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To pass complex data from a Java class, the best practice is to pass it as an xml or otherwise encoded/delimited string, and then break the xml/delimited fields into separate fields for processing. Check the simple Java Integration sample below for an example of how to turn an xml string returned from a java class into a dataset. An additional example can be found at https://github.com/hpcc-systems/TextAnalytics/blob/master/hpcc/ecl/medex/BWR_MedexDrugSignatures.ecl

the Java JVM starts up once at Thor startup, and continues running until Thor is restarted. Any classes you call remain loaded until Thor restart. Call static class methods, or use a Factory method pattern in any java code you're calling. When possible, incorporate all dependencies, configuration files and other resources within the jar to help avoid any classpath/dependency issues that could arise when running the JAR on the cluster.

Troubleshooting

  1. You can run the sample java, but get a class not found error when you try to run yours.

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Give it a try and see how easy it is to extend HPCC using Java libraries. HPCC provides you the framework to perform Big Data analytics. This example shows how you can easily extend ECL to perform advanced tasks like streaming data, text extraction, sentiment analysis etc., using Java libraries.

Additional Examples of Java Plugin usage:

https://github.com/hpcc-systems/TextAnalytics/tree/master/hpcc/ecl/stanfordnlp
https://github.com/hpcc-systems/kafka-integration/blob/master/ecl/DataCollection_Scheduler.ecl