Performance Improvement of Database Compression for OLTP Workloads

被引:2
|
作者
Lee, Ki-Hoon [1 ]
机构
[1] Kwangwoon Univ, Dept Comp Engn, Seoul, South Korea
来源
关键词
database compression; performance; online transaction processing;
D O I
10.1587/transinf.E97.D.976
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
As data volumes explode, data storage costs become a large fraction of total IT costs. We can reduce the costs substantially by using compression. However, it is generally known that database compression is not suitable for write-intensive workloads. In this paper, we provide a comprehensive solution to improve the performance of compressed databases for write-intensive OLTP workloads. We find that storing data too densely in compressed pages incurs many future page splits, which require exclusive locks. In order to avoid lock contention, we reduce page splits by sacrificing a couple of percent of space savings. We reserve enough space in each compressed page for future updates of records and prevent page merges that are prone to incur page splits in the near future. The experimental results using TPC-C benchmark and MySQL/InnoDB show that our method gives 1.5 times higher throughput with 33% space savings compared with the uncompressed counterpart and 1.8 times higher throughput with only 1% more space compared with the state-of-the-art compression method developed by Facebook.
引用
收藏
页码:976 / 980
页数:5
相关论文
共 50 条
  • [31] Database Integrity Mechanism between OLTP and Offline Data
    Salman, Muhammad
    Rehman, Nafees Ur
    Shahid, Muhammad
    [J]. INTELLIGENT INFORMATION AND DATABASE SYSTEMS (ACIIDS 2012), PT II, 2012, 7197 : 371 - 380
  • [32] RIB 2000 database for performance improvement
    Latorre, R.
    Miller, A.
    [J]. 1600, American Society of Naval Engineers (113):
  • [33] RIB 2000 database for performance improvement
    Latorre, R
    Miller, A
    [J]. NAVAL ENGINEERS JOURNAL, 2001, 113 (02) : 65 - 70
  • [34] Differentiated Performance in NoSQL Database Access for Hybrid Cloud-HPC Workloads
    Andreoli, Remo
    Cucinotta, Tommaso
    [J]. HIGH PERFORMANCE COMPUTING - ISC HIGH PERFORMANCE DIGITAL 2021 INTERNATIONAL WORKSHOPS, 2021, 12761 : 439 - 449
  • [35] Improving instruction cache performance in OLTP
    Harizopoulos, Stavros
    Ailamaki, Anastassia
    [J]. ACM TRANSACTIONS ON DATABASE SYSTEMS, 2006, 31 (03): : 887 - 920
  • [36] In-memory parallelism for database workloads
    Trancoso, P
    [J]. EURO-PAR 2002 PARALLEL PROCESSING, PROCEEDINGS, 2002, 2400 : 532 - 542
  • [37] Characterizing Resource Sensitivity of Database Workloads
    Sen, Rathijit
    Ramachandra, Karthik
    [J]. 2018 24TH IEEE INTERNATIONAL SYMPOSIUM ON HIGH PERFORMANCE COMPUTER ARCHITECTURE (HPCA), 2018, : 657 - 669
  • [38] Performance of OLTP via Intelligent Scheduling
    Zhang, Tieying
    Tomasic, Anthony
    Sheng, Yangjun
    Pavlo, Andrew
    [J]. 2018 IEEE 34TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2018, : 1288 - 1291
  • [39] Parallel Replication across Formats in SAP HANA for Scaling Out Mixed OLTP/OLAP Workloads
    Lee, Juchang
    Moon, SeungHyun
    Kim, Kyu Hwan
    Kim, Deok Hoe
    Cha, Sang Kyun
    Han, Wook-Shin
    [J]. PROCEEDINGS OF THE VLDB ENDOWMENT, 2017, 10 (12): : 1598 - 1609
  • [40] Enterprise Applications - OLTP and OLAP - Share One Database Architecture
    Plattner, Hasso
    [J]. ACM SIGMOD/PODS 2009 CONFERENCE, 2009, : 1 - 1