I have a requirement to bulk upload data from a excel file to an Azure SQL table on a daily basis. I did some research and found that we could create a VM install full SQL and use SSIS package to do this.
Is there any other reliable way to go about this? The excel may contain up to 10,000 rows.
I have also read we could upload file to a blob storage and read from there but found it's not very robust approach.
Can anyone suggest if this is feasible approach-
Place excel file in Azure Website accessed via FTP
Azure Timer job using SQL Bulk copy code to update the SQL table
Any help would be highly appreciated!
You could use Azure Data Factory - check out the documentation here. Place your files in Azure Data Lake and the ADF will process them.
Related
I tried using HTTP request I am able to send the data from HTTP request to azure SQL but I am manually Send the data through postman but that is not my requirement
Requirement:I need to use a scheduler and a particular time the data from the text file need to be read and to be stored into Azure-SqlDB
if you have any resource or examples please let me know
About how import Text file(CSV) data to Azure SQL by using logic-App, you could reference this tutorial: Quick, easy and cheap way to automate data loading from CSV file into Azure SQL:
Check out how to leverage Azure Blob Storage and Logic Apps for
simple scenario of data loading from CSV into Azure SQL in less than
30 minutes and with almost no coding.
About any developer out there at some point or another had to
automate ETL process for data loading. This article will present a
fast and convinient way to create data loading workflow for CSVs
using Azure SQL and blob storage.
It also introduced other ways you could reference:
How import Text file(CSV) data to Azure SQL by using Data Factory.
How import Text file(CSV) data from Blob stroage to Azure SQL by
using T-SQL.
You also could reference:
Upload Flat File on Azure SQL Database using Azure Logic App
Using Azure Logic Apps to Import CSV to SQL Server
I'm agree with #Mandar Dharmadhikari, Logic app is not the best way to do it.
If your csv file with large data, I also suggest you to use Data Factory，when the copy active pipeline created, you could trigger the pipeline executing in schedule.
Hope this helps.
I would suggest you yo use Azure Data Factory as it is more suited to the task that you want to perform. Following post gives the idea on how to move csv data fo SQL.
http://normalian.hatenablog.com/entry/2017/09/04/233320
I am new to Azure and hence trying to understand what services to use when and how.
At the moment, I have one excel file that has couple of tabs that require some transformation to create one excel file tab (inside the source file itself - say Tab "x"). The final tab "x" created is then being useful for creating one final excel file that is shared to various team.
At present, everything is done manually.
This needs to change and the excel file shared to team has to be automated. The source of the file is the excel file that has various tabs (excluding tab "x") and the reporting tool will be SSRS with excel data being stored in cloud.
Keeping this scenario in mind, what is the best way to store excel data into cloud? The excel data will be stored in cloud on a monthly basis. I am confused as to whether to store data in Azure-SQL, Azure Data Lake Gen 2 or Azure Data Lake Analytics or Azure SQL VM?
Every month data can be fetched from Excel file and populate into Azure using azure data factory. But I am not sure what is the best way to store data in the cloud considering the fact that some ETL process is needed to generate data in format similar to tab "X".
I think you can think about to using Azure SQL database.
Azure SQL database or SQL server support you import data from the excel( or csv) files. For more details and limits, please see: Import data from Excel to SQL Server or Azure SQL Database.
If your data have stored in Azure SQL database, you also can using EXCEL to get the data from Azure SQL database:
Connect Excel to a single database in Azure SQL Database and import data and create tables and charts based on values in the database. In this tutorial you will set up the connection between Excel and a database table, save the file that stores data and the connection information for Excel, and then create a pivot chart from the database values.
Reference: Import data from Excel to SQL Server or Azure SQL Database.
I think you don't need to store these excel files in Azure Data Lake.Azure Data Lake Storage Gen2 is a set of capabilities dedicated to big data analytics, built on Azure Blob storage. It's still a storage.
The more Azure resource you use, the more cost you need to pay.
If your excel file stored in you local computer, you can using Azure Data Factory to access these local files or with self host integration runtime.
Please reference： Copy data to or from a file system by using Azure Data Factory.
Hope this helps.
Your storage requirements are very minimal, so I would select Data Lake to store your documents. The alternative is Blob Storage, but I always prefer Data Lake because it works with Azure Active Directory.
In your scenario, drop it in the ADL, and use the ADL as the source in Azure Data Factory.
Edit:
Honestly, your original post is a little confusing. You have a RAW Excel document, you do some transformations on the RAW document, to generate an Excel Source document. This source document holds the final dataset that the dev team will use to build out SSRS reports. You need to make this dataset available to the teams so that they can connect to it to build the reports? My suggestion is to keep it simple and drop the final source dataset in Excel format, into blob or data lake storage and then ask the dev guys to pick it up from the location. If you are going the route of designing and maintaining a data pipeline (Blob > Data Factory > SQL, or CSV, TSV - then you are introducing unnecessary complications.
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
I'd like to have our daily csv log files transferred from GCS to Azure Datalake Store, but I can't really figure out what would be the easiest way for it.
Is there a built-in solution for that?
Can I do that with Data Factory?
I'd rather avoid running a VM scheduled to do this with the apis. The idea comes from the GCS->(DataFlow->)BigQuery solution.
Thanks for any ideas!
Yes, you can move data from Google Cloud Storage to Azure Data lake Store using Azure Data Factory by developing custom copy activity. However, in this activity, you will be using APIs for transferring that data. See details on this article.
I have read this SO question but mine is quite specific to the "import" of CSV and not how to access the blob to get the CSV out
Which is the best way?
1) CSV Stored in the Blob - use a worker role, read the CSV from the blob, parse data and update database
2) Is SQL BulkCopy/BulkInsert an option. The challenge here is that it should not have any on-premise involvement. All within Azure: blob->SQL DAtabase.
3) Will Azure Automation help? Are there PS scripts/workflows that help in such bulk update of CSV data to Azure SQL DB? I haven't found any though
Are there other options that help import blob CSV data to SQL DB without having to write custom code?
Appreciate any thoughts...
Your first method would work. You could also use azcopy (http://aka.ms/azcopy) to download the file locally, and then use BCP to load it into SQL - this way you wont have to write any code for this.
Azure Automation would help if you want to do this repeatedly. You should be able to set this up as a script even if one doesn't exist.
I know this is outdated question but for anyone looking for quick way to do this feel free to check my article on how to do this quickly using SQL prodecure triggered by Logic App.
In short you run on master
CREATE MASTER KEY ENCRYPTION BY PASSWORD = 'UNIQUE_STRING_HERE'
Then you run on DB
CREATE DATABASE SCOPED CREDENTIAL BlobCredential
WITH IDENTITY = 'SHARED ACCESS SIGNATURE',
SECRET = 'sv=SAS_TOKEN_HERE';
CREATE EXTERNAL DATA SOURCE AzureBlob
WITH (
TYPE = BLOB_STORAGE,
LOCATION = 'https://<account_name>.blob.core.windows.net/<container_name>',
CREDENTIAL = BlobCredential
);
And then
BULK INSERT <my_table>
FROM '<file_name>.csv'
WITH (
DATA_SOURCE = 'AzureBlob',
FORMAT = 'CSV',
FIRSTROW = 2
);
Just wrap this insert in procedure and execute it from logic app.
https://marczak.io/posts/azure-loading-csv-to-sql/
or just use ADF like here
https://azure4everyone.com/posts/2019/07/data-factory-intro/
Late answer to old question, but...
If you can use an Azure SQL Data warehouse you could take advantage of PolyBase to directly query the data in CSV format stored in the blob https://learn.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-load-polybase-guide#export-data-to-azure-blob-storage. This will allow you to directly map the data as an external table and query it dynamically.
This saves you the trouble of writing an external tool/solution for extracting, parsing and uploading the data to the Azure SQL database. Unfortunately PolyBase only works for Azure SQL Data warehouse, not Database, but you could setup something that read the structured data from the warehouse to your solution.
I know this question is two years old, but for those just now searching on the topic, I'd like to mention that the new Azure Feature Pack for SSIS makes this an easy task in SSIS. In VS Data Tools, after installing the Azure Feature pack, you would open an empty SSIS project and 1) Create an Azure Storage Connection Manager, then 2) Add a Data Flow Task, then open the Data Flow task and 3) Add a Blob Source tool to connect to the CSV, and then 4) using Destination Assistant connect to the SQL Table where the data is going. You can then execute this as a one-time load interactively inside the VS Data Tools IDE, or publish it to the SQL Server instance and create a recurring job.