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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 Καλογεράκης, Στέφανος Π.
Thesis advisor Μαγκούτης, Κωνσταντίνος
Reviewer Μπίλας, Άγγελος
Πλεξουσάκης, Δημήτρης
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.
Language English
Issue date 2023-07-21
Collection   School/Department--School of Sciences and Engineering--Department of Computer Science--Post-graduate theses
  Type of Work--Post-graduate theses
Permanent Link https://elocus.lib.uoc.gr//dlib/a/6/a/metadata-dlib-1688537433-235535-12168.tkl Bookmark and Share
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