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Distributed File System Metadata and its Applications

Time: Fri 2020-12-18 09.00

Location:, Sal C, Electrum, Kistagången 16, Stockholm (English)

Subject area: Information and Communication Technology

Doctoral student: Mahmoud Ismail , Programvaruteknik och datorsystem, SCS

Opponent: Luis Veiga, Instituto Superior Técnico (U.Lisboa) & INESC-ID

Supervisor: Jim Dowling, Datavetenskap; Seif Haridi, Programvaruteknik och datorsystem, SCS

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Distributed hierarchical file systems typically decouple the storage and serving of the file metadata from the file contents (file system blocks) to enable the file system to scale to store more data and support higher throughput. We designed HopsFS to take the scalability of the file system one step further by also decoupling the storage and serving of the file system metadata. HopsFS is an open-source, next- generation distribution of the Apache Hadoop Distributed File System (HDFS) that replaces the main scalability bottleneck in HDFS, the single-node in-memory metadata service, with a distributed metadata service built on a NewSQL database (NDB). HopsFS stores the file system’s metadata fully normalized in NDB, then it uses locking primitives and application-defined locks to ensure strongly consistent metadata.In this thesis, we leverage the consistent distributed hierarchical file system meta- data provided by HopsFS to efficiently build new classes of applications that are tightly coupled with the file system as well as to improve the internal file system operations. First, we introduce hbr, a new block reporting protocol for HopsFS that removes a scalability bottleneck that prevented HopsFS from scaling to tens of thousands of servers. Second, we introduce HopsFS-CL, a highly available cloud-native distribution of HopsFS that deploys the file system across Availability Zones in the cloud while maintaining the same file system semantics. Third, we introduce HopsFS-S3, a highly available cloud-native distribution of HopsFS that uses object stores as a backend for the block storage layer in the cloud while again maintaining the same file system semantics. Fourth, we introduce ePipe, a databus that both creates a consistent change stream for HopsFS and eventually delivers the correctly ordered stream with low latency to downstream clients. That is, ePipe extends HopsFS with a change-data-capture (CDC) API that provides not only efficient file system notifications but also enables polyglot storage for file system metadata. Polyglot storage enables us to offload metadata queries to a more appropriate engine - we use Elasticsearch to provide a free-text search of the file system namespace to demonstrate this capability. Finally, we introduce Hopsworks, a scalable, project-based multi-tenant big data platform that provides support for collaborative development and operations for teams through extended metadata.