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Štetje dogodkov s porazdeljenimi podatkovnimi tipi za dosego močne zakasnjene konsistentnosti
ID
ŠILOVINAC, LUKA
(
Author
),
ID
Lavbič, Dejan
(
Mentor
)
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MD5: 7DD4CE4253F15476EEFBFFD355739CF9
PID:
20.500.12556/rul/daa32439-90a8-4d2c-a560-3cddf8d7d6ae
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Abstract
Sodobne spletne aplikacije se soočajo z vse večjim obsegom spletnega prometa. Ker morajo takšne aplikacije hraniti vedno več s tem povezanih podatkov, se je v zadnjih letih razvilo več pristopov k hranjenju podatkov za različne namene. V diplomskem delu raziščemo problem štetja dogodkov in zanesljivega shranjevanja števcev v okoljih, kjer sta pomembna visoka razpoložljivost in skalabilnost. Z uporabo števcev je mogoče rešiti različne probleme, ki se pojavljajo v spletnih aplikacijah. V delu s simulacijo prometa primerjamo tri različne podatkovne baze, ki jih je mogoče uporabiti za shranjevanje števcev, in ugotovimo, da lahko s tipi CRDT učinkovito rešimo problem štetja.
Language:
Slovenian
Keywords:
porazdeljeni sistemi
,
podatkovne baze
,
štetje dogodkov
,
CRDT
,
MongoDB
,
HBase
Work type:
Undergraduate thesis
Organization:
FRI - Faculty of Computer and Information Science
Year:
2016
PID:
20.500.12556/RUL-84459
Publication date in RUL:
24.08.2016
Views:
1315
Downloads:
239
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Language:
English
Title:
Counting events with distributed data types to achieve strong eventual consistency
Abstract:
Modern web applications face an ever increasing amount of web traffic. The requirement to store data of this traffic at an increasing rate lead to development of a large number of database solutions for different purposes. We explore the problem of counting events and reliably storing counters in environments where high availability and scalability are a requirement. Counters can be used to solve different problems in web applications. We evaluate three different distributed database solutions that can be used to store counters by simulating network traffic and conclude that CRDT data types can be an effective solution to the problem of counting.
Keywords:
distributed systems
,
databases
,
counting events
,
CRDT
,
MongoDB
,
HBase
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