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Category: Storage

Disk Caching with SQL Server VM Disks in Azure

Published 2020-07-22 by Kevin Feasel

Niko Neugebauer performs some tests:

Microsoft has been extremely clear in the best practices recommendation for the SQL Server workloads on Azure VMs:
– use read caching for the data drives/storage pools
– use no caching for the log drives/storage pools
– use read caching for the temp db drives/storage pools

Sounds simple and direct, isn’t it ?
Let me borrow your attention for the next couple of minutes pointing to some situations where you might want to reconsider the best practices.

But do read on for some important notes.

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Backing Up Databases to Azure Blob Storage

Published 2020-06-24 by Kevin Feasel

David Fowler shows how you can back up databases to Azure Blob Storage:

SQL Server has given us the option to backup our databases directly to Azure BLOB storage for a while now but it’s not something that I’ve had all that much call to use until recently.

So this is just going to be a quick walk through on how you can backup your on premise SQL Servers to Azure BLOB storage. I’m going to assume that you’ve already got an Azure account, if you haven’t, you get set up a free trial which will see you good for this demo.

Performance typically won’t be as good as backing up locally to disk, so if you need the fastest backup performance and cloud storage, the best route would be to write backups to disk and have a separate process which migrates them to Blob Storage, S3, or wherever. But in many cases, doing this directly can work out just fine, especially if you are already using an Azure-based VM.

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Setting Drive Allocation Unit Size using Powershell

Published 2020-06-04 by Kevin Feasel

Eric Cobb has a tiny script for us:

There seems to be some ongoing debate around whether or not formatting your data and log drives with 64KB allocation unit size even matters anymore. I would encourage you to do your own research to determine if you want to do this or not. My personal take on it is: if it doesn’t hurt, and it may help, and it only takes 2 seconds to click the “go” button on my PowerShell script, then I would rather go ahead and do it and not need it than not do it and wish I had later down the road.

I don’t have a strong opinion in that debate, myself, so I’ll just say that if you want to see how to do this in a couple lines of Powershell code, check out Eric’s post.

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How Writing to Parquet Works

Published 2020-06-01 by Kevin Feasel

Dmitry Tolpeko walks us through the algorithm for writing to Parquet format:

After writing first 100 values for a column (for 100 rows), the Parquet writer checks if this 100-values column content exceeds the specified page size (default is 1 MB).

If the raw data size for the column does not exceed the page size threshold then the next page size check is constantly adjusted based on the actual column size, so it neither checked after every column value nor after every 100 values. Thus the page size is not the strict limit.

If the raw data size size exceeds the page size, the column content is compressed (if a compression is specified for the Parquet file), and flushed into the Page store for the column.

This is a nice explanation of the process.

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Blob Storage Enhancements

Published 2020-05-28 by Kevin Feasel

James Serra is keeping on top of things around Azure Blob Storage:

Account failover: Customer-initiated storage account failover is now generally available, allowing you to determine when to initiate a failover instead of waiting for Microsoft to do so.  When you perform a failover, the secondary replica of the storage account becomes the new primary. The DNS records for all storage service endpoints—blob, file, queue, and table—are updated to point to this new primary. Once the failover is complete, clients will automatically begin reading from and writing to data to the storage account in the new primary region, with no code changes. Customer initiated failover is available for GRS, RA-GRS, GZRS and RA-GZRS accounts.  To learn more, see Disaster recovery and account failover

Read on for several more improvements.

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Query Acceleration for Blob Storage and Data Lake Gen2

Published 2020-05-05 by Kevin Feasel

James Serra takes us through Query Acceleration for Azure Blob Storage and Azure Data Lake Storage Gen2:

Just announced is Query Acceleration for Azure Data Lake Storage Gen2 (ADLS) as well as Blob Storage. This is a new capability for ADLS that enables applications and analytics frameworks to dramatically optimize data processing by retrieving only the data that they require to perform a given operation from storage. This reduces the time and processing power that is required to query stored data.

For example, if an application will execute a SELECT statement that filters columns and rows from a csv file, instead of all pulling the entire csv file over the network into the application and then filtering the data, it will instead do the filtering at the time the data is read from the disk, so that only the filtered data is transferred over the network to the application. So if you have a csv file with 50 columns and 1 million rows, but the filters limit the data to 5 columns and 1000 rows, then only the 5 columns and 1000 rows will be retrieved from the disk and sent over the network to the application.

Click through to learn more, including current libraries which support this and information on the additional cost. I’d really like to see PolyBase support this, as it would alleviate one of the problems with using Blob Storage + PolyBase: the need to pull all of that data down to your SQL Server instance before doing any filtering.

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Querying Database and Log File Sizes with T-SQL

Published 2020-04-17 by Kevin Feasel

Allen White takes us through an easy technique to check database and log file sizes:

As a consultant, I have to be able to quickly spot problems, and one of the problems I frequently find is transaction log files that are incorrectly sized.

There are two catalog views in the master database which make this easy to do – sys.master_files and sys.databases. The sys.master_files view contains the database and individual file names, and the data_space_id column always has a value of 0 for the log file. The size column returns the value in 8KB pages, so we have to multiply the column by 8, then divide by 1024 to get the size in megabytes (MB).

Click through for the demo.

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Bulk Migration of Data and Log Files in SQL Server

Published 2020-04-16 by Kevin Feasel

David Fowler shows how you can change file paths for all of your databases in one fell swoop:

You’ve got a SQL Server with a few hundred databases on it (to be honest it doesn’t even need to be quite that many) and you need to move all the data and log files to a new location. Perhaps you’re going to be migrating onto a new, shiny SAN or maybe your disks are just about full and you need to shift a bunch of the files off somewhere else.

The first thing that you’re going to need to do is change the paths of the files in SQL. That’s easy enough to do with an ALTER DATABASE statement.

ALTER DATABASE SQLUndercover MODIFY FILE (NAME SQLUndercover_Log, FILENAME = 'F:\SQLLogs\SQLUndercover_Log.ldf'

But that’s going to get very tedious very quickly if you’ve got to do that for a whole lotta databases. So to help out, I thought I’d share a little script that I’ve been using for a while (or a variation on it at least) to make the process far easier and generate all the ALTER statements for you.

Click through for the script as well as a bit of advice around the actual moving of the files.

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Loading Data into Delta Lake

Published 2020-02-27 by Kevin Feasel

Prakash Chockalingam takes us through auto-loading Delta Lake from various sources:

Auto Loader is an optimized file source that overcomes all the above limitations and provides a seamless way for data teams to load the raw data at low cost and latency with minimal DevOps effort. You just need to provide a source directory path and start a streaming job. The new structured streaming source, called “cloudFiles”, will automatically set up file notification services that subscribe file events from the input directory and process new files as they arrive, with the option of also processing existing files in that directory.

This does look interesting.

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