Trino’s Memory Management Capabilities : Optimizing Performance

Trino, formerly known as PrestoSQL, is a distributed SQL query engine renowned for its high-performance query processing. An integral part of achieving this performance lies in Trino’s robust memory management capabilities. In this article, we will delve into the intricacies of how Trino handles memory for query execution, providing detailed insights, examples, and output comparisons. Trino’s memory management capabilities are integral to its exceptional query performance. With dynamic memory allocation, spill to disk, memory tracking, and query isolation, Trino ensures that queries can efficiently utilize available resources while preventing memory-related failures.

Understanding Trino’s Memory Management:

Trino employs several memory management techniques to optimize query performance and ensure efficient resource utilization. Let’s explore these capabilities in detail:

  1. Memory Allocation:
    • Trino dynamically allocates memory to various query components, such as operators, filters, and join algorithms, based on the query’s requirements.
    • Memory allocation is done efficiently to prevent excessive memory consumption and potential out-of-memory errors.
  2. Spill to Disk:
    • When memory usage approaches the allocated limit, Trino can spill intermediate data to disk temporarily, freeing up memory for other operations.
    • This prevents query failures due to memory exhaustion and ensures smoother query execution.
  3. Memory Tracking:
    • Trino keeps track of memory usage for each query and operator, allowing administrators to monitor and manage resource allocation effectively.
    • This feature is crucial for optimizing and troubleshooting query performance.
  4. Query Isolation:
    • Trino ensures that queries are isolated from each other, preventing one query from monopolizing memory and impacting others.
    • Resource allocation is controlled at the query level to maintain fairness and stability.

Examples and Output Comparisons:

To illustrate Trino’s memory management capabilities, let’s consider a complex query with limited memory resources and observe how Trino handles the situation.


SELECT product_name, SUM(sales_amount)
FROM sales_data
GROUP BY product_name;


| product_name | sum(sales_amount)|
| Product A    | 25000           |
| Product B    | 32000           |

Memory Usage:

  • Trino’s memory tracker reports memory usage during query execution.
  • It shows efficient memory allocation and spill to disk when necessary to accommodate the large intermediate data.

Query Optimization:

  • Trino optimizes memory usage by choosing efficient join algorithms and data structures.
  • This ensures that even complex queries with substantial memory requirements can be processed without running out of resources.
Author: user