Trino Plugin

This is a Trino plugin that provides a connector.

Quick Start

To run a Docker container with the connector, run the following: !!Get your docker tag from https://hub.docker.com/repository/docker/waseedockerhub9/trino-nlp-embeddings/tags

docker run \
  -d \
  --name trino-nlp-embeddings \
  -p 8080:8080 \
  waseedockerhub9/trino-nlp-embeddings:0.67

Then use your favourite SQL client to connect to Trino running at http://localhost:8080

Usage

Download one of the ZIP packages, unzip it and copy the trino-nlp-embeddings-0.1 directory to the plugin directory on every node in your Trino cluster. Create a nlp_embeddings_connector.properties file in your Trino catalog directory and set all the required properties.

connector.name=nlp_embeddings_connector

After reloading Trino, you should be able to connect to the nlp_embeddings_connector catalog.

Build

Run all the unit tests:

mvn test

Creates a deployable zip file:

mvn clean package

Unzip the archive from the target directory to use the connector in your Trino cluster.

unzip target/*.zip -d ${PLUGIN_DIRECTORY}/
mv ${PLUGIN_DIRECTORY}/trino-nlp-embeddings-* ${PLUGIN_DIRECTORY}/trino-nlp-embeddings

Debug

To test and debug the connector locally, run the NLPQueryRunner class located in tests:

mvn test-compile exec:java -Dexec.mainClass="ai.knorket.NLPQueryRunner" -Dexec.classpathScope=test

And then run the Trino CLI using trino --server localhost:8080 --no-progress and query it:

trino> show catalogs;
 Catalog
---------
 nlp_embeddings_connector
 system
(2 rows)

trino> show tables from nlp_embeddings_connector.default;
   Table
------------
 single_row
(1 row)

trino> select * from nlp_embeddings_connector.default.single_row;
 id |     type      |  name
----+---------------+---------
 x  | default-value | my-name
(1 row)