Category: Exadata

How to determine if you are getting all the benefits of Exadata via AWR

Last week Juan Loaiza introduced the latest generation of Oracle Exadata, X10M, , and with each new release comes more powerful compute power and larger flash and disk capacity. Along with all of the hardware improvements come a bunch of software enhancements that transparently accelerate your database workloads (RDMA, Smart Scan, Storage Indexes, Smart Flash Cache, etc.).

But how do you know if you are benefiting from these accelerators?

The easiest way to determine how your databases on Exadata are performing is via an Automatic Workload Repository (AWR) report, and two of my favorite Oracle experts have created step-by-step guides to help you do just that.

Cecilia Grant has written a fantastic white paper on Using AWR reports on Exadata. It provides a step-by-step guide to the Exadata performance statistics found in an AWR report and shares common challenges you may encounter and how to resolve them.

For those less familiar with Exadata, Kodi Umamageswaran(SVP of Exadata development) gave an excellent introductory talk at last year’s Oracle Database World called Transparent Performance with Exadata: What, When, How, and Why. In the session recording below, Kodi does a great job of introducing the capabilities of Exadata and how to identify those benefits using AWR to determine if you are getting all of the performance-enhancing benefits you should be.

Happy performance tuning!

What you can expect from Oracle Autonomous Transaction Processing

Today Larry Ellison announced the general availability of Oracle Autonomous Transaction Processing (ATP), the newest member of the Oracle Autonomous Database family, combining the flexibility of cloud with the power of machine learning to deliver data management as a service.

Traditionally, creating a database management system required a team of experts to custom build and manually maintain a complex hardware and software stack. With each system being unique, this approach led to poor economies of scale and a lack of the agility typically needed to give the business a competitive edge.

ATP enables businesses to safely run a complex mix of high-performance transactions, reporting, and batch processing using the most secure, available, performant, and proven platform – Oracle Database on Exadata in the cloud. Unlike manually managed transaction processing databases, ATP provides instant, elastic compute and storage, so only the required resources are provisioned at any given time, decreasing runtime costs.

But what does the Autonomous in Autonomous Transaction Processing really mean?

Self-Driving

ATP is a self-driving database, meaning it eliminates the human labor needed to provision, secure, update, monitor, backup, and troubleshooting a database.  This reduction in database maintenance tasks, reducing costs and freeing scarce administrator resources to work on higher value tasks.

Continue reading “What you can expect from Oracle Autonomous Transaction Processing”

Oracle Storage Index

If you are on Exadata or taking advantage of Database In-Memory it’s possible your queries will benefit for the automatically created and maintained Storage Indexes.

But what exactly are Storage Indexes and why don’t I always see a benefit from them?

Let me start by describing what Storage Indexes are in relation to Database In-Memory but remember they behavior in exactly the same way on the Exadata storage cell.

A Storage Index keeps track of minimum and maximum values for each column in an In-Memory Compression Unit (IMCU) or 1MB chunk on the Exadata storage cells. When a query specifies a WHERE clause predicate, the In-Memory Storage Index on the referenced column(s) is examined to determine if any entries with the specified value exist.

If you are on Exadata or taking advantage of Database In-Memory it’s possible your queries will benefit for the automatically created and maintained Storage Indexes.

What are Storage Indexes?

Let me start by describing what Storage Indexes are in relation to Database In-Memory but remember they behavior in exactly the same way on the Exadata storage cell.

A Storage Index keeps track of minimum and maximum values for each column in an In-Memory Compression Unit (IMCU) or 1MB chunk on the Exadata storage cells. When a query specifies a WHERE clause predicate, the In-Memory Storage Index on the referenced column(s) is examined to determine if any entries with the specified value exist.

Continue reading “Oracle Storage Index”

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