SELECT p.product_name, p.category, s.sale_amount FROM postgresql.public.products p JOIN memory.default.sales s ON p.product_id = s.order_id WHERE s.sale_date > DATE '2025-01-01'; Here, Presto 8.8 seamlessly pulls products from PostgreSQL and sales from the memory connector. Assuming you have a geotable with a geometry column (e.g., in Hive):

Introduction: Why Presto 8.8 Matters In the fast-paced world of big data, query speed and scalability are non-negotiable. Presto (now PrestoDB) has emerged as a leading distributed SQL query engine for running interactive analytics on datasets ranging from gigabytes to petabytes. With the release of Presto 8.8 , the open-source community introduced significant enhancements in stability, federation capabilities, and ANSI SQL compliance.

SELECT name, ST_Area(geometry) AS area_sqkm FROM hive.gis.locations WHERE ST_Within(geometry, ST_Point(-74.006, 40.7128)); In Presto 8.8, dynamic filtering is enabled by default. You can control it:

-- Insert data INSERT INTO memory.default.sales VALUES (1, 'Laptop', 999.99, DATE '2025-01-15'), (2, 'Mouse', 25.50, DATE '2025-01-16');

bin/launcher status Expected output: Running as [PID] . wget https://repo1.maven.org/maven2/io/prestosql/presto-cli/8.8/presto-cli-8.8-executable.jar mv presto-cli-8.8-executable.jar presto chmod +x presto ./presto --server localhost:8080 You should see the Presto shell: presto> Part 3: Configuring Catalogs in Presto 8.8 Presto’s superpower is its connector architecture. Let’s set up three common catalogs. 1. Hive Connector (for S3 or HDFS) Create etc/catalog/hive.properties :

-- List all catalogs SHOW CATALOGS; -- List schemas in the memory catalog SHOW SCHEMAS FROM memory;