Trino #

Introduction #

Trino, formerly known as PrestoSQL, is an open-source distributed SQL query engine designed for running fast, interactive analytic queries on large datasets. Trino can query data across multiple sources, making it a powerful tool for data warehousing, data lakes, and real-time analytics.

Key Features #

1. Distributed Query Processing:

• Executes queries across multiple nodes, offering high performance and scalability.
• Optimized for interactive, low-latency query execution.

2. SQL Compatibility:

• Supports standard ANSI SQL, making it accessible to users familiar with SQL.
• Advanced SQL features, including window functions, arrays, and nested data types.

3. Data Source Integration:

• Connects to a wide range of data sources: HDFS, S3, relational databases, NoSQL databases, and other data stores.
• Unified interface to query data across different storage systems.

4. Performance Optimization:

• Cost-Based Optimizer: Uses statistics to choose the most efficient execution plan.
• In-Memory Processing: Reduces query latency by processing data in memory.

5. Extensibility:

• Connector Architecture: Easily add new data sources by developing custom connectors.
• Support for User-Defined Functions (UDFs): Create custom functions to extend query capabilities.

6. Fault Tolerance and Reliability:

• Designed for high availability and fault tolerance, ensuring robust query execution even during node failures.

Architecture #

1. Coordinator:

• Manages the query lifecycle, including parsing, planning, and scheduling.
• Distributes tasks to worker nodes for execution.

2. Workers:

• Execute tasks assigned by the coordinator.
• Perform data processing tasks like reading from data sources, filtering, joining, and aggregating data.

3. Connectors:

• Plugins that enable Trino to communicate with various data sources.
• Provide a standardized way to access different types of data stores.

Use Cases #

1. Data Warehousing:

• Acts as a query layer on top of existing data warehouses, providing fast, scalable querying capabilities.

2. Data Lakes:

• Enables querying of large-scale data lakes, integrating data from various sources for comprehensive analysis.

3. Real-Time Analytics:

• Supports real-time data analysis by querying data across different systems with low latency.

4. Business Intelligence:

• Powers BI tools, offering fast and reliable access to large datasets for reporting and analytics.

5. Ad Hoc Queries:

• Facilitates exploratory data analysis with the ability to run complex, ad hoc queries on diverse data sources.

Advantages #

1. High Performance: Optimized for fast query execution with low latency.
2. Scalability: Easily scales out to handle increasing data volumes and complex queries.
3. Flexibility: Supports a wide range of data sources and formats, enabling comprehensive data analysis.
4. Ease of Use: Standard ANSI SQL support makes it accessible to users with SQL knowledge.
5. Extensibility: Connector architecture allows integration with new data sources and systems.

Trino is a robust and versatile SQL query engine designed for high-performance, distributed querying across diverse data sources. Its ability to handle large-scale data processing with low latency makes it ideal for data warehousing, data lakes, real-time analytics, business intelligence, and ad hoc querying. With its extensibility, high availability, and ease of use, Trino empowers organizations to derive insights from their data quickly and efficiently.

Learning Resources #

Books #

• Trino: The Definitive Guide, 2nd Edition

Courses #

• What is Trino?
• How does Trino process a query? | Starburst Academy
• Trino: An Origin Story
• Understanding Trino

Miscellaneous #

• Trino, a query engine that runs at ludicrous speed
• Understanding Trino Architecture: Unleashing the Power of Distributed SQL Queries
• Trino
• Trino Github