Production Spark and Tachyon Use Cases

Spark Summit Europe *

During the past several years, Spark has significantly changed the landscape of big data computing. It improves performance of various applications dramatically. However, in certain Spark use cases, the bottleneck is in the I/O stack. In this talk, we will introduce Tachyon, a distributed memory-centric storage system. In addition, we will talk about several production use cases where Tachyon further improves Spark applications’ performance by orders of magnitude.

Deep learning architecture using Tachyon and Spark & Tachyon New Features

Bay Area Meetup *

In the presentation, we will explore several potential industry use cases enabled by the new features. One-click cluster deployment enables users to experiment and prototype with Tachyon on AWS, launching not only Tachyon but also the computation framework and storage system of their choice. Mounting of multiple under storage systems and transparent naming enables more exciting use cases for Tachyon users.

Fast big data analytics and machine learning using Alluxio and Spark in Baidu

Strata+Hadoop World San Jose *

A few months ago, 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.

How Alluxio (formerly Tachyon) brings a 300x performance improvement to Qunar’s streaming processing

Strata+Hadoop World Singapore *

Alluxio is the first memory-speed virtual distributed storage system in the world. It unifies the interface between the various computing frameworks and under storages. Data access can be several magnitude faster because of Alluxio’s memory-centric architecture. In addition, Alluxio’s tiered storage, unified namespace, flexible file API, web UI, and command-line tools increase the usability in different application scenarios.
Qunar has been running Alluxio in production for over a year. Lei Xu explores how stream processing on Alluxio has led to a 16x performance improvement on average and 300x improvement at service peak time on workloads at Qunar.

How to Use Alluxio to improve Spark and Hadoop HDFS Performance of Data Access and System Reliability [Chinese]

Database Technology Conference China 2017 *

China Unicom is one of the five largest telecom operators in the world. China Unicom’s booming business in 4G and 5G networks has to serve an exploding base of hundreds of millions of smartphone users. This unprecedented growth brought enormous challenges and new requirements to the data processing infrastructure. The previous generation of its data processing system was based on IBM midrange computers, Oracle databases, and EMC storage devices. This architecture could not scale to process the amounts of data generated by the rapidly expanding number of mobile users. Even after deploying Hadoop and Greenplum database, it was still difficult to cover critical business scenarios with their varying massive data processing requirements. The complicated the architecture of its incumbent computing platform created a lot of new challenges to effectively use resources.

Guardant Health: Fast, scalable, data processing with Alluxio, Mesos, and Minio

Alluxio and Mesos Joint Meetup *

Speed is usually a key factor when analyzing large amounts of data. Alluxio enables analytics applications, such as Apache Spark, to retrieve stored data at memory speeds. DC/OS makes it easy to deploy distributed programs (such as Alluxio and Spark) and containers across large clusters.
In this talk, we will first discuss the development of the DC/OS Alluxio package, which deploys Alluxio on top of DC/OS, and then then demo the deployment a complete analytics stack, both with and without Alluxio, in order to see the benefits Alluxio provides.

Alluxio Exploration And Application Practice Meetup

Beijing Meetup *

In this issue, the Drip Technology Salon and the Alluxio community invited the core engineers of Didi Travel, Alluxio, Kyligence, JD.com, and Tencent to revolve around Alluxio’s position and design philosophy in the big data ecosystem, architectural features, latest developments, and well-known The company’s production-level environmental application exploration and practice, as well as the experience in the use of the process and other topics, and in-depth participants to share.

Using Alluxio (formerly Tachyon) as a fault-tolerant pluggable optimization component to compute frameworks of JD system

Strata London *

Alluxio has run in JD.com’s production environment on 100 nodes for six months. Mao Baolong, Yiran Wu, and Yupeng Fu explain how JD.com uses Alluxio to provide support for ad hoc and real-time stream computing, using Alluxio-compatible HDFS URLs and Alluxio as a pluggable optimization component. To give just one example, one framework, JDPresto, has seen a 10x performance improvement on average. This work has also extended Alluxio and enhanced the syncing between Alluxio and HDFS for consistency.

Two Sigma Open Source Meetup

New York Meetup *

TSOS meetups focus on the open source projects that Two Sigma cares most about, from projects we generated in-house then open sourced to large external open source projects that we depend on to do our work. This time, 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.