I have Source csv file, In which there is one column which have multiple values (data sep.by comma (,)) so I want extract that particular one column using data factory and store that multiple records into table (in database) with different column name
Could you please suggest how should I design that azure data factory pipeline ?
You can use the split function in the Data flow Derived Column transformation to split the column into multiple columns and load it to sink database as below.
Source transformation:
Derived Column transformation:
Using the split() function, splitting the column based on delimiter which returns an array.
Derived Column data preview:
Here 2 new columns are added in the derived column which stores the split data from the source column (name).
Select transformation (optional):
In Select transformation, we can remove columns which are not used in sink and only select required columns.
Sink:
Connect sink to the database and map the column to load the data.
Related
I am using Data flow in my Azure Data factory pipeline in order to copy data from one cosmos db collection to another cosmos db collection. I am using cosmos SQL Api as the source and sink datasets.
Problem is when copying the documents from one collection to other,I would like to add an additional column whose value will be same as one of the existing key in json. I am trying with Additional column thing in Source settings but i am not able to figure out how can I add an existing column value in there. anyone with any help on this_
In case of copy activity, you can assign the existing column value to new column under Additional column by specifying value as $$COLUMN and add the column name to be assigned.
If you are adding new column in data flow, you can achieve this using derived column
I want read the column names from a file stored in Azure Files And then validate the column names and sequence e.g. "First_Column"="First_Column", "Second_Column"= "Second_Column", ... etc and also the order should match. Please suggest a way to do this in Azure Data Factory.
Update:
Alternatively, we can use Lookup activity to view the headers, but the judgment condition will be a little complex.
At the If Condition1 we can use the expression: #and(and(equals(activity('Lookup1').output.firstRow.Prop_0,'First_Column'),equals(activity('Lookup1').output.firstRow.Prop_1,'Second_Column')),equals(activity('Lookup1').output.firstRow.Prop_2,'Third_Column'))
We can validate the column names and sequence in dataflow via column patterns in derived column.
For example:
The source data csv file is like this:
The dataflow is like this:
I don't select First row as header , so we can read the headers of the csv file into the dataflow.
Then I use SurrogateKey1 to add a row_no to the data.
The data preview is like this:
At ConditionalSplit1 activity, I use row_no == 1 to filter the headers.
At DerivedColumn1 activity, I use several column pattern to validate the column names and sequence.
The result is as follows:
Is it possible to split the column values in Azure Data Factory? I am wanting to split a value in a column from a CSV into a SQL table. I am wanting to keep the second value "Training Programmes Manager" in the same column deleting the 1st and 3rd and the 4th value "Education" moved to an already made column in SQL
Value separated by |
Image of value below:
Value in CSV
Thanks James
Since you need to work with a particular column value, you'll need to use a Data Flow.
Source: Create a DataSet for your CSV file.
In the Data Flow, use Derived Column to parse the | delimited column into new columns.
Sink to SQL, referencing the new column names.
I have a some file in an azure data lake 2 and I want to load them as a column value nvarchar(max) in AzureSQLDW. The table in AzureSQLDW is heap. I couldn't find any way to do it? All I see is column delimited when load them into multiple rows instead of one row in single column. How I achieve this?
I don't guarantee this will work, but try using COPY INTO and define non-present values for row and column delimiters. Make your target a single column table.
I would create a Source Dataset with a single column. You do this by specifying "No delimiter":
Next, go to the "Schema" tab and Import the schema, which should create a single column called "Prop_0":
Now the data should come through as a single string instead of delimited columns.
Is it possible to add data from a new BigQuery table to existing Tableau extract?
For example, there are BigQuery tables partitioned by date like access_20160101, access_20160102, ... and data from 2016/01/01 to 2016/01/24 is already in Tableau server extract. Now a new table for 2016/01/25, access_20160125 has been created and I want to add the data to the existing extract, but don't want to read the old tables because there is no change in them but loading them will be charged by Google.
If I understand correctly: you created an extract for a table in BigQuery and now you want to append data in a different table to that extract.
As long as both tables have exactly the same column names and data types in those columns you can do this:
Create an extract from the new table.
Append that extract to the old one. (see: add data from a file)
Now you have one extract with the data of both tables.