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Optimize Your SQL by Reformulating the Spec

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As SQL developers, we tend to think of performance tuning in terms of crafting the best table indices, avoiding scalar and table valued functions, and analyzing query plans (among other things). But sometimes going back to the spec and applying some properties of elementary math can be the best way to begin to improve performance of SQL queries which implement mathematical formulas. This article is a case study of how I used this technique to optimize my SQL implementation of the Inverse Simpson Index.

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2021-05-07 (first published: )

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Question of the Day

Adding new column with DEFAULT II

Which number did the two COUNT(*) return:

DROP TABLE IF EXISTS #tmp
CREATE TABLE #tmp (id INT NOT NULL)

INSERT INTO #tmp (id) 
SELECT gs.value
  FROM GENERATE_SERIES(1, 5) AS gs

ALTER TABLE #tmp ADD my_value INT NOT NULL CONSTRAINT df_tmp_my_value DEFAULT 1

SELECT COUNT(*)  FROM #tmp AS t WHERE my_value = 1

ALTER TABLE #tmp DROP CONSTRAINT df_tmp_my_value

ALTER TABLE #tmp ADD CONSTRAINT df_tmp_my_value DEFAULT 2 FOR my_value

SELECT COUNT(*)  FROM #tmp AS t WHERE my_value = 1

See possible answers