Creating Parent-Child Relationships
Let's start with an example to clearly understand its concept. Suppose . To extend the parent-child analogy, the primary key value is taken from the parent table. A hierarchy is built upon a parent-child relationship within the same table or view. Hierarchical query is one of the very first features of the Oracle Database and was The hierarchy can be traversed bottom-up; for example, to retrieve the top . AMPA is now part of Oracle MAF - oracle/mobile-persistence. For example, in the sample Toplink/EclipseLink payload we showed before, the In such a case, you can set-up this parent child relation manually so you.
If left blank, version ZJDE will be used. Specify a version of the Organizational Structure Revisions program for the system to use.
The version indicates a specific set of data selection and sequencing settings for the application. Versions may be named using any combination of alphabetic and numeric characters. Parent Number Enter the address book number of the parent entity for example, parent company.
Parent and Child Values and Rollup Groups (Oracle General Ledger Users' Guide)
The system uses this number to associate a particular address with a parent entity or location. Any value that you enter in this field updates the Address Organizational Structure Master table F for the specified structure type. This address number must exist in the Address Book Master table F Examples of address book records that would have a parent number include: A parent in one hierarchy can be a child in another hierarchy.
A hierarchy can be organized by business unit, employee, or position. Another typical example of this hierarchy is that of parent-child foreign key relationships.
The wizard connects to a data source a database in this casequeries the table you select, and determines the hierarchical relationship of the table's elements. Aside from presenting an easier means of interpreting the hierarchical relationships within the emp table, the chart leads us into the first example of how to record the relationships by using a nested set model.
The "emp" family The algorithm for creating a nested set model is pretty simple.
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Start at the top, enter the next number in the lower left corner of the element's box, then move down a level if there is one, or across the element, and enter the next number. If there are no lower elements, traverse across that element and enter the next number, then traverse across to the next sibling, and repeat the numbering.
Continue until you return to the top element of the current branch. Traverse across to the next branch and repeat. Putting an algorithm into words may make it seem confusing, but when applying the steps, the implementation is usually much easier, and even more so when you have an example to go by. We start with King and enter a 1 in the lower left corner.
Move down to Clark and enter a 2. Move across Miller and enter a 4, returning to Clark with a 5. Traverse across to Blake and enter a 6, and so on from there. Click for larger image Now that we have an ordered pair identification scheme e. Following along with an example in the book, the next step is to create a view.
If measure values at a particular level fully constitute aggregated measures at its parent level, select Supports rollup to higher level of aggregation. To define child logical levels, click Add. In the Browse dialog, select the child logical levels and click OK. The child levels appear in the Child Levels pane. To remove a previously defined child level, select the level in the Child Levels pane and click Remove. The child level and all of its child levels are deleted from the Child Levels pane.
Optional Type a description of the logical level. Associating a Logical Column and Its Table with a Dimension Level After you create all logical levels within a dimension, you need to drag and drop one or more columns from the dimension table to each logical level except the Grand Total level.
The first time you drag a column to a dimension it associates the logical table to the dimension. It also associates the logical column with that level of the dimension. To change the logical level to be associated with that logical column, you can drag a column from one logical level to another.
The logical column or columns that comprise the logical key of a dimension table must be associated with the lowest level of the dimension. After you associate a logical column with a dimension level, the tables in which these columns exist appear in the Tables tab of the Dimensions dialog. For time dimensions, ensure that all time-related logical columns in the source table are defined in the time dimension. For example, if a time-related logical table contains the columns Month Name and Month Code, you must ensure that both columns are dragged to the appropriate level within the dimension.
Figure shows how to associate logical columns with a logical level. In the Dimensions dialog, click the Tables tab. The tables list contains tables that you associated with that dimension. This list of tables includes only one logical dimension table and one or more logical fact tables if you created level-based measures. Click OK or Cancel to close the Dimensions dialog. Example and Example show how to associate measures to different levels of level-based dimension hierarchies.
Example Level-Based Measure Calculations A level-based measure is a column whose values are always calculated to a specific level of aggregation. For example, a company might want to measure its revenue based on the country, based on the region, and based on the city. When a query includes a level-based measure column, and the query grain is higher than the level of aggregation specific to the column, the query results return null.
Note that in previous releases, results were returned for this situation, but they were not deterministic. Level-based measures allow a single query to return data at multiple levels of aggregation. They are also useful in creating share measures, that are calculated by taking some measure and dividing it by a level-based measure to calculate a percentage. For example, you can divide salesperson revenue by regional revenue to calculate the share of the regional revenue each salesperson generates.
Trees and Hierarchies in Oracle
To set up these calculations, you need to build a dimensional hierarchy in your repository that contains the levels Grandtotal, Country, Region, and City. This hierarchy contains the metadata that defines a one-to-many relationship between Country and Region and a one-to-many relationship between Region and City. For each country, there are many regions, but each region is in only one country.
Similarly, for each region, there are many cities, but each city is in only one region. Each of these columns uses the logical column Revenue as its source.
Oracle / PLSQL: Foreign Keys
The Revenue column has a default aggregation rule of SUM and has sources in the underlying databases. Each query that requests one of these columns returns the revenue aggregated to its associated level.
Figure shows what the business model in the Business Model and Mapping layer looks like for this example. In the Sales Facts table, the Revenue column has a default aggregation rule of SUM and is mapped to physical detail data or physical aggregate data.
CountryRevenue and RegionRevenue columns use the Revenue column as their source. Additionally, there might be a column called Revenue that is defined with a default aggregation rule of Sum. You can then create a logical column, AllProductRevenue, that uses Revenue as its source as specified in the General tab of the Logical Column dialog.
Each query that includes this column returns the total revenue for all products. The value is returned regardless of any constraints on Brands or Products.
If you have constraints on columns in other tables, the grand total is limited to the scope of the query. For example, if the scope of the query asks for data from andthe grand total product revenue is for all products sold in and If you have three products, A, B, and C with total revenues of, and respectively, then the grand total product revenue is the sum of each product's revenue.
If you have set up a repository as described in this example, the following query produces the results listed: To specify a primary key for a dimension level: In the Business Model and Mapping layer of the Administration Tool, expand a dimension and then expand the highest level Grand Total level of the dimension. Double-click a logical level below the Grand Total level.
In the Logical Level dialog, click the Keys tab. In the Keys tab, from the Primary key list, select a level key.
If only one level key exists, it is the primary key by default. To add a column to the list, perform the following steps: In the Logical Level dialog, click New. In the Logical Level Key dialog, type a name for the key. In the Logical Level Key dialog, select a column or click Add. If you click Add, in the Browse dialog, select the column, and then click OK. The column you selected appears in the Columns list of the Logical Level Key dialog and is automatically selected.
You cannot use a derived logical column that is the result of a LOOKUP function as part of a primary logical level key.