Mapr Technologies, Inc.

Hewlett Packard Enterprise Development LP

Sathya Kavacheri

Chandra Guru Kiran Babu Sanapala

Uppaluri Vijaya Saradhi

Vivekanand Vellanki

Pindikura Ravindra

Amit Ashoke Hadke

Mandayam C Srivas

Arvind Arun Pande

Lohit Vijaya Renu

A map-reduce compatible distributed file system that consists of successive component layers that each provide the basis on which the next layer is built provides transactional read-write-update semantics with file chunk replication and huge file-create rates. Containers provide the fundamental basis for data replication, relocation, and transactional updates. A container location database allows containers to be found among all file servers, as well as defining precedence among replicas of containers to organize transactional updates of container contents. Volumes facilitate control of data placement, creation of snapshots and mirrors, and retention of a variety of control and policy information. Also addressed is the use of distributed transactions in a map-reduce system; the use of local and distributed snapshots; replication, including techniques for reconciling the divergence of replicated data after a crash; and mirroring.

Map-reduce ready distributed file system

A map-reduce compatible distributed file system that consists of successive component layers that each provide the basis on which the next layer is built provides transactional read-write-update semantics with file chunk replication and huge file-create rates. A primitive storage layer (storage pools) knits together raw block stores and provides a storage mechanism for containers and transaction logs. Storage pools are manipulated by individual file servers. Containers provide the fundamental basis for data replication, relocation, and transactional updates. A container location database allows containers to be found among all file servers, as well as defining precedence among replicas of containers to organize transactional updates of container contents. Volumes facilitate control of data placement, creation of snapshots and mirrors, and retention of a variety of control and policy information. Key-value stores relate keys to data for such purposes as directories, container location maps, and offset maps in compressed files.

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Fremont, CA, United States of America

Sathya Kavacheri