HIVE表数据的导入与导出(load data&insert overwrite)

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1. 准备测试数据

首先创建普通表:

create table test(id int, name string) ROW FORMAT DELIMITED FIELDS TERMINATED BY ‘,‘ STORED AS TEXTFILE;

创建分区表:

CREATE EXTERNAL TABLE test_p(
id int,
name string 
)
partitioned by (date STRING)
ROW FORMAT DELIMITED FIELDS TERMINATED BY ,LINES TERMINATED BY 
STORED AS TEXTFILE;

准备数据文件:

[/tmp]# cat test.txt 
1,a
2,b
3,c
4,d

2.加载数据

语法如下:

LOAD DATA [LOCAL] INPATH ‘filepath‘ [OVERWRITE] INTO TABLE tablename [PARTITION (partcol1=val1, partcol2=val2 ...)]

说明:

  • filepath 可能是:
  • 一个相对路径
  • 一个绝对路径,例如:/root/project/data1
  • 一个url地址,可选的可以带上授权信息,例如:hdfs://namenode:9000/user/hive/project/data1
  • 目标可能是一个表或者分区,如果该表是分区,则必须制定分区列。
  • filepath 可以是一个文件也可以是目录
  • 如果指定了 LOCAL,则:
  • load 命令会在本地查找 filepath。如果 filepath 是相对路径,则相对于当前路径,也可以指定一个 url 或者本地文件,例如:file:///user/hive/project/data1
  • 如果没有指定 LOCAL ,则hive会使用全路径的url,url 中如果没有制定 schema,则默认使用 fs.default.name的值;如果该路径不是绝对路径,则会相对于 /user/<username>
  • 如果使用 OVERWRITE ,则会删除原来的数据,然后导入新的数据,否则,就是追加数据。

需要注意的:

  • filepath 中不能包括子目录
  • 如果没有指定 LOCAL,则 filepath 指向目标表或者分区所在的文件系统。
  • 如果需要压缩,则参考 CompressedStorage

2.1 测试

2.1.1 加载本地文件

a) 加载到普通表中

hive> load data local inpath ‘/tmp/test.txt‘ into table test;                              
Copying data from file:/tmp/test.txt
Copying file: file:/tmp/test.txt
Loading data to table default.test
Table default.test stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 16, raw_data_size: 0]
OK
Time taken: 0.572 seconds

查看hdfs上的数据:

$ hadoop fs -ls /user/hive/warehouse/test
Found 1 items
-rwxrwxrwt   3 hive hadoop         16 2014-06-09 18:36 /user/hive/warehouse/test/test.txt

查看表中数据:

hive> select * from test;
OK
1	a
2	b
3	c
4	d
Time taken: 0.562 seconds, Fetched: 4 row(s)

b) 加载文件到分区表

通常是直接使用 load 命令加载:

LOAD DATA LOCAL INPATH "/tmp/test.txt" INTO TABLE test_p PARTITION (date=20140722)

注意:如果没有加上 overwrite 关键字,则加载相同文件最后会存在多个文件

还有一种方法是:创建分区目录,手动上传文件,最后再添加新的分区,代码如下:

hadoop fs -mkdir  /user/hive/warehouse/test/date=20140320
ALTER TABLE test_p ADD IF NOT EXISTS PARTITION (date=20140320);

hive hadoop fs -rm /user/hive/warehouse/test/date=20140320/test.txt
hadoop fs -put /tmp/test.txt  /user/hive/warehouse/test/date=20140320

同样,你也可以查看 hdfs 和表中的数据。

2.1.2 加载hdfs上的文件

拷贝 test.txt 为test_1.txt 并将其上传到 /user/hive/warehouse:

$ cp test.txt test_1.txt
$ sudo -u hive hadoop fs -put test_1.txt /user/hive/warehouse

然后将 /user/hive/warehouse/test_1.txt 导入到test表中:

hive> load data inpath ‘/user/hive/warehouse/test_1.txt‘ into table test; 
Loading data to table default.test
Table default.test stats: [num_partitions: 0, num_files: 1, num_rows: 0, total_size: 16, raw_data_size: 0]
OK
Time taken: 2.941 seconds

查看hdfs上的数据:

$ hadoop fs -ls /user/hive/warehouse/test
Found 2 items
-rwxr-xr-x   3 hive hadoop         16 2014-06-09 18:48 /user/hive/warehouse/test/test.txt
-rwxr-xr-x   3 hive hadoop         16 2014-06-09 18:45 /user/hive/warehouse/test/test_1.txt

查看表中数据:

hive> select * from test;                                                 
OK
1	a
2	b
3	c
4	d
1	a
2	b
3	c
4	d
Time taken: 0.302 seconds, Fetched: 8 row(s)

3. 插入数据

标准语法:

INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1 FROM from_statement;

INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1 FROM from_statement;

扩展语法(多个insert):

FROM from_statement
INSERT OVERWRITE TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...) [IF NOT EXISTS]] select_statement1
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2]
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2] ...;

FROM from_statement
INSERT INTO TABLE tablename1 [PARTITION (partcol1=val1, partcol2=val2 ...)] select_statement1
[INSERT INTO TABLE tablename2 [PARTITION ...] select_statement2]
[INSERT OVERWRITE TABLE tablename2 [PARTITION ... [IF NOT EXISTS]] select_statement2] ...;

扩展语法(动态分区insert):

INSERT OVERWRITE TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;

INSERT INTO TABLE tablename PARTITION (partcol1[=val1], partcol2[=val2] ...) select_statement FROM from_statement;

说明:

Dynamic Partition Inserts

dynamic partition inserts在hive 0.6.0中引入。相关的配置参数有:

hive.exec.dynamic.partition
hive.exec.dynamic.partition.mode
hive.exec.max.dynamic.partitions.pernode
hive.exec.max.dynamic.partitions
hive.exec.max.created.files
hive.error.on.empty.partition

一个示例:

FROM page_view_stg pvs
INSERT OVERWRITE TABLE page_view PARTITION(dt=‘2008-06-08‘, country)
       SELECT pvs.viewTime, pvs.userid, pvs.page_url, pvs.referrer_url, null, null, pvs.ip, pvs.cnt

4. 导出数据

标准语法:

INSERT OVERWRITE [LOCAL] DIRECTORY directory1
  [ROW FORMAT row_format] [STORED AS file_format] (Note: Only available starting with Hive 0.11.0)
  SELECT ... FROM ...

扩展语法(多个insert):

FROM from_statement
INSERT OVERWRITE [LOCAL] DIRECTORY directory1 select_statement1
[INSERT OVERWRITE [LOCAL] DIRECTORY directory2 select_statement2] ...

row_format相关语法:

DELIMITED [FIELDS TERMINATED BY char [ESCAPED BY char]] [COLLECTION ITEMS TERMINATED BY char]
        [MAP KEYS TERMINATED BY char] [LINES TERMINATED BY char]
        [NULL DEFINED AS char](Note: Only available starting with Hive 0.13)

说明:

  • Directory 可以是一个全路径的 url。
  • 如果指定 LOCAL,则会将数据写到本地文件系统。
  • 输出的数据序列化为 text 格式,分隔符为 ^A,行于行之间通过换行符连接。如果存在不是基本类型的列,则这些列将被序列化为 JSON 格式。
  • 在 Hive 0.11.0 可以输出字段的分隔符,之前版本的默认为 ^A

4.1 测试;

4.1.1 导出到本地文件系统

hive> insert overwrite local directory ‘/tmp/test‘ select * from test;
Total MapReduce jobs = 1
Launching Job 1 out of 1
Number of reduce tasks is set to 0 since there‘s no reduce operator
Starting Job = job_1402248601715_0016, Tracking URL = http://cdh1:8088/proxy/application_1402248601715_0016/
Kill Command = /usr/lib/hadoop/bin/hadoop job  -kill job_1402248601715_0016
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 0
2014-06-09 19:25:12,896 Stage-1 map = 0%,  reduce = 0%
2014-06-09 19:25:20,380 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 0.99 sec
2014-06-09 19:25:21,433 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 0.99 sec
MapReduce Total cumulative CPU time: 990 msec
Ended Job = job_1402248601715_0016
Copying data to local directory /tmp/test
Copying data to local directory /tmp/test
MapReduce Jobs Launched: 
Job 0: Map: 1   Cumulative CPU: 0.99 sec   HDFS Read: 305 HDFS Write: 32 SUCCESS
Total MapReduce CPU Time Spent: 990 msec
OK
Time taken: 18.438 seconds

导出后的数据预览如下:

[/tmp]# vim test/000000_0 
1^Aa
2^Ab
3^Ac
4^Ad
1^Aa
2^Ab
3^Ac
4^Ad

可以看到数据中的列与列之间的分隔符是^A(ascii码是0001),如果想修改分隔符,可以做如下修改:

hive> insert overwrite local directory ‘/tmp/test‘ row format delimited fields terminated by ‘,‘ select * from test;

再来查看数据:

vim test/000000_3 
1,a
2,b
3,c
4,d
1,a
2,b
3,c
4,d

4.1.2 导出到 HDFS 中

hive> insert overwrite  directory ‘/user/hive/tmp‘ select * from test;

注意:

和导出文件到本地文件系统的HQL少一个local,数据的存放路径不一样了。

4.1.3 导出到Hive的另一个表中

在实际情况中,表的输出结果可能太多,不适于显示在控制台上,这时候,将Hive的查询输出结果直接存在一个新的表中是非常方便的,我们称这种情况为CTAS( create table .. as select)如下:

hive> create table test2 as select * from test;

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