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MYSQL lookup filter plugin for Embulk
​ An Embulk filter plugin for Lookup Transformation with MySQL database ​
Configuration
-
mysql_lookup: Required attributes for the LookUp Filter Plugin -
-
filters:
- type: Name of lookup type (required)
- driver_path: path to the jar file of the MySQL JDBC driver. If not set, the bundled JDBC driver (MySQL Connector/J 8.0.19) will be used (string)
- driver_class: Here we can provide driver class name,if not set,the com.mysql.cj.jdbc.Driver class will be used
-
host: database host (example
localhost) (required) -
port: database port (example port for mssql
1433) (required - database: database name (required)
- table_name: table name of your database (required)
- username: username for your database (required)
- password: password for database (required)
-
mapping_from: (Name of columns to be matched with table 2 columns) (required)
- Name of column-1: column name-1 from input file
- Name of column-2: column name-2 from input file etc ...
-
mapping_to: (Name of columns to be matched with table 1 columns) (required)
- Name of column-1: column name-1 from input file
- Name of column-2: column name-2 from input file
-
new_columns: (New generated column names) (required)
- Name-1,Type-1: Any Name, Type of the name (name: pin, type: string)
- Name-2,Type-2: Any Name, Type of the name (name: gender, type: string)
- Name-3,Type-3: Any Name, Type of the name (name: phone_number, type: string) etc ...
-
filters:
Example - columns
​ Customer.csv for table 1 is as follows :-
id customer_name address email car_name company
1 John Doe 123 Main St, Anytown USA john.doe@example.com Civic Honda
2 Jane Smith 456 Elm St, Anytown USA jane.smith@example.com E-Class Mercedes-Benz
3 Bob Johnson 789 Oak St, Anytown USA bob.johnson@example.com GLE-Class Mercedes-Benz
4 Amanda Hernandez 999 Cedar St, Anytown USA amanda.hernandez@example.com 911 119
5 Tom Brown 567 Pine St, Anytown USA tom.brown@example.com C-Class Mercedes-Benz
6 Samantha Davis 890 Cedar St, Anytown USA samantha.davis@example.com Civic Honda
7 Mike Wilson 1234 Spruce St, Anytown USA mike.wilson@example.com GLE-Class Mercedes-Benz
8 Jason Brown 888 Pine St, Anytown USA jason.brown@example.com 911 Porsche
9 David Rodriguez 9010 Oak St, Anytown USA david.rodriguez@example.com GLC-Class Mercedes-Benz
10 Mark Davis 666 Spruce St, Anytown USA mark.davis@example.com C-Class Mercedes-Benz
11 Chris Thompson 222 Cedar St, Anytown USA chris.thompson@example.com Cayenne Porsche
12 Linda Young 555 Birch St, Anytown USA linda.young@example.com RAV4
13 Kevin Hernandez 444 Maple St, Anytown USA kevin.hernandez@example.com 911 119
Car.csv for table 2 is as follows :-
car_id model brand category fuel_capacity
87 GLE-Class Mercedes-Benz SUV 80
101 Cayenne Porsche SUV 75
119 911 Porsche Sports Car 64
205 Accord Honda Sedan 56
334 Pilot Honda SUV 70
434 CR-v Honda SUV 64
559 C-Class Mercedes-Benz Sedan 66
603 Civic Honda Sedan 42
697 E-Class Mercedes-Benz Sedan 72
812 GLC-Class Mercedes-Benz Sedan 68
As shown in yaml below, columns mentioned in mapping_from will be mapped with columns mentioned in mapping_to
ie:
car_name : model
company : brand
After successful mapping an Output.csv file containing the columns mentioned in new_columns will be generated
Output File generated :-
id customer_name address email car_name company car_id category fuel_capacity
1 John Doe 123 Main St, Anytown USA john.doe@example.com Civic Honda 603 Sedan 42
2 Jane Smith 456 Elm St, Anytown USA jane.smith@example.com E-Class Mercedes-Benz 697 Sedan 72
3 Bob Johnson 789 Oak St, Anytown USA bob.johnson@example.com GLE-Class Mercedes-Benz 87 SUV 80
4 Amanda Hernandez 999 Cedar St, Anytown USA amanda.hernandez@example.com 911 119 0
5 Tom Brown 567 Pine St, Anytown USA tom.brown@example.com C-Class Mercedes-Benz 559 Sedan 66
6 Samantha Davis 890 Cedar St, Anytown USA samantha.davis@example.com Civic Honda 603 Sedan 42
7 Mike Wilson 1234 Spruce St, Anytown USA mike.wilson@example.com GLE-Class Mercedes-Benz 87 SUV 80
8 Jason Brown 888 Pine St, Anytown USA jason.brown@example.com 911 Porsche 119 Sport Car 64
9 David Rodriguez 9010 Oak St, Anytown USA david.rodriguez@example.com GLC-Class Mercedes-Benz 812 SUV 68
10 Mark Davis 666 Spruce St, Anytown USA mark.davis@example.com C-Class Mercedes-Benz 559 Sedan 66
11 Chris Thompson 222 Cedar St, Anytown USA chris.thompson@example.com Cayenne Porsche 101 SUV 75
12 Linda Young 555 Birch St, Anytown USA linda.young@example.com RAV4 \N 0
13 Kevin Hernandez 444 Maple St, Anytown USA kevin.hernandez@example.com 911 119 0
​ ​ ​
filters:
- type: mysql_lookup
host: localhost
port: 3306
database: test
table_name: car
username: root
password: 'passsword'
mapping_from:
- car_name
- company
mapping_to:
- model
- brand
new_columns:
- { name: car_id, type: string }
- { name: category, type: string }
- { name: fuel_capacity, type: string }​ Notes:
- mapping_from attribute should be in the same order as mentioned in the input file. ​
- In case with JDBC plugin if any integer column returned as float/decimal then use to cast that column as long as below
column_options:
id: {value_type: long}
- Matching columns data types must be int,long and String
Development
​ Run example: ​
$ ./gradlew package
$ embulk run -I ./lib seed.yml
​ Deployment Steps: ​
Install ruby in your machine
$ gem install gemcutter (For windows OS)
​
$ ./gradlew gemPush
$ gem build NameOfYourPlugins (example: embulk-filter-mssql_lookup)
$ gem push embulk-filter-mssql_lookup-0.1.0.gem (You will get this name after running above command)
​ ​ Release gem: ​
$ ./gradlew gemPush
Licensing
InfoObjects license (MIT License)
