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Pandas is built around data structures called Series and DataFrames. Data for these collections can be imported from various file formats such as comma-separated values, JSON, Parquet, SQL database tables or queries, and Microsoft Excel. [8] A Series is a 1-dimensional data structure built on top of NumPy's array.
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 a variety of file formats such as simple row-oriented CSV and JSON data files to more performant open column-oriented data file formats like ORC or Parquet [2] [3] residing on different storage systems like ...
All columns are regular [i.e. rows have no hidden components such as row IDs, object IDs, or hidden timestamps]. Violation of any of these conditions would mean that the table is not strictly relational, and therefore that it is not in first normal form. Examples of tables (or views) that would not meet this definition of first normal form are:
For example, a table of 128 rows with a Boolean column requires 128 bytes a row-oriented format (one byte per Boolean) but 128 bits (16 bytes) in a column-oriented format (via a bitmap). Another example is the use of run-length encoding to encode a column.
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.)
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14] Character strings and national character strings. CHARACTER(n) (or CHAR(n)): fixed-width n-character string, padded with spaces as needed; CHARACTER VARYING(n) (or VARCHAR(n)): variable-width string with a maximum size of n ...
In relational databases a virtual column is a table column whose value(s) is automatically computed using other columns values, or another deterministic expression. Virtual columns are defined of SQL:2003 as Generated Column, [1] and are only implemented by some DBMSs, like MariaDB, SQL Server, Oracle, PostgreSQL, SQLite and Firebird (database server) (COMPUTED BY syntax).
Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.