Proceedings of ISP RAS

Deploying Apache Spark virtual clusters in cloud environments using orchestration technologies

O. Borisenko (ISP RAS, Moscow, Russia)
R. Pastukhov (ISP RAS, Moscow, Russia)
S. Kuznetsov (ISP RAS, Moscow, Russia, MSU, Moscow, Russia, MIPT, Dolgoprudny, Russia)


Apache Spark is a framework providing fast computations on Big Data using MapReduce model. With cloud environments Big Data processing becomes more flexible since they allow to create virtual clusters on-demand. One of the most powerful open-source cloud environments is Openstack. The main goal of this project is to provide an ability to create virtual clusters with Apache Spark and other Big Data tools in Openstack. There exist three approaches to do it. The first one is to use Openstack REST APIs to create instances and then deploy the environment. This approach is used by Apache Spark core team to create clusters in propriatary Amazon EC2 cloud. Almost the same method has been implemented for Openstack environments. Although since Openstack API changes frequently this solution is deprecated since Kilo release. The second approach is to integrate virtual clusters creation as a built-in service for Openstack. ISP RAS has provided several patches implementing universal Spark Job engine for Openstack Sahara and Openstack Swift integration with Apache Spark as a drop-in replacement for Apache Hadoop. This approach allows to use Spark clusters as a service in PaaS service model. Since Openstack releases are less frequent than Apache Spark this approach may be not convenient for developers using the latest releases. The third solution implemented uses Ansible for orchestration purposes. We implement the solution in loosely coupled way and provide an ability to add any auxiliary tool or even to use another cloud environment. Also, it provides an ability to choose any Apache Spark and Apache Hadoop versions to deploy in virtual clusters. All the listed approaches are available under Apache 2.0 license.


Apache Spark, Openstack, Amazon EC2, Map-Reduce, HDFS, virtual cluster, cloud computing, Big Data, Apache Ignite


Proceedings of the Institute for System Programming, vol. 28, issue 6, 2016, pp. 111-120.

ISSN 2220-6426 (Online), ISSN 2079-8156 (Print).

DOI: 10.15514/ISPRAS-2016-28(6)-8

Full text of the paper in pdf (in Russian) Back to the contents of the volume