Operational Reporting on YouTube Analytics Data from Spotfire Server

You can gain real-time access to YouTube Analytics data from your enterprise reporting solution with the CData JDBC Driver for YouTube Analytics's drop-in install into your Java reporting server. Use the data source template in this article to expand your Spotfire library to include remote YouTube Analytics data. You can then create and share real-time data visualizations that reflect any changes to YouTube Analytics data.

Connect to YouTube Analytics as a JDBC Data Source

To install the CData JDBC Driver for YouTube Analytics on Spotfire Server, drop the driver JAR into the classpath and use the data source template in this section.

1. To add the driver to Spotfire Server's classpath, copy the driver JAR from the lib subfolder in the driver installation folder to the lib subfolder for your Spotfire Server installation: For example, MySpotfireServerHomeDirectory/tomcat/lib.

   Note that the .lic file must be located in the same folder as the JAR.

2. In the TIBCO Spotfire Server Configuration Tool, click the Configuration tab and select data source templates in the Configuration Start node.
3. Create a new data source template with the following:

   
   <jdbc-type-settings>
     <type-name>youtubeanalytics</type-name>
     <driver>cdata.jdbc.youtubeanalytics.YouTubeAnalyticsDriver</driver>
     <connection-url-pattern>jdbc:youtubeanalytics:</connection-url-pattern>
     <ping-command>SELECT * FROM Projects LIMIT 1</ping-command>
     <connection-properties>
       <connection-property>
         <key>ContentOwnerId</key>
         <value>MyContentOwnerId</value>
       </connection-property>
       <connection-property>
         <key>ChannelId</key>
         <value>MyChannelId</value>
       </connection-property>
       <connection-property>
         <key>InitiateOAuth</key>
         <value>GETANDREFRESH</value>
       </connection-property>
     </connection-properties>
     <fetch-size>10000</fetch-size>
     <batch-size>100</batch-size>
     <max-column-name-length>32</max-column-name-length>
     <table-types>TABLE, VIEW</table-types>
     <supports-catalogs>true</supports-catalogs>
     <supports-schemas>true</supports-schemas>
     <supports-procedures>false</supports-procedures>
     <supports-distinct>true</supports-distinct>
     <supports-order-by>true</supports-order-by>
     <column-name-pattern>"$$name$$"</column-name-pattern>
     <table-name-pattern>"$$name$$"</table-name-pattern>
     <schema-name-pattern>"$$name$$"</schema-name-pattern>
     <catalog-name-pattern>"$$name$$"</catalog-name-pattern>
     <procedure-name-pattern>"$$name$$"</procedure-name-pattern>
     <column-alias-pattern>"$$name$$"</column-alias-pattern>
     <string-literal-quote>'</string-literal-quote>
     <max-in-clause-size>1000</max-in-clause-size>
     <condition-list-threshold>10000</condition-list-threshold>
     <expand-in-clause>false</expand-in-clause>
     <table-expression-pattern>[$$catalog$$.][$$schema$$.]$$table$$</table-expression-pattern>
     <procedure-expression-pattern>[$$catalog$$.][$$schema$$.]$$procedure$$</procedure-expression-pattern>
     <procedure-table-jdbc-type>0</procedure-table-jdbc-type>
     <procedure-table-type-name></procedure-table-type-name>
     <date-format-expression>$$value$$</date-format-expression>
     <date-literal-format-expression>'$$value$$'</date-literal-format-expression>
     <time-format-expression>$$value$$</time-format-expression> 
     <time-literal-format-expression>'$$value$$'</time-literal-format-expression>
     <date-time-format-expression>$$value$$</date-time-format-expression>
     <date-time-literal-format-expression>'$$value$$'</date-time-literal-format-expression>
     <java-to-sql-type-conversions>VARCHAR($$value$$) VARCHAR(255) INTEGER BIGINT REAL DOUBLE PRECISION DATE TIME TIMESTAMP</java-to-sql-type-conversions>
     <temp-table-name-pattern>$$name$$#TEMP</temp-table-name-pattern>
     <create-temp-table-command>CREATE TABLE $$name$$#TEMP $$column_list$$</create-temp-table-command>
     <drop-temp-table-command>DROP TABLE $$name$$#TEMP</drop-temp-table-command>
     <data-source-authentication>false</data-source-authentication>
     <lob-threshold>-1</lob-threshold>
     <use-ansii-style-outer-join>false</use-ansii-style-outer-join>
     <credentials-timeout>86400</credentials-timeout>
   </jdbc-type-settings>
   

4. Restart the Spotfire Server service.

The driver's support for standard SQL integrates real-time connectivity to YouTube Analytics data into the familiar interfaces of the Spotfire Platform. To access YouTube Analytics data from Spotfire Professional and other applications, including Jaspersoft Studio, create information links in the Information Designer.

As you select columns and filters, Spotfire Server builds the information link's underlying SQL query. Click Open Data to load the data into Spotfire.

Report authors can then build YouTube Analytics visualizations based on Spotfire data tables without writing SQL queries by hand. Report viewers can rely on accurate and current YouTube Analytics data.