top of page



Presto Tool for Big Data Managing

Many companies use multiple data warehouses based on different technologies. Analyzing the data, data engineers have to combine it from all sources. Moving data takes time and requires various transformations. When starting to explore, developers often do not know what kind of data will have value and what is the correct structure of the data store. Presto technology helps users request data from all sources without moving it.

What is a Presto Tool?

Presto is an open-source SQL query system that can simultaneously handle fast queries on large amounts of information in distributed data arrays. It is optimized for interactive, low-latency queries. Scales to support analytical applications that work with multiple petabytes of information in data stores and other repositories.

Purpose of Presto

Presto is a tool designed to efficiently query vast amounts of data using distributed queries. When working with terabytes or petabytes of data, developers often use tools that interact with Hadoop and HDFS. Presto was made as an alternative to frameworks that request HDFS using MapReduce job pipelines such as Hive or Pig, but it is not limited to access to HDFS. This software can be extended for use in various data sources, including traditional relational databases and other data sources.

Presto was developed to process data warehouses and prepare analytics: data analysis, big data consolidation, and reporting.

Functions of Presto

Presto includes the following functions:

• support data queries in Hive, various databases, and proprietary information stores;

• the ability to combine data from multiple sources into a single query;

• Query response time is usually less than a second to a few minutes.

Architecture of Presto

The Presto architecture is similar to the classic database management system using cluster computing. There are two types of Presto servers: coordinators and workers.

Presto Coordinator is the server responsible for parsing operators, scheduling queries, and managing Presto work nodes. The client connects to the nodes to submit execution requests. Each Presto system must have a Presto coordinator along with one or more Presto workers.

The coordinator monitors the activity of each worker and coordinates the request execution. It creates a logical query model that includes a series of steps, which are then translated into a series of related tasks performed on the Presto worker cluster.

The Presto worker is a server in the Presto system responsible for performing tasks and processing data. Work nodes extract data from connectors and exchange intermediate data with each other. The coordinator is responsible for obtaining results from workers and returning the final results to the client.

Advantages of Presto

Presto offers its users benefits such as:

• Specialized SQL operations

• Easy installation and debugging

• Simple storage abstraction

• Rapidly scales petabytes of low latency data.

Presto is a great tool to explore a company's data without moving anything. It is advantageous at the beginning of the data analysis process when users are not yet sure what data should be in the data store or data lake and need to experiment. Presto's analytical capabilities enable users to maximize business value.

13 views0 comments


bottom of page