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Identifier |
000456903 |
Title |
Stream processing of financial tick data with in-order guarantees |
Alternative Title |
Επεξεργασία ροών οικονομικών δεδομένων με εγγυήσεις διάταξης |
Author
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Καλογεράκης, Στέφανος Π.
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Thesis advisor
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Μαγκούτης, Κωνσταντίνος
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Reviewer
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Μπίλας, Άγγελος
Πλεξουσάκης, Δημήτρης
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Abstract |
Data related to all types of societal activity are nowadays being produced and
available in high volumes and velocity, in the form of data streams. This thesis
focuses on financial tick data generated by stock exchanges and the necessity for
stream processing analytics to assist traders in identifying trading opportunities.
We design and implement the Tick Analysis Platform (TAP), a streaming analytics application that performs event aggregation and complex event processing
to compute trend indicators and detect patterns, enabling the identification of
buy/sell opportunities for traders. Based on the need to process streaming data
as rapidly as possible, we investigate techniques for scalable stream processing,
with an additional guarantee, namely the in-order processing of such data based
on sequencing information available in batches of incoming data. The solutions
designed and implemented in this thesis, S-TAP (Single-source TAP) and P-TAP
(Parallel-source TAP), progressively enhance the scalability of TAP to achieve
high performance on a cluster of multi-core servers while ensuring the accuracy
of results via the in-order guarantees. An additional challenge investigated by
this thesis is efficient fault-tolerance mechanisms to achieve low down-times during recovery of data analysis jobs. This is achieved by aligning the deployment
of recovery tasks with the location of externally-stored checkpoint replicas, taking
advantage of data locality where possible. The solutions implemented and demonstrated in this thesis advance the state of the art in scalable streaming analytics
of financial tick data that are also rapidly recoverable in the face of failures.
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Language |
English |
Issue date |
2023-07-21 |
Collection
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School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
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Type of Work--Post-graduate theses
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Permanent Link |
https://elocus.lib.uoc.gr//dlib/a/6/a/metadata-dlib-1688537433-235535-12168.tkl
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Views |
676 |