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The CData JDBC driver for Telegram is easy to integrate with Java Web applications. This article shows how to efficiently connect to Telegram data in Jetty by configuring the driver for connection pooling. You will configure a JNDI resource for Telegram in Jetty.
Follow the steps below to connect to Salesforce from Jetty.
Enable the JNDI module for your Jetty base. The following command enables JNDI from the command-line:
java -jar ../start.jar --add-to-startd=jndi
Declare the resource and its scope. Enter the required connection properties in the resource declaration. This example declares the Telegram data source at the level of the Web app, in WEB-INF\jetty-env.xml.
<Configure id='telegramdemo' class="org.eclipse.jetty.webapp.WebAppContext"> <New id="telegramdemo" class="org.eclipse.jetty.plus.jndi.Resource"> <Arg><Ref refid="telegramdemo"/></Arg> <Arg>jdbc/telegramdb</Arg> <Arg> <New class="cdata.jdbc.api.APIDriver"> <Set name="url">jdbc:api:</Set> <Set name="Profile">C:\profiles\Telegram.apip</Set> <Set name="ProfileSettings">'APIKey</Set> </New> </Arg> </New> </Configure>
Telegram uses Bot Tokens to authenticate API requests. You can obtain a Bot Token by creating a bot via BotFather on Telegram (https://t.me/BotFather). Once created, BotFather will provide a token in the format
123456789:ABCdefGhIJKlmNoPQRsTUVwxyZ.
After setting the following connection properties, you are ready to connect:
Profile=C:\profiles\Telegram.apip;ProfileSettings='APIKey=your_bot_token';
Configure the resource in the Web.xml:
jdbc/telegramdb javax.sql.DataSource Container
You can then access Telegram with a lookup to java:comp/env/jdbc/telegramdb:
InitialContext ctx = new InitialContext();
DataSource mytelegram = (DataSource)ctx.lookup("java:comp/env/jdbc/telegramdb");
The steps above show how to configure the driver in a simple connection pooling scenario. For more use cases and information, see the Working with Jetty JNDI chapter in the Jetty documentation.
Connect to live data from Telegram with the API Driver
Connect to Telegram