Top-down real-time big data query optimization method based on bushy tree
A top-down, query optimization technology, applied in the field of big data query, can solve the problems of long optimization time, cost model system limitations, etc., to facilitate production and life, reduce execution time, and improve query efficiency
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[0066] The present invention will be described in detail below with reference to the drawings and specific embodiments.
[0067] In this embodiment, the cost of each query plan tree is defined as the comprehensive cost of the disk read cost, network transmission cost and table size of the query plan tree. The cost of any query plan tree T is according to the following formula (ie cost model) calculate:
[0068]
[0069] Among them, α L +α R +β+γ+δ=1;
[0070] L and R are respectively the left subtree and the right subtree of the query plan tree;
[0071] C L The cost of the left subtree, C R is the cost of the right subtree, calculated recursively using this formula;
[0072] IO L The cost of reading the data corresponding to the left subtree for the disk;
[0073] TR is the network transmission cost, S is the size of the data, S LR is the data size after hash-joining the left subtree and the right subtree.
[0074] Since the 2 subtrees can be executed in parallel...
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