Build Kintone-Connected ETL Processes in Google Data Fusion

Google Data Fusion allows users to perform self-service data integration to consolidate disparate data. Uploading the CData JDBC Driver for Kintone enables users to access live Kintone data from within their Google Data Fusion pipelines. While the CData JDBC Driver enables piping Kintone data to any data source natively supported in Google Data Fusion, this article walks through piping data from Kintone to Google BigQuery,

Upload the CData JDBC Driver for Kintone to Google Data Fusion

Upload the CData JDBC Driver for Kintone to your Google Data Fusion instance to work with live Kintone data. Due to the naming restrictions for JDBC drivers in Google Data Fusion, create a copy or rename the JAR file to match the following format driver-version.jar. For example: cdatakintone-2020.jar

1. Open your Google Data Fusion instance
2. Click the to add an entity and upload a driver
3. On the "Upload driver" tab, drag or browse to the renamed JAR file.
4. On the "Driver configuration" tab:
   • Name: Create a name for the driver (cdata.jdbc.kintone) and make note of the name
   • Class name: Set the JDBC class name: (cdata.jdbc.kintone.KintoneDriver)
5. Click "Finish"

Connect to Kintone Data in Google Data Fusion

With the JDBC Driver uploaded, you are ready to work with live Kintone data in Google Data Fusion Pipelines.

1. Navigate to the Pipeline Studio to create a new Pipeline
2. From the "Source" options, click "Database" to add a source for the JDBC Driver
3. Click "Properties" on the Database source to edit the properties

   NOTE: To use the JDBC Driver in Google Data Fusion, you will need a license (full or trial) and a Runtime Key (RTK). For more information on obtaining this license (or a trial), contact our sales team.

   • Set the Label
   • Set Reference Name to a value for any future references (i.e.: cdata-kintone)
   • Set Plugin Type to "jdbc"
   • Set Connection String to the JDBC URL for Kintone. For example:
     
     jdbc:kintone:RTK=5246...;User=myuseraccount;Password=mypassword;Url=http://subdomain.domain.com;GuestSpaceId=myspaceid

     In addition to the authentication values, set the following parameters to connect to and retrieve data from Kintone:

     • Url: The URL of your account.
     • GuestSpaceId: Optional. Set this when using a guest space.

     Authenticating with Kintone

     Kintone supports the following authentication methods.

     Using Password Authentication

     You must set the following to authenticate:

     • User: The username of your account.
     • Password: The password of your account.

     Using Basic Authentication

     If the basic authentication security feature is set on the domain, supply the additional login credentials with BasicAuthUser and BasicAuthPassword. Basic authentication requires these credentials in addition to User and Password.

     Using Client SSL

     Instead of basic authentication, you can specify a client certificate to authenticate. Set SSLClientCert, SSLClientCertType, SSLClientCertSubject, and SSLClientCertPassword. Additionally, set User and Password to your login credentials.

     Built-in Connection String Designer

     For assistance in constructing the JDBC URL, use the connection string designer built into the Kintone JDBC Driver. Either double-click the JAR file or execute the jar file from the command-line.

     java -jar cdata.jdbc.kintone.jar

     Fill in the connection properties and copy the connection string to the clipboard.

   • Set Import Query to a SQL query that will extract the data you want from Kintone, i.e.:
     SELECT * FROM Comments
4. From the "Sink" tab, click to add a destination sink (we use Google BigQuery in this example)
5. Click "Properties" on the BigQuery sink to edit the properties
   • Set the Label
   • Set Reference Name to a value like kintone-bigquery
   • Set Project ID to a specific Google BigQuery Project ID (or leave as the default, "auto-detect")
   • Set Dataset to a specific Google BigQuery dataset
   • Set Table to the name of the table you wish to insert Kintone data into

With the Source and Sink configured, you are ready to pipe Kintone data into Google BigQuery. Save and deploy the pipeline. When you run the pipeline, Google Data Fusion will request live data from Kintone and import it into Google BigQuery.

While this is a simple pipeline, you can create more complex Kintone pipelines with transforms, analytics, conditions, and more. Download a free, 30-day trial of the CData JDBC Driver for Kintone and start working with your live Kintone data in Google Data Fusion today.