Performance evaluation of a temporal database management system
SIGMOD '86 Proceedings of the 1986 ACM SIGMOD international conference on Management of data
SIGMOD '88 Proceedings of the 1988 ACM SIGMOD international conference on Management of data
Two techniques for on-line index modification in shared nothing parallel databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
A dynamic database reorganization algorithm
ACM Transactions on Database Systems (TODS)
Database Reorganization—Principles and Practice
ACM Computing Surveys (CSUR)
Query optimization in compressed database systems
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Incremental Reorganization of Relational Databases
VLDB '87 Proceedings of the 13th International Conference on Very Large Data Bases
Weaving Relations for Cache Performance
Proceedings of the 27th International Conference on Very Large Data Bases
Incremental Maintenance of Schema-Restructuring Views in SchemaSQL
IEEE Transactions on Knowledge and Data Engineering
C-store: a column-oriented DBMS
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Online balancing of range-partitioned data with applications to peer-to-peer systems
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Row-wise parallel predicate evaluation
Proceedings of the VLDB Endowment
Online reorganization of databases
ACM Computing Surveys (CSUR)
Constant-Time Query Processing
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Fast updates on read-optimized databases using multi-core CPUs
Proceedings of the VLDB Endowment
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Query performance is a critical factor in modern business intelligence and data warehouse systems. An increasing number of companies uses detailed analyses for conducting daily business and supporting management decisions. Thus, several techniques have been developed for achieving near realtime response times - techniques which try to alleviate I/O bottlenecks while increasing the throughputs of available processing units, i.e. by keeping relevant data in compressed main-memory data structures and exploiting the read-only characteristics of analytical workloads. However, update processing and skews in data distribution result in degenerations in these densely packed and highly compressed data structures affecting the memory efficiency and query performance negatively. Reorganization tasks can repair these data structures, but -- since these are usually costly operations -- require a well-considered decision which of several possible strategies should be processed and when, in order to reduce system downtimes. In this paper, we address these problems by presenting an approach for online reorganization in main-memory database systems (MMDBS). Based on a discussion of necessary reorganization strategies in IBM Smart Analytics Optimizer, a read optimized parallel MMDBS, we introduce a framework for executing arbitrary reorganization tasks online, i.e. in the background of normal user workloads without disrupting query results or performance.