Materialization is a necessary operation in the process of query execution. Materialization strategy and materialization technology play an important role in the process of query execution. Therefore, it is necessary to design a materialization strategy for column-store database. According to the shortcomings of early materialization and later materialization, we provide a strategy named Smart materialization that are different from the two strategies mentioned above. Here we need to define a concept in the logical query plan-projection, the structure is used to select the desired attributes, the physical table is cut by column, to ensure that the structure at the beginning of the query can reduce the direct load to memory of the amount of data, to avoid additional overhead. In the logical query plan, the projection is divided by columns, and the next required columns are predicted according to the relevance of the query in a set of queries, and the required columns are stabilized in one of the most appropriate projection. We use the data set of TPC-H to verify its validity worked on the disturbed in-memory database-CLAIMS.
ZHANG Han
,
ZHOU Min-qi
. Design and implementation of Smart materialization for column-store in CLAIMS[J]. Journal of East China Normal University(Natural Science), 2017
, 2017(5)
: 30
-39
.
DOI: 10.3969/j.issn.1000-5641.2017.05.004
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