Search results
Results from the WOW.Com Content Network
Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation.
For example, in Microsoft SQL Server, the key is retrieved via the SCOPE_IDENTITY() special function, while in SQLite the function is named last_insert_rowid(). Using a database-specific SELECT statement on a temporary table containing last inserted row(s). Db2 implements this feature in the following way:
To add an extra row into a table, you'll need to insert an extra row break and the same number of new cells as are in the other rows. The easiest way to do this in practice, is to duplicate an existing row by copying and pasting the markup. It's then just a matter of editing the cell contents.
Additionally there is a single-row version, UPDATE OR INSERT INTO tablename (columns) VALUES (values) [MATCHING (columns)], but the latter does not give you the option to take different actions on insert versus update (e.g. setting a new sequence value only for new rows, not for existing ones.)
In a SQL database query, a correlated subquery (also known as a synchronized subquery) is a subquery (a query nested inside another query) that uses values from the outer query. This can have major impact on performance because the correlated subquery might get recomputed every time for each row of the outer query is processed.
An SQL UPDATE statement changes the data of one or more records in a table. Either all the rows can be updated, or a subset may be chosen using a condition. The UPDATE statement has the following form: [1] UPDATE table_name SET column_name = value [, column_name = value ...] [WHERE condition]
In the above example, the application might supply the values "bike" for the first parameter and "10900" for the second parameter, and then later the values "shoes" and "7400". The alternative to a prepared statement is calling SQL directly from the application source code in a way that combines code and data.
Fact_Sales is the fact table and there are three dimension tables Dim_Date, Dim_Store and Dim_Product. Each dimension table has a primary key on its Id column, relating to one of the columns (viewed as rows in the example schema) of the Fact_Sales table's three-column (compound) primary key (Date_Id, Store_Id, Product_Id).