几种保存Hive查询结果的方法_hive client sql直接存储到本地

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