Reverse Key Index

by Yasin Baskan

In single instance databases there is also a case where reverse key indexes can be helpful. If you have a column populated by an increasing sequence, you delete some old rows from the table and you do not do range scans on that column and you have contention issues on index blocks, reverse key indexes can be considered. The reverse key index will scatter the entries accross different blocks during inserting and your many concurrent sessions will not have index block contention issues.

Read more: http://oracletoday.blogspot.com/2006/09/there-is-option-to-create-index.html#ixzz1wxx3qO4l

R is Ready for Big Data: Take the Open Road to Statistical Analysis

By Timothy Prickett Morgan

Statistical analysis has been around since mainframes were introduced to academia and corporations back in the 1960s.

But the great diversity of telemetry collected by systems today, the need to sift through it for insight and the growing popularity of open-source alternatives is transforming the R programming language for statistical analysis and visualisation. Its new nickname is Red Hat for stats…

http://www.theregister.co.uk/2012/06/03/big_data_r_statistical_analysis/

In the Oracle implementation of R, there is some integration that allows the R console to work with Hadoop distributed file systems and NoSQL databases, both of which are also core components of the world of “Big Data”

Seattle Area Lacks Computer Science Majors

There are some job seekers who aren’t having much trouble finding work – computer scientists. In Seattle alone, there are thousands of computer-related jobs waiting to be filled. And yet here’s the hang-up. While those jobs in Seattle are available, one of Washington State’s leading universities is not graduating enough people to fill them. The number of Bachelor’s degrees awarded in computer science has remained unchanged for the past decade.

http://www.npr.org/2012/05/31/154040185/seattle-area-lacks-computer-science-majors

Photo Credit: Canadian Veggie from Flickr.com

The future of computer science majors is expected to spike in demand for these graduates. Where will they come from? Certainly, government spending cannot afford that short-term bite of training this skilled workforce, but it has a very long term, and real impact on the nation’s economy. Perhaps attention to this looming demand of the workforce can be deferred; if so – for how long?

Photo Credit: Canadian Veggie from Flickr.com

Mark Hurd: ‘I felt Oracle was in a position to do something nobody else could do’

EU: Programming languages can’t be copyrighted

By Jennifer Baker
May 21, 2012 06:00 AM ET

Computerworld - Europe’s top court has ruled that the functionality of a computer program and the programming language it is written in cannot be protected by copyright.

The European Court of Justice made the decision in relation to a case thatSAS Institute, a maker of statistical programs, brought against World Programming Ltd. (WPL), which develops and sells an interpreter for the SAS language.

Although WPL used and studied SAS’s programs to understand their functionality, the court said, there was “nothing to suggest that WPL had access to or copied [SAS] source code.” The court ruled that “the purchaser of a license for a program is entitled, as a rule, to observe, study or test its functioning so as to determine the ideas and principles which underlie that program.” … (read more)

I think this ruling will better support more innovation and make life less stifling for talented developers looking for a better way of accomplishing business level tasks other than subscribing the status-quo of a handful of big vendor products. In turn, it will keep the big vendors on the alert and responsive to their customer base because they can quickly be replaced by a better engineered product.

Software Development as Artistic Practice: How Open Source Is Changing the Way Art is Made

by Kyle Chayka

Published: May 25, 2012

Artists are notoriously secretive about their processes. Rothko never revealed the complex formulas behind his diaphanous color fields. Picasso gave his famous dictum, “Bad artists copy. Good artists steal,” which may have been why Brancusi was so loathe to let the Cubist into his studio. But what about when sharing becomes a fundamental part of the artistic practice? For new media artists, whose work embraces the latest innovations in computing technology and digital imaging, being transparent with their working process is a fundamental part of being a member of the creative community — everyone copies and adapts from each other, sharing strategies, tools, and techniques… (read more)

This article can be found online at the following location:
http://www.databasejournal.com/news/mongodb-nosql.html

MongoDB – Why Does NoSQL Matter?
November 7, 2011

In recent years, the drumbeat of vendors proclaiming the ascendancy of NoSQL has become increasingly loud. One of the NoSQL vendors that is seeing business results from its NoSQL solution is 10gen, which is the lead commercial sponsor behind the open source MongoDB NoSQL database.

“We’re seeing the NoSQL space really taking off now and it’s being used in a significant way by a lot of people, including a lot of large enterprises,” Dwight Merriman, CEO and co-founder of 10gen, told InternetNews.com. “So big Internet companies like Craigslist and Shutterfly as well as big companies like SAP, Telefonica and LexisNexis are using it.”

Competition from the traditional database vendors also helps to validate the NoSQL space. At the OpenWorld Conference last month, Oracle announced its own NoSQL solution.

From a competitive perspective, Merriman sees MongoDB as the most popular NoSQL database in use today. His metrics for popular are somewhat indirect, though, and include MongoDB job postings and Google search popularity.

In terms of where NoSQL is fitting into enterprises, Merriman isn’t necessarily seeing NoSQL as a replacement for SQL databases but rather as a new tier of database technology usage. He noted that most Fortune 500 enterprises have an Oracle type relational database in their organizations already. The relational database is used for Online Transaction Processing (OLTP). Most big enterprises also have some form of data warehouse and a business reporting and intelligence database.

“Basically every large enterprise in the world has those two buckets for sure and what we’re seeing are enterprises adding a third bucket, which is a NoSQL basis,” Merriman said. “So on a forward basis, enterprises will have three classes of databases instead of two.”

When it comes to new Internet companies, Merriman expect that those companies will choose only one of three types of databases. The chosen database will likely be the one that maps closest to the problem the company is trying to solve.

Merriman noted that to use MongoDB, an organization must write new code.

“It doesn’t use SQL so if your old code assumes a relational data model so you have to write new code,” Merriman said.

For those that are looking to migrate to MongoDB, Merriman said enterprise developers need to re-write the code that talks to the database. He noted that there is not a lot of tooling for migration, since it’s not easy to automate.

“There are all the normal tools you’d expect in the database for import, export and monitoring of data,” Merriman said. “They’re just not specifically designed for migration.”

MongoDB 2.x

MongoDB 2.0 was recently released providing new concurrency features to the open source NoSQL database.

For the roadmap moving forward, Merriman said there is continuing work to further improve concurrency in the database. Additionally there is a new aggregation framework in the works that will make operations where users are aggregating and merging statistics easier and faster than the current model. MongoDB developers are also working on full-text search for a future release of MongoDB.

Sean Michael Kerner is a senior editor at InternetNews.com, the news service of Internet.com, the network for technology professionals.

Something tells me we’ll be seeing more of NoSQL as large and influential organizations such as Oracle and Google continue to utilize it as one of three different database solutions within their technical architecture. I suspect that most situations will not replace existing RDBMS structure, but instead initiate the database structure of newer projects and applications.

The following article can be found online at this location:
http://www.databasejournal.com/features/improving-dba-productivity.html

Thoughts on Improving DBA Productivity
November 18, 2011

Database administrators (DBAs) need to move away from reactive, repetitive tasks. Use the ideas presented here to become more productive.

Problem Resolution

DBAs should standardize problem resolution methods and the process of root cause analysis.

Most large IT organizations have multiple teams with which DBAs must collaborate. So, we need to consider how the extended team works together. If teams are in react mode, they tend to reactively approach problems; they concentrate on eliciting symptoms and applying quick fixes rather than searching for underlying causes. This leads to failure; or, at best, inefficient and overworked teams.

The most common reasons DBAs fail are the following.

Unclear problem definition: DBAs tend to see the symptoms and consider that the problem is now completely defined. For example, a long-running SQL statement may be diagnosed as “bad” and needing to be “fixed.” Work then proceeds on tuning the SQL statement without considering possible causes such as poorly organized data, invalid or unavailable data distribution statistics, data locking delays, incorrect lock granularity (row rather than page), disk synchronous I/O delays, or overall system load. Teams must begin by recognizing the difference between symptoms and their possible underlying causes. One way to accomplish this is to ask why a symptom or problem appears.

Making unfounded assumptions: Many experienced DBAs rely on their instincts or gut feelings only to discover that issues surface because their assumptions were false. Consider a distributed Java application that seems to be “locking” the mainframe DB2 data that it accesses, preventing other applications from reading the data. Without knowing the specific connection method and package bind parameters, the DBA may assume the fix will involve appending “WITH UR” (uncommitted read) to the SQL statements from the application. In some cases, non-standard parameters such a s ACQUIRE (ALLOCATE), ISOLATION(RR) or CURRENTDATA(YES) may be the real culprit.

No structured problem-solving process: Using a standard approach can help technical teams.

Stopping with the first good idea: When some teams encounter a problem, one technician will choose a solution and stop. It’s as if the purpose of the process was to generate a single answer. Rarely does the team consider multiple good ideas, which may then be combined or executed in parallel. Teams also need to consider and implement ideas for detecting the symptom or problem if it recurs, preventing the problem, or processes that will automatically detect and correct the problem.

Continual Improvement

Document, centralize, standardize. Assign quality measures to documents and processes. Productivity for the IT professional means doing the right work while minimizing wasted effort and redundancy. One of the original sources of continuous improvement comes from the Software Engineering Institute at Carnegie Mellon University. Their Capability Maturity Model (CMM) imposes an organizational structure on software development processes and, by extension, infrastructure support processes such as database administration. The model describes processes and practices in terms of a maturity level that can be used as a guide for gauging current maturity and for planning improvements. Continuous improvement is where you work on tasks that increase process and practice maturity.

Consider a process for database change control. Assume the process is poorly documented, uses non-standard scripts, and has no quality measures. Continuous improvement would involve raising the maturity level from repeatable to defined, which might involve improving documentation, standardizing processes, and adding process quality measures.

When implementing a continuous improvement process, follow these guidelines:

•       Make the processes repeatable so earlier successes aren’t wasted. This means standardized JCL and scripts that can be executed by anyone without modification, and instructions for execution and for follow-up on failure. Ensure the entire team is aware that processes exist and you have procedures for controlling changes to documentation and processes.

•       Standardize. Processes and documentation are all well-written in a standard format. Complete information is available in a centralized area, indexed for ease-of-use. The entire team should be familiar with approved ways to access and update information.

•       Manage. Implement initial quality measures. Processes and documentation should be regularly reviewed for possible updates.

Metrics and Dashboards

Be able to answer, “What have you done for us lately?” with numbers and dollars. Many DBAs fail to realize how much IT management depends on numbers when measuring activity or productivity. In today’s climate, the extended IT enterprise will be forced to increase productivity and reduce costs. How can this happen if management can’t measure what the DBA does?

Measures such as the number of tables, indexes, or columns moved to production, or the number of hours spent on a project concentrate on single, one-dimensional tasks; they fail to consider the DBA and the supported DBMS and infrastructure as an integrated system. Consider the performance of an online application from key perspectives:

•       The user dimension includes transaction rates, data throughput, and perceived transaction elapsed times.

•       The system dimension includes resource usage (CPU, DASD, etc.), availability of high-performance access paths (e.g., existence of indexes), and data clustering.

•       The DBA dimension includes scheduling of utilities such as reorg and copy, along with some subjective items such as how well the DBA knows the tables, the SQL, and the application.

To give IT management the numbers they need, you need to find measures of the application that correlate to its performance. You also need the same thing for yourself. What things correlate to your performance?

Measurements typically summarize resources spent on tasks, or measure the state of documentation and processes. The latter measurements include documentation and process quality (readability, repeatability, etc.). Many shops use a time-tracking system to gather resource use.

Without quality measures, it’s difficult to prioritize improvements. Documentation quality measures go beyond good grammar. Teams must decide what quality measures are important; some of these might be:

•       Applicability: Does this documentation apply to a large set of general conditions or only a few specific cases?

•       Verifiability: Can the documentation be cross-referenced to other documentation or publications such as product manuals? Are there simple means of verifying that the documentation is correct, current and complete?

•       Currency: Is the documentation up-to-date? When will the information expire or become useless? Must it be updated at specific times or at the time of certain events?

•       Reference- or task-centric: Is the documentation mostly reference material, or will it be used to complete some process? Does it include checklists, flowcharts, or other means of process management?

Start with these and use simple measures such as a one-to five-point scale. It isn’t necessary to be 100 percent accurate; the important point is to use the results to prioritize improvements.

As you fix problems, document the fixes along with your analysis. Compare the quality of the fix document with that of the process and related documentation. If the fixes are higher quality, then your documentation and processes need to be reviewed and updated. If the documentation and process have higher quality, then you need to improve either your problem-solving skills or your follow-up in documentation of repeatable processes.

Summary

The notions presented here can help the DBA move away from reactive tasks, initiate quality measures, and offload basic, repetitive tasks. Hopefully, you can use this material as you work to become more productive. Remember to quantify and document your results, then advertise your value.

Also found a useful, short video that highlights a typical day in the life of a DBA, which is also relevant to this post:

Note that the DBA was well prepared with scripts, procedures and tools that helped him quickly identify and resolve the various customer problems encountered. Given enough time to anticipate typical operational problems is a big part of a DBA’s responsibilities.

 The initial report breaks down the data into per capita spending, prices paid per service, out-of-pocket spending, utilization, and the mix or intensity of services used. The report covers data from 2010 for 33 million privately insured people.

What they found out was that it was the cost of the care provided and not the utilization that incurred the largest expense for the participants of the U.S. Health Care Cost Institute (HCCI), which included Aetna, Humana and United Health care.

Check out some of the metrics that they uncovered from analyzing the HCCI database of health care costs for the past few years. Comparative (past to previous) studies were also conducted.

Published on Business Finance (http://businessfinancemag.com)

Mining the Health Care Cost Database
by Joanne Sammer
Created 05/24/2012 – 17:50

A treasure trove of health care cost information is now available to researchers and others interested in understanding the trends and drivers of health care costs in the U.S. The Health Care Cost Institute (HCCI) issued its first Health Care Cost and Utilization Report based on data from three billion (yes, that’s billion with a “b”) health care claims provided by Aetna, Humana and UnitedHealthcare, three of the nation’s largest health plans, with Kaiser Permanente data to be added in the near future.

This database provides employers with important benchmarking data and opportunities to analyze trends in inpatient and outpatient care, professional services, and prescription drugs obtained by privately insured patients in employer-sponsored group health insurance plans. The initial report breaks down the data into per capita spending, prices paid per service, out-of-pocket spending, utilization, and the mix or intensity of services used. The report covers data from 2010 for 33 million privately insured people.

The key finding from this first report is the fact that it is the cost of care and not utilization that is the main driver of health costs. Although the overall use of health care services declined in 2010, overall costs did not. The spending increase in 2010 was lower at 3.3% for individuals under age 65 than it had been the prior two years, but it was still driven largely by prices for the privately insured that grew more than utilization. For example, prices increased significantly for two key elements of care – hospital care (5.1%) and ambulatory care facilities (10.1%). Meanwhile, usage dropped by more than 5% for medical inpatient admissions, emergency room visits, primary care provider office visits and radiology procedures.

Other key findings include the following:

• Average per capita spending on health care services was $4,255 for the entire sample, while per capita spending was much higher ($8,327) for people aged 55-64 and much lower ($2,123) for those under 18.

• Out-of-pocket per capita spending was $689 in 2010, which represents an increase of 7.1% from 2009.

• The price for an average hospital stay increased 5.1% to $14,662 in 2010, while the cost of an average emergency room visit increased 11% to $1,327. The latter figure emphasizes the potential payoff for any employer effort to reduce unnecessary emergency room visits, particularly if patients rely on the emergency room for non-emergency situations.
• The average cost of a prescription increased 3% from $80 to $82 in 2010, as brand name drug prices increased 13% and generic drug prices decreased by 6.3%. On average, each insured person filled more than nine prescriptions in 2010. The number of brand name prescriptions dropped by nearly 4%, while the number of generic prescriptions increased by 2.5%. Once again, this data shows the potential cost savings associated with efforts to encourage the use of available generics in lieu of brand name drugs.

Overall, costs to provide the same amount of care as in the previous year went up drastically. It isn’t that many more people are getting older and more frail, nor is it an increasing trend in hypochondriac activity. People are asking for care as much as they always have, and it’s just that the care provided costs more to deliver for one reason or another. Interesting find for the analytic teams involved…