I'm trying to use the data copy activity to extract information from azure databricks delta lake, but I've noticed that it doesn't pass the information directly from the delta lake to the SQL server I need, but must pass it to an azure blob storage, when running it, it throws the following error
ErrorCode=AzureDatabricksCommandError,Hit an error when running the command in Azure Databricks. Error details: Failure to initialize configurationInvalid configuration value detected for fs.azure.account.key Caused by: Invalid configuration value detected for fs.azure.account.key
Looking for information I found a possible solution but it didn't work.
Invalid configuration value detected for fs.azure.account.key copy activity fails
Does anyone have any idea how the hell to pass information from an azure databricks delta lake table to a table in Sql Server??
These are some images of the structure that I have in ADF:
In the image I get a message that tells me that I must have a Storage Account to continue
These are the configuration images, and execution failed:
Conf:
Fail:
Thank you very much
The solution for this problem was the following:
Correct the way the Storage Access Key configuration was being defined:
in the instruction: spark.hadoop.fs.azure.account.key..blob.core.windows.net
The following change must be made:
spark.hadoop.fs.azure.account.key.
storageaccountname.dfs.core.windows.net
Does anyone have any idea how the hell to pass information from an azure databricks delta lake table to a table in Sql Server??
To achieve Above scenario, follow below steps:
First go to your Databricks cluster Edit it and under Advance options >> spark >> spark config Add below code if you are using blob storage.
spark.hadoop.fs.azure.account.key.<storageaccountname>.blob.core.windows.net <Accesskey>
spark.databricks.delta.optimizeWrite.enabled true
spark.databricks.delta.autoCompact.enabled true
After that as you are using SQL Database as a sink.
Enable staging and give same blob storage account linked service as Staging account linked service give storage path from your blob storage.
And then debug it. make sure you complete Prerequisites from official document.
My sample Input:
Output in SQL:
Related
We have an ADF pipeline with Copy activity to transfer data from Azure Table Storage to a JSON file in an Azure Blob Storage container. When the data transfer is in progress, other pipelines that use this dataset as a source fail with the following error "Job failed due to reason: Path does not resolve to any file(s)".
The dataset has a property that indicates the container directory. This property is populated by the trigger time of the pipeline copying the data, so it writes to a different directory in each run. The other failing pipelines use a directory corresponding to an earlier run of the pipeline copying the data and I have confirmed that the path does exist.
Anyone knows why this is happening and how to solve it?
Probably your expression in directory and file textbox inside the dataset is not correct.
Check this link : Azure data flow not showing / in path to data source
I am setting up Data Federations and want to move data from cluster to S3 following guidance from How to Automate Continuous Data Copying from MongoDB to S3. I have setup my cluster and s3 as Data Sources in Data Federations. Next, I have created Linked Data Sources to service name "kaison-data-federation" for Data Federations. Next, in my triggers, I wrote the pipeline.
However, I am hitting error of "(Unauthorized) not authorized" with no exact error mentioning. I have refer to other posts like Unauth Error on Moving Data from DataLake to S3. But still not working. I have stucked here for 3 days. Can anyone provide some insight to me on this? Thank you
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I have a source of SAP BW Open Hub in data factory and a sink of Azure data lake gen2 and am using a copy activity to move the data.
I am attempting to transfer the data to the lake and split into numerous files, with 200000 rows per file. I would also like to be able to prefix all of the filenames e.g. 'cust_', so the files would be something along the lines of cust_1, cust_2, cust_3 etc.
This method only seems to be an issue when using SAP BW Open Hub as a source (it works fine when using SQL Server as a source. Please see the warning message below. After checking with out internal SAP BW team, they assure me that the data is in a tabular format, and no explicit partition is enabled, so there shouldn't be an issue.
When executing the copy activity, the files are transferred to the lake but the file name prefix setting is ignored, and the filenames instead are set automatically, as below (the name seems to be automatically made up of the SAP BW Open Hub table and the request ID):
Here is the source config:
All other properties on the other tabs are set to default and have been unchanged.
QUESTION: without using a data flow, is there any way to split the files when pulling from SAP BW Open Hub and also be able to dictate the filenames in the lake?
I tried to reproduce the issue and it works fine with a work around. Instead of splitting the data while copying from SAP BW to Azure data lake storage, you can just simply copy the entire exact data (without partition) into the Azure SQL Database. Please follow copy data from SAP Business warehouse by using azure data factory (make sure to use Azure SQL Database as sink).
Now the data is in you Azure SQL Database, you can now simply use the copy activity to copy the data to Azure data lake storage.
In source configuration, keep “Partition option” as None.
Source Config:
Sink config:
Output:
We have number of databricks DELTA tables created on ADLS Gen1. and also, there are external tables built on top each of those tables in one of the databricks workspace.
similarly, I am trying to create same sort of external tables on the same DELTA format files,but in different workspace.
I do have read only access via Service principle on ADLS Gen1. So I can read DELTA files through spark data-frames, as in given below:
read_data_df = spark.read.format("delta").load('dbfs:/mnt/data/<foldername>')
I can even able to create hive external tables, but I do see following warning while reading data from the same table:
Error in SQL statement: AnalysisException: Incompatible format detected.
A transaction log for Databricks Delta was found at `dbfs:/mnt/data/<foldername>/_delta_log`,
but you are trying to read from `dbfs:/mnt/data/<foldername>` using format("hive"). You must use
'format("delta")' when reading and writing to a delta table.
To disable this check, SET spark.databricks.delta.formatCheck.enabled=false
To learn more about Delta, see https://learn.microsoft.com/azure/databricks/delta/index
;
If I create external table 'using DELTA', then I see a different access error as in:
Caused by: org.apache.hadoop.security.AccessControlException:
OPEN failed with error 0x83090aa2 (Forbidden. ACL verification failed.
Either the resource does not exist or the user is not authorized to perform the requested operation.).
failed with error 0x83090aa2 (Forbidden. ACL verification failed.
Either the resource does not exist or the user is not authorized to perform the requested operation.).
Does it mean that I would need full access, rather just READ ONLY?, on those underneath file system?
Thanks
Resolved after upgrading to Databricks Runtime environment to runtime version DBR-7.3.
I have a pipeline which just copies data from On premise SQl Server database onto ADLS Gen2. It's very simple pipeline but I could see an error as in below but I don't have any parameter mentioned in accesskey in pipeline. :
error message
Activity Copy Data1 failed: 'Type=System.ArgumentException,Message=The required property is not specified.
Parameter name: accountKey,Source=Microsoft.DataTransfer.Common,'
When I use copy data approach I see following error.
The version "3.10.6838.1" of Self-hosted Integration Runtime "integrationRuntime1" is lower than 3.16.7033.3, which is not supported for your dataset. Please upgrade to the latest version.
I've upgraded self-hosted IR from 3.5 to 3.16. Now, am able to copy data from on premise sql server to adls gen2.