DataAI ETL Talend / MuleSoft — Production Installation Guide

Installation and Usage for Maven Central

Delivery model

The current repository-layout directory contains production-candidate artifacts. It is not a Central upload bundle because public metadata and Yanbor PGP signatures remain incomplete. Licensed production customers should continue using an authenticated private Maven repository.

Production-candidate artifacts

Install these matching-version modules together:

• dataai-spark-api-1.0.0.jar
• dataai-spark-quality-1.0.0.jar
• dataai-spark-core-1.0.0.jar
• dataai-spark-functions-1.0.0.jar

The CLI JAR is optional. Spark and Hadoop are provided by the customer runtime and are not bundled by DataAI.

Generic Spark usage

Add all required JARs to the Spark driver and executor classpaths using the target platform's supported library or --jars mechanism. Then call DataAiPipeline and the functions in com.dataai.etl.spark.functions. The complete inventory is in FUNCTION_CATALOG.md.

Customer code supplies Dataset<Row> inputs and decides whether returned DataFrames are written. DataAI performs no automatic persistence.

Production

Deploy immutable version 1.0.0 only after Yanbor release authorization, commercial entitlement, and target-platform validation. Obtain it from the approved marketplace artifact, authenticated Maven repository, or customer artifact repository. Verify checksums and pin the exact version.

Troubleshooting

• UnsupportedClassVersionError: select a Java 17-compatible runtime.
• Class not found: install API, quality, core, and functions at the same version.
• Scala linkage error: use a runtime compatible with Scala 2.12.
• Spark linkage error: validate against the documented Spark 3.5.x baseline.
• Permission failure: use customer-approved identity and storage permissions; DataAI does not bypass platform controls.