Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary


Bitmapped to Hell

Oracle bitmap indexes are generally used to index columns that have very sparse domains such as Y/N, gender, or any other list of member values that is small in number. You get the advantage of indexing without creating in imbalanced btree if a conventional index is used. There is lots of info on bitmap indexes. They are also very common in read-mostly applications like data warehousing.

Oracle bitmap indexes are generally used to index columns that have very sparse domains such as Y/N, gender, or any other list of member values that is small in number. You get the advantage of indexing without creating in imbalanced btree if a conventional index is used. There is lots of info on bitmap indexes. They are also very common in read-mostly applications like data warehousing.

I have a security application that has table ACCESS_LOG that logs access to person data and by whom. The only filter I had on the ACCESS_LOG within the Apex security application was on created_by, which was a relatively small number of users over time in what would ultimately become a very large table. And, the ACCESS_LOG is insert-only so it has the characteristics of a DW table. 

What we found is that concurrent access by two different users with functionality that writes to the ACCESS_LOG was causing the application to hang in the second session. Seems like an oddity for an application that only inserts into the ACCESS_LOG, not the scenario where one wold expect to find locking. The contention only happened when the value of created_by posted to the ACCESS_LOG was the same. Maddening since the procedural code doing the posting didn't have any issues and had been in production use for some time.

The mystery was resolved with my partners Andy and Jim at the University of Missouri who tracked the problem to the bitmap index on ACCESS_LOG. The problem was exposed when they started to use functionlaity that had not been used significantly before. Yet, the same procedural code was used elsewhere throughout the application and did not reveal this contention problem. Converting to a conventional index resolved the problem.

Andy and Jim had suspected a contention problem. Digging further into the documentation for Oracle 11.1, that is indeed what goes on with bitmap indexes. Oracle deals with blocks of indexes for a specific bitmap index value, not individual like in a btree index. The first session locked the block causing the second session to wait until a commit or rollback.

The conventional indexes that replaced the bitmaps may have performance issues over time. I also could not add a commit within the procedural code that did the posting due to that impacting a larger transaction. 

Lesson learned.  Even though it should have been insert only, the fact that the inserts come from multiple sessions and how Oracle processes bitmap indexes made the bitmap indexes a problem. How much of a problem we'll see.

 The other lesson learned - concurrent applications need concurrent testing with same and different data to test for issues like described above. Otherwise, the problem is hidden waiting to strike.

Bitmap indexes will return to my app in the audit tables and other places where the inserts come from one source and there is not concurrency issues.

++B 



Related Reading


More Insights




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.