Apache Spark has become the de facto standard for processing data at scale, whether for querying large datasets, training machine learning models to predict future trends, or processing streaming data ...

For data engineers looking to leverage Apache Spark™'s immense growth to build faster and more reliable data pipelines, Databricks is happy to provide The Data Engineer's Guide to Apache Spark. This ...

Here’s an image for you. There is no such thing as a data lake. The multi-petabyte storage racks nearly overflowing with unstructured and semi-structured data that are being built by hyperscalers, ...

Databricks Inc., the primary commercial steward behind the popular open source Apache Spark data processing framework for Big Data analytics, published a new report indicating the technology is still ...

At the heart of Apache Spark is the concept of the Resilient Distributed Dataset (RDD), a programming abstraction that represents an immutable collection of objects that can be split across a ...

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 ...

Don’t look now but Apache Spark is about to turn 10 years old. The open source project began quietly at UC Berkeley in 2009 before emerging as an open source project in 2010. For the past five years, ...

Apache Spark and Apache Hadoop are both popular, open-source data science tools offered by the Apache Software Foundation. Developed and supported by the community, they continue to grow in popularity ...

Reactive programming company Typesafe today released a survey that confirms the high adoption rate of Apache Spark, an open source Big Data processing framework that improves traditional Hadoop-based ...