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 ...

The Apache Spark community last week announced Spark 3.2, a significant new release of the distributed computing framework. Among the more exciting features are deeper support for the Python data ...

With Apache Spark Declarative Pipelines, engineers describe what their pipeline should do using SQL or Python, and Apache Spark handles the execution.

Spark can be deployed in a variety of ways, provides native bindings for the Java, Scala, Python, and R programming languages, and supports SQL, streaming data, machine learning, and graph processing.

Fastest Growing Areas in Spark (source: Databricks) "In Spark, a DataFrame is a distributed collection of data organized into named columns," the company said at the time. "It is conceptually ...

Both HANA and Spark can speak SQL, but with Vora SAP is not only making Spark speak a better and richer dialect of SQL – one that has support for the data hierarchies that are required for online ...

But Spark has also had its share of impedance mismatch issues, such as making R and Python programs first-class citizens, or adapting to more compute-intensive processing of AI models.

But there is more! SQL Server 2019 will come with built-in support for Spark and the Hadoop File System. That’s an acknowledgement of the popularity of these open-source tools, as well as the ...