As the first meetup after the rebranding from Tachyon to Alluxio, we will first present exciting updates and new developments of the community. Followed by many new features and improvements in Alluxio 1.0 and 1.1 releases.
Tag: big data
O’Reilly – An Alluxio tour to any data scientist, developer or system administrator looking to improve the performance of their workloads, develop applications with Alluxio, or deploy and manage Alluxio clusters.
DataDriven NYC 2016 – In the past year, the Alluxio project experienced a tremendous improvement in performance and scalability and was extended with key new features including tiered storage, transparent naming, and unified namespace. At the same time, the Alluxio ecosystem has expanded to include support for more under storage systems and computation frameworks.
Strata+Hadoop World 2016 – Baidu deployed Alluxio to accelerate its big data analytics workload. Bin Fan and Haojun Wang explain why Baidu chose Alluxio, as well as the details of how they achieved a 30x speedup with Alluxio in their production environment with hundreds of machines. Based on the success of the big data analytics engine, Baidu is currently expanding the Alluxio and Spark infrastructure to accelerate other applications, such as machine learning.
Strata+Hadoop World 2016 – Tachyon, a memory-centric fault-tolerant distributed storage system. An introduction of architecture, performance evaluation, and real world use cases.
Tachyon presents two talks at Strata + Hadoop World Singapore: Interactive data analytics with Spark on Tachyon in Baidu, and Make Tachyon ready for next-gen data center platforms with NVM
ODSC West 2015 – Tachyon, a memory-centric fault-tolerant distributed storage system. An introduction of architecture, performance evaluation, and real world use cases.
Tachyon: A reliable memory-centric distributed storage system presentation by founder Haoyuan Li.
We introduce Tachyon, a memory centric fault-tolerant distributed file system, which enables reliable file sharing at memory-speed across cluster frameworks, such as Spark and MapReduce.