一、Sqoop Help
$ sqoop help
usage: sqoop COMMAND [ARGS]
Available commands:
codegen Generate code to interact with database records
create-hive-table Import a table definition into Hive
eval Evaluate a SQL statement and display the results
export Export an HDFS directory to a database table
help List available commands
import Import a table from a database to HDFS
import-all-tables Import tables from a database to HDFS
list-databases List available databases on a server
list-tables List available tables in a database
version Display version information
See 'sqoop help COMMAND' for information on a specific command.你可以使用sqoop help （tool-name）也可以使用sqoop （tool-name）--help来使用帮助。
例如： sqoop help import. sqoop import --help.
二、Sqoop的别名
例如：sqoop import --help 等同于 sqoop-import --help，即sqoop-import是sqoop import的别名。
三、sqoop-import
$ sqoop help import
usage: sqoop import [GENERIC-ARGS] [TOOL-ARGS]
Common arguments:
--connect <jdbc-uri> Specify JDBC connect string
--connect-manager <jdbc-uri> Specify connection manager class to use
--driver <class-name> Manually specify JDBC driver class to use
--hadoop-home <dir> Override $HADOOP_HOME
--help Print usage instructions
-P Read password from console
--password <password> Set authentication password
--username <username> Set authentication username
--verbose Print more information while working
[...]
Generic Hadoop command-line arguments:
(must preceed any tool-specific arguments)
Generic options supported are
-conf <configuration file> specify an application configuration file
-D <property=value> use value for given property
-fs <local|namenode:port> specify a namenode
-jt <local|jobtracker:port> specify a job tracker
-files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster
-libjars <comma separated list of jars> specify comma separated jar files to include in the classpath.
-archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines.
The general command line syntax is
bin/hadoop command [genericOptions] [commandOptions]其中Generic option的设置要在Common arguments之前，-conf，-fs，-jt-，-D都是对hadoop服务进行设置的，例如 -D mapred.job.name=<job_name>能够制定job的名字，如果不指定的话Job的名字将以用到的Jar包作为Job的名字。
例如：
User: hdfs
Job Name: cn_opda_a_phonoalbumshoushou_json_120901.jar
Job File: hdfs://vm-nba01.in.dx:9000/home/hdfs/tmp/mapred/staging/hdfs/.staging/job_201210171559_0391/job.xml
Submit Host: vm-nba01.in.dx
Submit Host Address: 10.18.102.101
Job-ACLs: All users are allowed
Job Setup: Successful
Status: Succeeded
Started at: Tue Oct 23 15:18:41 CST 2012
Finished at: Tue Oct 23 15:23:20 CST 2012
Finished in: 4mins, 39sec
Job Cleanup: Successful而files、libjars 、archives 选项则不具有代表性质，因为这些选项在Hadoop内部命令中已经被支持了，可以查看hadoop job的帮助。
[work@vm-nba01 ~]$ hadoop job
Usage: JobClient <command> <args>
[-submit <job-file>]
[-status <job-id>]
[-counter <job-id> <group-name> <counter-name>]
[-kill <job-id>]
[-set-priority <job-id> <priority>]. Valid values for priorities are: VERY_HIGH HIGH NORMAL LOW VERY_LOW
[-events <job-id> <from-event-#> <#-of-events>]
[-history <jobOutputDir>]
[-list [all]]
[-list-active-trackers]
[-list-blacklisted-trackers]
[-list-attempt-ids <job-id> <task-type> <task-state>]
[-kill-task <task-id>]
[-fail-task <task-id>]
Generic options supported are
-conf <configuration file> specify an application configuration file
-D <property=value> use value for given property
-fs <local|namenode:port> specify a namenode
-jt <local|jobtracker:port> specify a job tracker
-files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster
-libjars <comma separated list of jars> specify comma separated jar files to include in the classpath.
-archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines.
四、sqoop脚本
举例：
$ sqoop import --connect jdbc:mysql://localhost/db --username foo --table TEST下面把这些选项参数做成脚本进行传递：（import.txt）
$ sqoop --options-file /users/homer/work/import.txt --table TEST那么import.txt中的参数要按照行来进行分隔，内容如下：
#
# Options file for Sqoop import
#
# Specifies the tool being invoked
import
# Connect parameter and value
--connect
jdbc:mysql://localhost/db
# Username parameter and value
--username
foo
#
# Remaining options should be specified in the command line.
#举个sqoop连接数据库，将数据库内的数据导入到HDFS中的例子：
sqoop import --connect jdbc:mysql://database.example.com/employees \
--username aaron --password 12345这样连接例子需要把mysql driver的jar包放到你的环境Path中，否则请这样使用：
$ sqoop import --driver com.microsoft.jdbc.sqlserver.SQLServerDriver \
--connect <connect-string> ...sqoop-import控制参数：
usage: sqoop import [GENERIC-ARGS] [TOOL-ARGS]
Common arguments:
--connect <jdbc-uri> Specify JDBC connect
string
--connection-manager <class-name> Specify connection manager
class name
--connection-param-file <properties-file> Specify connection
parameters file
--driver <class-name> Manually specify JDBC
driver class to use
--hadoop-home <dir> Override $HADOOP_HOME
--help Print usage instructions
-P Read password from console
--password <password> Set authentication
password
--username <username> Set authentication
username
--verbose Print more information
while working
Import control arguments:
--append Imports data in append mode
--as-avrodatafile Imports data to Avro data files
--as-sequencefile Imports data to SequenceFiles
--as-textfile Imports data as plain text (default)
--boundary-query <statement> Set boundary query for retrieving max
and min value of the primary key
--columns <col,col,col...> Columns to import from table
--compression-codec <codec> Compression codec to use for import
--direct Use direct import fast path
--direct-split-size <n> Split the input stream every 'n' bytes
when importing in direct mode
-e,--query <statement> Import results of SQL 'statement'
--fetch-size <n> Set number 'n' of rows to fetch from
the database when more rows are needed
--inline-lob-limit <n> Set the maximum size for an inline LOB
-m,--num-mappers <n> Use 'n' map tasks to import in parallel
--split-by <column-name> Column of the table used to split work
units
--table <table-name> Table to read
--target-dir <dir> HDFS plain table destination
--warehouse-dir <dir> HDFS parent for table destination
--where <where clause> WHERE clause to use during import
-z,--compress Enable compression
Incremental import arguments:
--check-column <column> Source column to check for incremental
change
--incremental <import-type> Define an incremental import of type
'append' or 'lastmodified'
--last-value <value> Last imported value in the incremental
check column
Output line formatting arguments:
--enclosed-by <char> Sets a required field enclosing
character
--escaped-by <char> Sets the escape character
--fields-terminated-by <char> Sets the field separator character
--lines-terminated-by <char> Sets the end-of-line character
--mysql-delimiters Uses MySQL's default delimiter set:
fields: , lines: \n escaped-by: \
optionally-enclosed-by: '
--optionally-enclosed-by <char> Sets a field enclosing character
Input parsing arguments:
--input-enclosed-by <char> Sets a required field encloser
--input-escaped-by <char> Sets the input escape
character
--input-fields-terminated-by <char> Sets the input field separator
--input-lines-terminated-by <char> Sets the input end-of-line
char
--input-optionally-enclosed-by <char> Sets a field enclosing
character
Hive arguments:
--create-hive-table Fail if the target hive
table exists
--hive-delims-replacement <arg> Replace Hive record \0x01
and row delimiters (\n\r)
from imported string fields
with user-defined string
--hive-drop-import-delims Drop Hive record \0x01 and
row delimiters (\n\r) from
imported string fields
--hive-home <dir> Override $HIVE_HOME
--hive-import Import tables into Hive
(Uses Hive's default
delimiters if none are
set.)
--hive-overwrite Overwrite existing data in
the Hive table
--hive-partition-key <partition-key> Sets the partition key to
use when importing to hive
--hive-partition-value <partition-value> Sets the partition value to
use when importing to hive
--hive-table <table-name> Sets the table name to use
when importing to hive
--map-column-hive <arg> Override mapping for
specific column to hive
types.
HBase arguments:
--column-family <family> Sets the target column family for the
import
--hbase-create-table If specified, create missing HBase tables
--hbase-row-key <col> Specifies which input column to use as the
row key
--hbase-table <table> Import to <table> in HBase
Code generation arguments:
--bindir <dir> Output directory for compiled
objects
--class-name <name> Sets the generated class name.
This overrides --package-name.
When combined with --jar-file,
sets the input class.
--input-null-non-string <null-str> Input null non-string
representation
--input-null-string <null-str> Input null string representation
--jar-file <file> Disable code generation; use
specified jar
--map-column-java <arg> Override mapping for specific
columns to java types
--null-non-string <null-str> Null non-string representation
--null-string <null-str> Null string representation
--outdir <dir> Output directory for generated
code
--package-name <name> Put auto-generated classes in
this package
Generic Hadoop command-line arguments:
(must preceed any tool-specific arguments)
Generic options supported are
-conf <configuration file> specify an application configuration file
-D <property=value> use value for given property
-fs <local|namenode:port> specify a namenode
-jt <local|jobtracker:port> specify a job tracker
-files <comma separated list of files> specify comma separated files to be copied to the map reduce cluster
-libjars <comma separated list of jars> specify comma separated jar files to include in the classpath.
-archives <comma separated list of archives> specify comma separated archives to be unarchived on the compute machines.
The general command line syntax is
bin/hadoop command [genericOptions] [commandOptions]
五、利用查询结果作为sqoop的导入内容
举例：其中split-by是导入后的数据按照a.id进行分割，--target-dir目标地址，查询后的结果将放入这个文件
$ sqoop import \
--query 'SELECT a.*, b.* FROM a JOIN b on (a.id == b.id) WHERE $CONDITIONS' \
--split-by a.id --target-dir /user/foo/joinresults举例：m代表只查询一次并且边查询边导入
$ sqoop import \
--query 'SELECT a.*, b.* FROM a JOIN b on (a.id == b.id) WHERE $CONDITIONS' \
-m 1 --target-dir /user/foo/joinresults导入时候可以控制分割文件大小，或者字符串转义例如：--direct-split-size 以及--warehouse-dir ，--default-character-set
例如：
$ sqoop import --connect jdbc:mysql://server.foo.com/db --table bar \
--direct -- --default-character-set=latin1
$ sqoop import --connnect <connect-str> --table foo --warehouse-dir /shared \
...
sqoop对java以及hive提供支持，所以你可以导入key/value这样的map数据，例如：
Argument Description
--map-column-java <mapping> Override mapping from SQL to Java type for configured columns.
--map-column-hive <mapping> Override mapping from SQL to Hive type for configured columns.
$ sqoop import ... --map-column-java id=String,value=Integer
六、sqoop的增量导入
Argument Description
--check-column (col) Specifies the column to be examined when determining which rows to import.
--incremental (mode) Specifies how Sqoop determines which rows are new. Legal values for mode include append and lastmodified.
--last-value (value) Specifies the maximum value of the check column from the previous import.通过增量导入你可以只导入一个已经存在表的增列值，或者表后面的值。
增量导入需要给定必要的参数，详情一个增量导入的例子。
当然你也可以指定导入到Hive后的文件格式：有2种
1.--as-textfile
这个参数你可以查看到hive内的原数据就是文本文件模式没有压缩
2.-z or --compress or --compression-codec
这个参数有3种写法不过导入到hive内的数据就是压缩过的了
七、sqoop的Hive与Hbase的数据导入
前六点都能看完后，Hive与Hbase的导入也就很简单了，其实就是多了一步导入的数据放在哪里而已。
Hive举例：
sqoop import --verbose --connect jdbc:mysql://10.18.102.133/tjss_opda --username tongji --password dx_tj --table opda_start_120604 --hive-import --hive-table opda_start_120604_incr --hive-overwrite --direct
sqoop job --create opda_start_120604 -- import --connect jdbc:mysql://10.18.102.133/tjss_opda --username tongji --password dx_tj --table opda_start_120604 --hive-import --hive-table opda_start_120604_incr --check-column id --incremental append --last-value 0 -m 8 --hive-overwrite --hive-delims-replacement="\t"注意事项：
1.注意Sqoop是在Hadoop上跑的，所以jdbc url不要写localhost，--direct的要求同理。
2.Sqoop也有metastore，目前看来，没有启动metastore service时其不是线程安全的。另外就是它只能使用hsqldb，暂不支持其他数据库，对hsqldb可靠性没有太高信心。
3.Metastore里password是明文存储的，所以它不建议存储password。
4.Sqoop有bug，目前数据库里有特殊表名时有问题。
5.Sqoop导入到hive里的表只能是TEXTFILE，不过可以选择压缩格式
6.Sqoop可以导入到一个已经存在的空hive表，但是是使用Load data导入数据，所以目标表的schema实际上是被无视了。
7.Sqoop导入hive若不加hive-overwirte，会留下hadoop目录，对下次若执行相同任务有影响。
8.注意加入delims-replace，否则很容易因为分隔符问题出现错误行。
9.Hive进行dynamic partition时，一次partition数量过多有Bug，必须加distribute by
10.Hive对大小写不区分，尽量全小写，否则有潜在bug
11.Sqoop要求运行时当前目录可写（code-gen）。
12.只要有jdbc驱动，所有jdbc兼容的数据库均可导入导入时除了用到sqoop相关的hive与Hbase的参数外，还会用到导入时候专用的参数：
Input parsing arguments:
--input-enclosed-by <char> Sets a required field encloser
--input-escaped-by <char> Sets the input escape
character
--input-fields-terminated-by <char> Sets the input field separator
--input-lines-terminated-by <char> Sets the input end-of-line
char
--input-optionally-enclosed-by <char> Sets a field enclosing
character
这个部分的参数有可能你会用到的。另外如果导入语句没有添加目的表或者地址则导入的内容会写在HDFS当前的操作目录下。
八、sqoop导入全部表和数据
举个例子，其他参数均与sqoop help参数相同：
$ sqoop import-all-tables --connect jdbc:mysql://db.foo.com/corp验证结果：
$ hadoop fs -ls
Found 4 items
drwxr-xr-x - someuser somegrp 0 2010-04-27 17:15 /user/someuser/EMPLOYEES
drwxr-xr-x - someuser somegrp 0 2010-04-27 17:15 /user/someuser/PAYCHECKS
drwxr-xr-x - someuser somegrp 0 2010-04-27 17:15 /user/someuser/DEPARTMENTS
drwxr-xr-x - someuser somegrp 0 2010-04-27 17:15 /user/someuser/OFFICE_SUPPLIES时间： 2024-10-29 17:48:17