Published May 2, 2023 | Version v1
Journal article Open

And synopses for all: A synopses data engine for extreme scale analytics-as-a-service

  • 1. Universite Libre de Bruxelles
  • 2. Technical University of Crete, Athena RC

Description

In this work, we detail 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. Our SDE is built on top of Apache Flink and implements a novel synopsis-as-a-service paradigm. In that, it achieves (i) concurrently maintaining thousands of synopses of various types for thousands of streams, on demand, (ii) reusing synopses that are common across various concurrent workflows, (iii) providing data summarization facilities even for cross-(Big Data) platform workflows, (iv) pluggability of new synopses on-the-fly, (v) increased potential for workflow execution optimization. The proposed SDE-as-a-service provides interactive analytics at scale by enabling 3 types of scalability: (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 across geo-distributed clusters and clouds by controlling the communication required to answer global queries.

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Additional details

Funding

DEDS – Data Engineering for Data Science 955895
European Commission
EVENFLOW – Robust Learning and Reasoning for Complex Event Forecasting 101070430
European Commission
STELAR – Spatio-TEmporal Linked data tools for the AgRi-food data space 101070122
European Commission