short-paper

Write-optimized indexing with partitioned b-trees

Authors:

iiWAS '17: Proceedings of the 19th International Conference on Information Integration and Web-based Applications & Services

Pages 296 - 300

https://doi.org/10.1145/3151759.3151814

Published: 04 December 2017 Publication History

Get Access

Abstract

Database management systems (DBMS) are critical performance component in large scale applications under modern update-intensive workloads. Additional access paths accelerate look-up performance in DBMS for frequently queried attributes, but the required maintenance slows down update performance. The ubiquitous B⁺-Tree is a commonly used key-indexed access path that is able to support many required functionalities with logarithmic access time to requested records. Modern processing and storage technologies and their characteristics require reconsideration of matured indexing approaches for today's workloads. Partitioned B-Trees (PBT) leverage characteristics of modern hardware technologies and complex memory hierarchies as well as high update rates and changes in workloads by maintaining partitions within one single B⁺-Tree. This paper includes an experimental evaluation of PBTs optimized write pattern and performance improvements. With PBT transactional throughput under TPC-C increases 30%; PBT results in beneficial sequential write patterns even in presence of updates and maintenance operations.

References

[1]

G. Graefe. Sorting and indexing with partitioned b-trees. In CIDR, 2003.

Google Scholar

[2]

G. Graefe. Write-optimized b-trees. pages 672--683. VLDB Endowment, 2004.

Digital Library

Google Scholar

[3]

G. Graefe. Modern b-tree techniques. Foundations and Trends in Databases, 3(4):203--402, 2011.

Digital Library

Google Scholar

[4]

G. Graefe and H. Kuno. Adaptive indexing for relational keys. In In ICDE, Workshops, 2010.

Crossref

Google Scholar

[5]

P. L. Lehman and s. B. Yao. Efficient locking for concurrent operations on b-trees. TODS, 6(4), 1981.

Digital Library

Google Scholar

[6]

P. O'Neil, E. Cheng, D. Gawlick, and E. O'Neil. The log-structured merge-tree (lsm-tree). Acta Inf., 33(4):351--385, June 1996.

Digital Library

Google Scholar

[7]

R. Sears and R. Ramakrishnan. blsm: A general purpose log structured merge tree. In In Proc. SIGMOD '12.

Digital Library

Google Scholar

Cited By

View all

Riegger CPetrov I(2024)Storage Management with Multi-Version Partitioned BTreesInformation Systems10.1016/j.is.2024.102403125(102403)Online publication date: Nov-2024
https://doi.org/10.1016/j.is.2024.102403
Riegger CPetrov I(2022)Storage Management with Multi-Version Partitioned BTreesAdvances in Databases and Information Systems10.1007/978-3-031-15740-0_19(255-269)Online publication date: 29-Aug-2022
https://doi.org/10.1007/978-3-031-15740-0_19
Riegger CVinçon TPetrov I(2018)Efficient Data and Indexing Structure for Blockchains in Enterprise SystemsProceedings of the 20th International Conference on Information Integration and Web-based Applications & Services10.1145/3282373.3282402(173-182)Online publication date: 19-Nov-2018
https://dl.acm.org/doi/10.1145/3282373.3282402

Index Terms

Write-optimized indexing with partitioned b-trees
1. Information systems
  1. Data management systems
    1. Data structures
      1. Data access methods
  2. Information storage systems
    1. Record storage systems
      1. Directory structures
        B-trees

Recommendations

LSM-Trees and B-Trees: The Best of Both Worlds
SIGMOD '19: Proceedings of the 2019 International Conference on Management of Data

LSM-Trees and B-Trees are the two primary data structures used as storage engines in modern key-value (KV) stores. These two structures are optimal for different workloads; LSM-Trees perform better on update queries, whereas B-Trees are preferable for ...
Write-optimized B-trees
VLDB '04: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30

Large writes are beneficial both on individual disks and on disk arrays, e.g., RAID-5. The presented design enables large writes of internal B-tree nodes and leaves. It supports both in-place updates and large append-only ("log-structured") write ...
Read/write-optimized tree indexing for solid-state drives

Flash-memory-based solid-state drives (SSDs) are used widely for secondary storage. To be effective for SSDs, traditional indices have to be redesigned to cope with the special properties of flash memory, such as asymmetric read/write latencies (fast ...

Comments

Information & Contributors

Information

Published In

iiWAS '17: Proceedings of the 19th International Conference on Information Integration and Web-based Applications & Services

December 2017

609 pages

ISBN:9781450352994

DOI:10.1145/3151759

Editors:
Maria Indrawan-Santiago
Monash University, Australia
,
Matthias Steinbauer
Johannes Kepler University Linz, Austria
,
Ivan Luiz Salvadori
Federal University of Santa Catarina, Brazil
,
Ismail Khalil
Johannes Kepler University Linz, Austria
,
Gabriele Anderst-Kotsis
Johannes Kepler University Linz, Austria

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 the author(s) 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].

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 December 2017

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Short-paper

Funding Sources

Ministry of Science of Baden-Wurttemberg, Germany

Conference

iiWAS2017

iiWAS2017: The 19th International Conference on Information Integration and Web-based Applications & Services

December 4 - 6, 2017

Salzburg, Austria

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

3
Total Citations
View Citations
90
Total Downloads

Downloads (Last 12 months)7
Downloads (Last 6 weeks)1

Reflects downloads up to 09 Aug 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Riegger CPetrov I(2024)Storage Management with Multi-Version Partitioned BTreesInformation Systems10.1016/j.is.2024.102403125(102403)Online publication date: Nov-2024
https://doi.org/10.1016/j.is.2024.102403
Riegger CPetrov I(2022)Storage Management with Multi-Version Partitioned BTreesAdvances in Databases and Information Systems10.1007/978-3-031-15740-0_19(255-269)Online publication date: 29-Aug-2022
https://doi.org/10.1007/978-3-031-15740-0_19
Riegger CVinçon TPetrov I(2018)Efficient Data and Indexing Structure for Blockchains in Enterprise SystemsProceedings of the 20th International Conference on Information Integration and Web-based Applications & Services10.1145/3282373.3282402(173-182)Online publication date: 19-Nov-2018
https://dl.acm.org/doi/10.1145/3282373.3282402

View Options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

LSM-Trees and B-Trees: The Best of Both Worlds

Write-optimized B-trees

Read/write-optimized tree indexing for solid-state drives