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Month: January 2021

A Review of AWS Athena

John McCormack updates an older review:

AWS’s own documentation is the best place for full details on the Athena offering, this post hopes to serve as further explanation and also act as an anchor to some more detailed information. As it is a managed service, Athena requires no administration, maintenance or patching. It’s not designed for regular querying of tables in a way that you would with an RDBMS. Performance is geared around querying large data sets which may include structured data or semi-structured data. There are no licensing costs like you may have with some Relational Database Management Systems (RDBMS) such as SQL Server and costs are kept low, as you only pay when you run queries in AWS Athena.

Click through for an overview of product benefits.

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Using Spark Pools in Azure Synapse Analytics

Rahul Mehta shows how to create and use an Apache Spark pool in Azure Synapse Analytics:

In the last part of the Azure Synapse Analytics article series, we learned how to create a dedicated SQL pool. Azure Synapse support three different types of pools – on-demand SQL pool, dedicated SQL pool and Spark pool. Spark provides an in-memory distributed processing framework for big data analytics, which suits many big data analytics use-cases. Azure Synapse Analytics provides mechanisms to use SQL on-demand pool to query data as a service, SQL dedicated pool for data warehousing using distributed data processing engine, and Spark pool for analytics using in-memory big data processing engine. This article shows how to create a Spark pool in Azure Synapse Analytics and further how to process the data using it.

Click through for a demo on setup and a sample notebook to get started.

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Resource Governor and Memory Grants

Deepthi Goguri explains how you can use Resource Governor to control memory utilization:

Queries doesn’t start unless available memory is 150% of requested query memory because sql server will always allocate a little bit of additional buffer memory. Lets take the 100MB query which will get 150MB with additional buffer. What if this query only get 100MB and doesn’t get that additional buffer in the beginning to run the query? In that case, the query will wait until the 25x the query cost which is in seconds. When the timeout occurs and if the exact grant (100MB) is available without the buffer amount then the query starts to run this time. In other scenario, even after waiting for so long and after the timeout, the exact memory (100MB) without the memory grant is not available and less than 100MB is available, in that case the grant can be decreased to the minimum required grant. What if even the minimum required grant is not available, in that case we will receive an error 8645. We can configure the timeout by using the resource governor.

Read on for more detail.

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Refreshing Power BI Report Server Reports

Aaron Nelson has some new cmdlets for us:

I just wanted to give everyone a heads-up that a new version of the ReportingServicesTools module went out last week, and it includes 3 new PowerShell functions for working with Power BI reports on a Power BI Report Server (PBIRS) instance.

You can now Create (New), Get, & Start a CacheRefreshPlan of a Power BI report deployed to a PBIRS instance.  For clarity, these only apply to reports using an Imported model, not those using Direct Query.

Click through for more detail.

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Improving Triggers

Ed Pollack tries to improve our usage of triggers:

SQL Server triggers are a subject of both functionality and controversy on any database platform. They can provide immense utility at a low cost, but are often misused by developers, DBAs, and architects alike, resulting in performance bottlenecks or maintainability challenges.

This article briefly reviews DML (data manipulation language) triggers and delves into a discussion about how triggers can be efficiently and effectively used as well as when triggers can dig developers into holes that are hard to escape.

Read the whole thing. Triggers are rather useful tools when used correctly, but it’s easy to misuse them on accident.

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Modifying a Linked Entity in Power BI Dataflows

Reza Rad gives us a method to modify linked entities in Power BI dataflows:

It is not possible to change a linked entity in a dataflow in Power BI. Linked entities has to be modified only in the dataflow in which they are created. However, sometimes, you need to do a small modification to the linked entity in a chained dataflow. There is a very simple trick, In this article and video, I’ll explain how you can do that.

Read on to see how.

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PASS Under New Ownership

Steve Jones announces that Redgate is the captain now:

Redgate Software confirmed today that it has acquired the assets of the Professional Association for SQL Server (PASS), which ended operations on January 15, and will revive the Summit, continue SQLSaturdays, and make available the library of content and training sessions.

Note that this will be different from PASS as it existed, so membership in the old association doesn’t carry over to the new. If you’re interested in keeping up to date on this, check out

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Rule 42 Software

John Mount describes a software development anti-pattern:

As software changes, it often accretes feature and drifts away from its design, if it even started with one, and many defaults and settings become undesirable. New users are blamed for not moving parameter settings away from the defaults to the “obvious” acceptable values.

Click through for the origin of the name and more info on how to avoid it.

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