Реализация сервиса для выполнения Apache Spark задач и создания Apache Spark кластеров на основе Openstack Sahara
In this paper the problem of creating virtual clusters in clouds for big data analysis with Apache Hadoop and Apache Spark is discussed. Existing methods for Apache Spark clusters creation are described in this work. Also the implemented solution for building Apache Spark clusters and Apache Spark jobs execution in Openstack environment is described. The implemented solution is a modification for OpenStack Sahara project and it was featured in Openstack Liberty release.
In this paper the problem of creating virtual clusters in clouds for big data analysis with Apache Hadoop and Apache Spark is discussed. Both clouds and MapReduce models are popular nowadays for a bunch of reasons: cheapness and efficient big data analysis respectively. For these thoughts, having an open source solution for building clusters is important. The article gives an overview on existing methods for Apache Spark cluster creation in clouds. We consider two open source cloud engines OpenStack and Eucalyptus and the most popular proprietary cloud service Amazon Web Services and examine cloud related features presented by these systems. Afterwards, we regard possible ways of creating virtual clusters for big data processing in OpenStack and describe their pros and cons. In the second part we describe in details one of these solutions that uses service Sahara. Sahara represents a cluster management system for OpenStack and it is used for setting up virtual clusters and executing MapReduce jobs. Sahara did not support contemporary versions of Apache Spark. The article introduces the results of our work that led to a Sahara modification, describes its idea and implementation details. By virtue of our modification, Sahara is able to create and use virtual clusters with contemporary versions of Apache Spark in OpenStack clouds.
In this paper we consider an association problem with constraints for two dynamically enlarging tables. We consider a base full association algorithm and propose a partial association algorithm that improves efficiency of the base algorithm. We implement and evaluate the algorithms in Apache Spark for a particular case on the cluster with Angara interconnect.
Video broadcasts on the Internet have become a commonplace and increasingly find their audience, supported by popular video services and social networks. But there are tasks, that require content delivery network (CDN), which lead to extra expences, and moreover, does not give sufficient flexibility and limits personalization of the broadcasts. This paper presents the principles of creating a flexible and scalable streaming content delivery network, created automatically for each individual broadcast over existing infrastructure of the cloud virtual machine hosting providers. The report originates from a commercial project dedicated to creation of media-content delivery network, currently being at development stage.
A model for organizing cargo transportation between two node stations connected by a railway line which contains a certain number of intermediate stations is considered. The movement of cargo is in one direction. Such a situation may occur, for example, if one of the node stations is located in a region which produce raw material for manufacturing industry located in another region, and there is another node station. The organization of freight traﬃc is performed by means of a number of technologies. These technologies determine the rules for taking on cargo at the initial node station, the rules of interaction between neighboring stations, as well as the rule of distribution of cargo to the ﬁnal node stations. The process of cargo transportation is followed by the set rule of control. For such a model, one must determine possible modes of cargo transportation and describe their properties. This model is described by a ﬁnite-dimensional system of diﬀerential equations with nonlocal linear restrictions. The class of the solution satisfying nonlocal linear restrictions is extremely narrow. It results in the need for the “correct” extension of solutions of a system of diﬀerential equations to a class of quasi-solutions having the distinctive feature of gaps in a countable number of points. It was possible numerically using the Runge–Kutta method of the fourth order to build these quasi-solutions and determine their rate of growth. Let us note that in the technical plan the main complexity consisted in obtaining quasi-solutions satisfying the nonlocal linear restrictions. Furthermore, we investigated the dependence of quasi-solutions and, in particular, sizes of gaps (jumps) of solutions on a number of parameters of the model characterizing a rule of control, technologies for transportation of cargo and intensity of giving of cargo on a node station.
Event logs collected by modern information and technical systems usually contain enough data for automated process models discovery. A variety of algorithms was developed for process models discovery, conformance checking, log to model alignment, comparison of process models, etc., nevertheless a quick analysis of ad-hoc selected parts of a journal still have not get a full-fledged implementation. This paper describes an ROLAP-based method of multidimensional event logs storage for process mining. The result of the analysis of the journal is visualized as directed graph representing the union of all possible event sequences, ranked by their occurrence probability. Our implementation allows the analyst to discover process models for sublogs defined by ad-hoc selection of criteria and value of occurrence probability
The geographic information system (GIS) is based on the first and only Russian Imperial Census of 1897 and the First All-Union Census of the Soviet Union of 1926. The GIS features vector data (shapefiles) of allprovinces of the two states. For the 1897 census, there is information about linguistic, religious, and social estate groups. The part based on the 1926 census features nationality. Both shapefiles include information on gender, rural and urban population. The GIS allows for producing any necessary maps for individual studies of the period which require the administrative boundaries and demographic information.
Existing approaches suggest that IT strategy should be a reflection of business strategy. However, actually organisations do not often follow business strategy even if it is formally declared. In these conditions, IT strategy can be viewed not as a plan, but as an organisational shared view on the role of information systems. This approach generally reflects only a top-down perspective of IT strategy. So, it can be supplemented by a strategic behaviour pattern (i.e., more or less standard response to a changes that is formed as result of previous experience) to implement bottom-up approach. Two components that can help to establish effective reaction regarding new initiatives in IT are proposed here: model of IT-related decision making, and efficiency measurement metric to estimate maturity of business processes and appropriate IT. Usage of proposed tools is demonstrated in practical cases.