Database Join

A self join or recursive join .. or is it ?

Searching for information in databases, text files, web services, and so on, is a very common task. In this guided demonstration, you will:

• Configure the following steps:

  • Database Join

Database Join

1. Data Grid

The Data Grid step allows you to enter a static list of rows in a grid. This is usually done for testing, reference or demo purposes.

1. Drag the Data Grid step onto the canvas.

2. Open the Data grid properties dialog box.

3. Ensure the following details are configured, as outlined below:

Data grid - Meta

Data grid - Data

2. Database Join

The Database Join step allows you to run a query against a database using data obtained from previous steps. The parameters for this query are specified as follows:

• The data grid in the step properties dialog. This allows you to select the data coming in from the source hop.

• As question marks (?) in the SQL query. When the step runs, these will be replaced with data coming in from the fields defined from the data grid. The question marks will be replaced in the same order as defined in the data grid.

1. Drag the Database Join step onto the canvas.

2. Open the Database Join properties dialog box.

3. Ensure the following details are configured, as outlined below:

Database join

The ‘Parameter fieldname’ is where you specify the parameters, therefore the values, for the conditions. Each row in the grid represents a comparison between a column in the table, and a field in your stream, by using one of the provided comparators.

LIKE matches values. You can't alias a column in the select clause and then use it in the where clause

The question marks you type in the SQL statement represent parameters. The purpose of these parameters is to be replaced with the fields you provide in ‘Parameter fieldname’. For each row in the stream, the Database join step replaces the parameters in the same order as they are in the grid, and executes the SQL statement.

So, let’s look at the WHERE conditions entered:

PRODUCTNAME LIKE like_statement and BUYPRICE < max_price

For the first record this translates as:

WHERE PRODUCTNAME LIKE concat ('%','Aston Martin','%') AND BUYPRICE < 90

As the Outer Join option is checked The FULL OUTER JOIN keyword returns all rows from the left table and from the right table. The FULL OUTER JOIN keyword combines the result of both LEFT and RIGHT joins.

The table dataset A is then compared with the stream dataset B. If there’s a match, then values for PRODUCTNAME and PRODUCTSCALE are returned.

This is not a database join. Instead of joining tables in a database, you are joining the result of a database query with a dataset.

For the second record:

WHERE PRODUCTNAME LIKE concat ('%','Ford Falcon','%') AND BUYPRICE < 70

As there is no record, NULL values are returned for:

PRODUCTNAME and PRODUCTSCALE.

So far, the results could be achieved using a Database Lookup step. However, there is a significant difference, as illustrated with the third row. For Corvette, the Database join found two matching rows in the database, and retrieved them both. Not possible with a Database lookup step.

3. RUN

1. Click the Run button in the Canvas Toolbar.

2. Click on the Preview tab:

Results

Note that there is more than one Corvette product. The database join is querying the table to return all the values, even NULL.