I'm currently using Azure Data Factory to load flat file data from our Gen 2 data lake into Synapse database tables. Unfortunately, we receive (many) thousands of files into timestamped folders for each feed. I'm currently using Synapse external tables to copy this data into standard heap tables.
Since each folder contains so many files, I'd like to move (or Copy/Delete) the entire folder (after processing) somewhere else in the lake. Is there some practical way to do that with Azure Data Factory?
Yes, you can use copy activity with a wild card. I tried to reproduce the same in my environment and I got the below results:
First, add source dataset and select wildcard with folder name. In my scenario, I have a folder name pool.
Then select sink dataset with file path
The pipeline run is successful. It transferred the file from one location to another location with the required name. Look at the following image for reference.
Related
I want to update a source excel column with a particular string.
My source contains n columns. I need to check where the string apple exists in any one of the columns. If the value exist in any column I need to replace the apple with orange string. And output the excel. How can I do this in ADF?
Note:I cannot use dataflows since we were using a self hosted vm
Excel files has lot of limitations in ADF like it is not supported in the copy activity sink and in Data flow sink as well.
You can raise the feature request for that in ADF.
So, try the above operation with a csv and copy the result to a csv in blob which later you can change it to Excel in your local machine.
To do the operations like above, Data flow can be a better option than doing it with normal activities as Dataflow deals with the transformations.
But Data flow won't support Self hosted linked service.
So, as a workaround first copy the Excel file as csv to Blob storage using copy activity. Create a Blob linked service for that to use in dataflow.
Now follow the below process in Data flow.
Source CSV from Blob:
Derived column transformation:
give the condition for each column case(col1=="apple", "orange", col1)
Sink :
In Sink settings specify as Output to single file.
After Pipeline execution a csv will be generated in the blob. You can convert it to Excel in your local machine.
I have flat files in adls source,
for full load we are adding 2 columns Insert and datatimestamp.
For change load we need to Lookup with full data, the data available in full should be taken as Updated and not available data as Insert and copy.
below is the approach I tried to work out, but i'm unable to perform.
Can any one help me on this.
Thanks you and waiting for quick response.
Currently, the feature to update the existing flat file using the Azure data factory sink is not supported. You have to create a new flat file.
You can also use data flow activity to read full and incremental data and load to a new file in sink transformation.
I have done data flow tutorial. Sink currently created 4 files to Azure Data Lake Gen2.
I suppose this is related to HDFS file system.
Is it possible to save without success, committed, started files?
What is best practice? Should they be removed after saving to data lake gen2?
Are then needed in further data processing?
https://learn.microsoft.com/en-us/azure/data-factory/tutorial-data-flow
There are a couple of options available.
You can mention the output filename in Sink transformation settings.
Select Output to single file from the dropdown of file name option and give the output file name.
You could also parameterize the output file name as required. Refer to this SO thread.
You can add delete activity after the data flow activity in the pipeline and delete the files from the folder.
I want to copy a file with given path from One Zone of Azure Data Lake to Other Zone of Data Lake.
Example:
Source: /RawZone/Incremental/2020/05/01/file.parquet
Destination: /StdZone/Incremental/2020/05/01/file.parquet
Should i be using Copy Activity to read source as dataset and write to Destination. Or is there a way to just copy file from source to destination in Azure Data Factory.
As far as I am aware the Copy Activity is the only way.
You will need a dataset to define where the file is coming from and going (though the path can be parameterised) and its format.
If you want to copy the file as is without alteration, set the dataset format to binary to avoid having to define the file structure and 'waste time' extracting and parsing the data within.
I am Coping files from Azure blob storage to azure data lake store, I need to pick files from year(folder)\month(folder)\day(txt files are on day bases).I am able to do one file with hadrcoded path but i am not able to pick file per day and process to copy in azure data lake store. Can anyone please help me.
I am using ADF V2 and using UI designer to create my connections,datasets and pipeline my steps are which i is working fine
copy file from blob storage to data lake store
picking that file from data lake store and processing through usql for transform data.
that transform data i am saving in Azure SQL DB
Please give me answer i am not able to get any help b/c all help is in JSON i am looking how i will define and pass parameters in UI designer.
Thanks
For the partitioned file path part, you could take a look at this post.
You could use copy data tool to handle it.