Vmware, Inc.

Yizheng Chen

Wenguang Wang

Li Zhou

Christos Karamanolis

Sandeep Madhav Uttamchandani

Jian Zhao

Jin Feng

Tao Xie

Zhaohui Guo

Zhou Huang

Haoran Zheng

Aditya Kotwal

A distributed storage system, such as a distributed storage system in a virtualized computing environment, stores data in storage nodes as immutable key-value entries. A coordinator storage node creates a key-value entry and attempts to store the key-value entry in the coordinator storage node and in neighbor storage nodes. If the storage of the key-value entry in the in the coordinator storage node and in the neighbor storage node is successful, the coordinator storage node pushes the key-value entry to other storage nodes in the distributed storage system for storage as replicas.

Storage of key-value entries in a distributed storage system

A given host machine in a virtualization system having a virtual distributed storage system may receive an iSCSI protocol packet from a computer system separate from the given host machine. Processing the iSCSI protocol may include accessing distributed storage device (iSCSI target) comprising storage connected to the two or more host machines in the virtualization system. The given host machine may generate an outbound iSCSI protocol packet comprising return data received from the target and send the outbound iSCSI protocol packet to the computer system.

Distributed iSCSI target for distributed hyper-converged storage

A control module is introduced to communicate with an application workload scheduler of a distributed computing application, such as a Job Tracker node of a Hadoop cluster, and with the virtualized computing environment underlying the application. The control module periodically queries for resource consumption data, such as CPU utilization, and uses the data to calculate how MapReduce task slots should be allocated on each task node of the Hadoop cluster. The control module passes the task slot allocation to the application workload scheduler, which honors the allocation by adjusting task assignments to task nodes accordingly. The task nodes may also activate and deactivate task slots according to the changed slot allocation. As a result, the distributed computing application is able to scale up and down when other workloads sharing the virtualized computing environment change.

Adaptive task scheduling of Hadoop in a virtualized environment

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Sunnyvale, CA, United States of America

Yizheng Chen