A Data Reusing Strategy Based on Column-Stores

2013 IEEE 11th International Conference on Dependable, Autonomic and Secure Computing ◽

10.1109/dasc.2013.56 ◽

2013 ◽

Author(s):

Mei Wang ◽

Jiaoling Zhou ◽

Yue Li ◽

Xiaoling Xia ◽

Jiajin Le

Keyword(s):

Column Stores

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LEA: A Learned Encoding Advisor for Column Stores

Fourth Workshop in Exploiting AI Techniques for Data Management ◽

10.1145/3464509.3464885 ◽

2021 ◽

Author(s):

Lujing Cen ◽

Andreas Kipf ◽

Ryan Marcus ◽

Tim Kraska

Keyword(s):

Column Stores

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LDI: Learned Distribution Index for Column Stores

10.1109/bigdata52589.2021.9671318 ◽

2021 ◽

Author(s):

Dai-Hai Ton That ◽

Mohammadsaleh Gharehdaghi ◽

Alexander Rasin ◽

Tanu Malik

Keyword(s):

Distribution Index ◽

Column Stores

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Entropy Aware Adaptive Compression for SQL Column Stores

Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety - Communications in Computer and Information Science ◽

10.1007/978-3-319-99987-6_7 ◽

2018 ◽

pp. 90-104 ◽

Cited By ~ 1

Author(s):

K. T. Sridhar ◽

Jimson Johnson

Keyword(s):

Adaptive Compression ◽

Column Stores

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Relational Data Access for Business Data Analytics

Encyclopedia of Business Analytics and Optimization ◽

10.4018/978-1-4666-5202-6.ch182 ◽

2014 ◽

pp. 2020-2027

Author(s):

Veit Köppen ◽

Andreas Lübcke

Keyword(s):

Time Horizon ◽

Architectural Design ◽

Response Times ◽

Data Access ◽

Transactional Analysis ◽

Business Analytics ◽

Weight Analysis ◽

Analytical Processing ◽

Architectural Decision ◽

Column Stores

The growing amount of data enables more complex business analytics. Data for business analytics is stored in databases or data warehouses. Analysts want to execute their queries under requirements in a suitable time horizon. An architectural decision has a significant influence on response times. Therefore, it is necessary not only to identify and weight analysis tasks, but also to decide on the storage architecture. The architectural design influences the query execution time up to factor 100. We present both architectures and their influence on the database workload. Classic row stores perform better on transactional analysis and column stores outperform the other in simple online analytical processing.

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