在Hive中查询语句往往都要被解析成MapReduce的job进行计算，但是有两个查询语句是不走MapReduce的，如下：
1.查询某张表的所有数据
select * from employees;
结果显示如下：
hive> select * from employees;
OK
lavimer 15000.0 ["li","lu","wang"] {"k1":1.0,"k2":2.0,"k3":3.0} {"street":"dingnan","city":"ganzhou","num":101}
liao 18000.0 ["liu","li","huang"] {"k4":2.0,"k5":3.0,"k6":6.0} {"street":"dingnan","city":"ganzhou","num":102}
zhang 19000.0 ["xiao","wen","tian"] {"k7":7.0,"k8":8.0,"k8":8.0} {"street":"dingnan","city":"ganzhou","num":103}
Time taken: 0.176 seconds
hive>
从上述语句中我们可以发现这个查询语句并没有走MapReduce。
2.抽样查询
select * from employees limit 2;
注：在MYSQL中limit是取前几条记录，但是在Hive中，limit是抽样，会随机返回对应的记录数。
结果显示如下：
hive> select * from employees limit 2;
OK
lavimer 15000.0 ["li","lu","wang"] {"k1":1.0,"k2":2.0,"k3":3.0} {"street":"dingnan","city":"ganzhou","num":101}
liao 18000.0 ["liu","li","huang"] {"k4":2.0,"k5":3.0,"k6":6.0} {"street":"dingnan","city":"ganzhou","num":102}
Time taken: 0.079 seconds
hive>
从上述语句中我们可以发现这个查询语句并没有走MapReduce。