This meetup presents an overview of the motivations and design decisions behind the major changes in the Alluxio 2.0 release, and Real-time Data Processing for Sales Attribution Analysis with Alluxio, Spark and Hive at VIPShop.
Welcome to the first event of the Cloud, Data, & Orchestration Austin Meetup! This meetup will feature two talks and an opportunity to engage with other data engineers, developers, and Alluxio users. Thanks to Bazaarvoice for hosting!
Alluxio maintainer and founding engineer Calvin Jia presents on Scalable Filesystem Metadata Services with RocksDB at the RocksDB meetup at Twitter.
This talk shares our design, implementation and optimization of Alluxio metadata service to address the scalability challenges, focusing on how to apply and combine techniques including tiered metadata storage (based on off-heap KV store RocksDB), fine-grained file system inode tree locking scheme, embedded state-replicate machine (based on RAFT), exploration and performance tuning in the correct RPC frameworks (thrift vs gRPC) and etc.
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!
[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.
The goal is to make Alluxio accessible to an even wider set of users through a focus on security, new language bindings, and further increased stability. In addition, the team is working on new APIs to allow applications to access data more efficiently and manage data across different under storage systems.
In the active community development of the past year, Alluxio has greatly improved its read and write performance, scalability and user experience. In addition, in terms of functionality, Alluxio has added a number of new features, such as scalable tiered storage, transparent UFS data reading and writing, unified namespaces, and more. These features bring more value to Alluxio users and more efficient and convenient cluster storage management.
The Alluxio project has greatly improved system performance, Scalability and user experience, and added a series of new features, including scalable tiered storage, transparent UFS data reading and writing, unified namespaces, and more. Easy to use with Alluxio. At the same time, the Alluxio ecosystem has expanded to support different storage systems and computing frameworks. Alluxio now supports a variety of storage systems, including Amazon S3, Google Cloud Storage, Gluster, Ceph, HDFS, NFS and OpenStack Swift, as well as big data processing frameworks such as Spark, MapReduce, Flink and more. These integrations allow Alluxio to manage and help with more and more complex data.