Comments on: Python in SQL Server 2017: enhanced in-database machine learning https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/ Official News from Microsoft’s Information Platform Wed, 03 May 2017 12:55:19 +0000 hourly 1 By: John https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8573 Wed, 03 May 2017 12:55:19 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8573 Will SQL Server 2016 be upgraded to include support for Python as well?

]]> By: Mario S77 https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8570 Tue, 02 May 2017 09:51:09 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8570 In reply to Umachandar Jayachandran – MS.

yipeee… only good news today 🙂

]]> By: Umachandar Jayachandran - MS https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8567 Mon, 01 May 2017 17:09:50 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8567 In reply to Keith Medcalf.

Based on our testing, we found that many packages have incompatibility issues with latest Python 3.6 version. We will look at feedback & figure out what version to ship with SQL Server 2017 RTM. Currently, we are shipping Python version 3.5.2.

]]> By: Umachandar Jayachandran - MS https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8564 Mon, 01 May 2017 17:08:13 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8564 In reply to Alex.

This integration is about moving the R/Python compute to SQL Server machine to eliminate data movement across machines. If you move millions/billions of rows to the client for modeling or scoring then the network overhead will dominate end-to-end execution time. Moreover the R/Python integration in SQL Server works with parallel query processing in SQL Server, security & resource governance.

For example, you can execute a query that runs in parallel (DOP = 8) that trains a model in parallel (with RevoScaleR or revoscalepy or MicrosoftML). This mode of execution can also be leveraged for scoring in parallel coupled with streaming capabilities in SQL Server. These features allow you to run more concurrent scripts with resource policies enforced from within SQL Server. This is hard to achieve if you run R / Python scripts on a standalone server.

Feel free to reach out to me offline & I will be happy to walk you through the integration, how it differs from running R/Python script from a client, performance advantages.

]]> By: Umachandar Jayachandran - MS https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8561 Mon, 01 May 2017 16:52:17 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8561 In reply to Raj.

We do not run R / Python within the SQL Server process or memory space. The R / Python processes run outside of the SQL Server address space & share the machine resources. This is also done for security reasons.

Yes, by default many of the data structures in R / Python are memory resident objects so the same limitations apply. However, Microsoft ships many algorithms as part of the R Server package (RevoScaleR or revoscalepy) that has a SQL Server data source object which can work with data that doesn’t fit in memory & supports parallel execution. Using SQL data source object, you can run a parallel query in SQL Server that sends data to many R / Python processes in parallel to compute say linmod/logit/tree model. This can also be used for scoring scenarios with streaming capability.

Feel free to reach out to me offline. I will be happy to walk-through the samples & demo the performance aspects.

]]> By: Umachandar Jayachandran - MS https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8558 Mon, 01 May 2017 16:47:13 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8558 In reply to Mr_Tree.

Yes, we are working on enabling both R & Python in Azure SQL DB. I do not have a timeline to share at the moment. But feel free to reach out to me offline & we can discuss further about your scenarios/roadmap in general.

]]> By: Owned https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8555 Tue, 25 Apr 2017 07:30:07 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8555 In reply to Alex.

I suggest you watch the video and read the text before making a post that makes you look like an ignorant idiot

]]> By: Keith Medcalf https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8552 Sat, 22 Apr 2017 17:40:54 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8552 Why suck an old version of Python?

]]> By: Raj https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8549 Sat, 22 Apr 2017 01:57:14 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8549 Gr8. Does this have memory limitation of R? Does tge dataset need to completely fit in Server’s memory space?

]]> By: Alex https://cloudblogs.microsoft.com/sqlserver/2017/04/19/python-in-sql-server-2017-enhanced-in-database-machine-learning/#comment-8546 Thu, 20 Apr 2017 22:54:18 +0000 https://blogs.technet.microsoft.com/dataplatforminsider/?p=19925#comment-8546 In reply to Alex.

R and Python already support loading data into data frame from SQL Server. What is this useful for?

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