I have a ADF data flow with many csv files as a source and a SQL database as a sink. The data in the csv files are similar with 170 plus columns wide however not all of the files have the same columns. Additionally, some column names are different in each file, but each column name starts with the same corresponding 3 digits. Example: 203-student name, 644-student GPA.
Is it possible to map source columns using the first 3 characters?
Go back to the data flow designer and edit the data flow.
Click on the parameters tab
Create a new parameter and choose string array data type
For the default value as per your requirement, enter ['203-student name','203-student grade',’203-student-marks']
Add a Select transformation. The Select transformation will be used to map incoming columns to new column names for output.
We're going to change the first 3 column names to the new names defined in the parameter
To do this, add 3 rule-based mapping entries in the bottom pane
For the first column, the matching rule will be position==1 and the name will be $parameter11
Follow the same pattern for column 2 and 3
Click on the Inspect and Data Preview tabs of the Select transformation to view the new column name.
Reference - https://learn.microsoft.com/en-us/azure/data-factory/tutorial-data-flow-dynamic-columns#parameterized-column-mapping
Related
I am trying to create the derived column based on the condition that met the value and trying to do the summation of multiple matching column values dynamically. So I am using reduce function in ADF derived column mapping data flow. But the column is not getting created even the transformation is correct.
Columns from source
Derived column logic
Derived column data preview without the new columns as per logic
I could see only the fields from source but not the derived column fields. If I use only the array($$) I could see the fields getting created.
Derived column data preview with logic only array($$)
How to get the derived column with the summation of all the fields matching the condition?
We are getting data of 48 weeks forecast and the data to be prepared on monthly basis.
eg: Input data
Output data:
JAN
----
506 -- This is for first record i.e. (94 + 105 + 109 + 103 + 95)
The problem is that the array($$) in the reduce function has only one element, so that the reduce function can not accumulate the content of the matching columns correctly.
You can solve this by using two derived columns and a data flow parameter as follows:
Create derived columns with pattern matching for each month-week you did it before, but put the reference $$ into the value field, instead of the reduce(...) function.
This will create derived columns like jan0, jan1, etc. containing the copy of the original values. For example Week 0 (1 Jan - 7 Jan) => 0jan with value 95.
This step gives you a predefined set of column names for each week, which you can use to summarize the values with specific column names.
Define Data Flow parameters for each month containing the month-week column names in a string array, like this:
ColNamesJan=['0jan' ,'1jan', etc.] ColNamesFeb=['0feb' ,'1feb', etc.] and so on.
You will use these column names in a reduce function to summarize the month-week columns to monthly column in the next step.
Create a derived column for each month, which will contain the monthly totals, and use the following reduce function to sum the weekly values:
reduce(array(byNames($ColNamesJan)), 0, #acc + toInteger(toString(#item)),#result)
Replace the parameter name accordingly.
I was able to summarize the columns dynamically with the above solution.
Please let me know if you need more information (e.g. screenshots) to reproduce the solution.
Update -- Here are the screenshots from my test environment.
Data source (data preview):
Derived columns with pattern matching (settings)
Derived columns with pattern matching (data preview)
Data flow parameter:
Derived column for monthly sum (settings):
Derived column for monthly sum (data preview):
I am using azure sql as source dataset and delimited file as sink dataset in the copy activity.
I tried copy activity but First row as header gives comma separated headers.
Is there way to change the header output style ?
Please note spacing is unequal (h3...h4)
In this repro, I tried to give
1 space between 1st and 2nd column,
2 spaces between 2nd and 3rd column,
3 spaces between 3rd and 4th column.
Also, I tried to give same column name for column2 and column3. The approach is as follows.
Data is copied from Azure SQL database to datalake in comma delimitted format as a staging file.
This staging file is taken as a source in Dataflow activity.
In source dataset, first row as header is not checked.
Data preview of Source transformation:
Derived column transformation is added to change the column name of column2 and column3.
In this case, date_col of column1 is header data. Thus when column1 is 'date_col' replace column2 and column3 data with same column name.
column_2 = iif(Column_1=='date_col','ECIX',Column_2);
column_3 = iif(Column_1=='date_col','ECIX',Column_3);
Again derived column transformation is added to concat all the columns with spaces. Column name is given as concat . Value for this column is
concat(Column_1,' ',Column_2,' ',Column_3,' ',Column_4)
Select transformation is added and only concat column is selected here.
In sink, new delimited file is added as a sink dataset. And in sink dataset also , first row as header is not checked.
Output file screenshot
After pipeline is run, the target file looks like this.
Keeping the source as azure sql itself in the dataflow, I created a single derived column 'OUTDC' and added all the columns from the source like this:
(h1)+' '+(h2)+' '+(h3)
Then fed the OUTDC to a delimited sink and kept the Headers option as single string like this:
['h1 h2 h2']
Anyone know how to add header to csv sink? I have a data flow that's source is a database table. Then I have used derived column and concatenated the columns to make one column and split the data in the column by commas (done in the source via a query). I have then selected the column that has been concatenated to be export to csv.
Data example:
Matt,Smith,10
Therefore I technically only have one column, however, I want to add a header for each section of the data.
Desired output:
FirstName,LastName,Age
Matt,Smith,10
You can add headers in CSV file.
Select Data Flow Activity.
Select Source and use Select activity.
Add column names as shown in below screenshot.
Finally add Sink and run Pipeline.
I have two fields that contain concatenated strings. The first field contains medical codes and the second field contains the descriptions of those codes. I don't want to break these into multiple fields because some of them would contain hundreds of splits. Is there any way to break them into a row each like below? The code and description values are separated by a semicolon (;)
code description
----- ------------
80400 description1
80402 description2
A sample of the data:
One way is you can custom split two columns at ; which will create separate columns for every entry then you can pivot code columns and description columns separately.
One issue will be you can't guarantee if every code is mapped to correct description.
One more way is export data to excel sheet and then split and pivot the columns and then match the code and description, Then take the excel as datasource to the tableau.
I'd like to create a combination bar/line chart and combine two data sets. I'd like the columns to be months and the rows to be the aggregate values within those months. However, I'd like one of the data sets to display as a bar chart and the other data set to display as a line chart. It should look like this:
I have the following data sets:
data_set1 = [{'value':10,'date':2016-01-01},{'value':15,'date':2016-01-02},{'value':5,'date':2016-01-03},{'value':10,'date':2016-01-04},{'value':120,'date':2016-02-01}]
data_set2 = [{'value':100,'date':2016-01-01},{'value':200,'date':2016-02-01}]
I've been able to create the bar chart (see below):
However when I try to add the values from the second data set by also adding it to the columns section, I get the following error:
"In order to use fields from dataset 2, a relationship needs to be created with dataset 1. Select Data > Edit Relationships to open the Relationships dialog box."
I tried to create a relationship between these two data sets by the following process:
Set the Primary Data Source as data_set2, since that is the smaller dataset.
Selected Custom to create a custom relationship
Selected Add and set both the 'Primary Data Source Field' and the 'Secondary Data Source Field' as Date
However,
When defining the relationship between two date type fields, try selecting the level of aggregation for the date fields, such as Month(Close_Date) in source 1 maps to Month(Date) in source 2. In effect, every value in those fields is first truncated to the beginning of the period (month in this case) before comparisons are made.