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Day: July 10, 2020

Schema References and Multiple Event Types in a Kafka Topic

Robert Yokota updates some prior knowledge:

In the article Should You Put Several Event Types in the Same Kafka Topic?, Martin Kleppmann discusses when to combine several event types in the same topic and introduces new subject name strategies for determining how Confluent Schema Registry should be used when producing events to an Apache Kafka® topic.

Schema Registry now supports schema references in Confluent Platform 5.5, and this blog post presents an alternative means of putting several event types in the same topic using schema references, discussing the advantages and disadvantages of this approach.

Click through to see how this works out.

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Performance Tuning for Cloudera’s Operational Database

Liliana Kadar, et al, show us the tools we can use to tune Cloudera’s Operatioanl Database:

A query optimizer determined the most efficient way to run a query. Query optimization helps you to reduce the hardware resources required to run a query and also speeds up your query-response time. Cloudera’s Operational Database provides you with various tools such as plan analyzers to make optimal use of your computing resources. 

Cloudera’s OpDB provides various cost-based and rules-based optimizers. You can use different optimizers based on your use cases. OpDB is primarily used for Online Transactional Processing (OLTP) use cases with Apache Phoenix in the OpDB used as a SQL engine. But you can also use Hive and Impala for Online Analytical Processing (OLAP) use cases. 

Read on for recommendations on platform choice as well as indexing and tuning options.

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Changing Power BI Models with Visual Studio Code

Phil Seamark has a integration I hadn’t expected to see:

Visual Studio Code is a reasonably new development environment which is a lightweight and quick install and get up and running. There is nothing you can do in VS Code that you can’t also do in another tool using TOM. I just thought it would be fun to show how quick and easy it is to get up and running in very few steps.

The following exercise uses VS Code to connect and manage a Power BI Desktop model. You can also connect to models hosted in Azure Analysis Services as well as models hosted in Power BI Premium.

Read on to see how to get everything going.

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SQL Server Assessment Reports

Dave Bland shares the results of a lot of effort:

When you click the SQL Server 2012 or newer you will be taken to a report that will return a great deal of information that will be useful when doing an assessment.  This is very similar to the report you will be taken to if you click the 2008r2 or older button.  Since many of these data points are not options in an Azure SQL DB, that button will take you to the Report Library.

Below are the 21 data points that will be returned in just a few seconds.  A number of these will be helpful when doing an assessment for performance reasons.  The boxes will also change color to yellow or red if issues are found, just like the image above.

Click through for samples as well as the download link.

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The Importance of Power BI Deployment Pipelines

Marc Lelijveld explains the importance of Power BI Deployment Pipelines:

You might have seen the announcement, Power BI Deployment Pipelines have been released in May 2020. It is around for about two months now. On different social channels I have seen a lot of buzz around it already, both positive and negative honestly. Though, I think this is a great step forward!

Back in 2018, I posted a blog about multi-tier architecture and continuous delivery with Power BI. If you are not familiar with a DTAP approach and why this helps you to structure your development processes, I advise you to first read that blog. Personally, I am really excited about Deployment Pipelines! With this functionality, Microsoft starts offering an out-of-the-box functionality that helps you to easier move your Power BI content through you DTAP pipeline.

I think it’s a pretty big step in the right direction, though the “Why this isn’t so great” section is a bit lengthy.

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Parallel Processing in Analysis Services

Kasper de Jonge takes us through parallel processing of partitions and tables in Analysis Services:

One thing that has come up several times in the last few weeks is a misconception that you cannot process multiple partitions on the same table or tables in parallel as it would cause a lock. This could be true if you try to do the parallelism yourself. Like in SQL Server you need to think about transactions, the AS engine is a transactional system too.

So, the AS engine is definitely capable of loading data in parallel but only if you let him do the puzzling on concurrency. This means you must send processing commands to the AS engine in one transaction so the AS engine can manage the locks itself. There are other benefits of letting AS doing the work like recalculating the calculated items (tables, columns etc) once instead of multiple times which improves processing performance.

Read on for an example.

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Migrating From Cosmos DB to SQL Server

Eitan Blumin builds an app:

The general idea is this:

The app executes a Cosmos DB query and collects a number of records into its “buffer”.

Once that “buffer” reaches a certain number of records (configurable), it’s time to “flush” it into the SQL Server. That could be either a database table receiving a Bulk Copy stream, or a stored procedure receiving a table valued parameter (again, configurable).

After the buffer is flushed, we have the option to execute a “merge” procedure. This is a stored procedure that would implement an “upsert” logic from the “staging” table and into the actual destination table.

Read on for more explanation and check out Eitan’s GitHub repo.

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