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  2. Full table scan - Wikipedia

    en.wikipedia.org/wiki/Full_table_scan

    However, SELECT COUNT(*) can't count the number of null columns. The query is unselective The number of return rows is too large and takes nearly 100% in the whole table. These rows are unselective. The table statistics does not update The number of rows in the table is higher than before, but table statistics haven't been updated yet. The ...

  3. Entity–attribute–value model - Wikipedia

    en.wikipedia.org/wiki/Entity–attribute–value...

    By contrast, in an EAV table, the conceptual data type of a value in a particular row depends on the attribute in that row. It follows that in production systems, allowing direct data entry into an EAV table would be a recipe for disaster, because the database engine itself would not be able to perform robust input validation.

  4. Database normalization - Wikipedia

    en.wikipedia.org/wiki/Database_normalization

    In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)

  5. Sparse matrix - Wikipedia

    en.wikipedia.org/wiki/Sparse_matrix

    To extract the row 1 (the second row) of this matrix we set row_start=1 and row_end=2. Then we make the slices V[1:2] = [8] and COL_INDEX[1:2] = [1]. We now know that in row 1 we have one element at column 1 with value 8. In this case the CSR representation contains 13 entries, compared to 16 in the original matrix.

  6. Statistical hypothesis test - Wikipedia

    en.wikipedia.org/wiki/Statistical_hypothesis_test

    Set up a statistical null hypothesis. The null need not be a nil hypothesis (i.e., zero difference). Set up two statistical hypotheses, H1 and H2, and decide about α, β, and sample size before the experiment, based on subjective cost-benefit considerations. These define a rejection region for each hypothesis. 2

  7. Null (SQL) - Wikipedia

    en.wikipedia.org/wiki/Null_(SQL)

    E. F. Codd mentioned nulls as a method of representing missing data in the relational model in a 1975 paper in the FDT Bulletin of ACM-SIGMOD.Codd's paper that is most commonly cited with the semantics of Null (as adopted in SQL) is his 1979 paper in the ACM Transactions on Database Systems, in which he also introduced his Relational Model/Tasmania, although much of the other proposals from ...

  8. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    ⁠ For example, in the above example the null space is spanned by the last row of ⁠ ⁠ and the range is spanned by the first three columns of ⁠. As a consequence, the rank of ⁠ M {\displaystyle \mathbf {M} } ⁠ equals the number of non-zero singular values which is the same as the number of non-zero diagonal elements in Σ ...

  9. SQL syntax - Wikipedia

    en.wikipedia.org/wiki/SQL_syntax

    As seen in the table above, direct equality comparisons between two NULLs in SQL (e.g. NULL = NULL) return a truth value of Unknown. This is in line with the interpretation that Null does not have a value (and is not a member of any data domain) but is rather a placeholder or "mark" for missing information.