The latest Alluxio meetups, webinars, conferences and more
Announcing the first Data Orchestration Summit in November 2019! This Summit brings together data engineers, cloud engineers, data scientists, and industry thought leaders who are solving data problems at the intersection of cloud, AI, and data.
This tech talk will share approaches to burst data to the cloud along with
how Alluxio can enable “zero-copy” bursting of Spark workloads to cloud data services like EMR and Dataproc. Learn how DBS bank uses Alluxio to solve for limited on-prem compute capacity.
In this online meetup, we will present the benefits of the fast analytics stack of Spark on Alluxio, and dive into China Unicom’s use case of leveraging Spark and Alluxio to process massive amounts of mobile data.
In this presentation, Ryte’s Chapter lead engineer, Danny Linden, shows why & how we solve some challenging technical issues, improve the speed, and reduce costs of our AWS EMR Hadoop & Presto -Backend with Alluxio to an awesome level!
In this webinar, Adit will present this new approach of bringing data locality to data-intensive compute workloads in Kubernetes environments, and demo how to setup and run Apache Spark and Alluxio in Kubernetes.
Hear about Bazaarvoice’s use case leveraging Apache Spark, Hive, and Alluxio on S3. And learn how to set up Hive with Alluxio so that Hive jobs can seamlessly read/write to S3.
In this presentation, Vitaliy Baklikov from DBS Bank and Dipti Borkar from Alluxio will share how DBS Bank has built a modern big data analytics stack leveraging an object store as persistent storage even for data-intensive workloads and how it uses Alluxio to orchestrate data locality and data access for Spark workloads. In addition, deploying Alluxio to access data, solves many challenges that cloud deployments bring with separated compute and storage.
Alluxio will be at Open Core Summit SF 2019. Founder & CTO Haoyuan Li gives keynote on state of open source across regions.
How to set up EMR Spark and Hive with Alluxio so jobs can seamlessly read from and write to your S3 data lake.