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Wednesday, May 11 • 5:10pm - 6:00pm
Less Is More: Doubling Storage Efficiency with HDFS Erasure Coding - Zhe Zhang, LinkedIn & Kai Zheng, Intel

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Ever since its creation, HDFS has been relying on data replication to shield against most failure scenarios. However, with the explosive growth in data volume, replication is getting expensive: the default 3x replication scheme incurs a 200% storage overhead. Erasure coding (EC) uses far less storage space while still providing the same level of fault tolerance. Under typical configurations, EC reduces the storage cost by ~50% compared with 3x replication.

In this talk we will introduce the design and implementation of HDFS-EC, and recommended use cases. We will also provide preliminary performance results. Equipped with the Intel ISA-L library, HDFS-EC has largely eliminated the computational overhead in codec calculation. Under sequential I/O workloads, it achieves twice the throughput compared with 3x replication, by performing striped I/O to multiple DataNodes in parallel.

Speakers
ZZ

Zhe Zhang

LinkedIn
Zhe Zhang is a software engineer at LinkedIn working on Hadoop. He’s an Apache Hadoop Committer and author of HDFS Erasure Coding. | | Before joining LinkedIn in Feburary 2016 Zhe was an engineer in Cloudera HDFS team. Prior to that he worked at the IBM T. J. Watson Research Center as a research staff member, where he worked on cloud computing technologies with a focus on SaaS/PaaS offerings. At IBM Research Zhe co-chaired the... Read More →
KZ

Kai Zheng

Kai is a senior software engineering in Intel that works in big data and security fields for quite a few of years. He is a key Apache Kerby initiator, Directory PMC member and Apache Hadoop committer.


Wednesday May 11, 2016 5:10pm - 6:00pm
Georgia B

Attendees (29)