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Trino is a fast, distributed SQL engine built for interactive analytics across large and diverse datasets. Trino enables several key capabilities in NexusOne:
  • Self-service analytics across curated and raw datasets
  • OpenID Connect (OIDC) for unified authentication and authorization
  • Federated SQL queries across Iceberg, Hive, PostgreSQL, and more
  • BI dashboards powered by Superset
  • DataOps workflows for validating and inspecting catalog data
  • AI-assisted SQL generation
By providing a single execution layer for all analytical workloads, Trino forms a core part of NexusOne’s data architecture.

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Environment configuration

This section describes how the NexusOne team configured Trino, and how different client tools connect to the service.

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Accessing the Trino UI

Trino provides that displays the details about the cluster. You can access the Trino UI on the NexusOne cluster using the following URL: 
https://trino-app.<client>.nx1cloud.com/ui/
When you purchase NexusOne, you receive a client name. Replace client with your assigned client name.
After visiting the URL, enter your NexusOne credentials to log in.

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Trino client setup

Within NexusOne, Trino supports OAuth 2.0 authenticated connections for JDBC, Python, and the command-line tool clients.

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Python

Example of connecting to Trino using Python. 
from trino.dbapi import connect
from trino.auth import OAuth2Authentication

conn = connect(
    host="trino-app.<client>.nx1cloud.com",
    port=443,
    http_scheme="https",
    user="your_username",
    password="your_password",
    verify=False, #OPTIONAL FOR SSL ERROR
    catalog="iceberg",
    schema="default"
)
Use your NexusOne credentials as the user and password.

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JDBC

Example of connecting to Trino using JDBC. 
jdbc:trino://trino-app.<client>.nx1cloud.com:443/iceberg/default?SSL=true

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Command-line tool

Example of connecting to Trino using a command-line tool. 
java -jar trino.jar \
  --user <user_id> \
  --server https://trino-app.<client>.nx1cloud.com/ \
  --catalog iceberg \
  --schema default \
  --debug
Use your NexusOne credential as the user.

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Iceberg/Hive integration

Trino integrates directly with the NexusOne data platform through preconfigured Iceberg and Hive catalogs. These catalogs use S3 as the underlying storage layer for all datasets and a Hive Metastore for providing centralized table and schema metadata.

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Superset integration

Superset connects to Trino using OAuth 2.0. Each Trino catalog appears as a database, and each schema inside a catalog is available for querying in SQL Lab, Superset’s interactive SQL editor. Connection example: 
trino://token@trino-app.<client>.nx1cloud.com/iceberg/default?auth=oauth
Once connected, Superset uses Trino to run queries, create charts, and build dashboards.

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Types of Trino queries

Trino supports different types of queries depending on the purpose and data sources. Understanding these types helps you choose the right approach when analyzing data.

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Analytical queries

Analytical queries interact with data within a single catalog or schema. One example is counting employees per job role in a single table, employees1, and calculating their average salary. 
SELECT job_id, COUNT(*) AS employee_count, AVG(salary) AS avg_salary
FROM employees1
GROUP BY job_id
ORDER BY employee_count DESC;

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Federated queries

Federated queries combine data across multiple catalogs or schemas. One example is aggregating employee data by department, combining information from an Iceberg table, employees1, and a Hive table, departments, in a single query. 
SELECT d.department_name,
       COUNT(e.employee_id) AS total_employees,
       AVG(e.salary) AS avg_salary,
       MAX(e.salary) AS max_salary
FROM iceberg.demo.employees1 e
JOIN hive.default.departments d
ON e.department_id = d.department_id
GROUP BY d.department_name
ORDER BY avg_salary DESC;
Understanding these types helps you decide which queries to use.

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Query execution management

Trino provides system-level mechanisms to keep query execution efficient in a multi-tenant environment such as NexusOne. This includes the following:
  • Parallel query execution across Kubernetes nodes
  • Configurable query management properties that control query behavior and resource usage, such as:
    • retry-policy: Defines how many times and how often to retry a failed query
    • query_max_run_time: Maximum time a query can run before Trino stops it
    • query_max_memory: Maximum memory a query can use during execution
    • query_max_execution_time: Maximum CPU execution time a query can consume

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Additional resources

  • To learn about best practices when using Trino, refer to the Trino best practices page.
  • To learn practical ways to use Trino in the NexusOne environment, refer to the Trino hands-on examples page.
  • For more details about Trino, refer to the Trino official documentation.
  • If you are using the NexusOne portal and want to learn how to launch Trino, refer to the Launch a hosted app page.