I have an Azure Data Lake instance. It has tables in it. The tables have data in them. I simply want to look at the data in the tables, interactively, without having to run an Azure Data Lake batch job and turn them into CSV or TSV files.
This seems like an ordinary request but I can't figure out how to do it. What am I missing here?
Browsing U-SQL tables is not currently supported. If you go via the Azure Portal, you can use Data Explorer which makes scripting the job easy, via its 'Query Table' option, or just script it yourself.
If you genuinely feel this is missing, create a feedback item and vote for it here.
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Good morning! I've found TONS of articles, questions, and guides on how to import data from local excel documents to Azure SQL databases, or how to pull from an Azure database to Excel, but nothing about how I could use SQL to query an excel online document (which would be hosted on SharePoint).
I'm fairly new in my learning - I'd be setting this up via a query in SQL written/executed via Azure Data Studio. The excel file is one that I'd be creating, and hosting via our company's SharePoint system. The Azure SQL database will also be one that I'm constructing myself, which is in progress. I've tried to find walkthroughs, scripts, explanations, something. But it's totally silent. Granted, that could be an indicator that it can't be done, but I figured I'd ask here. Overall, I'm just trying to figure out what is possible, so I can come up with a decent range of simple, easy-to-use means of data input for my team, or, in this case, to capture some of the ways they're tracking their work.
Not sure if this is sufficient detail, please feel free to ask any follow-up questions.
Azure Data Studio is a tool to work with SQL databases, most notably MS SQL. Though you can connect to some other types as well.
Therefore, in order to use Data Studio to query your data, it needs to be in a SQL database. To accomplish that, you need to setup a process to load the data from your Excel document into a table in you database and run that process on a regular basis to update the table. You could look into Azure Data Factory to do that, though I don't see why you should bother to do that just to use Azure Data Studio, when you can browse the data in Excel, use PowerBI, Qlik or any other tool that can connect directly to Excel.
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.
I need to create a database solely for analytical purposes. The idea here is for it to start off as a 1:1 replica of a current SQL Server database but we will then add in additional tables. The idea here is to be able to have read-write access to a db without dropping anything in production inadvertently.
We would ideally like to set a daily refresh schedule to update all tables in the new tb to match the tables in the live environment.
In terms of the DBMS for the new database, I am very easy - MySQL, SQL Server, PostgreSQL would be great -- I am not hugely familiar with the Google Storage/BigQuery stack but if this is an easy option, I'm open to it.
You could use a standard HA/DR solution with a readable secondary (Availability Groups/mirroring /log shipping).
then have a second database on the new server for your additional tables.
Cloud Storage and BigQuery are not RDBMS services themselves, but could be used in this case to store the backups/exports/dumps from the replica, and then have the analytical work performed on those backups.
Here is an example workflow:
Perform a backup and restore in a different database
Add the new tables in the new database
Export the database as a CSV file on your local machine
Here you could either directly load the CSV file in BigQuery, or upload that file in a Cloud Storage bucket previously created
Query the data
I suggest to take a look at the multiple methods for loading data in BigQuery, as well as the methods for querying against external data sources which may help to determine which database replication/export method might be best for your use case.
I need to export a multi terabyte dataset processed via Azure Data Lake Analytics(ADLA) onto a SQL Server database.
Based on my research so far, I know that I can write the result of (ADLA) output to a Data Lake store or WASB using built-in outputters, and then read the output data from SQL server using Polybase.
However, creating the result of ADLA processing as an ADLA table seems pretty enticing to us. It is a clean solution (no files to manage), multiple readers, built-in partitioning, distribution keys and the potential for allowing other processes to access the tables.
If we use ADLA tables, can I access ADLA tables via SQL Polybase? If not, is there any way to access the files underlying the ADLA tables directly from Polybase?
I know that I can probably do this using ADF, but at this point I want to avoid ADF to the extent possible - to minimize costs, and to keep the process simple.
Unfortunately, Polybase support for ADLA Tables is still on the roadmap and not yet available. Please file a feature request through the SQL Data Warehouse User voice page.
The suggested work-around is to produce the information as Csv in ADLA and then create the partitioned and distributed table in SQL DW and use Polybase to read the data and fill the SQL DW managed table.
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