Abstract
SQL is the most common language to interact with databases. Users are accustomed to the table-oriented output format of SQL. To provide the same data interfaces as known from row stores in column stores, the returned results have to be transformed into tuples in row format. The process of transforming encoded columnar data into row-oriented tuples is called materialization.
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References
D.J. Abadi, D.S. Myers, D.J. DeWitt, S. Madden, Materialization strategies in a column-oriented dbms, in ICDE, ed. by R. Chirkova, A. Dogac, M.T. Ã-zsu, T.K. Sellis (IEEE, New York, 2007), pp. 466–475 Url: http://dblp.uni-trier.de/db/conf/icde/icde2007.html#AbadiMDM07
M. Grund, J. Krueger, M. Kleine, A. Zeier, H. Plattner, Optimal Query Operator Materialization Strategy for Hybrid Databases, in DBKDA (IARIA, Cancun, 2011), pp. 169–174
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Self Test Questions
Self Test Questions
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1.
Which Strategy is Faster?
Which materialization strategy—late or early materialization—provides the better performance?
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(a)
Early materialization
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(b)
Late materialization
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(c)
Depends on the characteristics of the executed query
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(d)
Late and early materialization always provide the same performance.
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(a)
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2.
Disadvantages of Early Materialization
Which of the following statements is true?
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(a)
The execution of an early materialized query plan can not be parallelized
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(b)
Whether late or early materialization is used is determined by the system clock
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(c)
Early materialization requires lookups into the dictionary, which can be very expensive and are not required when using late materialization
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(d)
Depending on the persisted value types of a column, using positional information instead of actual values can be advantageous (e.g. in terms of cache usage or SIMD execution).
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(a)
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Plattner, H. (2013). Materialization Strategies. In: A Course in In-Memory Data Management. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36524-9_16
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DOI: https://doi.org/10.1007/978-3-642-36524-9_16
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