3.1. Queries Federation with Apache Trino

Introduction

Apache Trino is a distributed SQL query engine designed to query large datasets across multiple data sources. This section explores how to set up and use Trino for query federation, enabling seamless data access and analytics.

Key Features

  • Federated Queries: Combine data from multiple sources, such as relational databases, object storage, and NoSQL systems.

  • High Performance: Optimized for low-latency and high-throughput queries.

  • Scalability: Supports scaling to thousands of nodes for large-scale analytics.

Setup and Configuration

### AWS Setup

  1. Provision an EC2 Instance: - Launch an EC2 instance with a Linux AMI (e.g., Amazon Linux 2). - Ensure the instance has sufficient resources (e.g., 4 vCPUs, 16 GB RAM) for Trino. - Install Java and Trino on the instance:

    `bash sudo yum update -y sudo yum install java-11-amazon-corretto -y wget https://repo1.maven.org/maven2/io/trino/trino-server/403/trino-server-403.tar.gz tar -xvzf trino-server-403.tar.gz cd trino-server-403 mkdir etc `

  2. Configure Trino: - Create a config.properties file in the etc directory to define Trino’s coordinator and discovery settings:

    `properties coordinator=true node-scheduler.include-coordinator=true http-server.http.port=8080 query.max-memory=5GB query.max-memory-per-node=1GB discovery-server.enabled=true discovery.uri=http://localhost:8080 `

    • Create a node.properties file to specify node-specific configurations:

      `properties node.environment=production node.id=unique-node-id node.data-dir=/var/trino/data `

    • Start Trino using the launcher script:

      `bash bin/launcher start `

  3. Configure AWS S3 Connector: - Add an S3 catalog in the etc/catalog directory (e.g., s3.properties) to enable querying data stored in S3:

    `properties connector.name=hive hive.metastore=glue hive.s3.aws-access-key=YOUR_ACCESS_KEY hive.s3.aws-secret-key=YOUR_SECRET_KEY hive.s3.bucket=your-bucket-name `

    • Use AWS Glue as the metastore for managing table schemas.

### Kubernetes Setup

  1. Deploy Trino on Kubernetes: - Create a Kubernetes deployment YAML file to define the Trino pods:

  1. Expose Trino Service: - Create a service YAML file to expose Trino to external clients:

Best Practices

  • Resource Allocation: - Allocate sufficient memory and CPU resources for Trino nodes to handle query workloads efficiently. - Use Kubernetes auto-scaling to dynamically adjust resources based on demand.

  • Security: - Use IAM roles for AWS S3 access to avoid hardcoding credentials in configuration files. - Enable HTTPS for secure communication between Trino nodes and clients. - Restrict access to Trino’s HTTP port using security groups or network policies.

  • Monitoring and Logging: - Integrate Trino with Prometheus and Grafana for real-time monitoring of query performance and resource usage. - Enable detailed logging to troubleshoot query issues and optimize performance.

  • Data Partitioning: - Partition large datasets by frequently queried columns (e.g., date, region) to improve query performance. - Use appropriate partitioning strategies based on query patterns and data distribution.

  • Query Optimization: - Use filters and projections early in queries to reduce the amount of data processed. - Avoid cross-joins and use indexed columns for join conditions.

Use Cases

### Data Lake Analytics

  • Configuration: - Set up an S3 catalog as described in the AWS setup to query data stored in S3.

  • Code Example:

    `sql SELECT region, COUNT(*) FROM s3.sales_data WHERE year = 2025 GROUP BY region; `

    This query counts the number of sales records for each region in the year 2025.

### Cross-Database Joins

  • Configuration: - Set up catalogs for MySQL and PostgreSQL to enable cross-database queries:

  • Code Example:

    `sql SELECT a.user_id, b.order_id FROM mysql.users a JOIN postgresql.orders b ON a.user_id = b.user_id; `

    This query joins user data from MySQL with order data from PostgreSQL based on the user_id column.

### Ad-Hoc Analysis

  • Configuration: - Use Trino CLI or connect a BI tool like Tableau to Trino for interactive analysis.

  • Code Example:

    `sql SELECT product_id, AVG(sales) FROM s3.sales_data WHERE category = 'electronics' GROUP BY product_id; `

    This query calculates the average sales for each product in the “electronics” category.