Trino Advanced SQL

Mastering Advanced SQL Techniques in Trino

Trino, formerly known as PrestoSQL, is a sophisticated distributed SQL query engine designed for big data analytics. This tutorial focuses on advanced SQL techniques in Trino, guiding enterprise data professionals through complex queries, performance optimization, and leveraging unique Trino features. Ideal for data engineers and analysts, this tutorial aims to enhance your SQL skills within the Trino environment.

Understanding Trino’s SQL Capabilities

1. Complex Queries and Analytic Functions

Trino supports a wide range of complex queries and analytic functions. Understanding these can significantly improve your data analysis capabilities.

SELECT 
    employee_id,
    department,
    salary,
    AVG(salary) OVER (PARTITION BY department) as avg_department_salary
FROM 
    employee_salary
ORDER BY 
    department, salary DESC;

Sample Result:

2. Query Optimization Techniques

Optimizing queries in Trino involves understanding its distributed architecture. Efficient use of JOINs and partitioning can drastically reduce query times.

SELECT /*+ REPARTITION */
    a.name,
    b.total_sales
FROM 
    customers a
JOIN 
    sales b ON a.customer_id = b.customer_id;

This example uses the REPARTITION hint to suggest repartitioning of data on the join key, optimizing the JOIN operation and improving performance in distributed environments.

Platform-Specific Considerations

– Amazon Redshift: Trino connects to Redshift, allowing users to perform queries across both Redshift and other data sources. Pay attention to Redshift-specific functions when writing Trino queries.
– Snowflake: Similar to Redshift, Trino can connect to Snowflake. Ensure compatibility with Snowflake’s SQL dialect.
– Google BigQuery: While connecting to BigQuery, consider the differences in SQL syntax, especially for functions and data types.
– Microsoft SQL Server and PostgreSQL: Trino’s SQL syntax is quite compatible with these databases, but always check for any function or feature discrepancies.

Enhancing Trino with CoginitiScript

Trino’s functionality can be further enhanced with CoginitiScript. This allows you to create modular, scalable, and dynamic SQL queries. For example:

#+src sql GetTopSales(limit)
#+meta { 
  :doc "Retrieve top sales data."
}
#+begin
  SELECT customer_id, total_sales
  FROM sales
  ORDER BY total_sales DESC
  LIMIT {{limit}}
#+end

SELECT * FROM {{ GetTopSales(10) }};

This CoginitiScript block creates a reusable query module for retrieving top sales data, demonstrating how you can modularize and simplify complex Trino queries.

Conclusion

Mastering advanced SQL in Trino opens up new data analytics possibilities. These techniques, combined with the power of CoginitiScript, can significantly enhance your data productivity. Try integrating these advanced methods in your next Trino project with a free trial of Coginiti.