Institutional Repository
Technical University of Crete
EN  |  EL



My Space

Design and implementation of a distributed synopsis data engine on Apache Flink

Kontaxakis Antonios

Simple record

Extent65 pagesen
TitleDesign and implementation of a distributed synopsis data engine on Apache Flinken
TitleΣχεδίαση και υλοποίηση ενός κατανεμημένου συστήματος συνόψεων στο Apache Flinkel
CreatorKontaxakis Antoniosen
CreatorΚονταξακης Αντωνιοςel
Contributor [Committee Member]Garofalakis Minosen
Contributor [Committee Member]Γαροφαλακης Μινωςel
Contributor [Thesis Supervisor]Deligiannakis Antoniosen
Contributor [Thesis Supervisor]Δεληγιαννακης Αντωνιοςel
Contributor [Committee Member]Samoladas Vasilisen
Contributor [Committee Member]Σαμολαδας Βασιληςel
PublisherΠολυτεχνείο Κρήτηςel
PublisherTechnical University of Creteen
Academic UnitTechnical University of Crete::School of Electrical and Computer Engineeringen
Academic UnitΠολυτεχνείο Κρήτης::Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστώνel
Content SummaryThis work, it details the design and structure of a Synopses Data Engine (SDE) which combines the virtues of parallel processing and stream summarization towards delivering interactive analytics at extreme scale. The SDE is built on top of Apache Flink and implements a synopsis-as-a-service paradigm. In that it achieves (a) concurrently maintaining thousands of synopses of various types for thousands of streams on demand, (b) reusing maintained synopses among various concurrent workflows, (c) providing data summarization facilities even for cross-(Big Data) platform workflows, (d) pluggability of new synopses on-the-fly, (e) increased potential for workflow execution optimization. The proposed SDE is useful for interactive analytics at extreme scales because it enables (i) enhanced horizontal scalability, i.e., not only scaling out the computation to a number of processing units available in a computer cluster, but also harnessing the processing load assigned to each by operating on carefully-crafted data summaries, (ii) vertical scalability, i.e., scaling the computation to very high numbers of processed streams and (iii) federated scalability i.e., scaling the computation beyond single clusters and clouds by controlling the communication required to answer global queries posed over a number of potentially geo-dispersed clusters.en
Type of ItemΜεταπτυχιακή Διατριβήel
Type of ItemMaster Thesisen
Date of Item2020-05-29-
Date of Publication2020-
SubjectData stream managementen
Bibliographic CitationAntonios Kontaxakis, "Design and implementation of a distributed synopsis data engine on Apache Flink", Master Thesis, School of Electrical and Computer Engineering, Technical University of Crete, Chania, Greece, 2020en
Bibliographic CitationΑντώνιος Κονταξάκης, "Σχεδίαση και υλοποίηση ενός κατανεμημένου συστήματος συνόψεων στο Apache Flink", Μεταπτυχιακή Διατριβή, Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών, Πολυτεχνείο Κρήτης, Χανιά, Ελλάς, 2020el

Available Files