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Day: April 26, 2021

HDFS Data Encryption at Rest

Published 2021-04-26 by Kevin Feasel

Arun Kumar Natva takes us through the process of encrypting data at rest in Cloudera Data Platform:

HDFS Encryption delivers transparent end-to-end encryption of data at rest and is an integral part of HDFS. End to end encryption means that the data is only encrypted and decrypted by the client. In other words, data remains encrypted until it reaches the HDFS client.

Each HDFS file is encrypted using an encryption key. To prevent the management of these keys (which can run in the millions) from becoming a performance bottleneck, the encryption key itself is stored in the file metadata. To add another layer of security, the file encryption key is stored in encrypted form, using another “encryption zone key”.

Read on to learn more and to see how it all fits together.

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Grafana Changing License

Published 2021-04-26 by Kevin Feasel

Alex Woodie has some bad news for us:

Grafana is switching licensing of its core products from Apache License 2.0 to the more restrictive Affero General Public License (GPL) v3. The company made the change in an attempt to balance the value of open source with Grafana’s monetization strategy, CEO Raj Dutt announced yesterday.

Grafana has been considering a license change for some time, Dutt wrote in a blog post on April 20. This week, the company finally felt the time was right to move.

“Oof” was my first response. I know that a pretty large percentage of companies won’t touch AGPL. I don’t know if we’ll see these companies adopt the commercial version of Grafana, see the companies switch over to something else, or see developers fork Grafana and come up with some other product. AGPL is not quite as scary for companies when a product is at the end of the chain, as visualization and dashboarding products tend to be, but for many companies, that doesn’t matter.

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Read-Ahead Reads

Published 2021-04-26 by Kevin Feasel

Chad Callihan provides some helpful tips around read-ahead:

What are read-ahead reads and how do they impact SQL Server performance? Read-ahead reads allow SQL Server to think ahead to pull pages into the buffer cache before they are actually requested for a query. Up to 64 contiguous pages from a file can be read and the ability to read-ahead can be used for both data pages and index pages. Once data is in the buffer cache, it will not need to be pulled in for future queries unless it has been pushed out by other SQL Server tasks.

Click through to see what they are and how you could disable them if you really need to.

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Service Endpoints in Azure SQL Database

Published 2021-04-26 by Kevin Feasel

Mike Wood takes us through service endpoints in Azure:

In previous installments of my “Securing Azure SQL Database” series, I covered Azure SQL Database firewall rules and private endpoints—the first of which is a way to help reduce the public exposure of your database endpoint and the second being a means to remove all public access if necessary. Each option has unique benefits, and some scenarios might call for a mix of the two options.

In this blog post, I’ll cover a third option for securing Azure SQL Database—service endpoints. This option is similar to private endpoints in that you restrict public access and only grant access to the database through your Virtual Network (VNet).

Read on to learn more.

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T-SQL Tuesday 137 Round-Up

Published 2021-04-26 by Kevin Feasel

Steve Jones wraps up the latest T-SQL Tuesday:

I hosted the blog party this month, with the invite to write about notebooks. These are a neat technology, and I’ve written about them at SQLServerCentral.

This post is a wrap-up of the various responses to my invitation. First, quite a few people give credit to either Aaron Nelson or Rob Sewell for their writings and work with notebooks, so check out their blogs.

Click through for the list of respondents.

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Using Calendar Tables

Published 2021-04-26 by Kevin Feasel

Aaron Bertrand has a post up on using a calendar table:

A while back, I wrote an article called Creating a date dimension or calendar table in SQL Server. I have used this pattern repeatedly and, based on the questions I get from the community, many of you are using it, too. Some of the questions I get are along the lines of “how do I actually use this table in my queries?” and “what are the performance characteristics compared to other approaches?” So, I thought I would put together a collection of use cases and analysis, starting with business day problems.

I’m a big fan of calendar tables as well. They’re quite useful for a variety of business problems and make date math problems really easy, especially when dealing with non-standard calendars (e.g., work weeks, fiscal years, figuring out what day Easter is).

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