Join us June 24 in Menlo Park for our next meetup! We’ll have 3 valuable talks, a delicious BBQ dinner and amazing summertime-themed raffle prizes! This free event is sponsored by GridGain Systems and Oracle.
This Alluxio Meetup features a chance to interact with other Alluxio users and developers, as well as three talks. Thanks to our joint host Data Council!
Carlos Queiroz of DBS presents on how to decouple compute and storage for data workloads using Alluxio.
[Talk 1] A “how-to” presentation for building a real-time alerting, analytics and reporting system (at scale). With Denis Magda, vice president of the Apache Ignite PMC and director of product management at GridGain Systems. And Viktor Gamov, developer advocate at Confluent.
[Talk 2] Using In-Memory technology for real time analytics. With Andy Rivenes is a Product Manager at Oracle for Database In-Memory.
[Talk 3] Feeding data to the Kubernetes beast: bringing data locality to your containerized big data workloads. With Bin Fan, founding engineer of Alluxio, Inc. and PMC member of Alluxio open source project.
Hear how DBS Bank is taking a new approach to making data-intensive compute independent of the storage. They will share the challenges as well as the new technology stack that includes technologies like Spark, Alluxio and object stores.
This technical salon will focus on big data, storage, database and Alluxio application practice, and invite Tencent technical experts and industry technical experts to share the basic principles of Alluxio system, big data system architecture, database application operation and maintenance, AI computer. Themes such as visual technology and landing practice bring rich practical content and experience exchange.
In this meetup, Bin Fan from Alluxio and Wenbo Zhao from Two Sigma co-presented a reference stack (running Alluxio as a data access layer for Apache Spark) that can enable independent and separated compute and storage for big data and machine learning workloads. Two Sigma’s use case is a great example of the benefits of this reference stack for bursting machine learning computation to the public cloud while still being able to access data stored on-premise efficiently. Their data scientists want to leverage the public cloud as a scalable and elastic computation resource to speed up the end-to-end model training process. By using Alluxio as the data access layer co-located with compute in the cloud, their researchers achieved 10x faster end to end processing, which enables them to perform more iterations on their models.
Wenbo Zhao (Two Sigma) and Bin Fan (Alluxio) will be presenting on how Two Sigma uses Alluxio to make data-intensive compute independent of the storage beneath.
Tachyon is a memory-centric fault-tolerant distributed storage system, which enables reliable file sharing at memory-speed. It originated from AMPLab, UC Berkeley in 2012, the same lab produced Apache Mesos and Apache Spark. Soon later, it became an open source project and is deployed at many companies. Since then, Tachyon has attracted more than 200 contributors from over 50 institutions. In 2015, company Tachyon Nexus was founded to further accelerate the development of Tachyon. In this talk, we will review Tachyon’s new features, deployments, and developments in 2015, and look into 2016.