索引是标准的数据库技术,hive0.7版本之后支持索引。Hive提供有限的索引功能,这不像传统的关系型数据库那样有"键(Key)"的概念,用户可以再某些列上创建索引来加速某些操作,给一个表创建的索引数据被保存在另外的表中。Hive的索引功能现在还相对较晚,提供的选项还较少。但是,索引被设计为可使用内置的可插拔的java代码来控制,用户可以扩展这个功能来满足自己的需求。当然不是说所有的查询都会受惠于Hive索引。用户可以使用EXPLAIN语法来分析HiveQL语句是否可以使用索引来提升用户查询的性能。像RDBMS中的索引一样,需要评估索引创建的是否合理,毕竟,索引需要更多的磁盘空间,并且创建维护索引也会有一定的的代价。用户必须要权衡从索引得到的好处和代价。
下面说说怎么创建索引:
1.先创建表:
hive> create table user( id int, name string) > ROW FORMAT DELIMITED > FIELDS TERMINATED BY '\t' > STORED AS TEXTFILE;
hive> load data local inpath '/export1/tmp/wyp/row.txt' > overwrite into table user;
hive> select * from user where id =500000; Total MapReduce jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Cannot run job locally: Input Size (= 356888890) is larger than hive.exec.mode.local.auto.inputbytes.max (= 134217728) Starting Job = job_1384246387966_0247, Tracking URL = http://l-datalogm1.data.cn1:9981/proxy/application_1384246387966_0247/ Kill Command=/home/q/hadoop/bin/hadoop job -kill job_1384246387966_0247 Hadoop job information for Stage-1: number of mappers:2; number of reducers:0 2013-11-13 15:09:53,336 Stage-1 map = 0%, reduce = 0% 2013-11-13 15:09:59,500 Stage-1 map=50%,reduce=0%, Cumulative CPU 2.0 sec 2013-11-13 15:10:00,531 Stage-1 map=100%,reduce=0%, Cumulative CPU 5.63 sec 2013-11-13 15:10:01,560 Stage-1 map=100%,reduce=0%, Cumulative CPU 5.63 sec MapReduce Total cumulative CPU time: 5 seconds 630 msec Ended Job = job_1384246387966_0247 MapReduce Jobs Launched: Job 0: Map: 2 Cumulative CPU: 5.63 sec HDFS Read: 361084006 HDFS Write: 357 SUCCESS Total MapReduce CPU Time Spent: 5 seconds 630 msec OK 500000 wyp. Time taken: 14.107 seconds, Fetched: 1 row(s)一共用了14.107s
4.对user创建索引:
hive> create index user_index on table user(id) > as 'org.apache.hadoop.hive.ql.index.compact.CompactIndexHandler' > with deferred rebuild > IN TABLE user_index_table; hive> alter index user_index on user rebuild; hive> select * from user_index_table limit 5; 0 hdfs://mycluster/user/hive/warehouse/table02/000000_0 [0] 1 hdfs://mycluster/user/hive/warehouse/table02/000000_0 [352] 2 hdfs://mycluster/user/hive/warehouse/table02/000000_0 [704] 3 hdfs://mycluster/user/hive/warehouse/table02/000000_0 [1056] 4 hdfs://mycluster/user/hive/warehouse/table02/000000_0 [1408] Time taken: 0.244 seconds, Fetched: 5 row(s)这样就对user表创建好了一个索引。
5.对创建索引后的user再进行测试:
hive> select * from user where id =500000; Total MapReduce jobs = 1 Launching Job 1 out of 1 Number of reduce tasks is set to 0 since there's no reduce operator Cannot run job locally: Input Size (= 356888890) is larger than hive.exec.mode.local.auto.inputbytes.max (= 134217728) Starting Job = job_1384246387966_0247, Tracking URL = http://l-datalogm1.data.cn1:9981/proxy/application_1384246387966_0247/ Kill Command=/home/q/hadoop/bin/hadoop job -kill job_1384246387966_0247 Hadoop job information for Stage-1: number of mappers:2; number of reducers:0 2013-11-13 15:23:12,336 Stage-1 map = 0%, reduce = 0% 2013-11-13 15:23:53,240 Stage-1 map=50%,reduce=0%, Cumulative CPU 2.0 sec 2013-11-13 15:24:00,253 Stage-1 map=100%,reduce=0%, Cumulative CPU 5.27 sec 2013-11-13 15:24:01,650 Stage-1 map=100%,reduce=0%, Cumulative CPU 5.27 sec MapReduce Total cumulative CPU time: 5 seconds 630 msec Ended Job = job_1384246387966_0247 MapReduce Jobs Launched: Job 0: Map: 2 Cumulative CPU: 5.63 sec HDFS Read: 361084006 HDFS Write: 357 SUCCESS Total MapReduce CPU Time Spent: 5 seconds 630 msec OK 500000 wyp. Time taken: 13.042 seconds, Fetched: 1 row(s)时间用了13.042s,这和没有建索引的效果差别不大。
在Hive创建索引还存在bug:如果表格的模式信息来自SerDe,Hive将不能创建索引:
hive> CREATE INDEX employees_index > ON TABLE employees (country) > AS 'org.apache.hadoop.hive.ql.index.compact.CompactIndexHandler' > WITH DEFERRED REBUILD > IDXPROPERTIES ('creator' = 'me','created_at' = 'some_time') > IN TABLE employees_index_table > COMMENT 'Employees indexed by country and name.'; FAILED: Error in metadata: java.lang.RuntimeException: \ Check the index columns, they should appear in the table being indexed. FAILED: Execution Error, return code 1 from \ org.apache.hadoop.hive.ql.exec.DDLTask这个bug发生在Hive0.10.0、0.10.1、0.11.0,在Hive0.12.0已经修复了,详情请参见: https://issues.apache.org/jira/browse/HIVE-4251