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<>摘要
MapJoin是Hive的一种优化操作，其适用于小表JOIN大表的场景，由于表的JOIN操作是在Map端且在内存进行的，所以其并不需要启动Reduce任务也就不需要经过shuffle阶段，从而能在一定程度上节省资源提高JOIN效率
<>使用
方法一：
在Hive0.11前，必须使用MAPJOIN来标记显示地启动该优化操作，由于其需要将小表加载进内存所以要注意小表的大小
SELECT /*+ MAPJOIN(smalltable)*/ .key,value FROM smalltable JOIN bigtable ON
smalltable.key= bigtable.key
方法二：
在Hive0.11后，Hive默认启动该优化，也就是不在需要显示的使用MAPJOIN标记，其会在必要的时候触发该优化操作将普通JOIN转换成MapJoin，可以通过以下两个属性来设置该优化的触发时机
hive.auto.convert.join
默认值为true，自动开户MAPJOIN优化
hive.mapjoin.smalltable.filesize
默认值为2500000(25M),通过配置该属性来确定使用该优化的表的大小，如果表的大小小于此值就会被加载进内存中
注意：使用默认启动该优化的方式如果出现默名奇妙的BUG(比如MAPJOIN并不起作用),就将以下两个属性置为fase手动使用MAPJOIN标记来启动该优化
hive.auto.convert.join=false(关闭自动MAPJOIN转换操作) hive.ignore.mapjoin.hint=false(
不忽略MAPJOIN标记)
对于以下查询是不支持使用方法二(MAPJOIN标记)来启动该优化的
select /*+MAPJOIN(smallTableTwo)*/ idOne, idTwo, value FROM ( select /*+MAPJOIN
(smallTableOne)*/ idOne, idTwo, value FROM bigTable JOIN smallTableOne on (
bigTable.idOne= smallTableOne.idOne) ) firstjoin JOIN smallTableTwo ON (
firstjoin.idTwo= smallTableTwo.idTwo)
但是，如果使用的是方法一即没有MAPJOIN标记则以上查询语句将会被作为两个MJ执行，进一步的，如果预先知道表大小是能够被加载进内存的，则可以通过以下属性来将两个MJ合并成一个MJ
hive.auto.convert.join.
noconditionaltask：Hive在基于输入文件大小的前提下将普通JOIN转换成MapJoin，并是否将多个MJ合并成一个 hive.auto.
convert.join.noconditionaltask.size：多个MJ合并成一个MJ时，其表的总的大小须小于该值，同时hive.auto.
convert.join.noconditionaltask必须为true
