Spark Remote Debugging Hi everybody! I’m a Big Data Engineer @ Agile Lab, a remote-first Big Data engineering and R&D firm located in Italy. Our main focus is to
Spark 3.0: First hands-on approach with Adaptive Query Execution (Part 3) In the previous articles (1)(2), we started analyzing the individual features of Adaptive Query Execution introduced on Spark 3.0.
In the previous article, we started analyzing the individual features of Adaptive Query Execution introduced on Spark 3.0. In particular, the first feature analyzed was “dynamically coalescing shuffle partitions”. Let’s get
Who of you has right now the reasonable certainty that all your Spark jobs are performing at their maximum without wasting more computational resources than necessary? If so, what information
Apache Spark is a distributed data processing framework that is suitable for any Big Data context thanks to its features. Despite being a relatively recent product (the first open-source BSD license was
Apache Spark is the most widely used in-memory parallel distributed processing framework in the field of Big Data advanced analytics. The main reasons for its success are the simplicity of use
Quali sono i framework tipici del mondo Big Data? Perchè Spark è il più diffuso e come viene adottato in contesti industriali? Quali sono gli use case più significativi? Queste
In today’s data intensive society Big Data applications are becoming more and more common. Their success stems from the ability to analyze huge collections of data opening up new business prospectives.
WASP is a framework that enables the development of full stack complex real time applications like IoT for example, complex big data streaming analytics, massive data ingestion or data offload from
Agile Lab unveils its onsite big data training programs!! We want to share knowledge about big data topics, to bring innovation. Right now the focus is on Spark and Cassandra. But we