For validation rules that need numerous inputs, it is frequently easier to construct and comprehend the Java code if it is written in that language. Validation rules assist to guarantee that your database users are entering the correct types or quantities of data in a particular field. This article will walk you through the process of creating validation rules for more complicated criteria.
Validation rules restrict what users can enter in a given field, and also help ensure that your database users enter the proper types or amounts of data.
Table of Contents
You can create two basic types of validation rules:
You can define validation rules for tables and for controls on forms. When you define rules for tables, those rules apply when you import data. To add validation rules to a table, you open the table in Design view and set various table properties. To add validation rules to a form, you open the form in Design view and add rules to the properties of individual controls.
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Your validation rules can contain expressions — functions that return a single value. You can use expressions to perform calculations, manipulate characters, or test data. When you create validation rules, you use expressions primarily to test data. For example, an expression can check for one of a series of values, such as “Tokyo” Or “Moscow” Or “Paris” Or “Helsinki”.
Expressions can also perform mathematical operations. For example, the expression <100 forces users to enter values less than 100. The expression ([OrderDate] – [ShipDate]) calculates the number of days that elapsed between the time an order was placed and the time it shipped.
The steps in the following sections explain how to validate data for tables, forms, queries, and import operations.
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Create a validation rule
1. In the Navigation Pane, right-click the form that you want to change, and then click Design View.
2. Right-click the control that you want to change, and then click Properties to open the property sheet for the control.
3 Click the All tab, and then enter your validation rule in the Validation Rule property box.-or-Click Builder button next to start the Expression Builder and create an expression.
4. Enter a message in the Validation Text property box.
Save your changes.
Sometimes, it is desirable to perform multiple checks on a row at the same time, so that when a row is rejected, all of the problems with the data can be identified from a single error message. An excellent method of recording this is to create a binary error code.
A binary error code is a binary number, where each of the digit position represents the result of a validation test: 0 being pass and 1 being fail.
For example, 1101 = failed test 1 (rightmost digit), test 3 and test 4 and passed test 2. This binary value can be held as a decimal integer, in this case 13.
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Open the job jo_cook_ch03_0070_binaryErrorCode.
How to do it…
1. Open tMap and create six new Integer type variables:
nameTest, dateOfBirthTest, timestampTest, ageTest, countryOfBirthTest and errorCode.
2. Copy the following lines into the Expressions:
customer.name.equals("") ? 1 << 0 : 0 customer.dateOfBirth == null ? 1 << 1 : 0 customer.timestamp == null ? 1 << 2 : 0 customer.age == null ? 1 << 3 : 0 customer.countryOfBirth.equals("") ? 1 << 4 : 0 Var.nameTest + Var.dateOfBirthTest + Var.timestampTest + Var.ageTest + Var.countryOfBirthTest
3. Add a condition in the ValidRows output
Var.errorCode == 0
The operator << performs a bitwise shift of the value by the relevant number of places. For example 1<<3 would place a 1 in the 4th position of a binary number (0 being the first position).
So if the field is null, the variable is assigned a bit-shifted value, otherwise it is set to 0.By adding the numbers together, we eventually arrive at a decimal value which represents a 1 in each of the positions where a null is found.
This may be simpler to explain using an example. The following is the output from tLogRow. In this case, it is one of the rejects where three nulls have been found.So from this output the binary value will be built as shown:
So the decimal total is 0+2+4+8+0 = 14
An alternative to using the << operator is to assign the actual decimal values to each position: 1,2,4,8 (2 power 0, 2 power 1, and so on) being positioned 0 to 3. Again, adding the values gives us the desired integer result.
Decrypting a binary error message is achieved by testing the individual bits of the integer. This can be achieved by using the shift function to create the binary bit position and performing a bitwise AND against the integer value. If the result is greater than 0, then the position is set.
For instance, if we have the value 0101 (7) in an integer column:
0101 & 1 (where the 1 equates to 1 <<0) = 1 (test 1 failed) 0101 & 10 (where 10 equates to 1<<1) = 0 (test 2 passed) 0101 & 100 (where 100 equates to 1<<2) = 100 (test 3 failed) 0101 & 1000 (where 1000 equates to 1<<3) = 0 (test 4 passed)
So the logic for our errors will look like this:
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Ravindra Savaram is a Content Lead at Mindmajix.com. His passion lies in writing articles on the most popular IT platforms including Machine learning, DevOps, Data Science, Artificial Intelligence, RPA, Deep Learning, and so on. You can stay up to date on all these technologies by following him on LinkedIn and Twitter.
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