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.

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Metadaten
Name:Riegger, Christian; Petrov, Ilia
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
Pagenumber:5
Dewey Decimal Classification:004 Informatik
Open Access:Nein
Licence (English):License Logo  Lizenzbedingungen ACM