网上有篇关于hive的partition的使用讲解的比较好,转载了: 一、背景 1、在Hive Select查询中一般会扫描整个表内容,会消耗很多时间做没必要的工作。有时候只需要扫描表中关心的一部分数据,因此建表时引入了partition概念。 2、分区表指的是在创建表时指定
网上有篇关于hive的partition的使用讲解的比较好,转载了:
一、背景
1、在Hive Select查询中一般会扫描整个表内容,会消耗很多时间做没必要的工作。有时候只需要扫描表中关心的一部分数据,因此建表时引入了partition概念。
2、分区表指的是在创建表时指定的partition的分区空间。
3、如果需要创建有分区的表,需要在create表的时候调用可选参数partitioned by,详见表创建的语法结构。
二、技术细节
1、一个表可以拥有一个或者多个分区,每个分区以文件夹的形式单独存在表文件夹的目录下。
2、表和列名不区分大小写。
3、分区是以字段的形式在表结构中存在,通过describe table命令可以查看到字段存在,但是该字段不存放实际的数据内容,仅仅是分区的表示。
4、建表的语法(建分区可参见PARTITIONED BY参数):
CREATE [EXTERNAL] TABLE [IF NOT EXISTS] table_name [(col_name data_type [COMMENT col_comment], ...)] [COMMENT table_comment] [PARTITIONED BY (col_name data_type [COMMENT col_comment], ...)] [CLUSTERED BY (col_name, col_name, ...) [SORTED BY (col_name [ASC|DESC], ...)] INTO num_buckets BUCKETS] [ROW FORMAT row_format] [STORED AS file_format] [LOCATION hdfs_path]
5、分区建表分为2种,一种是单分区,也就是说在表文件夹目录下只有一级文件夹目录。另外一种是多分区,表文件夹下出现多文件夹嵌套模式。
a、单分区建表语句:create table day_table (id int, content string) partitioned by (dt string);单分区表,按天分区,在表结构中存在id,content,dt三列。
b、双分区建表语句:create table day_hour_table (id int, content string) partitioned by (dt string, hour string);双分区表,按天和小时分区,在表结构中新增加了dt和hour两列。
表文件夹目录示意图(多分区表):
6、添加分区表语法(表已创建,在此基础上添加分区):
ALTER TABLE table_name ADD partition_spec [ LOCATION 'location1' ] partition_spec [ LOCATION 'location2' ] ... partition_spec: : PARTITION (partition_col = partition_col_value, partition_col = partiton_col_value, ...)
用户可以用 ALTER TABLE ADD PARTITION 来向一个表中增加分区。当分区名是字符串时加引号。例:
ALTER TABLE day_table ADD PARTITION (dt='2008-08-08', hour='08') location '/path/pv1.txt' PARTITION (dt='2008-08-08', hour='09') location '/path/pv2.txt';
7、删除分区语法:
ALTER TABLE table_name DROP partition_spec, partition_spec,...
用户可以用 ALTER TABLE DROP PARTITION 来删除分区。分区的元数据和数据将被一并删除。例:
ALTER TABLE day_hour_table DROP PARTITION (dt='2008-08-08', hour='09');
8、数据加载进分区表中语法:
LOAD DATA [LOCAL] INPATH 'filepath' [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]
例:
LOAD DATA INPATH '/user/pv.txt' INTO TABLE day_hour_table PARTITION(dt='2008-08- 08', hour='08'); LOAD DATA local INPATH '/user/hua/*' INTO TABLE day_hour partition(dt='2010-07- 07');
当数据被加载至表中时,不会对数据进行任何转换。Load操作只是将数据复制至Hive表对应的位置。数据加载时在表下自动创建一个目录,文件存放在该分区下。
9、基于分区的查询的语句:
SELECT day_table.* FROM day_table WHERE day_table.dt>= '2008-08-08';
10、查看分区语句:
hive> show partitions day_hour_table; OK dt=2008-08-08/hour=08 dt=2008-08-08/hour=09 dt=2008-08-09/hour=09
三、总结
1、在 Hive 中,表中的一个 Partition 对应于表下的一个目录,所有的 Partition 的数据都存储在最字集的目录中。
2、总的说来partition就是辅助查询,缩小查询范围,加快数据的检索速度和对数据按照一定的规格和条件进行管理。
——————————————————————————————————————
hive中关于partition的操作:
hive> create table mp (a string) partitioned by (b string, c string);
OK
Time taken: 0.044 seconds
hive> alter table mp add partition (b='1', c='1');
OK
Time taken: 0.079 seconds
hive> alter table mp add partition (b='1', c='2');
OK
Time taken: 0.052 seconds
hive> alter table mp add partition (b='2', c='2');
OK
Time taken: 0.056 seconds
hive> show partitions mp ;
OK
b=1/c=1
b=1/c=2
b=2/c=2
Time taken: 0.046 seconds
hive> explain extended alter table mp drop partition (b='1');
OK
ABSTRACT SYNTAX TREE:
(TOK_ALTERTABLE_DROPPARTS mp (TOK_PARTSPEC (TOK_PARTVAL b '1')))
STAGE DEPENDENCIES:
Stage-0 is a root stage
STAGE PLANS:
Stage: Stage-0
Drop Table Operator:
Drop Table
table: mp
Time taken: 0.048 seconds
hive> alter table mp drop partition (b='1');
FAILED: Error in metadata: table is partitioned but partition spec is not specified or tab: {b=1}
FAILED: Execution Error, return code 1 from org.apache.hadoop.hive.ql.exec.DDLTask
hive> show partitions mp ;
OK
b=1/c=1
b=1/c=2
b=2/c=2
Time taken: 0.044 seconds
hive> alter table mp add partition ( b='1', c = '3') partition ( b='1' , c='4');
OK
Time taken: 0.168 seconds
hive> show partitions mp ;
OK
b=1/c=1
b=1/c=2
b=1/c=3
b=1/c=4
b=2/c=2
b=2/c=3
Time taken: 0.066 seconds
hive>insert overwrite table mp partition (b='1', c='1') select cnt from tmp_et3 ;
hive>alter table mp add columns (newcol string);
location指定目录结构
hive> alter table alter2 add partition (insertdate='2008-01-01') location '2008/01/01';
hive> alter table alter2 add partition (insertdate='2008-01-02') location '2008/01/02';

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