In my azure subscription I have a storage account with a lot of tables that contains important data.
As far as I know azure offers a backup point-in-time for the storages and blobs, and geo redundancy in event of a failover. But I couldn't find anything regarding the backup of table storages.
The only way to do so is by using azCopy which is fine and a logic, but I couldn't make it work as I had some issues with permissions even if I set the Azure Blob Data Contributor to my container.
So as an option, I was thinking if there is a way how to implement this using python code to loop throu all the tables in a specific container and make a copy into another container.
Can anyone enlighten me on this matter please?
Did you set the Azure Storage firewall: allow access from all networks?:
Python code is a way but we can't help you design the code. And there isn't an example for you. It doesn't meet Stack Overflow's guideline.
If you still couldn't figure it out with AzCopy, I would suggest you think about use Data Factory to schedule backup the data from table storage to another container.
Create a pipeline with copy active to copy the data from Table
Storage. Ref this tutorial:Copy data to and from Azure Table
storage by using Azure Data Factory.
Create a schedule trigger for the pipeline to make the jobs
automatic.
If the Table storage has many tables, the easiest way is using Copy Data Tool.
Update:
Copy data tool source settings:
Sink settings: auto create the table in sink table storage
HTH.
Related
Is anyone aware of a way to anonomise data within a storage account container on Azure?
I was assuming no but wanted to see if anyone had any ideas on this?
I'm aware of data masking on SQL databases on Azure but within containers we have files with data that are used within a data lake.
I know my details a little sparse... But I'm still trying to understand the underlying architecture I'm working with atm.
Any questions/ideas/thoughts, throw them at me!
Azure storage account(data lake) don't support data masking. so mask at the source of the data is not possible.
You can create app to mask the data and put it in the same VNET with your data lake(In this way, the others can not access the primary data). And then send the data to target storage.
But maybe what you need is customer managed keys to do data encryption？
I have the following ETL requirements for Snowflake on Azure and would like to implement the simplest possible solution because of timeline and technology constraints.
Requirements :
Load CSV data (only a few MBs) from Azure Blob Storage into Snowflake Warehouse daily into a staging table.
Transform the loaded data above within Snowflake itself where transformation is limited to just a few joins and aggregations to obtain a few measures. And finally, park this data into our final tables in a Datamart within the same Snowflake DB.
Lastly, automate the above pipeline using a schedule OR using an event based trigger (i.e. steps to kick in as soon as file lands in Blob Store).
Constraints :
We cannot use use Azure Data Factory to achieve this simplest design.
We cannot use Azure Functions to deploy Python Transformation scripts and schedule them either.
And, I found that Transformation using Snowflake SQL is a limited feature where it only allows certain things as part of COPY INTO command but does not support JOINS and GROUP BY. Furthermore, although the following THREAD suggests that scheduling SQL is possible, but that doesn't address my Transformation requirement.
Regards,
Roy
Attaching the following Idea diagram for more clarity.
https://community.snowflake.com/s/question/0D50Z00009Z3O7hSAF/how-to-schedule-jobs-from-azure-cloud-for-loading-data-from-blobscheduling-snowflake-scripts-since-dont-have-cost-for-etl-tool-purchase-for-scheduling
https://docs.snowflake.com/en/user-guide/data-load-transform.html#:~:text=Snowflake%20supports%20transforming%20data%20while,columns%20during%20a%20data%20load.
You can create snowpipe on Azure blob storage, Once snowpipe created on top of your azure blob storage, It will monitor bucket and file will be loaded into your stage table as soon as new file comes in. After copied the data into stage table you can schedule transformation SQL using snowflake task.
You can refer snowpipe creation step for azure blob storage in below link:
Snowpipe on microsoft Azure blob storage
Is there any way to do Azure Table Storage backup in to an another Azure Table Storage incrementally. AZcopy has solution for full backup for the table but not incremental.
We don’t not support backup of Azure Tables currently, and we may not be doing that in the near future
Going forward future Table investments will be in Cosmos DB. See the documentation for Azure CosmosDB online backup and restore
There is a similar thread discussion in the SO link, this provides some idea on your scenario
My company has two Azure environments. The first one was a temporary environment and is being re-purposed / decommissioned / I'm not sure. All I know is I need to get files from one Data Lake on one environment, to a DataLake on another. I've looked at adlcopy and azcopy and neither seem like they will do what I need done. Has anyone encountered this before and if so, what did you use to solve it?
Maybe you can think about Azure Data Factory, it can helps you transfer files or data from one Azure Data Lake to Another Data Lake.
You can reference Copy data to or from Azure Data Lake Storage Gen2 using Azure Data Factory.
This article outlines how to use Copy Activity in Azure Data Factory to copy data to and from Data Lake Storage Gen2. It builds on the Copy Activity overview article that presents a general overview of Copy Activity.
For example, you can learn from this tutorial: Quickstart: Use the Copy Data tool to copy data.
In this quickstart, you use the Azure portal to create a data factory. Then, you use the Copy Data tool to create a pipeline that copies data from a folder in Azure Blob storage to another folder.
Hope this helps.
I'm trying to understand the best way to migrate a large set of data - ~ 6M text rows from (an Azure Hosted) SQL Server to Blob storage.
For the most part, these records are archived records, and are rarely accessed - blob storage made sense as a place to hold these.
I have had a look at Azure Data Factory and it seems to be the right option, but I am unsure of it fulfilling requirements.
Simply the scenario is, for each row in the table, I want to create a blob, with the contents of 1 column from this row.
I see the tutorial (i.e. https://learn.microsoft.com/en-us/azure/data-factory/data-factory-copy-activity-tutorial-using-azure-portal) is good at explaining migration of bulk-to-bulk data pipeline, but I would like to migrate from a bulk-to-many dataset.
Hope that makes sense and someone can help?
As of now, Azure Data Factory does not have anything built in like a For Each loop in SSIS. You could use a custom .net activity to do this but it would require a lot of custom code.
I would ask, if you were transferring this to another database, would you create 6 million tables all with the same structure? What is to be gained by having the separate items?
Another alternative might be converting it to JSON which would be easy using Data Factory. Here is an example I did recently moving data into DocumentDB.
Copy From OnPrem SQL server to DocumentDB using custom activity in ADF Pipeline
SSIS 2016 with the Azure Feature Pack, giving Azure Tasks such as Azure Blob Upload Task and Azure Blob Destination. You might be better off using this, maybe an OLEDB command or the For Each loop with an Azure Blob destination could be another option.
Good luck!
Azure has a ForEach activity which can be place after LookUp or Metadata to get the each row from SQL to blob
ForEach