Microsoft Machine Learning ServerPart I: Architecture View

Dmitry Petukhov,Machine Learning Preacher, Microsoft AI MVP && Coffee Addicted

Machine Intelligence Researcher @ OpenWay

#DataGeeks

> 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

References

Source: https://biz-excellence.com/technologies/microsoft-r-server/

Microsoft ML Server: Key Components

Community components

Open source components

Proprietary components

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

Open Source

# For Windows# Download installer from https://mran.microsoft.com/download

# For Linuxwget 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.gzcd microsoft-r-open/sudo ./install.sh

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

# For Windows

# Download installer from http://aka.ms/rclient/

# For Linux (see full listing in install_scripts.sh [4])

# For Windows

# Read docs.microsoft.com

# For Linux (see full listing in install_scripts.sh [4])

Azure Resource Manager templates

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.

© 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.

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