I need expert opinion on a project I am working on. We currently get data files that we load into our Azure sql database using a local script that calls stored procedures. I am planning on replacing the script with ssis jobs to load the data into our Azure Sql but wondering if that's a good option given our needs.I am opened to different suggestions too. The process we go through is to load data file to staging tables and validate before making updates to live tables. The validation and updates are done by calling stored procedures...so the ssis package will just load the data and make calls to those stored procedures. I have looked at ADF IR and Databricks but they seem overkill but am open to hear people with experience using those as well. I am currently running the ssis package locally as well. Any suggestion on better architecture or tools for this scenario? Thanks!
I would definitely have a look at Azure Data Factory Data flows. With this you can easily build your ETL pipelines in the a Azure Data Factory GUI.
In the following example two text files from a Blob Storage are read, joined, a surrogate key is added and finally the data is loaded to Azure Synapse Analytics (would be the same for Azure SQL):
You finally put this Mapping Data Flow into a pipeline and can trigger it, e. g. if new data arrives.
You can just BULK INSERT data from Azure Blob Store:
https://learn.microsoft.com/en-us/sql/relational-databases/import-export/examples-of-bulk-access-to-data-in-azure-blob-storage?view=sql-server-ver15#accessing-data-in-a-csv-file-referencing-an-azure-blob-storage-location
Then you can use ADF (no IR) or Databricks or Azure Batch or Azure Elastic Jobs to schedule the execution.
Related
I am moving from SSIS to Azure.
we have 100's of files and MSSQL tables that we want to push into a Gen2 data lake
using 3 zones then SQL Data Lake
Zones being Raw, Staging & Presentation (Change names as you wish)
What is the best process to automate this as much as possible
for example build a table with files / folders / tables to bring into Raw zone
then have Synapse bring these objects either full or incremental load
then process the them into the next 2 zones I guess more custom code as we progress.
Your requirement can be accomplished using multiple activities in Azure Data Factory.
To migrate SSIS packages, you need to use SSIS Integrated Runtime (IR). ADF supports SSIS Integration which can be configured by creating a new SSIS Integration runtime. To create the same, click on the Configure SSIS Integration, provide the basic details and create a new runtime.
Refer below image to create new SSIS IR.
Refer this third-party tutorial by SQLShack to Move local SSIS packages to Azure Data Factory.
Now, to copy the data to different zones using copy activity. You can make as much copy of your data as your requirement using copy activity. Refer Copy data between Azure data stores using Azure Data Factory.
ADF also supports Incrementally load data using Change Data Capture (CDC).
Note: Both Azure SQL MI and SQL Server support the Change Data Capture technology.
Tumbling window trigger and CDC window parameters need to be configured to make the incremental load automated. Check this official tutorial.
The last part:
then process them into the next 2 zones
This you need to manage programmatically as there is no such feature available in ADF which can update the other copies of the data based on CDC. You need to either create a separate CDC for those zones or do it logically.
I read a few threads on this but noticed most are outdated, with excel becoming an integration in 2020.
I have a few excel files stored in Drobox, I would like to automate the extraction of that data into azure data factory, perform some ETL functions with data coming from other sources, and finally push the final, complete table to Azure SQL.
I would like to ask what is the most efficient way of doing so?
Would it be on the basis of automating a logic app to extract the xlsx files into Azure Blob, use data factory for ETL, join with other SQL tables, and finally push the final table to Azure SQL?
Appreciate it!
Before using Logic app to extract excel file Know Issues and Limitations with respect to excel connectors.
If you are importing large files using logic app depending on size of files you are importing consider this thread once - logic apps vs azure functions for large files
Just to summarize approach, I have mentioned below steps:
Step1: Use Azure Logic app to upload excel files from Dropbox to blob storage
Step2: Create data factory pipeline with copy data activity
Step3: Use blob storage service as a source dataset.
Step4: Create SQL database with required schema.
Step5: Do schema mapping
Step6: Finally Use SQL database table as sink
how to schedule a Query in Azure Synapse On-demand and save the result to a azure storage every 1 hour
my idea is to materialize the results into a separate storage and use PowerBI to access the results
Besides the fact that PowerBI can directly access your Synapse instance, if you want to go this route you have several options:
This can be done using a pipeline in the new Synapse Workspace. You should be aware that this technology is still in preview.
Use Polybase and Stored Procedures on a Job Scheduler to INSERT to a Blob Storage location. There is a lot of configuration in this option.
At present, I would recommend Azure Data Factory (ADF) on a Schedule Trigger. This is the simplest and most reliable of the current options. Based on the scenario you described, a single Copy activity could easily perform this task.
I am new to data lake analytics and using USQL.
I am currently setting up data factory pipeline which would replace an existing SSIS workflow. The data factory pipeline would essentially
Extract data transactional database into ADLS
Transform raw entities using USQL
Load the data into SSAS using custom activity
Question
I have a USQL project set up and wanted if there was a standard way of deploying them to ADLA other than just uploading the scripts to a folder in the store.
Great question!
I'm not sure about a standard way, or even a way that might be considered best practice yet. But I use all of the tools you mention to perform very similar tasks.
To try and answer your question: What I do is create the U-SQL scripts as stored procedures within the logical ADLA database. In the VS USQL project I have 1 script per stored proc. The ADF activities then call the proc name. This gives you the right level of disconnection between services and also means you don't need additional blob storage for USQL files.
In my VS solution I often also have a PowerShell project to help manage things. Specifically one what takes all my 'usp_' U-SQL scripts to create one big DDL style thing that can be deployed to the logical ADLA database.
The PowerShell then does the deployment for me using the submit job cmdlet. Example below.
Submit-AzureRmDataLakeAnalyticsJob `
-Name $JobName `
-AccountName $DLAnalytics `
–Script $USQLProcDeployAll `
-DegreeOfParallelism $DLAnalyticsDoP
Hope this gives you a steer. I also accept that these tools are still fairly new. So open to other suggestions.
Cheers
I've done a fair bit of reading and it seems like there are a couple of off-the-shelf products that replicate/sync data from on-premise database to Azure SQL Data Warehouse but I've found nothing that syncs using an Azure database as the source. The Azure Data Factory holds some promise however it looks more suited to one off loads.
Anyone know of a way? (SSIS package not really an option as I want the transfer to occur wholly inside the cloud)
Azure Data Factory can run continuous loads from SQL Database to SQL Data Warehouse. You'll want to look into the frequency and interval parameters for the pipeline
The documentation is here https://azure.microsoft.com/en-us/documentation/articles/data-factory-create-datasets/.