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High-cardinality refers to columns with values that are very uncommon or unique. High-cardinality column values are typically identification numbers, email addresses, or user names. An example of a data table column with high-cardinality would be a USERS table with a column named USER_ID. This column would contain unique values of 1-n. Each ...
Reserved words in SQL and related products In SQL:2023 [3] In IBM Db2 13 [4] In Mimer SQL 11.0 [5] In MySQL 8.0 [6] In Oracle Database 23c [7] In PostgreSQL 16 [1] In Microsoft SQL Server 2022 [2]
Title Authors ----- ----- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1 Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
The SQL SELECT statement returns a result set of rows, from one or more tables. [1] [2] A SELECT statement retrieves zero or more rows from one or more database tables or database views. In most applications, SELECT is the most commonly used data manipulation language (DML) command.
For example, Microsoft SQL Server documentation states the following: [24] For indexing purposes, NULLs compare as equal. Therefore, a unique index, or UNIQUE constraint, cannot be created if the keys are NULL in more than one row. Select columns that are defined as NOT NULL when columns for a unique index or unique constraint are chosen.
A database index is a data structure that improves the speed of data retrieval operations on a database table at the cost of additional writes and storage space to maintain the index data structure. Indexes are used to quickly locate data without having to search every row in a database table every time said table is accessed.
In SQL, the unique keys have a UNIQUE constraint assigned to them in order to prevent duplicates (a duplicate entry is not valid in a unique column). Alternate keys may be used like the primary key when doing a single-table select or when filtering in a where clause, but are not typically used to join multiple tables.
If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.