Every cluster will include SQL Server, the Hadoop file system and Spark. As for the name, it’s worth noting that many pundits expected a “SQL Server 2018,” but Microsoft opted to skip a year ...

PySpark development is now fully supported in Visual Studio Code. Through an extension built for the aforementioned purpose, users can run Spark jobs with SQL Server 2019 Big Data Clusters.

Nodes can run as SQL compute nodes, SQL storage nodes or HDFS data nodes. In the HDFS case, SQL Server and Apache Spark run co-located, in the same container. All of this interoperability is ...

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 ...

Spark SQL, part of Apache Spark, is used for structured data processing by running SQL queries on Spark data. Srini Penchikala discusses Spark SQL module & how it simplifies data analytics using SQL.

Databricks, the primary commercial steward behind the popular open source Apache Spark project, published a new report indicating the technology is still red-hot, driven by more use of SQL, streaming ...

Fast, flexible, and developer-friendly, Apache Spark is the leading platform for large-scale SQL, batch processing, stream processing, and machine learning.

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 ...

According to market research from International Data Corporation (IDC), Microsoft's SQL Server product is slowly catching up to Oracle and IBM in relational database management system (RDBMS ...