How can we add headers to the files existing in the blob/ azure data lake using azure data factory.
I am using a copy activity to move the header less files to the sink, but while moving the files should have default headers like "Prop_0" or "Column_1". Any method available to achieve the same?
Any help would be appreciated.
Thanks and Regards,
Sandeep
In usually, Data factory will using the default header Prop_0, Prop_1...Prop_N for the less header csv file to help us copy the data, if we don't set the first row as header.
This is to help us do the column mapping but won't change the csv file.
According my experience and know about Data Factory, it doesn't support us do the schema change of the csv file. It's impossible to add the header of the csv files at least for now.
Hope this helps
In ADF, create a new Data Flow. Add your CSV source with a no header dataset. Then add your Sink with a dataset that writes to ADLS G2 folder as a text delimited file WITH headers. In the Sink Mapping, you can name your columns:
I tried a different solution. Used the 'no delimiter' option to keep all of them as one column. Then, In the derived column action, I split the single column into multiple columns and provided a proper name for each column. Now we can map the columns into the target table.
Related
We are trying to load a delimited file which has blank data for few columns located in azure blob and would like to get a value like NA in our target snowflake table whenever we encounter a blank value in source csv file. We have been trying to provide a NA against the Null option but it is not working, any suggestions?
Here is the screenshot of what i have mentioned above.
I have used data flow activity in Azure data factory to resolve this issue.
Source file with NULL value in “Name” column.
Now use Derived Column transformation. In Derived column's settings Select column name and use iifNull({Name}, 'NA') expression.
In data preview, Null value in Name column is replaced with NA.
You can follow the above steps to replace Null values and Sink data from blob storage to Snowflake.
I have an Azure Data factory trigger that is fired off when a file is placed in blob storage, this trigger will start pipeline execution and pass the file name to the data flow activity. I would like to make sure that all the column names from the header row in the file are in the sink table. There is an identity column in the sink table that should not be in the comparison. Not sure how to tackle this task, I've read about the 'derived column' activity, is that the route I should take?
You can select or filter which columns reside in sink dataset or table by using "Field mapping". You can optionally use "derived columns" transformation, however in the "sink transformation" you will have this by default and is set to "Auto mapping". Here you can add or remove which columns are written to sink.
In the below example the column "id" can be assumed as similar to "Identity" column in your table. Assuming all the files have same columns:
Once you have modified as per your need, you can confirm the same from the "inspect" tab before run.
Strategy:
Use two ADF pipelines, one to get a list of all files and another one to process each file copying its content to a specific SQL table.
Setup:
I’ve created 4 CSV files, following the pattern you need: “[CustomerID][TableName][FileID].csv” and 4 SQL tables, one for each type of file.
A_inventory_0001.csv: inventory records for customer A, to be
inserted into the SQL table “A_Inventory”.
A_sales_0003.csv: sales
records for customer A, to be inserted into the SQL table “A_Sales”.
B_inventory_0002.csv: inventory records for customer B, to be
inserted into the SQL table “B_Inventory”.
B_sales_0004.csv: sales
records for customer B, to be inserted into the SQL table “B_Sales”
Linked Services
In Azure Data Factory, the following linked services were create using Key Vault (Key Vault is optional).
Datasets
The following datasets were created. Note we have created some parameters to allow the pipeline to specify the source file and the destination SQL table.
The dataset “AzureSQLTable” has a parameter to specify the name of the destination SQL table.
The dataset “DelimitedTextFile” has a parameter to specify the name of the source CSV file.
The dataset “DelimitedTextFiles” has no parameter because it will be used to list all files from source folder.
Pipelines
The first pipeline “Get Files” will get the list of CSV files from source folder (Get Metadata activity), and then, for each file, call the second pipeline passing the CSV file name as a parameter.
Inside the foreach loop, there is a call to the second pipeline “Process File” passing the file name as a parameter.
The second pipeline has a parameter “pFileName” to receive the name of the file to be processed and a variable to calculate the name of the destination table based on the file name.
The first activity is to use a split in the file name to extract the parts we need to compose the destination table name.
In the expression bellow we are splitting the file name using the “__” separator and then using the first and second parts to compose the destination table name.
#concat(string(split(pipeline().parameters.pFileName, '_')[0]),'_',string(split(pipeline().parameters.pFileName, '_')[10]))
The second activity will then copy the file from the source “pFileName” to the desnation table “vTableName” using dynamic mapping, ie not adding specific column names as this will be dynamic.
The files I used in this example and the ADF code are available here:
https://github.com/diegoeick/stack-overflow/tree/main/69340699
I hope this will resolve your issue.
In case you still need to save the CustomerID and FileID in the database tables, you can use the dynamic mapping and use the available parameters (filename) and create a json with the dynamic mapping in the mapping tab of your copy activity. You can find more details here: https://learn.microsoft.com/en-us/azure/data-factory/copy-activity-schema-and-type-mapping#parameterize-mapping
I'm trying to do a Data Flow using ADL1 as the source and Data Explorer as the sink; I can create the source but when I select Dataset for Sink Type the only available options in the Dataset pulldown are my ADL1 Datasets. If I use Data Copy instead I can choose Data Explorer as a sink but this won't work as Data Copy won't allow null values into Data Explorer number data types. Any insight on how to fix this?
I figured out a workaround. First I Data Copy the csv file into a staging table where all columns are strings. Then I Data Copy from staging table to production table using a KQL query that converts strings to their destination data types.
I have an ADF Copy Data flow and I'm getting the following error at runtime:
My source is defined as follows:
In my data set, the column is defined as shown below:
As you can see from the second image, the column IsLiftStation is defined in the source. Any idea why ADF cannot find the column?
I've had the same error. You can solve this by either selecting all columns (*) in the source and then mapping those you want to the sink schema, or by 'clearing' the mapping in which case the ADF Copy component will auto map to columns in the sink schema (best if columns have the same names in source and sink). Either of these approaches works.
Unfortunately, clicking the import schema button in the mapping tab doesn't work. It does produce the correct column mappings based on the columns in the source query but I still get the original error 'the column could not be located in the actual source' after doing this mapping.
could you check that is there a column named 'ae_type_id' in your schema? If that's the case, could you remove that column and try again? The columns in the schema must be aligned with columns in the query.
The issue is caused by an incomplete schema in one of the data sources. My solution is:
Step through the data flow selecting the first schema, Import projection
Go to the flow and Data Preview
Repeat for each step.
In my case, there were trailing commas in one of the CSV files. This caused automated column names to be created in the import allowing me to fix the data file.
I have an ADF pipeline with copy activity, I'm copying data from blob storage CSV file to SQL database, this is working as expected. I need to map Name of the CSV file (this coming from pipeline parameters) and save it in the destination table. I'm wondering if there is a way to map parameters to destination columns.
Column name can't directly use parameters. But you can use parameter for the whole structure property in dataset and columnMappings property in copy activity.
This might be a little tedious as you will need to write the whole structure array and columnMappings on your own and pass them as parameters into pipeline.
In DF v2 in Copy Data activity, it is possible to add a new column to the source with value $$FILEPATH, and then each record will have a name of the input file.
Azure DF v2, CopyData activity -> Source