Outer Join Elimination in the Teradata RDBMS

Ghazal, Ahmad; Crolotte, Alain; Bhashyam, Ramesh

doi:10.1007/978-3-540-30075-5_70

Cited by 6 publications

(3 citation statements)

References 16 publications

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“…Query rewrite plays an important role in optimizing complex queries where join elimination is important technique [9].…”

Section: Discussionmentioning

confidence: 99%

“…As several mature implementations of data warehousing systems are fully operational, a crucial role in preserving their up-to-dateness is played by the ability to manage the changes that the data warehouse schema undergo over time in response to evolving business requirements [9]. Malinowski and Zimányi realized that there is no well-accepted model for either data warehouses or temporal databases that can be used to capture users' requirements [21].…”

Section: Temporal Data Modelling In a Data Warehousementioning

confidence: 99%

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Relational model of temporal data based on 6th normal form

Golec

Mahnič²,

Kovač

2017

Teh. vjesn.

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Original scientific paper This paper brings together two different research areas, i.e. Temporal Data and Relational Modelling. Temporal data is data that represents a state in time while temporal database is a database with built-in support for handling data involving time. Most of temporal systems provide sufficient temporal features, but the relational models are improperly normalized, and modelling approaches are missing or unconvincing. This proposal offers advantages for a temporal database modelling, primarily used in analytics and reporting, where typical queries involve a small subset of attributes and a big amount of records. The paper defines a distinctive logical model, which supports temporal data and consistency, based on vertical decomposition and sixth normal form (6NF). The use of 6NF allows attribute values to change independently of each other, thus preventing redundancy and anomalies. Our proposal is evaluated against other temporal models and super-fast querying is demonstrated, achieved by database join elimination. The paper is intended to help database professionals in practice of temporal modelling. Keywords: logical model; relation; relational modelling; 6 th Normal Form; temporal dataRelacijski model vremenskih podataka zasnovan na 6. normalnoj formi Izvorni znanstveni članak Ovaj rad povezuje dva različita područja istraživanja, tj. Temporalne podatke i Relacijsko modeliranje. Temporalni podaci su podaci koji predstavljaju stanje u vremenu, a temporalna baza podataka je baza podataka s ugrađenom podrškom za baratanje s podacima koji uključuju vrijeme. Većina temporalnih sustava pruža dovoljno temporalnih karakteristika, ali su relacijski modeli nepravilno normalizirani, a pristupi modeliranju nedostaju ili nisu uvjerljivi. Ovim se prijedlogom daju prednosti modeliranja temporalne baze podataka, prvenstveno korištene u analitici i izvještavanju, gdje tipična pretraživanja uključuju mali podniz atributa i veliku količinu zapisa. U radu se definira posebni logički model koji podržava temporalne podatke i konzistenciju, zasnovan na vertikalnoj dekompoziciji i šestoj normalnoj formi (6NF). Primjena 6NF omogućuje neovisnost u promjeni atributnih vrijednosti i tako sprečava redundanciju i anomalije. Naš je model uspoređen s drugim temporalnim modelima i demonstrirano je super brzo pretraživanje postignuto eliminacijom spajanja baze podataka (database join elimination). Svrha je rada pomoći stručnjacima koji se bave bazama podataka u primjeni temporalnog modeliranja.

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“…Query rewrite plays an important role in optimizing complex queries where join elimination is important technique [9].…”

Section: Discussionmentioning

confidence: 99%

Section: Temporal Data Modelling In a Data Warehousementioning

confidence: 99%

Relational model of temporal data based on 6th normal form

Golec

Mahnič²,

Kovač

2017

Teh. vjesn.

View full text Add to dashboard Cite

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“…Research has also been done on other aspects of optimizing outer joins including outer join elimination [9,5,4,3] and view matching for outer join views [16,17,18,11]. However, none of the above work handles data skew in outer joins.…”

Section: Related Workmentioning

confidence: 99%

Efficient outer join data skew handling in parallel DBMS

Kostamaa

2009

Proc. VLDB Endow.

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Large enterprises have been relying on parallel database management systems (PDBMS) to process their ever-increasing data volume and complex queries. The scalability and performance of a PDBMS comes from load balancing on all nodes in the system. Skewed processing will significantly slow down query response time and degrade the overall system performance. Business intelligence tools used by enterprises frequently generate a large number of outer joins and require high performance from the underlying database systems. Although extensive research has been done on handling skewed processing for inner joins in PDBMS, there is no known research on data skew handling for parallel outer joins. We propose a simple and efficient outer join algorithm called OJSO (Outer Join Skew Optimization) to improve the performance and scalability of parallel outer joins. Our experimental results show that the OJSO algorithm significantly speeds up query elapsed time in the presence of data skew.

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