Press "Enter" to skip to content

Day: March 18, 2025

Asynchronous SQL Statement Execution in Snowflake

Published 2025-03-18 by Kevin Feasel

Koen Verbeeck doesn’t want to wait for an answer:

It’s been a while since I blogged about Snowflake, but a recent LinkedIn post caught my attention: the ability to add asynchronous execution of SQL statements in a stored procedure. In other words: parallel execution of SQL statements. This got me excited, because in my opinion this is something that has been missing in T-SQL since forever. Every time you want to do something in parallel, you need to use external tools to accomplish this in SQL Server (or Azure SQL DB, or Fabric Warehouse, or Fabric SQL DB, or … you get the point). You needed to use SQL Server Agent Jobs, or SSIS packages, or Azure Data Factory and so on.

Snowflake introduces the ASYNC and AWAIT keywords, which can be used to trigger asynchronous execution. 

Read on for a very simple example and some thoughts from Koen. Aside from possibly making data modifications faster (assuming there are no constraint checks), I’m not quite sure what the major benefit to this is. I’d generally use asynchronous calls to support UI operations, letting a calling application respond to user input while some background thread processes data. But I’m not positive what you get from pushing async/await logic into the database itself.

Leave a Comment

Iceberg Data Support in OneLake

Published 2025-03-18 by Kevin Feasel

Matthew Hicks isn’t replicating data anymore:

Microsoft OneLake is the single, unified, logical data lake that allows your entire organization to store, manage, and analyze data in one place. It provides seamless integration with various data sources and engines, making it easier to derive insights and drive innovation.

At the most recent Microsoft Build conference, we announced the integration effort between Snowflake and OneLake, which aims to allow users of both Snowflake and Microsoft Fabric to work on the same Iceberg data in OneLake, with no data duplication/movement needed. More recently, we released the preview of OneLake’s Iceberg table format support, which included the ability for Snowflake to write Iceberg tables directly to OneLake.

Click through for more information about the current status of this feature, as well as what’s coming soon.

Leave a Comment

Using the Excel Solver with Power Pivot

Published 2025-03-18 by Kevin Feasel

Chris Webb remembers a few functions:

After years of meaning to learn how to use Excel Solver, this week I’ve finally made a start: I want to use it to work out the optimal way of distributing workspaces across capacities in a Fabric tenant from the point of view of CU usage. I’m a long way from knowing how to do this properly (I’ll blog about it when I’m ready) but one of the first things I found is that while there are lots of resources on the internet showing how to use Solver, there are no examples of how to use Solver when your source data is stored in the Excel Data Model, aka Power Pivot. Getting that data onto the worksheet is fairly straightforward, but what if you also need Solver to change how that data is sliced and diced? It turns out that not hard to do if you know how to use cube functions.

Read on to see what Chris means and how you can send data from the Excel Data Model into the Solver.

Leave a Comment

Identifying an Object Name from a Wait Resource

Published 2025-03-18 by Kevin Feasel

Haripriya Naidu wants to know what object this is:

You run a query to check for locking or blocking in SSMS and find a wait resource in the format (8:1:3610). To identify the object name, you would typically run multiple queries, first find database name, turn on trace flag 3604, then find object id from DBCC PAGE and then find object name from sys.objects.
However, with a new function “sys.dm_db_page_info” introduced in SQL Server 2019, you no longer need to go through these steps. Instead, you can run a single query to get the object name directly.

Read on to see how it all works. This is definitely a lot easier than in the olden days.

Leave a Comment