A Tool for Automatic Index Selection in Database Management Systems

Pedrozo, Wendel Góes; Vaz, Maria Salete Marcon Gomes

doi:10.1109/is3c.2014.277

Cited by 9 publications

(7 citation statements)

References 3 publications

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“…Systems covered by temporal paradigm and separate temporal layer do not need to deal with such limitation, because such error cannot occur; it is always possible to get a historical image using the query to the temporal layer access. The only problem could arise with the use of the purge and volatility methods …”

Section: Query Processingmentioning

confidence: 99%

“…It is a significant limitation for the commercial usage. Some improvements have been done based on data tuple size and merging operations . The online solution forms the second group.…”

Section: Existing Index Access Solutionsmentioning

confidence: 99%

“…Thanks to that, if no migrated row is defined, each data block loading is relevant, although it stores data to be evaluated (no free block can occur). Principles of eliminating migrated row using an index are described in other works …”

Section: Own Solution ‐ Flower Index Approachmentioning

confidence: 99%

“…The only problem could arise with the use of the purge and volatility methods. 14 Performance of the query is strongly influenced by the parsing method, which looks for the optimized method to access data. It deals with index methods to locate particular data sooner.…”

Section: Query Processingmentioning

confidence: 99%

“…Some improvements have been done based on data tuple size and merging operations. 14 The online solution forms the second group. The principle is based on storing the list of tuple size using which data blocks are filled to minimize the number of assigned blocks.…”

Section: Existing Index Access Solutionsmentioning

confidence: 99%

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Locating and accessing large datasets using Flower Index Approach

Kvet

Kršák

2019

Concurrency and Computation

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Summary Information system core part is just the data stored in the database. Over the decades, the number and structure of the data have been changed. Nowadays, data must reflect not only current valid data but also historical and future images as well. Each data tuple is therefore delimited by the validity timeframe forming a temporal paradigm. Several temporal models have been developed with an emphasis on the data structure, the frequency of changes, and synchronization processes. Although the system stores time delimited data during the object lifecycle, it is not efficient, even useful to store data in the main system indefinitely. Reliability is another significant aspect of the processing covered by the purging processes. Query processing is based on the accessing data in the memory buffer cache of the database instance preceded by the loading process from the physical database. This paper proposes a Flower Index Approach as the main contribution. It removes the impact of the High Water Mark, removes useless block loading with no relevant data, and provides effective data access stream using a specific index. Full Table Scan is then not used and data are accessed directly using index ROWID locators.

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Section: Query Processingmentioning

confidence: 99%

“…It is a significant limitation for the commercial usage. Some improvements have been done based on data tuple size and merging operations . The online solution forms the second group.…”

Section: Existing Index Access Solutionsmentioning

confidence: 99%

Section: Own Solution ‐ Flower Index Approachmentioning

confidence: 99%

Section: Query Processingmentioning

confidence: 99%

Section: Existing Index Access Solutionsmentioning

confidence: 99%

See 3 more Smart Citations