A year later, with Spark 2.0, Zaharia and the Spark community added the concept of Datasets, which is a type-safe object-oriented programming interface based on DataFrames. (The RDD API has been ...

Low-Code Apache Spark and Delta Lake Even though Spark and Delta are the perfect basis for your future data pipeline, and the Data Lakehouse architecture allows us to enable a tremendous amount of new ...

Get the source code for the example applications demonstrated in this article: “Aggregating with Apache Spark.” Created by Ravishankar Nair for JavaWorld.

Spark is the hottest big data tool around, and most Hadoop users are moving towards using it in production. Problem is, programming and tuning Spark is hard. But Pepperdata and Alpine Data bring ...

A year ago, Microsoft enabled .NET developers to work with Apache Spark using C# or F#, instead of Python or Scala. More functionality and performance enhancements have since been layered on. The ...

Set up and use Spark to analyze data contained in Hadoop, Splunk, files on a file system, local databases, and more.

It’s hard to believe, but Apache Spark is turning 10 years old this year, as we wrote about last month. The technology has been a huge success, and become a critical component of many big data ...

This is a comprehensive Apache Hadoop and Spark comparison, covering their differences, features, benefits, and use cases.

I’m seeing that over the past 12 months there’s been almost 10,000 commits of our code into the Apache Spark code base, compared with slightly fewer than 3,000 for doing MapReduce which of course is ...

Low-Code Apache Spark and Delta Lake Historically, the need for cost-effective storage, performant processing, and low-latency querying required a two-tier architecture: a data lake for raw storage of ...