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Merging data sets directly from database tables
By the end of this chapter you will be able to:
- Merge directly from database collectors
- Popuate attributes with key values using the '_key[n]' notation
In this exercise you will repeat the comparison you did in the previous exercise, of the full channel list in your model against the list in the inventory database – but this time using a Merge:
- Add a new Merge Stream to your model, by dragging the icon onto your model pane
- Call this stream Name Channel List Reconciliation 2
- Add an input pipe from Latest Package All Channels, with Name sales
- Drag the following attributes from Latest Package All Channels to Channel List Reconciliation 2:
- CustomerRef
- Channel
- Add an pipe from the Database Collector SOURCE_ALL_CHANNELS_LIST to Channel List Reconciliation 2
Call this pipe inv
If you set up a merge directly from an external database table you cannot use PhixFlow's automated merge builder – therefore, if possible, always load data from external tables into PhixFlow first, and then merge |
- Set up the grouping attributes on the input pipes:
- Double click on the pipe sales
- Go to the Sort/Group tab
- Press and drag in CustomerRef and Channel
- Press to save your changes
- Double-click on the pipe inv
- Go to the Sort/Group tab
- Press
- In the new Grouping Attribute form that pops up:
- Select the attribute CustomerRef from the drop down list
- Tick the Group flag
- Press
- Add the grouping attribute Channel in the same way
- Back in the main pipe configuration form, press
- Double click on the pipe sales
Now you will complete the configuration of the Merge Stream, using the _key internal variable to write key values into the Stream:
- Double-click on Channel List Reconciliation 2 to open the configuration form
- Double-click the Attribute CustomerRef
- In the Attribute details form that pops up, update Expression to: _key[1]
- This writes the first key value into this attribute – if you have a look at one of the merges you created with PhixFlow's automated merge builder, you will see an expression like this for the grouping attributes
- Press
- Double-click the Attribute Channel
- In the Attribute details form that pops up, update Expression to: _key[2]
- This writes the second key value into this attribute
- Press
- Add an Attribute SalesCheck, and set the Expression to
- In the Attribute details form that pops up, update Expression to: _key[1]
if (countElements(sales) == 1, "YES" , "NO" )
- Add an Attribute InvCheck, and set the Expression to
if (countElements(inv) == 1, "YES" , "NO" )
- Press in the main stream configuration form to save your changes
- Update the query in the Database Collector to:
select * from SOURCE_ALL_CHANNELS_LIST order by CustomerRef, Channel (the ordering is needed to support the merge)
When merging directly from database tables –you have to repeat the ordering of data across the query and the pipe; that is, the ordering of data in the Database Collector query much match the grouping on the pipe from the Database Collector |
- Run Analysis on Channel List Reconciliation 2
- In your results you should see an additional 3 records that were not included in the reconciliation you did in the previous exercise – channels that are recorded in the inventory, but not in the channels list, are included in your output
This is because a Merge will generate an output record for every key value it finds across all input pipes, whereas if you do a data enrichment using a lookup pipe – you will only get an output record for every record from the input pipe
Filter unmatched rows
To help you find unmatched rows in your output data, you will now add a filter (if you have already done the User course or Dashboards and Forms course, this should be familiar):
- Open the data set you have just generated in Channel List Reconciliation 2
- Press - Select, create or clear a filter
- Press in the drop-down list that appears
- In the filter details form, press the condition at the top of conditions list that says Where ALL of the following are true
- From the drop down list select ANY item true
- The top condition will now say Where ANY of the following are true
- In the second condition in the conditions list:
- Select SalesCheck
- Leave the operator as equals
- In the value field enter: NO
- Add a third condition:
- Select InvCheck
- Leave the operator as equals
- In the value field enter: NO
- Press - Apply the filter without saving
- You will get a list of all non-matched records, that is, all records where the SalesCheck value is NO or the InvCheck value is NO
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