Real-Time Data Processing with Trino: Strategies and Examples

Trino, formerly known as PrestoSQL, is a powerful distributed SQL query engine that excels at processing large-scale datasets. But can Trino be used for real-time data processing, and if so, how? In this article, we’ll delve into the strategies and examples of using Trino for real-time data processing, demonstrating its capabilities in efficiently handling streaming data.

Understanding Real-Time Data Processing with Trino

Real-time data processing involves ingesting, processing, and analyzing data as it arrives, typically within milliseconds to seconds. Trino can be leveraged for real-time processing by integrating with streaming data sources and utilizing its distributed computing capabilities.

Strategies for Real-Time Data Processing with Trino

1. Streaming Data Source Integration: Trino supports integration with streaming data sources such as Apache Kafka and Apache Pulsar. By querying data directly from these sources, Trino can process streaming data in real-time.
2. Continuous Queries: Trino supports continuous queries, allowing users to execute queries continuously over a specified time window. This enables real-time analysis of streaming data without the need for manual intervention.
3. Materialized Views: Materialized views in Trino can be used to precompute and store aggregated results of streaming data. By querying materialized views, users can access real-time insights without the overhead of processing raw streaming data on-the-fly.

Example: Real-Time Analysis of Streaming Data

Let’s consider an example where we have a streaming data source from Apache Kafka containing user activity events. We’ll demonstrate how to use Trino to perform real-time analysis on the streaming data.

-- Create a table for Kafka integration
CREATE TABLE user_activity (
    user_id INT,
    event_type VARCHAR,
    timestamp TIMESTAMP
)
WITH (
    connector = 'kafka',
    topic = 'user_activity',
    format = 'json'
);

-- Query recent user activity events
SELECT * FROM user_activity WHERE timestamp >= TIMESTAMP '2024-03-01 00:00:00';

 user_id | event_type |         timestamp          
---------+------------+----------------------------
       1 | login      | 2024-03-01 12:30:45.123456
       2 | purchase   | 2024-03-01 12:31:20.987654
       3 | logout     | 2024-03-01 12:32:15.234567