Microsoft Machine Learning Server (former Microsoft R Server): Architecture View. Slides from Data Geeks Meetup (Moscow)

1. Microsoft Machine Learning Server
Part I: Architecture View
Dmitry Petukhov,
Machine Learning Preacher, Microsoft AI MVP && Coffee Addicted
Machine Intelligence Researcher @ OpenWay
#DataGeeks

2. > quantile(c(0:10, 10:0), probs = seq(0, 1, .25)) # vectorization (SIMD)
0% 25% 50% 75% 100% 0.00
2.25 5.00 7.75 10.00
> data.table::fread("data/100MB_file.csv") # C implementation
Read 2567487 rows and 4 (of 4) columns from 0.109 GB file in 00:00:08
V1 V2 V3 V4
1: EUR/USD 20140101 21:55:34.378 1.37622 1.37693
2: EUR/USD 20140101 21:55:40.410 1.37624 1.37698
3: EUR/USD 20140101 21:55:47.210 1.37619 1.37696
4: EUR/USD 20140101 21:55:57.963 1.37616 1.37696
5: EUR/USD 20140101 21:56:03.117 1.37616 1.37694

4. References
Source: https://biz-excellence.com/technologies/microsoft-r-server/
Microsoft ML Server: Key Components
Community components
Open source components
Proprietary components

6. Source: https://mran.microsoft.com/documents/rro/multithread/

7. Open Source
# For Windows
# Download installer from https://mran.microsoft.com/download
# For Linux
wget https://mran.blob.core.windows.net/install/mro/3.4.2/microsoft-r-open-3.4.2.tar.gz
tar -xf microsoft-r-open-3.4.2.tar.gz
cd microsoft-r-open/
sudo ./install.sh

12. R Open Microsoft ML Server
DeployRDS4VS
ConnectR
• High-speed & direct
connectors
Available for:
• High-performance XDF
• SAS, SPSS, delimited & fixed
format text data files
• Hadoop HDFS (text & XDF)
• Teradata Database & Aster
• EDWs and ADWs
• ODBC
ScaleR
• Ready-to-Use high-performance
big data big analytics
• Fully-parallelized analytics
• Data prep & data distillation
• Descriptive statistics & statistical tests
• Range of predictive functions
• User tools for distributing customized R algorithms
across nodes
• Wide data sets supported – thousands of variables
DistributedR
• Distributed computing framework
• Delivers cross-platform portability
R+CRAN
• Open source R interpreter
• Freely-available huge range of R
algorithms
• Embeddable in R scripts
• 100% compatible with existing R scripts,
functions and packages
Microsoft R Open
• Based on open source R
• High-performance math library
to speed up linear algebra
functions
• Checkpoint package to easily
share R code and replicate
results using specific R package
versions
DeployR
• RESTful APIs for easy
integration from Java,
JavaScript, .NET
• Enterprise authentication &
security
• Horizontal scaling
Data Science for VSMicrosoft ML Server: Components
Source: https://channel9.msdn.com/Events/Build/2016/B805
Community components
Open source / free components
Proprietary components

13. # For Windows
# Download installer from http://aka.ms/rclient/
# For Linux (see full listing in install_scripts.sh [4])

15. # For Windows
# Read docs.microsoft.com
# For Linux (see full listing in install_scripts.sh [4])
Azure Resource Manager templates

17. 1. Machine Learning Server Documentation.
2. Analyzing Big Data with Microsoft R Server. Online Course, EdX.
3. Big Data Analysis with Revolution R Enterprise. Online Course, DataCamp.
Advanced references
4. Slides and demo source code, GitHub.

18. © 2017, Dmitry Petukhov. CC BY-SA 4.0 license. Microsoft and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.
I AI

19. Q&A
Now or later (see contacts below)
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