ITCamp 2018 - Damian Widera U-SQL in great depth

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I would like to invite to the session about Microsoft Azure Data Lake and the USQL. I would like to show how quickly you can do data analysis using traditional C# and a new language that is a bit similar to the TSQL. I will also show more complicated things -how to run Python and R scripts to perform even more robust analysis

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U-SQL in great depth
Damian Widera + Dominika Widera
Microsoft Data Platform MVP, Microsoft Certified Trainer MCT
EUVIC
@damianwidera
http://sqlplayer.net

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Damian Widera
Project Manager & Technical Lead | EUVIC (www.euvic.pl)
MVP | MCT | MCSE | MCITP
damian.widera@euvic.pl
+48 665-229-227
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http://sqlplayer.net
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And now…

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Data Warehouse vs Data Lake

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Azure Data Lake
• Comprehensive, big-data storage + analytics platform
• Purpose-built from real-world experiences
– Office 365, Skype, Bing, etc.
• Leverage existing skills and technologies
• Benefits of an Azure-hosted service
– Elastic, dynamically provisioned compute resources for varying query needs
– Infinite storage capacity
– Focus on extracting meaning from data, not on infrastructure

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Azure Ecosystem Integration

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But what is Data Lake in fact
• A repository for analyzing large quantities of disparate sources of data
in its native format
• One architectural platform to house all types of data:
– Machine-generated data (ex: IoT, logs)
– Human-generated data (ex: tweets, e-mail)
– Traditional operational data (ex: sales, inventory)

@ITCAMPRO #ITCAMP18Community Conference for IT Professionals
Data Lake use case
• Staging for the Data Warehouse
• So called Active Archiving
–You can run queries against historical data, too
–It will be federated query to access historical and current
data
–The data is stored for the indefinite time

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Data Lake use case
• An external system loads data to the Data Lake
• The data is analyzed case by case. Processing is highly
parallel
–Schema on read – we read all the data to determine the
value of the data
• Deliver the data once the requirements are fully
known
–Data warehouse – schema on write
–Data Virtualization

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U-SQL
• Based on SQL and C#
– C# expressions and types
– Tables, views, window functions, etc.
– User-defined functions/operators/aggregators in C#
• Typical job
1. Read data from file/table/federated source
2. Transform rowset in a pipeline
3. Output rowset to table (INSERT) or file

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U-SQL - extensibility
• C# expressions
• UDF’s – functions
• UDAGG’s – aggregates
• UDO’s - operators

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UDO’s - operators
• Extractors  EXTRACT
• Outputters  OUTPUT
• Processors PROCESS
• Appliers  PROCESS
• Combiners  COMBINE
• Reducers REDUCE

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UDO’s – extractor & outputter
• User-defined extractors
–Extract row by row
–Used to implement data extraction from custom structured
files
• User-defined outputters
–Output row by row
–Used to output custom data types or custom file formats

@ITCAMPRO #ITCAMP18Community Conference for IT Professionals
UDO’s – processor & applier
• User-defined processors
–Take one row and produce one row
–Used to reduce the number of columns or produce new
columns with values that are derived from an existing
column set
• User-defined appliers
–Take one row and produce 0 to n rows
–Used with OUTER/CROSS APPLY

@ITCAMPRO #ITCAMP18Community Conference for IT Professionals
UDO’s – combiner & reducer
• User-defined combiners
–Combines rowsets--user-defined JOINs
• User-defined reducers
–Take n rows and produce one row
–Used to reduce the number of rows

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What else can you do?
• JSON
• R
• Python
• Cognitive Services

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USQL & Cognitive
• Imaging: Detect faces
• Imaging: Detect emotion
• Imaging: Detect objects (tagging)
• Imaging: OCR (optical character recognition)
• Text: Key Phrase Extraction
• Text: Sentiment Analysis
•

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No more slides. Never

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Thank you!

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Building and running a service for a truly global audience has always been the ultimate challenge for any business and for any application developer. In this session, we will discuss global perspectives on running your application tier in a scalable way – WebApps/APIs, Traffic Manager and Serverless. We will discuss the new Cosmos DB service offering in Azure and it’s built in global sync with little more than a press of a button on your end – data was always the final frontier of globalization of your app. We will look at what it takes to monitor this kind of an environment. Naturally this is a very big set of topics which means this session is aimed to give an overview, spark a discussion and provide some directional and inspirational input.

ITCamp 2018 - Magnus Mårtensson - Azure Resource Manager For The Win

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With the new model, Azure Resource Manger Microsoft are gaining the repeatability they always wanted to have for deployment to the Cloud and removing the dreary, repetitive, error prone manual deployment tasks which has always held us back! With ARM, you can create a Template for your environment and use that for deploying identical environments every time without fail! There is some news in the world of “infrastructure as code” that we need to consider while setting up our Cloud environments. The Win we get from being able to deploy our development environment or our temporary load test environment automatically and identically to our production environment cannot be understated. This is ARM from a project efficiency, development and DevOps perspective. This is what you need to know to make you much more efficient every day of development.

ITCamp 2018 - Ionut Balan - A beginner’s guide to Windows Mixed Reality

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With Fall Creators update for Windows 10, Microsoft provided the foundation for everyone to get accustomed with the Mixed Reality concept and try to create and consume VR at home. Along with the recent lunch of several headset by Microsoft’s OEM partners, Mixed Reality is closer than ever before. Through this presentation I will walk through the basic concepts, hardware, tools and API’s you’ll need to start building your Windows Mixed Reality experience. At the end of the presentation, you will be ready to create your first Mixer Reality app for Microsoft’s HoloLens and other Windows Mixed Reality devices, in a matter of minutes. With the recent release of the Microsoft Mixed Reality headsets, controllers and Fall Creators update for Windows 10, it has never been a better time to immerse yourself in to the Mixed Reality space.

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ITCamp 2018 - Damian Widera U-SQL in great depth

1. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals U-SQL in great depth Damian Widera + Dominika Widera Microsoft Data Platform MVP, Microsoft Certified Trainer MCT EUVIC @damianwidera http://sqlplayer.net

2. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Many thanks to our sponsors & partners! GOLD SILVER PARTNERS PLATINUM POWERED BY

3. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Damian Widera Project Manager & Technical Lead | EUVIC (www.euvic.pl) MVP | MCT | MCSE | MCITP damian.widera@euvic.pl +48 665-229-227 @damian.widera facebook.com/damian.widera.10 http://sqlplayer.net Channel9

4. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals EUVIC PALO ALTO NOWY JORK WARSZAWA KATOWICE GLIWICE BIELSKO BIAŁA WROCŁAW CZĘSTOCHOWA GDYNIA KRAKÓW BYDGOSZCZ WIEDEŃ BIAŁYSTOK

5. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals And now…

6. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Data Warehouse vs Data Lake

7. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Azure Data Lake • Comprehensive, big-data storage + analytics platform • Purpose-built from real-world experiences – Office 365, Skype, Bing, etc. • Leverage existing skills and technologies • Benefits of an Azure-hosted service – Elastic, dynamically provisioned compute resources for varying query needs – Infinite storage capacity – Focus on extracting meaning from data, not on infrastructure

8. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Azure Ecosystem Integration

9. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals But what is Data Lake in fact • A repository for analyzing large quantities of disparate sources of data in its native format • One architectural platform to house all types of data: – Machine-generated data (ex: IoT, logs) – Human-generated data (ex: tweets, e-mail) – Traditional operational data (ex: sales, inventory)

10. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Data Warehouse vs Data Lake

11. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Data Lake use case • Staging for the Data Warehouse • So called Active Archiving –You can run queries against historical data, too –It will be federated query to access historical and current data –The data is stored for the indefinite time

12. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Data Lake use case • An external system loads data to the Data Lake • The data is analyzed case by case. Processing is highly parallel –Schema on read – we read all the data to determine the value of the data • Deliver the data once the requirements are fully known –Data warehouse – schema on write –Data Virtualization

13. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals U-SQL • Based on SQL and C# – C# expressions and types – Tables, views, window functions, etc. – User-defined functions/operators/aggregators in C# • Typical job 1. Read data from file/table/federated source 2. Transform rowset in a pipeline 3. Output rowset to table (INSERT) or file

14. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals U-SQL - extensibility • C# expressions • UDF’s – functions • UDAGG’s – aggregates • UDO’s - operators

15. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals UDO’s - operators • Extractors  EXTRACT • Outputters  OUTPUT • Processors PROCESS • Appliers  PROCESS • Combiners  COMBINE • Reducers REDUCE

16. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals UDO’s – extractor & outputter • User-defined extractors –Extract row by row –Used to implement data extraction from custom structured files • User-defined outputters –Output row by row –Used to output custom data types or custom file formats

17. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals UDO’s – processor & applier • User-defined processors –Take one row and produce one row –Used to reduce the number of columns or produce new columns with values that are derived from an existing column set • User-defined appliers –Take one row and produce 0 to n rows –Used with OUTER/CROSS APPLY

18. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals UDO’s – combiner & reducer • User-defined combiners –Combines rowsets--user-defined JOINs • User-defined reducers –Take n rows and produce one row –Used to reduce the number of rows

19. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals What else can you do? • JSON • R • Python • Cognitive Services

20. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals USQL & Cognitive • Imaging: Detect faces • Imaging: Detect emotion • Imaging: Detect objects (tagging) • Imaging: OCR (optical character recognition) • Text: Key Phrase Extraction • Text: Sentiment Analysis •

21. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals No more slides. Never

22. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Thank you!

23. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Q & A

24. @ITCAMPRO #ITCAMP18Community Conference for IT Professionals Many thanks to our sponsors & partners! GOLD SILVER PARTNERS PLATINUM POWERED BY

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