In theory, data lakes sound like a good idea: One big repository to store all data your organization needs to process, unifying myriads of data sources. In practice, most data lakes are a mess in one ...

In the ecosystem of big data technology, Apache Spark has become one of the most mainstream distributed computing frameworks ...

Originally created at U.C. Berkeley’s AMPLab in 2009, Apache Spark is a “lightning-fast unified analytics engine” designed for large-scale data processing. It works with cluster computing platforms ...

Overview of Core Features and Architecture of Spark 3.x Before starting practical work, we must first understand the core ...

In this annual report, the InfoQ editors discuss the current state of AI, ML, and data engineering and what emerging trends you as a software engineer, architect, or data scientist should watch. We ...

Big data adoption has been growing by leaps and bounds over the past few years, which has necessitated new technologies to analyze that data holistically. Individual big data solutions provide their ...

Apache Spark is one of the most popular open source projects in the world, and has lowered the barrier of entry for processing and analyzing data at scale. We asked some of the leaders in the big data ...

Apache Spark 3.0 is now here, and it’s bringing a host of enhancements across its diverse range of capabilities. The headliner is an big bump in performance for the SQL engine and better coverage of ...

Hadoop, Spark and Kafka have already had a defining influence on the world of big data, and now there’s yet another Apache project with the potential to shape the landscape even further: Apache Arrow.