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Timeline index: a unified data structure for processing queries on temporal data in SAP HANA

Published: 22 June 2013 Publication History

Abstract

Managing temporal data is becoming increasingly important for many applications. Several database systems already support the time dimension, but provide only few temporal operators, which also often exhibit poor performance characteristics. On the academic side, a large number of algorithms and data structures have been proposed, but they often address a subset of these temporal operators only. In this paper, we develop the Timeline Index as a novel, unified data structure that efficiently supports temporal operators such as temporal aggregation, time travel, and temporal joins. As the Timeline Index is independent of the physical order of the data, it provides flexibility in physical design; e.g., it supports any kind of compression scheme, which is crucial for main memory column stores. Our experiments show that the Timeline Index has predictable performance and beats state-of-the-art approaches significantly, sometimes by orders of magnitude.

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      cover image ACM Conferences
      SIGMOD '13: Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data
      June 2013
      1322 pages
      ISBN:9781450320375
      DOI:10.1145/2463676
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Published: 22 June 2013

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      Author Tags

      1. algorithm
      2. index
      3. temporal data
      4. temporal operator

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      SIGMOD '13 Paper Acceptance Rate 76 of 372 submissions, 20%;
      Overall Acceptance Rate 785 of 4,003 submissions, 20%

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      Cited By

      View all
      • (2025)Indexing temporal relations for range-duration queriesDistributed and Parallel Databases10.1007/s10619-024-07452-643:1Online publication date: 9-Jan-2025
      • (2024)LIT: Lightning-fast In-memory Temporal IndexingProceedings of the ACM on Management of Data10.1145/36392752:1(1-27)Online publication date: 26-Mar-2024
      • (2024)Independent Range Sampling on Interval Data2024 IEEE 40th International Conference on Data Engineering (ICDE)10.1109/ICDE60146.2024.00041(449-461)Online publication date: 13-May-2024
      • (2024)Parallel Processing of Temporal Anti-Joins in MemoryDatabase Systems for Advanced Applications10.1007/978-981-97-5552-3_6(86-102)Online publication date: 1-Oct-2024
      • (2023)Efficiently Answering Top-k Window Aggregate Queries: Calculating Coverage Number Sequences over Hierarchical Structures2023 IEEE 39th International Conference on Data Engineering (ICDE)10.1109/ICDE55515.2023.00104(1300-1312)Online publication date: Apr-2023
      • (2023)HINT: a hierarchical interval index for Allen relationshipsThe VLDB Journal10.1007/s00778-023-00798-w33:1(73-100)Online publication date: 1-Jun-2023
      • (2022)Visualising Time-evolving Semantic Biomedical Data2022 IEEE 35th International Symposium on Computer-Based Medical Systems (CBMS)10.1109/CBMS55023.2022.00053(264-269)Online publication date: Jul-2022
      • (2022)Querying Temporal Anomalies in Healthcare Information Systems and BeyondAdvances in Databases and Information Systems10.1007/978-3-031-15740-0_16(209-222)Online publication date: 29-Aug-2022
      • (2021)A variational database management systemProceedings of the 20th ACM SIGPLAN International Conference on Generative Programming: Concepts and Experiences10.1145/3486609.3487197(29-42)Online publication date: 17-Oct-2021
      • (2021)Index-Accelerated Pattern Matching in Event StoresProceedings of the 2021 International Conference on Management of Data10.1145/3448016.3457245(1023-1036)Online publication date: 9-Jun-2021
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