Azure Datacamp Power Hour Dr Greg Low greggreglow

Azure Datacamp Power Hour Dr Greg Low (greg@greglow. com) CLD 213

SQL

Subscription Logical Server 1 Server Logical Server 2 Database master User. DB 1 Logins/Users Logins Users …

P 11 P 6 B S 0 S 1 S 2 S 3 P 1 P 2 P 4

OLTP Cloud Application SQL TDS, ODBC, JDBC, ADO Elastic Jobs Elastic Tools Libraries DB DB DB EQ DB DB DB Elastic Query DB DB

SQL Server in a VM SQL Database Document. DB HBase Tables/Blobs fully featured RDBMS rich query transactional processing managed as a service elastic scale schema-free data model internet accessible http/rest

Document. DB account Databases { } Collections Documents Attachments 101 010 { } Users Stored procedures JS Permissions Triggers JS User-defined functions JS your Documents here

Collections Document 2 Document 1 { { "name": "John", "country": "Canada", "age": 43, "last. Use": "March 4, 2014" "name": "Eva", "country": "Germany", "age": 25 } } Document 4 Document 3 JSON { { "name": "Lou", "country": "Australia", "age": 51, "first. Use": "May 8, 2013" } "doc. Count": 3, "last": "May 1, 2014" }

Collections Documents Attachments 101 010

JS Stored procedures Triggers

Machine learning & predictive analytics are core capabilities that are needed throughout your business

1. 2.

Example 1 example B example A Example 1 example A Example 3 example B Example 2 example C Example 3

Web/thick client dashboards Applications Legacy IOT (custom protocols) Devices Cloud gateways (web APIs) Storage adapters IP-capable devices (Windows/Linux) Low-power devices (RTOS) Stream processing Field gateways Search and query Data analytics (Excel) Devices to take action

Azure Event Hubs Azure Blob Storage Azure SQL DB Events have defined schema and are temporal (sequenced in time) Reference Data Query runs continuously against the incoming stream of events Azure Blob Storage Azure Event Hubs

Entry. Stream – Events about entering toll station Toll. Id License Plate Entry. Time State Make Model Type Weight 1 2014 -10 -25 T 19: 33: 30. 0000000 Z JNB 7001 NY Honda CRV 1 3010 1 2014 -10 -25 T 19: 33: 31. 0000000 Z YXZ 1001 NY Toyota Camry 2 3020 3 2014 -10 -25 T 19: 33: 32. 0000000 Z ABC 1004 CT Ford Taurus 2 3800 2 2014 -10 -25 T 19: 33. 0000000 Z XYZ 1003 CT Toyota Corolla 2 2900 1 2014 -10 -25 T 19: 33: 34. 0000000 Z BNJ 1007 NY Honda CRV 1 3400 2 2014 -10 -25 T 19: 33: 35. 0000000 Z CDE 1007 NJ Toyota 4 x 4 1 3800 … … … … Registration. Data – Reference data … Exit. Stream - Data about vehicles leaving the toll station Toll. I d Exit. Time License. Plate 1 2014 -10 -25 T 19: 33: 40. 0000000 Z JNB 7001 1 2014 -10 -25 T 19: 33: 41. 0000000 Z YXZ 1001 3 2014 -10 -25 T 19: 33: 42. 0000000 Z ABC 1004 License. Plate Registartion. Id Expired SVT 6023 285429838 1 XLZ 3463 362715656 0 2 2014 -10 -25 T 19: 33: 43. 0000000 Z XYZ 1003 QMZ 1273 876133137 1 … … … RIV 8632 992711956 0 … … ….

SELECT Toll. Id, COUNT(*) FROM Entry. Stream TIMESTAMP BY Entry. Time GROUP BY Toll. Id, Tumbling. Window (second, 20) A 20 -second Tumbling Window 1 5 4 6 2 8 6 5 3 6 1 Time (secs) 1 5 4 6 2 8 6 5 3 6 1

A 20 -second Hopping Window with a 10 -second “Hop” 1 5 1 4 5 4 6 6 2 8 7 5 6 3 1 2 4 6 2 8 6 5 3 6 1

A 20 -second Sliding Window 1 5 9 8 1 5 1 9 8

Web browser Business analyst tools Microsoft cloud SQL Server analysis services Databases and other data sources On-premises data Microsoft cloud Non-Microsoft cloud Mobile apps

My Ignite

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