Database indexes how does it work

This is a pretty complicated subject. I would really like to know. Please leave a comment. Kris Wenzel has been working with databases over the past 30 years as a developer, analyst, and DBA. Kris has written hundreds of blog articles and many online courses. He loves helping others learn SQL. Thank you so much for the example with the book index! It really helped solidify the concept of indexes in my mind. Are there other DB related areas that you would like see articles about?

Thanks for finding the error in the text. I corrected the scenario to finding 15 rather than That works better with the example. Good explanation all around, thanks. Where is 15 found and its corresponding record returned?

Would be nice to have a little narrative on that to wrap up the example. My greater than and less than symbols did not show up. 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.

The card sorting is a great example! Thanks for the explanation and example , the article is very useful , examples which you have used served the subject well. Very well explained. I am just wondering about the multikey indexes. I was trying out a few multikey indexes in mongodb, so could you please explain more about the multikey indexes. Thanks :. Thanks for this article! The cards example is different than anything I have heard before; it really makes sense!

Question: In the diagram, are the light blue boxes the key values representing indices added to the database? I would love to dive more into what the code looks like directing the query to the index. Is that something that would be written in ActiveRecord somewhere? Our developer put in several new indexes on various tables and brought a 4. Awesome explanation. Thanks a bunch! As others have pointed out the book analogy is spot on.

If there are other topics that you find vexing, let me know. I can write another article. 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. When this query is executed, what goes on behind the scenes? This effectively means that the entire table will have to be scanned known as the full table scan. An index is a data structure that stores the values for a certain specific column of a table and helps us avoid a full table scan.

B-trees B-trees are the most commonly used data structures for indexes as they are time-efficient for lookups, deletions, and insertions. All these operations can be done in logarithmic time. Data that is stored inside of a B-tree can be sorted. Hash Tables Indexes that use hash tables are generally referred to as hash index. Hash tables are extremely efficient for looking up values, which means that queries that look for an exact match can be executed very quickly.

In a hash index, the key is the column value and the value in the hash table is a pointer to the row data in the table. However, hash tables are not sorted data structures, so they may not be efficient for other types of queries.

R-tree R-tree is commonly used with spatial databases. It helps with queries like "find all the coffee shops within 2 miles of my location". Bitmap Index Bitmap index works for columns that have many instances of those values, i. The more indices you have, the more the storage requirement. The column name can contain large values of any length.

Example: the following command creates an index on the first 4 bytes of name. So whatever index we create, MySQL in the background creates a backing composite index which in-turn points to the primary key.

This means that the primary key is a first class citizen in the MySQL indexing world. It also proves that all the indexes are backed by a copy of the primary index —but I am not sure whether a single copy of the primary index is shared or different copies are used for different indexes. It will help while doing low level system designing. Many real-life optimizations of our applications depend on knowledge of such intricate details.

Engineer PayPal, loves to have deep discussion on distributed and scalable systems, system architecture, design patterns, algorithmic problem solving. If you read this far, tweet to the author to show them you care. Tweet a thanks. Learn to code for free. Get started. Forum Donate. Kousik Nath. Now Insert some random data in the table, my table with 5 rows looks like the following: I have not created any index till now on this table.

Primary Key: The above query is very inefficient. Take the following into consideration when creating a primary key: A primary key should be part of many vital queries in your application. Primary key is a constraint that uniquely identifies each row in a table. If multiple columns are part of the primary key, that combination should be unique for each row. Primary key should be Non-null.

Never make null-able fields your primary key. By ANSI SQL standards, primary keys should be comparable to each other, and you should definitely be able to tell whether the primary key column value for a particular row is greater, smaller or equal to the same from other row.

The columns of the following images are described as follows: Table : The table on which the index is created.

Comment : The information about the index not described in its own column. Clustered Index: A clustered index is collocated with the data in the same table space or same disk file.

What does physical data organization mean? These small blocks are nothing but sort of pointers pointing to offsets of the records. Advantage of Clustered Index: This ordering or co-location of related data actually makes a clustered index faster. Constraints of Clustered Index: Since a clustered index impacts the physical organization of the data, there can be only one clustered index per table.

Define a primary key for each table that you create. If there is no logical unique and non-null column or set of columns, add a new auto-increment column, whose values are filled in automatically. The row ID is a 6-byte field that increases monotonically as new rows are inserted.

Thus, the rows ordered by the row ID are physically in insertion order. Is it possible to create a primary index on a non-primary key? Is it possible to delete a primary key? So the locality of data can be provided by the primary index. Any query that takes advantage of primary key is very fast. So DML operations puts some pressure on the performance of the primary index. Secondary Index: Any index other than a clustered index is called a secondary index.

When do you need a Secondary Index? How to create a secondary index in MySQL? Advantages of a Secondary Index: Logically you can create as many secondary indices as you want.

UNIQUE Key Index: Like primary keys, unique keys can also identify records uniquely with one difference — the unique key column can contain null values. Why do we use composite indices? Why not define multiple secondary indices on the columns we are interested in? How does composite index work? If you see certain fields are appearing together in many queries, you may consider creating a composite index.

Consider cardinality.