Indexing large updatable datasets in multi-version database management systems
- Database Management Systems (DBMS) need to handle large updatable datasets in on-line transaction processing (OLTP) workloads. Most modern DBMS provide snapshots of data in multi-version concurrency control (MVCC) transaction management scheme. Each transaction operates on a snapshot of the database, which is calculated from a set of tuple versions. High parallelism and resource-efficient append-only data placement on secondary storage is enabled. One major issue in indexing tuple versions on modern hardware technologies is the high write amplification for tree-indexes. Partitioned B-Trees (PBT) [5] is based on the structure of the ubiquitous B+ Tree [8]. They achieve a near optimal write amplification and beneficial sequential writes on secondary storage. Yet they have not been implemented in a MVCC enabled DBMS to date. In this paper we present the implementation of PBTs in PostgreSQL extended with SIAS. Compared to PostgreSQL’s B+–Trees PBTs have 50% better transaction throughput under TPC-C and a 30% improvement to standard PostgreSQL with Heap-Only Tuples.
Author of HS Reutlingen | Riegger, Christian; Petrov, Ilia |
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URN: | urn:nbn:de:bsz:rt2-opus4-23269 |
DOI: | https://doi.org/10.1145/3331076.3331118 |
ISBN: | 978-1-4503-6249-8 |
Erschienen in: | IDEAS '19 : proceedings of the 23rd International Database Applications & Engineering Symposium, Athens, Greece, June 10-12, 2019 |
Publisher: | ACM |
Place of publication: | New York, NY |
Document Type: | Conference Proceeding |
Language: | English |
Year of Publication: | 2019 |
Page Number: | 5 |
DDC classes: | 004 Informatik |
Open Access?: | Nein |
Licence (English): | ![]() |