Wednesday, May 19, 2021

My best practices: How to search Db2 documentation

I often answer technical product questions, for Db2 and IBM Cloud topics. To provide relevant links and to back up my "hunch" after reading a question, I typically search the relevant documentation. But what are efficient way to search in the Db2 documentation? What are good ways to find the relevant parts in the IBM Cloud documentation? Here are my best practices on searching documentation.


Before I start with the actual search, let's begin with some basics. Most documentation is organized, structured into categories or parts. Typically, the product documentation itself provides a search form, in many cases with some filtering options. And most documentation is missing an introduction on how to use the documentation and its search. The good news is that most search engines, either built into the documentation portal or regular Internet search portals, offer some basic logical operators and common search capabilities.

Navigate, then read

Use table of contents to navigate
This first approach is a quick way to find the relevant parts when you know where to locate it. Let's take a look at the Db2 11.5 documentation as shown on the right. First, I tick the checkmark for "Show full table of contents" to have all topics. Next, to go to the SQL reference, I expand the Database reference section and see the list of subtopics, including SQL. In that list I could unfold the Statements section and could navigate to, e.g., ALTER TABLE and would be ready to read.

Similar to the Database reference there is Database fundamentals which covers the product life cycle with everything from installing, configuration, applying fixes to monitoring and performance tuning. If looking into topics for the application developer, I start with the section Developing code for accessing and managing data.

The bottom line is that this strategy works well, when you are experienced in RTFM or want to explore the documentation for whatever reason...

Built-in search

Generally, when searching for something, it is best practice to enter the correct search term. Thus, when I search for the documentation on the ALTER TABLE statement, use the term "ALTER TABLE" not ALTER TABLE (no quotes). This might be not too obvious, but it forces the search engine to only consider occurrences of the entire quoted string.

I typically use the logical operator AND to combine search terms. It tells the engine to look for documents matching both terms. Sometimes, it is even a good idea to reinforce that you want to search only the Db2 documentation, nothing else. Compare the screenshot below for the optimal search Python AND SDK AND Db2 with the results for just searching for Python AND SDK.

Combine (AND) search terms and enforce the topic Db2

Internet search engines

An alternative to the built-in search are utilizing Internet search engines like Bing, DuckDuckGo, Ecosia, Google, Startpage, Qwant or others. Type in your search term including the keywords Db2 11.5 and press the search button. It often leads to good results. 

But did you know that you could optimize it by telling most search engines what / where to search? Use the term to scope the search to the Db2 11.5 documentation only. Searching for the Python SDK in the Db2 11.5 documentation with DuckDuckGo gives this result:

Scoping an Internet search to a website and path only

Each search engine has its own style and set of features to use. Check out the, e.g., DuckDuckGo search guide. They even have a so-called bang for the IBM Documentation. Use !ibmkc in their search to redirect it to an IBM Documentation search. Thus, the search !ibmkc python sdk db2 11.5 actually searches the Db2 docs.


There is no single way of how to consume or search documentation. It depends (!) on what you are searching for, your experience with the specific documentation and with search engines. Thus, try out the discussed options and pick what fits your best, both in terms of results and convenience. The shown techniques work for IBM Cloud documentation, too. Only the URLs are different.

If you have feedback, suggestions, or questions about this post, please reach out to me on Twitter (@data_henrik) or LinkedIn.