Database indexes how do they work

It is very practical and makes clear to me how indexing in databases work. Very well written! Both examples are great, actually both put into picture explain it much clearer than giving out only one. Thanks Kris..

It is really helpful to understand the concepts in beginner level.. Thank Keshav, If there are other topics that you would like to know about, please let me know. Hi Kris. Nicely done to let us understand indexes easily. I do not find a clear explanation on this anywhere. Hahaha that was a nice pun. Thank you! Great explanation. I am converting from relational to big data indexed database as an analyst and I am trying to gain a deeper understanding.

Feel like I am back at data :. I was looking for a article with a simple, clear description of why indexing is important and how they work … this is definitely what I was looking for. Now, do you have any advice on not creating too many indexes especially unnecessary , as maintenance can negatively impact performance?

I was looking for a high-level explanation of how indexes work and this article was very helpful! Awesome post, thank you very much, Kris. It seems like a critical topic to understand. Thanks Kris. Easiest to understand yet crisp and clear write up and helped me.

I LOVE examples that are common and easy to relate and understand. But in short, indexing is just a way for a system or database to quickly access data on the fly, […]. Nothing is worse than, being excited to learn a new tool but not knowing where to start, wasting time learning the wrong features, and being overwhelmed.

Please log in again. The login page will open in a new tab. After logging in you can close it and return to this page. April 16, Good Question! Share 0. Tweet 0. About the author. Kris Wenzel. Let me know. Yes indeed, that was the ice breaker, the aha moment. Great article, thanks. Hi Kris, I really appreciate for your efforts and valuable time doing such a great Hard work regarding SQL Server and Thank you so much for educating us.

Can you please have a post in Ranking Functions and Cursors,Derived tables if possible. Thanks in Advance. Yes, the blue boxes represent index entries. Best, Emil. I use the query plan to help with this. Hey Kris, thanks a lot for this article. Thanks again for your work and explanation. Regards Marcus. You have explained it in a very easy way. Keep it up! Non-clustered indexes hold the field that they are responsible for sorting and a pointer from each of those entries back to the full entry in the table.

You can think of these just like indexes in a book. The index points to the location in the book where you can find the data you are looking for. Non-clustered indexes point to memory addresses instead of storing data themselves. This makes them slower to query than clustered indexes but typically much faster than a non-indexed column.

You can create many non-clustered indexes. That is because indexes do not store all of the information from the original table. The pointer logic would look like this:. That means the query plan , the plan that SQL creates when determining the best way to perform a query, will begin to use the index when queries are being made. That is the clustered index that was referenced earlier in the article that is automatically created based off of the primary key.

That index was created similarly to the names index:. This provides a way for our database to swiftly query city names. After your non-clustered indexes are created you can begin querying with them.

Indexes use an optimal search method known as binary search. Binary searches work by constantly cutting the data in half and checking if the entry you are searching for comes before or after the entry in the middle of the current portion of data.

This works well with B-trees because they are designed to start at the middle entry; to search for the entries within the tree you know the entries down the left path will be smaller or before the current entry and the entries to the right will be larger or after the current entry. In a table this would look like:. Comparing this method to the query of the non-indexed table at the beginning of the article, we are able to reduce the total number of searches from eight to three.

Using this method, a search of 1,, entries can be reduced down to just 20 jumps in a binary search. Indexes are meant to speed up the performance of a database, so use indexing whenever it significantly improves the performance of your database. Tables increase in size and searching increases in execution time.

In reality the database table does not reorder itself every time the query conditions change in order to optimize the query performance: that would be unrealistic. In actuality, what happens is the index causes the database to create a data structure. The data structure type is very likely a B-Tree. While the advantages of the B-Tree are numerous, the main advantage for our purposes is that it is sortable.

When the data structure is sorted in order it makes our search more efficient for the obvious reasons we pointed out above. When the index creates a data structure on a specific column it is important to note that no other column is stored in the data structure. Database indexes will also store pointers which are simply reference information for the location of the additional information in memory. The index will actually look like this:.