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So if two tables are T1 and T2, SELECT * FROM T1, T2 will result in every combination of T1 rows with every T2 rows. E.g., if T1 has 3 rows and T2 has 5 rows, then 15 rows will result. Although not in standard, most DBMS allows using a select clause without a table by pretending that an imaginary table with one row is used.
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 ...
To SELECT one row of data from a table called tab with a primary key column (pk) set to 100 — use the condition pk = 100: SELECT * FROM tab WHERE pk = 100 To identify whether a table tab has rows of data with a duplicated column dk — use the condition having count(*) > 1 :
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.
The following example of a SELECT query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the ...
As an example, here is a query which uses a window function to compare the salary of each employee with the average salary of their department (example from the PostgreSQL documentation): [3] SELECT depname , empno , salary , avg ( salary ) OVER ( PARTITION BY depname ) FROM empsalary ;
For example, AVERAGE=SUM/COUNT and RANGE=MAX−MIN. In the MapReduce framework, these steps are known as InitialReduce (value on individual record/singleton set), Combine (binary merge on two aggregations), and FinalReduce (final function on auxiliary values), [ 5 ] and moving decomposable aggregation before the Shuffle phase is known as an ...
In relational databases, the information schema (information_schema) is an ANSI-standard set of read-only views that provide information about all of the tables, views, columns, and procedures in a database. [1] It can be used as a source of the information that some databases make available through non-standard commands, such as: