O'Reilly、Cloudera 主办
Make Data Work

使用开源的Alluxio解耦计算与存储的架构 (The architecture of decoupling compute and storage with open source Alluxio)

此演讲使用中文 (This will be presented in Chinese)

Yupeng Fu (Alluxio)
11:15–11:55 Saturday, 2017-07-15
数据工程和架构 (Data engineering and architecture)
地点: 多功能厅6A+B(Function Room 6A+B) 观众水平 (Level): Non-technical

必要预备知识 (Prerequisite Knowledge)

A basic understanding of big data platform concepts

您将学到什么 (What you'll learn)

Understand the benefits of decoupling storage and computation

描述 (Description)


Frameworks like Spark and MapReduce are increasingly being widely deployed at enterprise productions. As a result, efficient and flexible compute and storage architecture has become a hot topic for debate among both IT and LOB practitioners. Although there are good reasons to run compute in a traditional hyperconverge environment as a part of a data lake implementation, the decoupling of storage and computation is becoming more and more popular, as O’Reilly pointed out in a recent 2017 trend post. Recently Alluxio, IBM, Huawei, EMC, and Red Hat teams joined together to examine real-world application examples and provide joint solutions.

Yupeng Fu shares production best practices and solutions to best utilize CPUs, memory, and different tiers of disaggregated compute and storage systems to build out a multitenant high-performance platform that addresses real-world business demands. Along the way, Yupeng also outlines decision factors and considerations, such as application workload patterns, data locality, cost of infrastructure, network bandwidth, and cloud deployment, to name just a few.

Photo of Yupeng Fu

Yupeng Fu


Yupeng Fu is a software engineer at Alluxio and a PMC member of the Alluxio open source project. Previously, Yupeng worked at Palantir, where he led the efforts to build the company’s storage solution. Yupeng holds a BS and an MS from Tsinghua University and has completed coursework toward a PhD at UCSD.



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