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  2. Trino (SQL query engine) - Wikipedia

    en.wikipedia.org/wiki/Trino_(SQL_query_engine)

    Trino is an open-source distributed SQL query engine designed to query large data sets distributed over one or more heterogeneous data sources. [1] Trino can query data lakes that contain open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like HDFS, AWS S3, Google Cloud Storage, or Azure Blob Storage [4] using the Hive [2] and Iceberg [3 ...

  3. In-place matrix transposition - Wikipedia

    en.wikipedia.org/wiki/In-place_matrix_transposition

    For example, with a matrix stored in row-major order, the rows of the matrix are contiguous in memory and the columns are discontiguous. If repeated operations need to be performed on the columns, for example in a fast Fourier transform algorithm (e.g. Frigo & Johnson, 2005), transposing the matrix in memory (to make the columns contiguous) may ...

  4. Row and column vectors - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_vectors

    The transpose (indicated by T) of any row vector is a column vector, and the transpose of any column vector is a row vector: […] = [] and [] = […]. The set of all row vectors with n entries in a given field (such as the real numbers ) forms an n -dimensional vector space ; similarly, the set of all column vectors with m entries forms an m ...

  5. Vectorization (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Vectorization_(mathematics)

    In Python NumPy arrays implement the flatten method, [note 1] while in R the desired effect can be achieved via the c() or as.vector() functions. In R , function vec() of package 'ks' allows vectorization and function vech() implemented in both packages 'ks' and 'sn' allows half-vectorization.

  6. Transpose - Wikipedia

    en.wikipedia.org/wiki/Transpose

    For example, with a matrix stored in row-major order, the rows of the matrix are contiguous in memory and the columns are discontiguous. If repeated operations need to be performed on the columns, for example in a fast Fourier transform algorithm, transposing the matrix in memory (to make the columns contiguous) may improve performance by ...

  7. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    Since text reads from left to right, column vectors are preferred when transformation matrices are composed: If A and B are the matrices of two linear transformations, then the effect of first applying A and then B to a column vector x {\displaystyle \mathbf {x} } is given by: B ( A x ) = ( B A ) x . {\displaystyle \mathbf {B} (\mathbf {A ...

  8. Transpositions matrix - Wikipedia

    en.wikipedia.org/wiki/Transpositions_matrix

    In example if , and , are two arbitrary selected elements from the same column q of matrix, then, matrix consists one fours of elements (,,,,,), for which are satisfied the equations , =, and , =,. This property, named “Tr-property” is specific to T r {\displaystyle Tr} matrices.

  9. Orthogonal matrix - Wikipedia

    en.wikipedia.org/wiki/Orthogonal_matrix

    Visual understanding of multiplication by the transpose of a matrix. If A is an orthogonal matrix and B is its transpose, the ij-th element of the product AA T will vanish if i≠j, because the i-th row of A is orthogonal to the j-th row of A. An orthogonal matrix is the real specialization of a unitary matrix, and thus always a normal matrix.