很多时候，我们需要将Hive的查询（select）结果保存起来，方便进一步处理或查看。
在Hive里面提供了不同的方式来保存查询结果，在这里做下总结：

一、保存结果到本地

这个方法最为常见，笔者也经常使用。sql的查询结果将直接保存到/tmp/out.txt中

$ hive -e "select user, login_timestamp from user_login" > /tmp/out.txt

 

当然我们也可以查询保存到某个文件file.sql中，按下面的方式执行查询，并保存结果

$ hive -f file.sql > /tmp/out.txt

 下面是file.sql的内容：

$ cat file.sql

select user, login_timestamp from user_login

 

hive客户的的详细使用方法可以参考hive的官方文档《 Hive Batch Mode Commands》

hive -e '<query-string>' executes the query string.
hive -f <filepath> executes one or more SQL queries from a file.

 

方法2：使用INSERT OVERWRITE LOCAL DIRECTORY结果到本地

hive> insert overwrite local directory "/tmp/out/"                                        
    > select user, login_time from user_login;

上面的命令会将select user, login_time from user_login的查询结果保存到/tmp/out/本地目录下。

我们查看一下/tmp/out/目录下的文件，发现命令执行后，多了两个文件：

$ find /tmp/out/ -type f
/tmp/out/.000000_0.crc
/tmp/out/000000_0

这两个文件存放的内容不一样，其中000000_0存放查询的结果，带有crc后缀的存放那个文件的crc32校验。

用vim打开查看下000000_0的内容：

vim /tmp/out/000000_0
 1 user_1^A20140701
 2 user_2^A20140701
 3 user_2^A20140701

可以看到，导出的查询结果字段之间是用^A（Ctrl+A）作为分割符，行与行之间用\n作为分割。

默认的字段分割符有时候可能不太方便，幸好Hive提供了修改分割符号的方法，我们只要在导出时指定就可以了：

hive> insert overwrite local directory "/tmp/out/"
    > row format delimited fields terminated by "\t" > select user, login_time from user_login;

$ vim /tmp/out/000000_0
1 user_1 20140701
2 user_2 20140701 3 user_2 20140701 

可以看到字段分割符已经变成了tab（人眼看起来更舒服^-^）。

同样，我们也可以指定复杂类型(collection、map)的输出格式

更多关于INSERT OVERWRITE LOCAL DIRECTORY的语法，可以参考HIVE的官方文档《Writing data into the filesystem from queries》。

Standard syntax:
INSERT OVERWRITE <span style="color:#ff0000;">[LOCAL] </span>DIRECTORY directory1 [ROW FORMAT row_format] [STORED AS file_format] (Note: Only available starting with Hive 0.11.0) SELECT ... FROM ... Hive extension (multiple inserts): FROM from_statement INSERT OVERWRITE [LOCAL] DIRECTORY directory1 select_statement1 [INSERT OVERWRITE [LOCAL] DIRECTORY directory2 select_statement2] ... row_format : 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)

二、保存结果到hdfs

如果结果表已经建好，可以使用INSERT OVERWRITE TABLE将结果写入结果表：

hive> desc query_result;
OK
user                	string,

login_time          	bigint
hive> insert overwrite table query_result     
    > select user, login_time from user_login;

hive> select * from query_result;             
OK
user_1	20140701
user_2	20140701
user_3	20140701

当然，HIVE也提供了追加方式INSERT TABLE，可以在原有数据后面加上新的查询结果。在上面这个例子基础上，我们再追加一个查询结果：

hive> insert into table query_result
    > select * from query_result;

hive> select * from query_result;
OK
user_1	20140701
user_2	20140701
user_3	20140701
<span style="color:#ff0000;">user_1	20140701
user_2	20140701
user_3	20140701</span>

注意标红的部分，使用INSERT TABLE后，query_result增加了三行数据

更多关于INSERT OVERWRITE TABLE的语法，可以参考HIVE官方文档《Inserting data into Hive Tables from queries》

Standard syntax:
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; Hive extension (multiple inserts): 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] ...; Hive extension (dynamic partition inserts): 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;

方法2、如果需要新建一个表，用于存放查询结果，可以使用CREATE TABLE AS SELECT语法

hive> create table query_result 
    > as
    > select user, login_time from user_login; 

hive> select * from query_result;            
OK
user_1	20140701
user_2	20140701
user_3	20140701

更多关于CREATE TABLE AS SELECT的语法，可以参考HIVE官方文档《 Create Table As Select (CTAS)》

CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name (Note: TEMPORARY available starting with Hive 0.14.0) [(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] [SKEWED BY (col_name, col_name, ...) ON ([(col_value, col_value, ...), ...|col_value, col_value, ...]) [STORED AS DIRECTORIES] (Note: Only available starting with Hive 0.10.0)] [ [ROW FORMAT row_format] [STORED AS file_format] | STORED BY 'storage.handler.class.name' [WITH SERDEPROPERTIES (...)] (Note: Only available starting with Hive 0.6.0) ] [LOCATION hdfs_path] [TBLPROPERTIES (property_name=property_value, ...)] (Note: Only available starting with Hive 0.6.0) [AS select_statement] (Note: Only available starting with Hive 0.5.0, and not supported when creating external tables.) CREATE [TEMPORARY] [EXTERNAL] TABLE [IF NOT EXISTS] [db_name.]table_name LIKE existing_table_or_view_name [LOCATION hdfs_path] data_type : primitive_type | array_type | map_type | struct_type | union_type (Note: Only available starting with Hive 0.7.0) primitive_type : TINYINT | SMALLINT | INT | BIGINT | BOOLEAN | FLOAT | DOUBLE | STRING | BINARY (Note: Only available starting with Hive 0.8.0) | TIMESTAMP (Note: Only available starting with Hive 0.8.0) | DECIMAL (Note: Only available starting with Hive 0.11.0) | DECIMAL(precision, scale) (Note: Only available starting with Hive 0.13.0) | VARCHAR (Note: Only available starting with Hive 0.12.0) | CHAR (Note: Only available starting with Hive 0.13.0) array_type : ARRAY < data_type > map_type : MAP < primitive_type, data_type > struct_type : STRUCT < col_name : data_type [COMMENT col_comment], ...> union_type : UNIONTYPE < data_type, data_type, ... > (Note: Only available starting with Hive 0.7.0) row_format : 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) | SERDE serde_name [WITH SERDEPROPERTIES (property_name=property_value, property_name=property_value, ...)] file_format: : SEQUENCEFILE | TEXTFILE | RCFILE (Note: Only available starting with Hive 0.6.0) | ORC (Note: Only available starting with Hive 0.11.0) | AVRO (Note: Only available starting with Hive 0.14.0) | INPUTFORMAT input_format_classname OUTPUTFORMAT output_format_classname

四、使用hdfs直接导出表