> For the complete documentation index, see [llms.txt](https://docs.pentaho.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.pentaho.com/pdia-data-integration/9.3-data-integration/pdi-transformation-steps-reference-overview/hbase-setup-for-spark/set-up-the-vendor-specified-jars.md).

# Set up the vendor-specified JARs

Each vendor has differences in their byte conversion for HBase, so you must use the JAR files for the Hadoop distribution you are using.

**Note:** Vendor-specific JARS for HBase are not shipped with Spark or HDFS.

Perform the following steps to set up the vendor-specific JARs:

1. Navigate to the `design-tools/data-integration/adaptive-execution/extra` directory and delete the three HBase JAR files.
2. Navigate to the `design-tools/data-integration/plugins/pentaho-big-data-plugin/hadoop-configurations` directory and locate your CDH or HDP distribution folder.
3. Locate the `lib/pmr` directory in your distribution folder.
4. Copy the six HBase files, along with the metrics-core file to the `design-tools/data-integration/adaptive-execution/extra` folder.
5. To complete your setup, you must restart the AEL daemon.

   See the **Administer Pentaho Data Integration and Analytics** document for instructions.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation by asking a question.

Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters:

```
GET https://docs.pentaho.com/pdia-data-integration/9.3-data-integration/pdi-transformation-steps-reference-overview/hbase-setup-for-spark/set-up-the-vendor-specified-jars.md?ask=<question>&goal=<user_goal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.