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.

But Spark’s affinity for rapid iteration soon drew the attention of data scientists working to fine-tune machine learning algorithms. With the addition of a SQL layer, Spark would excel with ...

Apache Spark has released version 1.3 of their project. The main improvements are the addition of the DataFrames API, better maturity of the Spark SQL, as well as a number of new methods added to ...

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 ...

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 ...

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 ...

Apache Spark Definition: Big data as the main application Apache Spark is an open source big data processing framework built to perform sophisticated analysis and designed for speed and ease of use.

Apache Spark, the extremely popular data analytics execution engine, was initially released in 2012. It wasn’t until 2015 that Spark really saw an uptick in support, but by November 2015, Spark ...

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 ...

Another feature sported by Spark, Spark SQL, which is only in alpha at the moment, allows SQL-like queries to be run against data stored in Apache Hive. Extracting data from Hadoop via SQL queries ...