Build button in dbt

Build button in dbt

In dbt, you do dbt build by typing this:

dbt build -s Dim_Product.sql

You can build the predecessors of that model too (meaning upstream), by adding a plus sign like this:

dbt build -s +Dim_Product.sql

That means that all the models which are used by Dim_Product will be built first. And that is not just 1 layer before, but ALL the layers before. All the upstream model will be build.

You can build the downstream models too, by adding a plus sign after the model name, like this:

dbt build -s Dim_Product.sql+

That “.sql” is optional actually. You don’t have to put it in. So this is perfectly valid:

dbt build -s Dim_Product+

Now here’s what I’d like to tell you about today: in dbt we have a button to do all that so you don’t have to type anything!

This is dbt development screen:

Notice the red arrow above? That’s the Build button? If you don’t click the Build button but the down arrow next to it, you’ll see this:

You can build just the model currently on the screen, or with the downstream, or with the upstream. Or both. Or run the model. Or test the model.

Very useful isn’t it?

Andy Webster

Data Cloud Platform, Data Analytics Engineer, Certified DBA MSc, BSc

4 个月

Cool Vincent. Very cool..

回复
Andy Webster

Data Cloud Platform, Data Analytics Engineer, Certified DBA MSc, BSc

4 个月

... and I'm still learning, new data platforms, new data execution paradigms, etc. etc. every day... to become a better and better Data Engineer it's a journey, not just a pivot and a certification or two - sorry software engineers, sorry...

Andy Webster

Data Cloud Platform, Data Analytics Engineer, Certified DBA MSc, BSc

4 个月

OK for transformations and like the idea of SQL transformations as"code" wrapped up with git, ci/cd and other software engineering principles and pretty straight forward and useful, very popular, but IMHO too geared towards software engineers who think they are data engineers because they can write Python, use pandas, SQL alchemy etc. to connect to a database. No - a data engineer is way, way more than that - I know, I have been both and know what I had to learn to go from SE, through DBA to Data & Analytics Engineer. Regards, Andy. ??

要查看或添加评论,请登录

Vincent Rainardi的更多文章

  • Snowflake vs SQL Server

    Snowflake vs SQL Server

    Sometimes we need to remind ourselves that Snowflake is not an OLTP database. I know today is the era of Hybrid tables…

    6 条评论
  • Data engineer becoming solution architect

    Data engineer becoming solution architect

    Are you a data engineer thinking about transitioning to a cloud solution architect? Data engineer are good with…

    2 条评论
  • Asset Mgt vs Fund Mgt vs Investment Mgt vs Wealth Mgt: What's the difference?

    Asset Mgt vs Fund Mgt vs Investment Mgt vs Wealth Mgt: What's the difference?

    If you work in banking or investment or any other sector in financial services, you might be wondering about the above.…

  • Data Warehousing Basics: Cost

    Data Warehousing Basics: Cost

    If you call yourself a data engineer you need to be aware of 2 additional things compared to a developer. The first one…

    2 条评论
  • My Linkedin post & articles

    My Linkedin post & articles

    The list below goes back to Nov 2024. For older than that see here.

    9 条评论
  • Data Warehousing Basics: Single Customer View

    Data Warehousing Basics: Single Customer View

    Imagine that you work for an insurance company who sell health insurance (HI), life insurance (LI), general insurance…

    2 条评论
  • Data Warehousing Basics: NFR

    Data Warehousing Basics: NFR

    What I’m about to tell you today failed a lot of data warehousing projects which is why it’s worth paying attention so…

    1 条评论
  • ML and AI - What's the difference?

    ML and AI - What's the difference?

    Machine Learning covers about 20-30 algorithms such as Logistic Regression, Decision Tree, Gradient Boosting, Random…

    4 条评论
  • Microsoft Fabric or Synapse Analytics?

    Microsoft Fabric or Synapse Analytics?

    When it comes to Data Warehousing, Microsoft is confusing. Why? Because it has Microsoft Fabric and it also has Synapse…

    16 条评论
  • Data Warehousing Basics: Transformations

    Data Warehousing Basics: Transformations

    As Bill Inmon said, T is the most difficult thing to do in the ETL. And that is why ETL vendors swap it around - they…

    2 条评论

社区洞察

其他会员也浏览了