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Known issues in SQL Server Machine Learning Services.; 30 minutes to read; In this article. APPLIES TO: SQL Server Azure SQL Database Azure Synapse Analytics (SQL DW) Parallel Data Warehouse This article describes known problems or limitations with machine learning components that are provided as an option in SQL Server Machine Learning Services and SQL Server 2016 R Services. The problem: To completely uninstall Antares Auto-Tune Evo VST is not always that simple, the default uninstaller that came with the program always fails to remove all the components of Antares Auto-Tune Evo VST. For example, the registry entries that created during the program installation are always left inside the computer even you perform. Per rubo77's answer, I'm running powertop -auto-tune in /etc/rc.local and then undoing an unwanted default change. However, since the device I want to disable auto power control for is an external USB device that could potentially appear with a different /sys tree device number, I did a bit more scripting to dynamically identify it. Many small bug fixes and usability tweaks. 9 Dec 2014 (MSI Installer) (Source code) Added support for LSA25A-T4 and parallel drive LAR/BAR products. Fixed Zaber Console throwing RequestTimeoutException when attempting to connect to devices with firmware version 2.93. By default FreeRIP creates a folder named after the artist, then the files are named 'Track Number-Track Title'. There are many combinations you can use in your customized templates. For example, for the Fall Out Boy album I am using, I could enter.
This article describes known problems or limitations with machine learning components that are provided as an option in SQL Server Machine Learning Services and SQL Server 2016 R Services.
Setup and configuration issues
For a description of processes and common questions that are related to initial setup and configuration, see Upgrade and installation FAQ. It contains information about upgrades, side-by-side installation, and installation of new R or Python components.
1. Inconsistent results in MKL computations due to missing environment variable
Applies to: R_SERVER binaries 9.0, 9.1, 9.2 or 9.3.
R_SERVER uses the Intel Math Kernel Library (MKL). For computations involving MKL, inconsistent results can occur if your system is missing an environment variable.
Set the environment variable
'MKL_CBWR'=AUTO
to ensure conditional numerical reproducibility in R_SERVER. For more information, see Introduction to Conditional Numerical Reproducibility (CNR).Workaround
- In Control Panel, click System and Security > System > Advanced System Settings > Environment Variables.
- Create a new User or System variable.
- Set variable name to 'MKL_CBWR'.
- Set the 'Variable value' to 'AUTO'.
- Restart R_SERVER. On SQL Server, you can restart SQL Server Launchpad Service.
Note
If you are running the SQL Server 2019 on Linux, edit or create .bash_profile in your user home directory, adding the line
export MKL_CBWR='AUTO'
. Execute this file by typing source .bash_profile
at a bash command prompt. Restart R_SERVER by typing Sys.getenv()
at the R command prompt.2. R Script runtime error (SQL Server 2017 CU5-CU7 Regression)
For SQL Server 2017, in cumulative updates 5 through 7, there is a regression in the rlauncher.config file where the temp directory file path includes a space. This regression is corrected in CU8.
The error you will see when running R script includes the following messages:
Unable to communicate with the runtime for 'R' script. Please check the requirements of 'R' runtime.
STDERR message(s) from external script:
Fatal error: cannot create 'R_TempDir'
Workaround
Apply CU8 when it becomes available. Alternatively, you can recreate rlauncher.config by running registerrext with uninstall/install on an elevated command prompt.
The following example shows the commands with the default instance 'MSSQL14.MSSQLSERVER' installed into 'C:Program FilesMicrosoft SQL Server':
3. Unable to install SQL Server machine learning features on a domain controller
If you try to install SQL Server 2016 R Services or SQL Server Machine Learning Services on a domain controller, setup fails, with these errors:
An error occurred during the setup process of the feature
Cannot find group with identity
Component error code: 0x80131509
The failure occurs because, on a domain controller, the service cannot create the 20 local accounts required to run machine learning. In general, we do not recommend installing SQL Server on a domain controller. For more information, see Support bulletin 2032911.
4. Install the latest service release to ensure compatibility with Microsoft R Client
If you install the latest version of Microsoft R Client and use it to run R on SQL Server in a remote compute context, you might get an error like the following:
You are running version 9.x.x of Microsoft R Client on your computer, which is incompatible with Microsoft R Server version 8.x.x. Download and install a compatible version.
SQL Server 2016 requires that the R libraries on the client exactly match the R libraries on the server. The restriction has been removed for releases later than R Server 9.0.1. However, if you encounter this error, verify the version of the R libraries that's used by your client and the server and, if necessary, update the client to match the server version.
The version of R that is installed with SQL Server R Services is updated whenever a SQL Server service release is installed. To ensure that you always have the most up-to-date versions of R components, be sure to install all service packs.
To ensure compatibility with Microsoft R Client 9.0.0, install the updates that are described in this support article.
To avoid problems with R packages, you can also upgrade the version of the R libraries that are installed on the server, by changing your servicing agreement to use the Modern Lifecycle Support policy, as described in the next section. When you do so, the version of R that's installed with SQL Server is updated on the same schedule used for updates of machine Learning Server (formerly Microsoft R Server).
Applies to: SQL Server 2016 R Services, with R Server version 9.0.0 or earlier
5. R components missing from CU3 setup
A limited number of Azure virtual machines were provisioned without the R installation files that should be included with SQL Server. The issue applies to virtual machines provisioned in the period from 2018-01-05 to 2018-01-23. This issue might also affect on-premises installations, if you applied the CU3 update for SQL Server 2017 during the period from 2018-01-05 to 2018-01-23.
A service release has been provided that includes the correct version of the R installation files.
- Cumulative Update Package 3 for SQL Server 2017 KB4052987.
To install the components and repair SQL Server 2017 CU3, you must uninstall CU3, and reinstall the updated version:
- Download the updated CU3 installation file, which includes the R installers.
- Uninstall CU3. In Control Panel, search for Uninstall an update, and then select 'Hotfix 3015 for SQL Server 2017 (KB4052987) (64-bit)'. Proceed with uninstall steps.
- Reinstall the CU3 update, by double-clicking on the update for KB4052987 that you just downloaded:
SQLServer2017-KB4052987-x64.exe
. Follow the installation instructions.
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6. Unable to install Python components in offline installations of SQL Server 2017 CTP 2.0 or later
If you install a pre-release version of SQL Server 2017 on a computer without internet access, the installer might fail to display the page that prompts for the location of the downloaded Python components. In such an instance, you can install the Machine Learning Services feature, but not the Python components.
This issue is fixed in the release version. Also, this limitation does not apply to R components.
Applies to: SQL Server 2017 with Python
Warning of incompatible version when you connect to an older version of SQL Server R Services from a client by using SQL Server 2017 (14.x)
When you run R code in a SQL Server 2016 compute context, you might see the following error:
You are running version 9.0.0 of Microsoft R Client on your computer, which is incompatible with the Microsoft R Server version 8.0.3. Download and install a compatible version.
This message is displayed if either of the following two statements is true,
- You installed R Server (Standalone) on a client computer by using the setup wizard for SQL Server 2017 (14.x).
- You installed Microsoft R Server by using the separate Windows installer.
To ensure that the server and client use the same version you might need to use binding, supported for Microsoft R Server 9.0 and later releases, to upgrade the R components in SQL Server 2016 instances. To determine if support for upgrades is available for your version of R Services, see Upgrade an instance of R Services using SqlBindR.exe.
Applies to: SQL Server 2016 R Services, with R Server version 9.0.0 or earlier
7. Setup for SQL Server 2016 service releases might fail to install newer versions of R components
When you install a cumulative update or install a service pack for SQL Server 2016 on a computer that is not connected to the internet, the setup wizard might fail to display the prompt that lets you update the R components by using downloaded CAB files. This failure typically occurs when multiple components were installed together with the database engine.
As a workaround, you can install the service release by using the command line and specifying the
MRCACHEDIRECTORY
argument as shown in this example, which installs CU1 updates:C:<path to installation media>SQLServer2016-KB3164674-x64.exe /Action=Patch /IACCEPTROPENLICENSETERMS /MRCACHEDIRECTORY=<path to CU1 CAB files>
To get the latest installers, see Install machine learning components without internet access.
Applies to: SQL Server 2016 R Services, with R Server version 9.0.0 or earlier
8. Launchpad services fails to start if the version is different from the R version
If you install SQL Server R Services separately from the database engine, and the build versions are different, you might see the following error in the System Event log:
The SQL Server Launchpad service failed to start due to the following error: The service did not respond to the start or control request in a timely fashion.
For example, this error might occur if you install the database engine by using the release version, apply a patch to upgrade the database engine, and then add the R Services feature by using the release version.
To avoid this problem, use a utility such as File Manager to compare the versions of Launchpad.exe with version of SQL binaries, such as sqldk.dll. All components should have the same version number. If you upgrade one component, be sure to apply the same upgrade to all other installed components.
Look for Launchpad in the
Binn
folder for the instance. For example, in a default installation of SQL Server 2016, the path might be C:Program FilesMicrosoft SQL ServerMSSQL.13.InstanceNameMSSQLBinn
.9. Remote compute contexts are blocked by a firewall in SQL Server instances that are running on Azure virtual machines
If you have installed SQL Server 2019 (15.x) on an Azure virtual machine, you might not be able to use compute contexts that require the use of the virtual machine's workspace. The reason is that, by default, the firewall on Azure virtual machines includes a rule that blocks network access for local R user accounts.
As a workaround, on the Azure VM, open Windows Firewall with Advanced Security, select Outbound Rules, and disable the following rule: Block network access for R local user accounts in SQL Server instance MSSQLSERVER. You can also leave the rule enabled, but change the security property to Allow if secure.
10. Implied authentication in SQLEXPRESS
When you run R jobs from a remote: Access is denied
The reason is that an R function attempts to read the path, and fails if the built-in users group SQLRUserGroup, does not have read access. The warning that is raised does not block execution of the current R script, but the warning might recur repeatedly whenever the user runs any other R script.
If you have installed SQL Server to the default location, this error does not occur, because all Windows users have read permissions on the
Program Files
folder.This issue ia addressed in an upcoming service release. As a workaround, provide the group, SQLRUserGroup, with read access for all parent folders of
ExternalLibraries
.2. Serialization error between old and new versions of RevoScaleR
When you pass a model using a serialized format to a remote SQL Server instance, you might get the error:
Error in memDecompress(data, type = decompress) internal error -3 in memDecompress(2).
This error is raised if you saved the model using a recent version of the serialization function, rxSerializeModel, but the SQL Server instance where you deserialize the model has an older version of the RevoScaleR APIs, from SQL Server 2017 CU2 or earlier.
As a workaround, you can upgrade the SQL Server 2017 instance to CU3 or later.
The error does not appear if the API version is the same, or if you are moving a model saved with an older serialization function to a server that uses a newer version of the serialization API.
In other words, use the same version of RevoScaleR for both serialization and deserialization operations.
3. Real-time scoring does not correctly handle the learningRate parameter in tree and forest models
If you create a model using a decision tree or decision forest method and specify the learning rate, you might see inconsistent results when using
sp_rxpredict
or the SQL PREDICT
function, as compared to using rxPredict
.The cause is an error in the API that processes serialized models, and is limited to the
learningRate
parameter: for example, in rxBTrees, orThis issue is addressed in an upcoming service release.
4. Limitations on processor affinity for R jobs
In the initial release build of SQL Server 2016, you could set processor affinity only for CPUs in the first k-group. For example, if the server is a 2-socket machine with two k-groups, only processors from the first k-group are used for the R processes. The same limitation applies when you configure resource governance for R script jobs.
This issue is fixed in SQL Server 2016 Service Pack 1. We recommend that you upgrade to the latest service release.
Applies to: SQL Server 2016 R Services RTM version
5. Changes to column types cannot be performed when reading data in a SQL Server compute context
If your compute context is set to the SQL Server instance, you cannot use the colClasses argument (or other similar arguments) to change the data type of columns in your R code.
For example, the following statement would result in an error if the column CRSDepTimeStr is not already an integer:
As a workaround, you can rewrite the SQL query to use CAST or CONVERT and present the data to R by using the correct data type. In general, performance is better when you work with data by using SQL rather than by changing data in the R code.
Applies to: SQL Server 2016 R Services
6. Limits on size of serialized models
When you save a model to a SQL Server table, you must serialize the model and save it in a binary format. Theoretically the maximum size of a model that can be stored with this method is 2 GB, which is the maximum size of varbinary columns in SQL Server.
If you need to use larger models, the following workarounds are available:
- Take steps to reduce the size of your model. Some open source R packages include a great deal of information in the model object, and much of this information can be removed for deployment.
- Use feature selection to remove unnecessary columns.
- If you are using an open source algorithm, consider a similar implementation using the corresponding algorithm in MicrosoftML or RevoScaleR. These packages have been optimized for deployment scenarios.
- After the model has been rationalized and the size reduced using the preceding steps, see if the memCompress function in base R can be used to reduce the size of the model before passing it to SQL Server. This option is best when the model is close to the 2 GB limit.
- For larger models, you can use the SQL Server FileTable feature to store the models, rather than using a varbinary column.To use FileTables, you must add a firewall exception, because data stored in FileTables is managed by the Filestream filesystem driver in SQL Server, and default firewall rules block network file access. For more information, see Enable Prerequisites for FileTable.After you have enabled FileTable, to write the model, you get a path from SQL using the FileTable API, and then write the model to that location from your code. When you need to read the model, you get the path from SQL and then call the model using the path from your script. For more information, see Access FileTables with File Input-Output APIs.
7. Avoid clearing workspaces when you execute R code in a SQL Server compute context
If you use an R command to clear your workspace of objects while running R code in a SQL Server compute context, or if you clear the workspace as part of an R script called by using sp_execute_external_script, you might get this error: workspace object revoScriptConnection not found
revoScriptConnection
is an object in the R workspace that contains information about an R session that is called from SQL Server. However, if your R code includes a command to clear the workspace (such as rm(list=ls()))
, all information about the session and other objects in the R workspace is cleared as well.As a workaround, avoid indiscriminate clearing of variables and other objects while you're running R in SQL Server. Although clearing the workspace is common when working in the R console, it can have unintended consequences.
- To delete specific variables, use the R
remove
function: for example,remove('name1', 'name2', ...)
- If there are multiple variables to delete, save the names of temporary variables to a list and perform periodic garbage collection.
8. Restrictions on data that can be provided as input to an R script
You cannot use in an R script the following types of query results:
- Data from a Transact-SQL query that references AlwaysEncrypted columns.
- Data from a Transact-SQL query that references masked columns.If you need to use masked data in an R script, a possible workaround is to make a copy of the data in a temporary table and use that data instead.
9. Use of strings as factors can lead to performance degradation
Using string type variables as factors can greatly increase the amount of memory used for R operations. This is a known issue with R in general, and there are many articles on the subject. For example, see Factors are not first-class citizens in R, by John Mount, in R-bloggers) or stringsAsFactors: An unauthorized biography, by Roger Peng.
Although the issue is not specific to SQL Server, it can greatly affect performance of R code run in SQl Server. Strings are typically stored as varchar or nvarchar, and if a column of string data has many unique values, the process of internally converting these to integers and back to strings by R can even lead to memory allocation errors.
If you do not absolutely require a string data type for other operations, mapping the string values to a numeric (integer) data type as part of data preparation would be beneficial from a performance and scale perspective.
For a discussion of this issue, and other tips, see Performance for R Services - data optimization.
10. Arguments varsToKeep and varsToDrop are not supported for SQL Server data sources
When you use the rxDataStep function to write results to a table, using the varsToKeep and varsToDrop is a handy way of specifying the columns to include or exclude as part of the operation. However, these arguments are not supported for SQL Server data sources.
11. Limited support for SQL data types in sp_execute_external_script
Not all data types that are supported in SQL can be used in R. As a workaround, consider casting the unsupported data type to a supported data type before passing the data to sp_execute_external_script.
For more information, see R libraries and data types.
12. Possible string corruption using unicode strings in varchar columns
Passing unicode data in varchar columns from SQL Server to R/Python can result in string corruption. This is due to the encoding for these unicode string in SQL Server collations may not match with the default UTF-8 encoding used in R/Python.
To send any non-ASCII string data from SQL Server to R/Python, use UTF-8 encoding (available in SQL Server 2019 (15.x)) or use nvarchar type for the same.
13. Only one value of type raw
can be returned from sp_execute_external_script
When a binary data type (the R raw data type) is returned from R, the value must be sent in the output data frame.
With data types other than raw, you can return parameter values along with the results of the stored procedure by adding the OUTPUT keyword. For more information, see Parameters.
If you want to use multiple output sets that include values of type raw, one possible workaround is to do multiple calls of the stored procedure, or to send the result sets back to SQL Server by using ODBC.
14. Loss of precision
Because Transact-SQL and R support various data types, numeric data types can suffer loss of precision during conversion.
For more information about implicit error.
For example:
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Workaround
Run the following command:
Applies to: SQL Server 2019 on Linux
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Revolution R Enterprise and Microsoft R Open
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This section lists issues specific to R connectivity, development, and performance tools that are provided by Revolution Analytics. These tools were provided in earlier pre-release versions of SQL Server 2019 (15.x).
In general, we recommend that you uninstall these previous versions and install the latest version of SQL Server or Microsoft R Server.
1. Revolution R Enterprise is not supported
Installing Revolution R Enterprise side by side with any version of R Services (In-Database) is not supported.
If you have an existing license for Revolution R Enterprise, you must put it on a separate computer from both the SQL Server instance and any workstation that you want to use to connect to the SQL Server instance.
Some pre-release versions of R Services (In-Database) included an R development environment for Windows that was created by Revolution Analytics. This tool is no longer provided, and is not supported.
For compatibility with R Services (In-Database), we recommend that you install Microsoft R Client instead. R Tools for Visual Studio and Visual Studio Code also supports Microsoft R solutions.
2. Compatibility issues with SQLite ODBC driver and RevoScaleR
Revision 0.92 of the SQLite ODBC driver is incompatible with RevoScaleR. Revisions 0.88-0.91 and 0.93 and later are known to be compatible.