Question

mongodb用mongoexport命令导出数据为什么一直显示百分之零

Answer 1

一、导出工具mongoexport
Mongodb中的mongoexport工具可以把一个collection导出成JSON格式或CSV格式的文件。可以通过参数指定导出的数据项，也可以根据指定的条件导出数据。mongoexport具体用法如下所示：
Shell代码
[root@localhost mongodb]# ./bin/mongoexport --help
Export MongoDB data to CSV, TSV or JSON files.

options:
--help produce help message
-v [ --verbose ] be more verbose (include multiple times for more
verbosity e.g. -vvvvv)
--version print the program's version and exit
-h [ --host ] arg mongo host to connect to ( <set name>/s1,s2 for
sets)
--port arg server port. Can also use --host hostname:port
--ipv6 enable IPv6 support (disabled by default)
-u [ --username ] arg username
-p [ --password ] arg password
--dbpath arg directly access mongod database files in the given
path, instead of connecting to a mongod server -
needs to lock the data directory, so cannot be used
if a mongod is currently accessing the same path
--directoryperdb if dbpath specified, each db is in a separate
directory
--journal enable journaling
-d [ --db ] arg database to use
-c [ --collection ] arg collection to use (some commands)
-f [ --fields ] arg comma separated list of field names e.g. -f
name,age
--fieldFile arg file with fields names - 1 per line
-q [ --query ] arg query filter, as a JSON string
--csv export to csv instead of json
-o [ --out ] arg output file; if not specified, stdout is used
--jsonArray output to a json array rather than one object per
line
-k [ --slaveOk ] arg (=1) use secondaries for export if available, default
true
参数说明：
-h:指明数据库宿主机的IP
-u:指明数据库的用户名
-p:指明数据库的密码
-d:指明数据库的名字
-c:指明collection的名字
-f:指明要导出那些列
-o:指明到要导出的文件名
-q:指明导出数据的过滤条件

实例：test库中存在着一个students集合，集合中数据如下：
Js代码
> db.students.find()
{ "_id" : ObjectId("5031143350f2481577ea81e5"), "classid" : 1, "age" : 20, "name" : "kobe" }
{ "_id" : ObjectId("5031144a50f2481577ea81e6"), "classid" : 1, "age" : 23, "name" : "nash" }
{ "_id" : ObjectId("5031145a50f2481577ea81e7"), "classid" : 2, "age" : 18, "name" : "james" }
{ "_id" : ObjectId("5031146a50f2481577ea81e8"), "classid" : 2, "age" : 19, "name" : "wade" }
{ "_id" : ObjectId("5031147450f2481577ea81e9"), "classid" : 2, "age" : 19, "name" : "bosh" }
{ "_id" : ObjectId("5031148650f2481577ea81ea"), "classid" : 2, "age" : 25, "name" : "allen" }
{ "_id" : ObjectId("5031149b50f2481577ea81eb"), "classid" : 1, "age" : 19, "name" : "howard" }
{ "_id" : ObjectId("503114a750f2481577ea81ec"), "classid" : 1, "age" : 22, "name" : "paul" }
{ "_id" : ObjectId("503114cd50f2481577ea81ed"), "classid" : 2, "age" : 24, "name" : "shane" }
由上可以看出文档中存在着3个字段：classid、age、name
1.直接导出数据到文件中
Shell代码
[root@localhost mongodb]# ./bin/mongoexport -d test -c students -o students.dat
connected to: 127.0.0.1
exported 9 records
命令执行完后使用ll命令查看，发现目录下生成了一个students.dat的文件
Shell代码
-rw-r--r-- 1 root root 869 Aug 21 00:05 students.dat
查看该文件信息，具体信息如下：
Shell代码
[root@localhost mongodb]# cat students.dat
{ "_id" : { "$oid" : "5031143350f2481577ea81e5" }, "classid" : 1, "age" : 20, "name" : "kobe" }
{ "_id" : { "$oid" : "5031144a50f2481577ea81e6" }, "classid" : 1, "age" : 23, "name" : "nash" }
{ "_id" : { "$oid" : "5031145a50f2481577ea81e7" }, "classid" : 2, "age" : 18, "name" : "james" }
{ "_id" : { "$oid" : "5031146a50f2481577ea81e8" }, "classid" : 2, "age" : 19, "name" : "wade" }
{ "_id" : { "$oid" : "5031147450f2481577ea81e9" }, "classid" : 2, "age" : 19, "name" : "bosh" }
{ "_id" : { "$oid" : "5031148650f2481577ea81ea" }, "classid" : 2, "age" : 25, "name" : "allen" }
{ "_id" : { "$oid" : "5031149b50f2481577ea81eb" }, "classid" : 1, "age" : 19, "name" : "howard" }
{ "_id" : { "$oid" : "503114a750f2481577ea81ec" }, "classid" : 1, "age" : 22, "name" : "paul" }
{ "_id" : { "$oid" : "503114cd50f2481577ea81ed" }, "classid" : 2, "age" : 24, "name" : "shane" }
参数说明：
-d:指明使用的库，本例中为test
-c:指明要导出的集合，本例中为students
-o:指明要导出的文件名，本例中为students.dat
从上面的结果可以看出，我们在导出数据时没有显示指定导出样式 ，默认导出了JSON格式的数据。如果我们需要导出CSV格式的数据，则需要使用--csv参数，具体如下所示：
Shell代码
[root@localhost mongodb]# ./bin/mongoexport -d test -c students --csv -f classid,name,age -o students_csv.dat
connected to: 127.0.0.1
exported 9 records
[root@localhost mongodb]# cat students_csv.dat
classid,name,age
1.0,"kobe",20.0
1.0,"nash",23.0
2.0,"james",18.0
2.0,"wade",19.0
2.0,"bosh",19.0
2.0,"allen",25.0
1.0,"howard",19.0
1.0,"paul",22.0
2.0,"shane",24.0
[root@localhost mongodb]#
参数说明：
-csv：指明要导出为csv格式
-f：指明需要导出classid、name、age这3列的数据
由上面结果可以看出，mongoexport成功地将数据根据csv格式导出到了students_csv.dat文件中。

二、导入工具mongoimport
Mongodb中的mongoimport工具可以把一个特定格式文件中的内容导入到指定的collection中。该工具可以导入JSON格式数据，也可以导入CSV格式数据。具体使用如下所示：
Shell代码
[root@localhost mongodb]# ./bin/mongoimport --help
options:
--help produce help message
-v [ --verbose ] be more verbose (include multiple times for more
verbosity e.g. -vvvvv)
--version print the program's version and exit
-h [ --host ] arg mongo host to connect to ( <set name>/s1,s2 for sets)
--port arg server port. Can also use --host hostname:port
--ipv6 enable IPv6 support (disabled by default)
-u [ --username ] arg username
-p [ --password ] arg password
--dbpath arg directly access mongod database files in the given
path, instead of connecting to a mongod server -
needs to lock the data directory, so cannot be used
if a mongod is currently accessing the same path
--directoryperdb if dbpath specified, each db is in a separate
directory
--journal enable journaling
-d [ --db ] arg database to use
-c [ --collection ] arg collection to use (some commands)
-f [ --fields ] arg comma separated list of field names e.g. -f name,age
--fieldFile arg file with fields names - 1 per line
--ignoreBlanks if given, empty fields in csv and tsv will be ignored
--type arg type of file to import. default: json (json,csv,tsv)
--file arg file to import from; if not specified stdin is used
--drop drop collection first
--headerline CSV,TSV only - use first line as headers
--upsert insert or update objects that already exist
--upsertFields arg comma-separated fields for the query part of the
upsert. You should make sure this is indexed
--stopOnError stop importing at first error rather than continuing
--jsonArray load a json array, not one item per line. Currently
limited to 4MB.
参数说明：
-h:指明数据库宿主机的IP
-u:指明数据库的用户名
-p:指明数据库的密码
-d:指明数据库的名字
-c:指明collection的名字
-f:指明要导入那些列

示例：先删除students中的数据，并验证
Js代码
> db.students.remove()
> db.students.find()
>
然后再导入上面导出的students.dat文件中的内容
Shell代码
[root@localhost mongodb]# ./bin/mongoimport -d test -c students students.dat
connected to: 127.0.0.1
imported 9 objects
[root@localhost mongodb]#
参数说明：
-d:指明数据库名，本例中为test
-c:指明collection名，本例中为students
students.dat：导入的文件名
查询students集合中的数据
Js代码
> db.students.find()
{ "_id" : ObjectId("5031143350f2481577ea81e5"), "classid" : 1, "age" : 20, "name" : "kobe" }
{ "_id" : ObjectId("5031144a50f2481577ea81e6"), "classid" : 1, "age" : 23, "name" : "nash" }
{ "_id" : ObjectId("5031145a50f2481577ea81e7"), "classid" : 2, "age" : 18, "name" : "james" }
{ "_id" : ObjectId("5031146a50f2481577ea81e8"), "classid" : 2, "age" : 19, "name" : "wade" }
{ "_id" : ObjectId("5031147450f2481577ea81e9"), "classid" : 2, "age" : 19, "name" : "bosh" }
{ "_id" : ObjectId("5031148650f2481577ea81ea"), "classid" : 2, "age" : 25, "name" : "allen" }
{ "_id" : ObjectId("5031149b50f2481577ea81eb"), "classid" : 1, "age" : 19, "name" : "howard" }
{ "_id" : ObjectId("503114a750f2481577ea81ec"), "classid" : 1, "age" : 22, "name" : "paul" }
{ "_id" : ObjectId("503114cd50f2481577ea81ed"), "classid" : 2, "age" : 24, "name" : "shane" }
>
证明数据导入成功
上面演示的是导入JSON格式的文件中的内容，如果要导入CSV格式文件中的内容，则需要通过--type参数指定导入格式，具体如下所示：
先删除数据
Js代码
> db.students.remove()
> db.students.find()
>
再导入之前导出的students_csv.dat文件

Shell代码
[root@localhost mongodb]# ./bin/mongoimport -d test -c students --type csv --headerline --file students_csv.dat
connected to: 127.0.0.1
imported 10 objects
[root@localhost mongodb]#
参数说明：
-type:指明要导入的文件格式
-headerline:指明第一行是列名，不需要导入
-file：指明要导入的文件
查询students集合，验证导入是否成功：

Js代码
> db.students.find()
{ "_id" : ObjectId("503266029355c632cd118ad8"), "classid" : 1, "name" : "kobe", "age" : 20 }
{ "_id" : ObjectId("503266029355c632cd118ad9"), "classid" : 1, "name" : "nash", "age" : 23 }
{ "_id" : ObjectId("503266029355c632cd118ada"), "classid" : 2, "name" : "james", "age" : 18 }
{ "_id" : ObjectId("503266029355c632cd118adb"), "classid" : 2, "name" : "wade", "age" : 19 }
{ "_id" : ObjectId("503266029355c632cd118adc"), "classid" : 2, "name" : "bosh", "age" : 19 }
{ "_id" : ObjectId("503266029355c632cd118add"), "classid" : 2, "name" : "allen", "age" : 25 }
{ "_id" : ObjectId("503266029355c632cd118ade"), "classid" : 1, "name" : "howard", "age" : 19 }
{ "_id" : ObjectId("503266029355c632cd118adf"), "classid" : 1, "name" : "paul", "age" : 22 }
{ "_id" : ObjectId("503266029355c632cd118ae0"), "classid" : 2, "name" : "shane", "age" : 24 }
>