National Repository of Grey Literature 4 records found  Search took 0.00 seconds. 
Vyhodnocování relačních dotazů v proudově orientovaném prostředí
Kikta, Marcel ; Bednárek, David (advisor) ; Černý, Tomáš (referee)
This thesis deals with the design and implementation of an optimizer and a transformer of relational queries. Firstly, the thesis describes the theory of the relational query compilers. Secondly, we present the data structures and algorithms used in the implemented tool. Finally, the important implementation details of the developed tool are discussed. Part of the thesis is the selection of used relational algebra operators and design of an appropriate input. Input of the implemented software is a query written in a XML file in the form of relational algebra. Query is optimized and transformed into physical plan which will be executed in the parallelization framework Bobox. Developed compiler outputs physical plan written in the Bobolang language, which serves as an input for the Bobox. Powered by TCPDF (www.tcpdf.org)
Scalable machine learning using Hadoop and Mahout tools
Kryške, Lukáš ; Atassi, Hicham (referee) ; Burget, Radim (advisor)
This bachelor’s thesis compares several tools for building a scalable, machine learning platform and describes their advantages and disadvantages. It also practically demonstrates functionality of this scalable platform based on the Apache Hadoop and Apache Mahout tools and measures performance of the K-Means algorithm for total of five computing nodes.
Scalable preprocessing of data using Hadoop tool
Marinič, Michal ; Šmirg, Ondřej (referee) ; Burget, Radim (advisor)
The thesis is concerned with scalable pre-processing of data using Hadoop tool which is used for processing of large volumes of data. In the first theoretical part it focuses on explaining of functioning and structure of the basic elements of Hadoop distributed file system and MapReduce methods for parallel processing. The latter practical part of the thesis describes the implementation of basic Hadoop cluster in pseudo-distributed mode for easy program-debugging, and also describes an implementation of Hadoop cluster in fully-distributed mode for simulation in practice.
Analysis of progressive hardware for real-time media processing
Režný, Jan ; Vrba, Kamil (referee) ; Sysel, Petr (advisor)
Diploma thesis focuses on the selection of suitable HW solution for parallell processing of multiple audio sources. Compares several different platforms based on architectures ARM, x86 and Epiphany, compares their performance in serial and parallel data processing, their energy consumption and price.

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