Microsoft Fabric Product Group presents T-SQL support in Microsoft Fabric Notebooks

hi everyone welcome back another episode of fabric espresso you CBS directly from Microsoft fabric product engineering group welcome today I have a pleasure to host kicha to discuss the newest feature in the area of fabric notebooks so I heard that recently we have announced tsql notebooks meaning that fabric supports now tsql as a language inside fabric notebook supports why we are doing that what's the purpose yeah again thanks for having me this is CH out I'm the PM from the Microsoft PR data engineer teams so uh go to our CR I think since we launched the notebooks we have a lot of adoptions people love it like experience and starting I think starting from last year we are kind of thinking about how we can expand the supporting scenario in terms supporting more language so initially we are supporting notebook using the spot language you can write spot CLE write P Spot to carry like house that spot basically is the only engine we support inside the no notebooks then with this initiative we kind of expand the engine we can support for the notebooks T is one of them and also we also actually also supporting P pons but for the tle meaning that as a CLE Developers now you can use the notebook as your authoring tools you can write all the foods tcq commands inside the notebook and also run the tsq executions or t carry against the warehouse or even the sqle endpoint to run your TC code so you can benefit from the all existing notebook experience for example you have can one Coale to have one query or one L or one statement you can have some markdown to EXP explain hey what this TQ Carri is doing because in the CQ edit size we have one big kind of the editing areas once you have a complex CLE Carri it's kind of the hard to maintains now you can have a different Co out to split the complex TC carrier or command into different Co out make it much more easier to maintains and also you can add the markdown celles to explain make some comments why I'm doing this why I'm doing that and why this TC doing this weight why the following codell in doing this we making the a experience and even the maintaining is much easier as a long-term runs and also because it's inside notebooks all the cool features charting visualizations andot co-pilot yes collaborations all these good things is already available for the SLE developers and one thing is mention is the one kind of the limitation right now on the warehouse is the it's kind of hard to share the code without sharing the data because once you need to share the TC go you need the code you also kind of the need to share with the data the warehouse ex now with the tcq notebooks you have the freedom to say hey I just like to share this code with my colleague I don't want to kind of to share my datas so you just need to share the notebooks and in that way you can just purely share the tle code with your colleague so that's kind of the motivation behind the scenes why we enable this tsq notbook experience so we announced the public preview in the Fab call in Europe so since we launched that we already see a kind of the high adoptions but we're expecting the adoption can be increased based on more and more user aware of these features that's awesome is that integrated with monitoring experience monitoring C yes that's one of the areas we are keep working around so right now if you run the TC notebooks you notice that because there's two different areas you can basically can do the monitorings one is the inside the notebooks we have that recent run panel you can show all the history of existing execution work from The Spar we are going to expand that view to including all the history Run for the tcq executions that's still in the developments and also on the monitor Hub you should be able to see later on once the design is ready or execution is done you should see the for the notebook run is the tal notbook or the spark notb or python notbook that's something we are working on modulators but right now the monitoring is one of the areas we are still working to make the experience complete so you can expect something I don't know later off this year or next year the monitor experience will be much more complete sounds good uh want to ask okay so I create a notebook I switch to tsql as a language I attach my Lakehouse then I write a query create a view and then what's the end Eng behind

it meaning that am I using the Lakehouse or Warehouse or spark SQL how to know which one and when if you pick the language as the tsql meaning that you are using the DW Warehouse as the engines as the compute to execute the code so actually inside the notebooks once you switch the language to TC code for the all the existing Co out if the co out is written in different language for example for the spot language you notice that the Cod SM as unsupported meaning that if you try to run all the code the coell Mark is unsupported you have option to skip that meaning that hey I'm running all the coell and the current language is the TC code I'm using the DW as the engines so it doesn't make any sense to run any spark code anymore because the DW engine doesn't understand how to run a spark right so in that case W the language is the TC code and the engine is the warehouse but once you pick the language as a sparkk one of the spark language meaning that P spark C code again you are falling back to the spark as engines now in the coell you notice that all the TC coell will be Mark as a warning marker and or and supported status once you try to click run all in this case all the TC code will be skipped only the spot language only the codell using The Spar as a language will be posted to the spark run as the current weight how the spot not is execute so in that way actually as a users if you're really a powerful user you know how to write spark TC code some for some other language we support you can use the same notebook and by switch different language you can write a different language in a different Cod out and also operate with the different data source for example if I'm writing tsql I set the tsql as a language I use some coer with the tle I'm curing the warehouse now once I'm done with the tle developments using the same us the same notebook I switch language the pbar now I can write pbar and curve like house so that's kind of the freedom of or flexibility we are offering to the user saying that if you really are powerful users and you do have a scenario with the different data items with a different language and use a different compute it's your choice so you don't need to stick with one particular notebooks and this notebook must be stick with one computer or one Androids so you do have the freedom to say I like to pick what's the Android I like to use I like to pick which language compatible with that Lang with that engines and that's your freedoms so that's the flexibility we like to offer with these kind of multi personal things for that makes sense and uh I can imagine that it a huge benefit for those who are processing as you said different data sources different uh tables different languages different engines many times we try to switch in between because one language supports some specific functionalities handling time stamps differently processing xmls so it looks that the fabric notebook is becoming a language and engine agnostic notebook where you write the code comment that with markdown share it across your team share the code and then uh collaborate life as well and leverage different engines nice so thanks a lot uh thanks for joining us today sharing all those details and for those who are watching us remember to leave the like button leave a comment subscribe to our Channel suggest the topic for the next episode and until the next time happy exploring and coding with using tsql in fabric notebooks thank thanks a lot