Presto in Data Lake

Presto is an open-source, distributed SQL query engine designed for interactive analytics. It is often used in conjunction with data lakes to query and analyze large volumes of data stored in various formats without the need for extensive data movement or transformation.

Key Features:

• Distributed Query Processing: Presto enables distributed query processing, allowing it to efficiently query and analyze data across multiple nodes in a cluster.
• Support for Multiple Data Sources: It can seamlessly query data from various data sources, including Hadoop Distributed File System (HDFS), Amazon S3, relational databases, and more.
• Schema-On-Read: Similar to other technologies in the big data ecosystem, Presto adopts a schema-on-read approach, providing flexibility in working with semi-structured and unstructured data.
• High Performance: Presto is designed for high-performance interactive queries, making it suitable for ad-hoc analysis and exploration of large datasets.
• SQL Compatibility: Presto supports standard SQL syntax, making it accessible to users familiar with SQL for querying and analyzing data.

Components:

The main components of Presto include:

• Coordinator: The Presto coordinator is responsible for receiving SQL queries, planning query execution, and coordinating tasks across worker nodes.
• Worker Nodes: Worker nodes execute tasks as directed by the coordinator. They store data locally and perform distributed processing.
• Catalog: Presto uses catalogs to interface with different data sources. Each catalog represents a connector to a specific data storage system.

Usage in Data Lakes:

Presto is commonly used in data lake environments to perform fast and interactive queries on large-scale data stored in a variety of formats within the data lake. It allows users to explore and analyze data without the need for complex ETL processes.

For more detailed information, refer to the official Presto documentation.