thanks for coming in.
I am trying to develop a Mapping Data Flow in an Azure Synapse workspace (so I believe that this can also apply to ADFv2) that takes a Delta input and transforms it straight into a Parquet -formatted output, with the relevant detail of using a Parquet dataset pointing to ADLSGen2 with parameterized file system and folder, in opposition to a hard-coded file-system and folder, because this would take creating too many datasets as there are too many folders of interest in the Data Lake.
The Mapping Data Flow:
As I try to use it as a Source in my Mapping Data Flows, the debug configuration (as well as the parent pipeline configuration) will duly ask for my input on those parameters, which I am happy to enter.
Then, as soon I try to debug or run the pipeline I get this error in less than 1 second:
{
"Message": "ErrorCode=InvalidTemplate, ErrorMessage=The expression 'body('DataFlowDebugExpressionResolver')?.50_DeltaToParquet_xxxxxxxxx?.ParquetCurrent.directory' is not valid: the string character '_' at position '43' is not expected."
}
RunId: xxx-xxxxxx-xxxxxx
This error message is not very specific to know where I should look.
I tried replacing the parameterized Parquet dataset with a hard-coded one, and it works perfectly both in debug and pipeline -run modes. However, this does not gets me what I need which is the ability to reuse my Parquet dataset instead of having to create a specific dataset for each Data Lake folder.
There are also no spaces in the Data Lake file system. Please refer to these parameters that look a lot like my production environment:
File System: prodfs001
Directory: synapse/workspace01/parquet/dim_mydim
Thanks in advance to all of you, folks!
The directory name synapse/workspace01/parquet/dim_mydim has an _ in dim_mydim, can you try replacing the underscore, or maybe you can use dimmydim to test whether it works.
Related
In Azure Data Factory I have a pipeline, created from the built-in copy data task, that copies data from 12 entities (campaign, lead, contact etc.) from Dynamics CRM (using a linked service) and outputs the contents as parquet files in account storage. This is run every day, into a folder structure based on the date. The output structure in the container looks something like this:
Raw/CRM/2022/05/28/campaign.parquet
Raw/CRM/2022/05/28/lead.parquet
Raw/CRM/2022/05/29/campaign.parquet
Raw/CRM/2022/05/29/lead.parquet
That's just an example, but there is a folder structure for every year/month/day that the pipeline runs, and a parquet file for each of the 12 entities I'm retrieving.
This involved creating a pipeline, dataset for the source and dataset for the target. I modified the pipeline to add the pipeline's run date/time as a column in the parquet files, called RowStartDate (which I'll need in the next stage of processing)
My next step is to process the data into a staging area, which I'd like to output to a different folder in my container. My plan was to create 12 scripts (one for campaigns, one for leads, one for contact etc.) that essentially does the following:
accesses all of the correct files, using a wildcard path along the lines of: Raw/CRM/ * / * / * /campaign.parquet
selects the columns that I need
Rename column headings
in some cases, just take the most recent data (using the RowStartDate)
in some cases, create a slowly changing dimension, ensuring every row has a RowEndDate
I made some progress figuring out how to do this in SQL, by running a query using OPENROWSET with wildcards in the path as per above - but I don't think I can use my SQL script in ADF to move/process the data into a separate folder in my container.
My question is, how can I do this (preferably in ADF pipelines):
for each of my 12 entities, access each occurrence in the container with some sort of Raw/CRM///*/campaign.parquet statement
Process it as per the logic I've described above - a script of some sort
Output the contents back to a different folder in my container (each script would produce 1 output)
I've tried:
Using Azure Data Factory, but when I tell it which dataset to use, I point it to the dataset I created in my original pipeline - but this dataset has all 12 entities in the dataset and the data flow activity produces the error: "No value provided for Parameter 'cw_fileName" - but I don't see any place when configuring the data flow to specify a parameter (its not under source settings, source options, projection, optimize or inspect)
using Azure Data Factory, tried to add a script - but in trying to connect to my SQL script in Synapse - I don't know my Service Principal Key for the synapse workspace
using a notebook Databricks, I tried to mount my container but got an error along the lines that "adding secret to Databricks scope doesn't work in Standard Tier" so couldn't proceed
using Synapse, but as expected, it wants things in SQL whereas I'm trying to keep things in a container for now.
Could anybody point me in the right direction. What's the best approach that I should take? And if its one that I've described above, how do I go about getting past the issue I've described?
Pass the data flow dataset parameter values from the pipeline data flow activity settings.
I am copying data from sql to adls dynamically, i want to rename the file name after copied into ADLS. How to achieve it? Requesting you suggest.
Thanks in Advance.
Regards,
Ashok
My first question would be "why bother renaming parquet files?" Hopefully you aren't generating a single parquet file, which would seem to defeat the purpose of using Parquet. Instead, my focus would be on the folder name.
OPTION 1
If I did care about the file names, I would use Data Flow and configure the Sink to use patterned naming:
You could then pass the desired file name in as Data Flow Parameter:
And set it dynamically using an expression:
[NOTE: I haven't tested this syntax, but I recommend you always use the Expression Builder to enter these expressions].
OPTION 2
If none of that suits your purposes, then aonther option would be brute force. Use a COPY activity with binary data sets to copy the file to a new file with the desired name, then a DELETE activity to remove the old one.
I have a azure blob container where some json files with data gets put every 6 hours and I want to use Azure Data Factory to copy it to an Azure SQL DB. The file pattern for the files are like this: "customer_year_month_day_hour_min_sec.json.data.json"
The blob container also has other json data files as well so I have filter for the files in the dataset.
First question is how can I set the file path on the blob dataset to only look for the json files that I want? I tried with the wildcard *.data.json but that doesn't work. The only filename wildcard I have gotten to work is *.json
Second question is how can I copy data only from the new files (with the specific file pattern) that lands in the blob storage to Azure SQL? I have no control of the process that puts the data in the blob container and cannot move the files to another location which makes it harder.
Please help.
You could use ADF event trigger to achieve this.
Define your event trigger as 'blob created' and specify the blobPathBeginsWith and blobPathEndsWith property based on your filename pattern.
For the first question, when an event trigger fires for a specific blob, the event captures the folder path and file name of the blob into the properties #triggerBody().folderPath and #triggerBody().fileName. You need to map the properties to pipeline parameters and pass #pipeline.parameters.parameterName expression to your fileName in copy activity.
This also answers the second question, each time the trigger is fired, you'll get the fileName of the newest created files in #triggerBody().folderPath and #triggerBody().fileName.
Thanks.
I understand your situation. Seems they've used a new platform to recreate a decades old problem. :)
The patter I would setup first looks something like:
Create a Storage Account Trigger that will fire on every new file in the source container.
In the triggered Pipeline, examine the blog name to see if it fits your parameters. If no, just end, taking no action. If so, binary copy the blob to a account/container your app owns, leaving the original in place.
Create another Trigger on your container that runs the import Pipeline.
Run your import process.
Couple caveats your management has to understand. You can be very, very reliable, but cannot guarantee compliance because there is no transaction/contract between you and the source container. Also, there may be a sequence gap since a small file can usually process while a larger file is processing.
If for any reason you do miss a file, all you need to do is copy it to your container where your process will pick it up. You can load all previous blobs in the same way.
I have configured a Stream Analytics Jobs so that input data goes to an Azure Data Lake repository every hour.
Sometimes there is no event to track, so no output. But my Data Factory goes in error because the file doesn't exist.
I wonder if exist a way to force empty file out from Stream Analytics?
Many thanks!
You can look at our common query patterns here. In particular I think you can use the one named "fill missing values" to generate some events regularly, even when there is no input.
Let me know if it works for you.
Thanks!
JS
Are you using ADF v2?
I didn't find anything inbuilt in ADF to come up with it.
But I can see few workarounds - starting from simplest one:
In your ASA query, you can use WITH statement and union your input with a fake empty message. - Then there will be always output
As a second output in ASA job you can store in some DB info whenever a file was produced. Then in ADF you can check whenever there are files and run copy conditionally.
In ADF run web activity e.g. LogicApp/FunctionApp to get info whenever files in container exist.
Find the way to do it...
I had an activity using the data lake analytics, what I do is to run an U-SQL than read data with no transformation and write it to the output with headers.
In that way the activity always write an output file!
Very easy!
I have a datastage job that is comparring a previous dataset with a current one and loads the values into another dataset. The problem is that it does not search for the correct previous dataset and fails to see the physical file.
This happens to only a part of the files and is not a parameter problem as all the parameters are project level and set up correctly.
Is there a possibility of being overwriting? What type of error do you get? Was the dataset correctly created? Is the file system asociated full? There are many possibilities, that could be happening to you.