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 ...

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 ...

在 6 月 10 日至 12 日于美国旧金山举行的 Databricks Data+AI 峰会上，Databricks 宣布将 Delta Live Tables（DLT）背后的技术贡献给 Apache Spark 项目，这个项目中，它将被称为 Spark 声明式管道（Spark Declarative Pipelines）。这一举措将使 Spark 用户更容易开发和维护流式管道，并 ...

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 ...

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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, ...

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 ...

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 ...