Mapr Technologies, Inc.

Hewlett Packard Enterprise Development LP

Arvind Arun Pande

Chandra Guru Kiran Babu Sanapala

Uppaluri Vijaya Saradhi

Vivekanand Vellanki

Amit Ashoke Hadke

Mandayam C Srivas

Pindikura Ravindra

Lohit Vijaya Renu

Sathya Kavacheri

Premkumar Jonnala

Rajesh Boddu

Giri Prasad Reddy Desireddygari

Ashish Sangwan

Kanishk Rastogi

Nikhil Bhupale

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 file server receives a request for data from a user device. The data is represented at the file server by a virtual cluster descriptor. The file server queries an identifier map using an identifier of the virtual cluster descriptor. Responsive to the identifier map indicating that the requested data is stored at a location remote from the file server, the file server accesses a cold tier translation table that stores a mapping between an identifier of each of a plurality of virtual cluster descriptors and a storage location of data associated with the respective virtual cluster descriptor. The cold tier translation table is queried using the identifier of the virtual cluster descriptor to identify a storage location of the requested data, and the data is loaded to the file server from the identified storage location.

Tiered storage in a 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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Mumbai, India

Arvind Arun Pande