVTgBIOmF2coO78eOp1zbtIszcSZNexUiF0qcM7NhSg7s7XslFUCTqFmCMtORmFxZnQ7RGTZySgsTumhoVOkjv4SFE6+DfRNopNLS6HzBJzs+6i/d06yUn4pdG446VLo3HDSpdA5Hef7tjvF2r4K4ZyrRQOpWOya3eS+iTib/aKjeDks3fOZH+eMLRpIhWN3O63n2YYMxbbZL1b7i2ixnbhFA6l6snMwpLJzoOKy864CcTb7hVu+NJIfheb6Kjiq2nDmsETiVMuyrQxnJksMTs0s26pwnp9yGqZROOdr0UCqHpxfD53OOeckPtnO2KKBVD04WYadCrHLcNKl0LnhpEuh8wSccs0lk6yUXwqdY3FmdI9EpDAoSCl0jsVpo5SBwsm3gb7JspNXCTjZ95HdO9llOOlS6Nxw0qXQOR1nf85H+7ITg7M/59N5dBuLXUGHfOen7usU+r8JjB/Bfx7UzhAXjMKxK7i55HJYLg4fosVWZ29JTdnZj4+XlVB29lLaW1Idzma/EL13tl3Z0gizPpxdsbXWL6+KxGmNmSGVg9PaptuacF4Hz5201MRkZ//cqTA128pw5g87FWKX4aRLoXPDSZdC5wk4rbnkQQqdY3FmdI9EpDAoSCl0jsVpo4gR5e02sf8HyVSQDGdVMpxV6T/ofdeHt5fCxQAAAABJRU5ErkJggg==" alt="" />
当数据量达到一定指数时,我们必须要进行调整,而选择哪种方法是靠技术决策人的,我们每个开发人员都应该把自己当成是技术的决策人,对自己的代码和自己的人生负责!
感谢您的阅读!