By Joel Peréz ACED.gifSkant Gupta

 

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Oracle Autonomous Data Warehouse Cloud is a kind a new service that will solve many typical difficulties in the past, the main conception of this kind of special service is the Fully Tuned

  • "Load and Go"
  • Define tables, load data, run queries
    • No tuning
    • No special database expertise required
  • Good performance out of the box

 

If you want to know how this service will perform all this.. keep reading the rest of this article..

 

So.. at the last OOW17 the word "Autonomous" was the most sounded in the enviroment, people very interested in these new kind of services more close to those futuristics things that are happening on the 20th Century. Personally, when I heard all related to "Load and go..", no tuning.. no expertise.. amazing performance without doing anything.. the first question that came to my mind was.. "How they will do that.. ?", well, let's read a bit about it..

 

Firstable, Let's define the main characteristics of "Autonomous Data Warehouse Cloud"

  • Easy
    • Fully-managed, pre-configured and optimized for DW workloads
    • Simply load data and run
      • No need to define indexes, create partitions, etc.
  • Fast
    • Based on Exadata technology
  • Elastic
    • Instant scaling of compute or storage with no downtime

 

Fast -> "Based on Exadata technology", this is one of the key point that is behind of all this super-power service.. "running on Exadata", it's pretty well known the extreme processing power that has Exadata, so.. things can run extreme fast even when they are not optimized, of course this will not be the case of "Autonomous Data Warehouse Cloud" but as we are talking about a kind Artificial Intelligence behind of all this, at the beginning of the workload, the resolution of things they will not be still optimized, basically because something must learn about the typical use of this database and that something is the "Machine Learning".

So, the Machine Learning must and will LEARN from the typical and common activities related to that database to generate POSSIBLY internal ( objects, components, structures, etc.. ) this is a big and deep point of conversation.. according to what people was guessing, the autonomous database service could create or not some objects to make the processing faster..

I had a big conversation about that point with Mr. Andrew Holdsworth (“Oracle Real World Performance Vice President” ) and he told me something simple with a great value.. He mentioned.. “I’m not sure if in autonomous database will be created objects like “indexes”.. etc.. possibly “yes..” possibly “not”, this service is still getting shape.. and it will get a real shape with the real use of customers, up to now we are not thinking to create indexes because when you create an index, something can get better and at the same time something can get worst.. so.. create indexes or some other structures open the door of a huge variation of results and that’s not what we want.. “

He mentioned as well “While you are more standard.. more predictable you are..” so.. if we do not create indexes, we can have more standard results and a higher scalability to keep them over the time. I will cover all this in some articles later..

 

Now, We will come back to talk about Machine Learning. When a database start to run in "Autonomous Data Warehouse Cloud", the Machine Learning does not have too much information about how the data will be accessed.. so.. once the workloads.. queries.. and everything start to go.. the Machine Learning will start to collect information and take internal actions to make these access ways more optimal, in "Autonomous Data Warehouse Cloud" while you use more your database will be more optimized..

 

Since, we mentioned "Machine Learning", let's dedicate some lines to understand in a general way, what is "Machine Learning"

 

Machine Learning in the Cloud

On top of these proven high availability and scalability technologies, Oracle Autonomous Database Cloud integrates a set of next-generation monitoring, management, and analytics capabilities that leverage machine learning and artificial intelligence techniques to automate performance tuning, prevent application outages, and harden security across the entire application and infrastructure portfolio.

The first such service scheduled to be available will be Oracle Autonomous Data Warehouse Cloud, followed by an autonomous OLTP and mixed workload cloud and an autonomous NoSQL cloud after that. Oracle Autonomous Data Warehouse Cloud leverages years of investment in self-tuning technologies like Oracle Exadata storage indexes and flash cache, powerful query optimization, automatic memory management, and automatic storage management to provide a completely self-tuning database.

No traditional performance tuning by administrators and developers is required. With Oracle Autonomous Data Warehouse Cloud, Mendelsohn said, "You just define tables, load data, and run queries; the database is completely self-tuning." The service is so efficient that at Oracle Openworld CTO Ellison discussed offering a guarantee that customers could move their analytic databases from Amazon's cloud and run them at half the cost on Oracle Autonomous Database Cloud.

 

The foundations of Machine Learning are not new theories.. Machine learning works based on analysis techniques developed and published even starting the past century, many things around us works with Machine Learning (ML), if you want to read about it, go here:

https://blogs.oracle.com/machine-learning-explained

 

If you want to go knowing a bit more about Machine Learning, you can watch here:

First Look Advanced Analytics and Machine Learning in the Oracle Database Environment

https://www.youtube.com/watch?v=kK2krDjO-fQ

 

Machine Learning with Oracle

https://www.youtube.com/watch?v=91X73YYSA30

 

Let’s explore some of the web interfaces we will find working with “Autonomous Database”

 

Fully-managed

Oracle automates end-to-end management of the data warehouse

  • Provisioning new databases
  • Growing/shrinking storage and/or compute
  • Patching and upgrades
  • Backup and recovery

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Full lifecycle managed using the service console

  • Alternatively, can be managed via command-line interface or REST API

 

Fully Tuned

  • "Load and Go"
  • Define tables, load data, run queries
    • No tuning
    • No special database expertise required
  • Good performance out of the box

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Query using any business analytics tool or cloud service

  • Built-in SQL worksheet and notebook also included

 

Fully-elastic

Size the DW to the exact compute and storage required

  • Not constrained by fixed building blocks, no predefined shapes

Scale the DW on demand

  • Independently scale compute or storage
  • Resizing occurs instantly, fully online

Shut off idle compute to save money

  • Restart instantly

 

Full Support of DW Ecosystem

  • Autonomous Data Warehouse Cloud supports :
    • Existing tools, running on-premises or in the cloud
      • Third-party BI tools
      • Third-party data-integration tools
      • Oracle BI and data-integration tools: BIEE, ODI, etc
    • Oracle cloud services: Analytics Cloud Service, Golden Gate Cloud Service, Integration Cloud Service, and others
    • Connectivity via SQL*Net, JDBC, ODBC

 

At this following image we can see the integration and interaction of "Autonomous Datawarehouse Cloud" with:

  • Developer Tools
  • Data Integration Services
  • Business Intelligent Services and more

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Getting Started with Autonomous Data Warehouse Cloud

Provisioning a database

 

Provisioning requires only 5 simple questions:

  • Database name?
  • Data center?
  • Number of CPUs?
  • Storage capacity?
  • Admin user password?

New service created in <30 seconds (regardless of size)

  • and Ready to connect

 

The interface is very alike to when you are creating a regular Cloud Database with the options already known. The last 3 fields are corresponding to the objects from where we can start to load information for our Data Warehouse

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Demo

Provisioning a database

 

Being at the section of “Autonomous Data Warehouse Cloud”, We proceed to create a “Service”

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We fill the fields of what We talked before

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In this opportunity we have filled just the mandatory ones and press "Next"

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We realised the summary of the options chosen and we press “Create”

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Now We can see our "salesdb" Service already created.

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Now that the Service is already created, Let’s read an article about how to load data in Autonomous Database for Data Warehouse

Oracle 18c: How to load data in Oracle Autonomous Data Warehouse Cloud..

 

As an additional resource you can listen here an interesting Podcast about this topic

Oracle Cloud Podcast Series: Oracle Autonomous Data Warehouse Cloud

http://streaming.oracle.com/ebn/podcasts/media/30324001_Autonomous-Data-Warehouse_Sep_2017.mp3

Oracle Cloud Podcast Series Featuring Oracle's VP of Product Management Discussing the new Oracle Autonomous Data Warehouse Cloud.

 

If you want to be updated with all our articles send us the Invitation or Follow us:

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Skant Gupta's LinkedIn: www.linkedin.com/in/skantali/

or Join our LinkedIn group: Oracle Cloud DBaaS

 

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Author Bios:

 

Joel Pérez is an Expert DBA ( Oracle ACE Director, Maximum Availability OCM, OCM Cloud Admin. & OCM12c/11g ) with over 17 years of Real World Experience in Oracle Technology, specialised in design and implement solutions of: High Availability, Disaster Recovery, Upgrades, Replication, Cloud and all area related to Oracle Databases. International consultant with duties, conferences & activities in more than 50 countries and countless clients around the world. Habitual and one of leading writers of Technical Oracle articles for: OTN Spanish, Portuguese, English and more. Regular Speaker in worldwide Oracle events  like: OTN LAD (Latin America), OTN MENA (Middle East & Africa), OTN APAC ( Asian Pacific), DTCC China, Oracle Code.. . Joel has always been known for being a pioneer in Oracle technology since the early days of his career being the first Latin American awarded as “OTN Expert” at year 2003 by Oracle Corp., one of the first “Oracle ACE” globally in the Oracle ACE Program at year 2004. He was honoured as one of the first “OCM Database Cloud Administrator” & Maximum Availability OCM in the world. Currently Joel works as Senior Cloud Database Architect in “Yunhe Enmo (Beijing) Technology Co.,Ltd”., company located in Beijing, China En.enmotech.com

 

Skant Gupta is an Oracle Certified Cloud Professional in Oracle Database 12c, an Oracle Certified Expert in Oracle Real Application Clusters (Oracle RAC) in Oracle Database 11g and 12c, and an Oracle Exadata Certified and an Oracle Certified Professional in Oracle Database 10g, 11g, and 12c. He works at Vodafone Technology in the UK and formerly worked as a senior DBA at Etisalat in Dubai. He has six years of experience with various Oracle technologies, focusing mainly on Cloud, database, and high availability solutions, Oracle WebLogic Suite, Oracle Exadata and Oracle GoldenGate. He has presented at several Oracle user groups worldwide, most recently in the US, the United Arab Emirates, and the India. Skant website link: oracle-help.co