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The first thing we need to do is create a source endpoint. We do this by clicking the Manage Endpoint Connections
button at the top of the screen.
And you will see this window.
From there, click on Add New Endpoint Connection
link or the + New Endpoint Connection
button at the top of the screen.
Once you do that you will see this window:
We will now create a MySQL source endpoint:
MySQL Source
,Source
radio button is selected,MySQL
from the dropdown selection box.You will notice as we proceed that the content of the configuration window is context-sensitive.
Fill in the blanks as indicated in the images above:
mysqldb
3306
root
eI3chl835qMRWt2F
None
and then click on Test Connection
. Your screen should look like the following, indicating that your connection succeeded.
Assuming so, click Save
and the configuration of your MySQL source endpoint is complete. Click Close
to close the window.
For more details about using MySQL as a source, please review the section “Using a MyQL-Based Database as a Source” in Chapter 8 “Adding and Managing Source Endpoints” of the Qlik Replicate User Guide
Next we need to configure our Postgres target endpoint. The process is much the same as you saw with the MySQL source, and once again you will note that the configuration process is context-sensitive as we move along.
As before, the first step in the configuration process is to tell Replicate that we want to create a new endpoint. If you are back on the main window, you will need to click on Manage Endpoint Connections
button.
and then press the + New Endpoint Connection
button.
and you will see a window that resembles this:
We will now create a PostgreSQL Target endpoint:
Postgres Target
,Target
radio button is selected,PostgreSQL
from the dropdown selection box.Fill in the blanks as indicated in the image above:
postgresdb
5432
qlik
eI3chl835qMRWt2F
qlikdb
disable
and then click on Test Connection
. Your screen should look like the following, indicating that your connection succeeded.
Assuming so, click Save
and the configuration of your Postgres target endpoint is complete. Click Close
to close the window.
For more details about using PostgreSQL as a target, please review the section “Using a PostgreSQL-Based as a Target” in Chapter 9 “Adding and Managing Target Endpoints” of the Qlik Replicate User Guide
Now that we have configured our MySQL source and Postgres target endpoints, we need to tie them together in what we call a Replicate task. In short, a task defines the following:
To get started, we need to create a task. Click on the + New Task
button at the top of the screen.
Once you do, a window like this will pop up:
Give this task a meaningful name like MySQL to Postgres
. For this task we will take the defaults:
MySQL to Postgres
Unidirectional
enabled
(Blue highlight is enabled; click to enable / disable.)enabled
(Blue highlight is enabled; click to enable / disable.)disabled
(Blue highlight is enabled; click to enable / disable.)Once you have everything set, press OK
to create the task. When you have completed this step you will see a window that looks like this:
Qlik Replicate is all about ease of use. The interface is point-and-click, drag-and-drop. To configure our task, we need to select a source endpoint (MySQL) and a target endpoint (Postgres). You can either drag the MySQL Source
endpoint from the box on the left of the screen and drop it into the circle that says Drop source endpoint here
, or you can click on the arrow that appears just to the right of the endpoint when you highlight it.
Repeat the same process for the Postgres Target endpoint. Your screen should now look like this:
Our next step is to select the tables we want to replicate from MySQL into Postgres. Click on the Table Selection...
button in the top center of your browser.
and from there select the testdrive
schema.
Enter %
where it says Table: and press the Search
button. This will retrieve a list of all the tables in the testdrive schema.
Note: entering
%
is not strictly required. By default, Qlik Replicate will search for all tables (%
) if you do not limit the search.
and then press the >>
button to move all of the tables from the Results list into the Selected Tables list. Note that we also had the option of simply wildcarding all tables, or selectively choosing tables from the Results list.
The transformation we will create in this section will:
To get started, double click
on the Player table in the Selected Tables frame.
Then click on the Transform
button.
And click on Add Column
.
Call the new column fullName
,
and change its default type from STRING(50) to WSTRING(100)
. You can get a dropdown of valid types you can choose by clicking the type column next to fullName.
Note though, that the default precision of the WSTRING type is 50 … we will need more space than that due to the width of some of the data we will be working with, so you will need to type WSTRING(100)
into the type column.
Now we need to define the transformation we want to use to populate the column. Click on fx
to bring up the trasformation Expression Builder.
The expression we are going to build will involve concatenating three columns, nameGiven, nameFirst, and nameLast into a column called fullName. Start by double clicking nameGiven
which will put $nameGiven into the expression builder.
Now press the concatenation operator ||
and add the string `’ (‘.
and repeat those steps with nameFirst
and nameLast
until you have an expression that looks like
$nameGiven||’ (‘||$nameFirst||’) ‘||$nameLast
Note that you could just as easily have typed the the expression in directly, or even copied and pasted it from this web page.
Now click the Parse Expression
button and enter the data:
first middle
nickname
lastname
and press the Test Expression
button. This process allows us to put test values in the columns that make up the expression and validate that the output looks as we expect it to.
Assuming your output looks like the output indicated (first middle (nickname) lastname), your transformation is correct. Press OK
to save the transfomration and return to the previous screen.
You will note below that we can see that there is now an expression next to the fullName column. If you hover your mouse over that column you will be able to inspect the transformation without having to click into it. Press OK
again to return to the previous screen.
Notice the word (Changed) next to the testdrive.Player column. This indicates that a transformation has been defined that alters the state of the data as it moves from the source to the target.
That is it for configuration. We are now ready to save our task and run it. Press Save
at the top left of the window and then press Run
.
After you press Run
, Replicate will automatically switch from Designer mode to Monitor mode. You will be able to watch the status of the full load as it occurs, and then switch to monitoring change data capture as well.
When Full Load is complete, click on the Completed
bar to display the tables. There is DML activity running in the background. Click on the Change Processing
tab to see it in action.
If you would like to explore the data that we have delviered to Postgres, click on the folowing link:
This link will open PGAdmin in another window in your browser. Log in with:
pgadmin@qlik.com
eI3chl835qMRWt2F
From there, click on > Servers
in the navigation pane.
And then double-click on Test Drive PostgresDB
which will open a window for you to enter the password to log into the server.
eI3chl835qMRWt2F
This will log you into the database. From there you can navigate to:
Databases => qlik => Schemas => testdrive => Tables
Feel free to explore the structure, etc. associated with the tables we have created. If you look at the structure for the Player table, you will see that the additional column, fullName that we added to the table as a part of our transformation is present in the table here.
Now we will enter a couple of queries. Click on Tools
at the top of the screen and select Query Tool
to open the query editor.
Now type
select count(*) from testdrive."Player";
Note the quotes around Player and that it begins with a capital ‘P’. The schemas are case-sensitive, so we need the quotes in order to find the table in the query. Highlight that line and press the lightning bolt at the top of the screen to execute. This will give you the count of rows the Player table. That vaule should be displayed in the Data Output area at the bottom of the screen.
Next, we will query a few rows from the Player table to examine the data. Type
select * from testdrive."Player" limit 5;
Once again, highlight that query statement and press the lightning bolt at the top of the screen to execute it. Five rows should be returned in the Data Output area at the bottom of the screen.
If you scroll all the way to the right, you will see the fullName column that we created during the transformation. You will also note that the values set in that column are just as we coded them to look in the transformation.
When you have seen enough, you can declare Victory! for this part of the Test Drive. Press Stop
in the top left corner of the Replicate console to end the task. After pressing Stop
and clicking Yes
in the confirmation dialog, click on the TASKS
tab at the top of the screen. This will return you to the main window.
You just:
All that in 5 easy steps!
You can now move on to the next part of the Test Drive.
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