In this session at Performance Summit 2021 on September 30th, Luca Chiabrera (Head of Customer Success and Sales Engineering at Akamas) describes how Akamas ML-based optimization helps to tailor Google Dataproc to reduce Spark execution time and cut the bill. Dataproc is a
Google Dataproc is a fully-managed service that hosts open-source distributed processing platforms such as Apache Spark, Presto, and Apache Hadoop on Google Cloud. Dataproc provides the flexibility to manage and configure clusters of varying size, on-demand. However, even with Dataproc users
Big data applications often offer relevant opportunities for gains both in terms of performance and of cost reduction. Typically, the underlying infrastructure – whether on-premise or on cloud – is both inefficient and over-provisioned to ensure a good performance vs
The big data analytics market is growing fast, driven by the rapid increase in volume and complexity of enterprise data in virtually every industry. Leading among analytics engines and frameworks, Apache Spark features greater speed and scalability compared to many
During the Neotys Jurassic PAC 2020 virtual conference, Luca Cavazzana (Software Engineer at Akamas) explained how Akamas uses AI techniques to find the optimal configuration for Spark applications. He presented a study where Akamas tuned both Apache Spark parameters and EC2 cluster size, finding
Experience the benefits of Akamas AI-powered optimization. No strings attached, no commitments, no sales calls.