## View updating rule in sql

If the cells do not exist, and the rule has appropriate notation, they are inserted. If any of the cell references are symbolic, no cells are inserted. If the cell values do not exist, no updates are done. This means that a cell not supplied to MODEL by the query result set will be treated as a zero for the calculation. This can be used at a global level for all measures in a model. This is the default, and can be omitted. Calculation Definition The set of values that are modified or created by the model.

This is the default. This uniqueness is explicitly verified at query execution when necessary, in which case it may increase processing time. This may reduce processing time by avoiding explicit checks for uniqueness at query execution. ORDER BY country, product, year; This partitions the data by country and defines within each partition, a two-dimensional array on product and year.

The cells of this array contain two measures: An example of a cell reference is as follows: This section contains the following topics: Positional Dimension References A positional dimension reference or positional reference, in short is a constant or a constant expression specified for a dimension.

For example, the cell reference sales['Bounce'] has a positional reference on the product dimension and accesses sales value for the product Bounce. The following example shows the usage of positional references on dimensions: Based on how they are specified, cell references are either single cell or multi-cell reference.

A rule is an assignment statement whose left side represents a cell or a range of cells and whose right side is an expression involving constants, bind variables, individual cells or an aggregate function on a range of cells.

Rules can use wild cards and looping constructs for maximum expressiveness. An example of a rule is the following: Note that this rule refers to single cells on both the left and right side and is relatively simple. Complex rules can be written with multi-cell references, aggregates, and nested cell references. Single Cell References This type of rule involves single cell reference on the left side with constants and single cell references on the right side.

Some examples are the following: All existing aggregate functions including analytic aggregates inverse percentile functions, hypothetical rank and distribution functions and so on and statistical aggregates correlation, regression slope and so on , and user-defined aggregate functions can be used. For example, the rule to compute the sales of Bounce for to be more than the maximum sales in the period to would be: Arguments to the aggregate function can be constants, bind variables, measures of the MODEL clause, or expressions involving them.

For example, the rule computes the sales of Bounce for to be the weighted average of its sales for years from to would be: This computation is simple in that the right side cell references and hence the right side expression are the same for all cells referenced on the left.

Use of the CV Function The use of the CV function provides the capability of relative indexing where dimension values of the cell referenced on the left side are used on the right side cell references.

As an example, consider the following: CV may be used outside a cell reference, but when used in this way its argument must contain the name of the dimension desired. You can also write the preceding rule as: The CV function can be used only in right side cell references.

Another example of the usage of CV function is the following: ANY may be used on both the left and right side of rules. Nested Cell References Cell references can be nested. In other words, cell references providing dimension values can be used within a cell reference. The following rule computes the sales of Standard Mouse Pad for to be the average of Standard Mouse Pad sales for the years in which Finding Fido sales were highest and lowest: Aggregates on multi-cell references cannot be used in nested cell references.

SQL models with sequential rule order of evaluation are called sequential order models. Oracle examines the cell references within rules and finds dependencies among rules. If cells referenced on the left side of rule R1 are referenced on the right side of another rule R2, then R2 is considered to depend on R1. In other words, rule R1 should be evaluated before rule R2. This is because rule 1 depends on rules 2 and 3 and hence need to be evaluated after rules 2 and 3. The order of evaluation among second and third rules can be arbitrary as they do not depend on one another.

The order of evaluation among rules independent of one another can be arbitrary. SQL models with an automatic order of evaluation, as in the preceding fragment, are called automatic order models.

In an automatic order model, multiple assignments to the same cell are not allowed. In other words, measure of a cell can be assigned only once. Oracle Database will return an error in such cases as results would be non-deterministic.

For example, the following rule specification will generate an error as sales['Bounce', ] is assigned more than once: This leads to non-deterministic results as the evaluation order is arbitrary - sales['Bounce', ] can be or or sum of Bounce sales for years and However, multiple assignments are fine in sequential order models. These options can be specified at a local level with each rule and in which case, they override the global behavior.

For example, in the following specification: Note that no option was specified for the third rule and hence it inherits the update behavior from the global option. The following sections discuss these three types of behavior: