TWO SIGMA OPEN SOURCE 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.
The rise of computation-intensive workloads and the adoption of the cloud has driven organizations to adopt a decoupled architecture for modern workloads — one in which compute scales independently from storage. However, while enabling scaling elasticity, it introduces new problems — how do you co-locate data with compute, how do you unify data across multiple remote data centers, how do you keep storage and I/O egress costs down and many more.
In this meetup, the Wenbo and Bin will present a new approach to making data-intensive compute independent of the storage beneath using open source project Alluxio, an open-source distributed file system, which sits between compute and storage layer. Applications like Apache Spark or TensorFlow can then seamlessly access multiple disparate data sources with consistent performance without knowing where the data is actually persisted.
Wenbo will present why Two Sigma needed to disaggregate compute and storage and how they decided to adopt the Spark + Alluxio + HDFS architecture.
Bin will present a deep dive into the Alluxio open source project, a distributed file system, including the reference architecture, the data & metadata paths to serve requests from compute from remote understores and the compute API’s supported for accessing data from Alluxio.
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Presentations
Use Alluxio to Unify Storage Systems in Suning
Suning is one of the leading commercial enterprises in China with two public companies in China and Japan respectively. It uses Alluxio to unify storage systems and manage multiple HDFS clusters.
STRATA DATA CONFERENCE LONDON 2018
JD.com is China’s largest online retailer and its biggest overall retailer, as well as the country’s biggest internet company by revenue. Currently, JD.com’s BDP platform runs more than 400,000 jobs (15+ PB) daily, on a system with more than 15,000 cluster nodes and a total capacity of 210 PB.
Alluxio, formerly Tachyon, is the world’s first system that unifies disparate storage systems at memory speed. In the big data ecosystem, Alluxio lies between computation frameworks or jobs and various kinds of storage systems. Additionally, Alluxio’s memory-centric architecture enables data access orders of magnitude faster than existing solutions.
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 HDFSURLs 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.
Alluxio in MOMO: Accelerating Ad Hoc Analysis
From our friends at MOMO
MOMO, a leading pan-entertainment social platform in China, has deployed Alluxio to accelerate ad-hoc query analytics. In the course of evaluating the best fit for Alluxio in their infrastructure they conducted several performance tests to understand how ad-hoc query analytics behaved in several scenarios. These tests give real-world insight to the performance benefits Alluxio provides. The MOMO findings include:
- With Alluxio, performance was improved 3-5x over the current mode
- Even when initially reading ‘cold’ data Alluxio delivered superior performance in most cases
- Alluxio can effectively scale-out to improve performance as requirements grow