intro
The HEAP data structure is often thought of in the sense of a pile of objects where the biggest or smallest item is always at the top. In the database world, this concept is understood a little differently.
Think of the HEAP data structure like a priority queue where the most important element is always at the top. The key characteristic of a heap is efficient access due to the root element always being either the minimum or maximum value, so retrieval is quick. In databases, this has a different meaning. Let’s find out!
How is the HEAP Data Structure Related to Databases?
Given that you’re reading a database blog, you may wonder just how the HEAP data structure may be related to database management systems and the answer is quite simple: a HEAP generally refers to data stored directly in memory instead of the disk.
In fact, one of MySQL/MariaDB’s storage engines—MEMORY —was initially known as HEAP because it had initially stored data in heap memory which is a region of memory used to dynamically allocate it.
In databases, memory storage refers to just that: it refers to data stored directly in the operating memory (RAM) of a server instead of it being stored on disk. This is important because of a couple of reasons with the main one of those being related to speed because accessing data in operating memory is way faster than accessing it on the disk. This way, we can power real-time data processing since data stored in memory allows databases to perform transactions and analytics in real-time at the same time minimizing disk I/O and boosting performance even further.
Look at databases that store data in-memory: Redis, for example, stores data entirely in RAM and the result is rapid data access. MariaDB and MySQL does exactly the same thing with the MEMORY storage engine: it simply stores data in RAM and once your server is powered down, all data is gone. The upside? Rapid data access. In MySQL or MariaDB, we can create a table that holds all data in memory by specifying the storage engine at the end of a SQL CREATE TABLE statement like so:
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CREATE TABLE demo (
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column_name datatype(length) [options]
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) ENGINE = MEMORY;
The Internals of the HEAP Data Structure and MEMORY in MySQL
At the core of the MEMORY (HEAP data structure) storage engine in MySQL is a hash table the purpose of which is to provide the same time complexity for inserts, selects, updates, and deletes. In other words, all operations should take pretty much the same amount of time if we are running the MEMORY storage engine.
As for the data storage, the MEMORY storage engine stores data entirely in memory (in RAM) and allocates data dynamically for each table and data structures that are necessary. According to MySQL, the maximum size of HEAP/MEMORY tables is limited by the max_heap_table_size variable which, by default, has a value of 16MB.
In regards to the storage, the MEMORY storage engine maintains row pointers to facilitate quick access to data since when such a table is created, MySQL/MariaDB allocates a hash table for the data of the table in question. The engine uses table-level locking and does not provide any support for indexes or partitioning since it stores data in memory to begin with.
You may not need the HEAP data structure in your daily work, but at the same time, it will likely come in handy if you’re dealing with products that necessitate rapid data access and you don’t have to worry about your server going down.
Regardless of what storage engine you find yourself using though, using database clients like DbVisualizer is never a bad choice. DbVisualizer comes with a free 21-day trial and comes with a variety of features useful for data analysts, developers, and DBAs alike. Add in the useful mix of formatting your SQL queries, and you have a nice companion on your hands regardless of what storage engine or data structures you find yourself using.
Summary
The HEAP data structure is a powerful concept linked to heap memory in database management systems like MySQL, MariaDB, Postgres, and others. With it, databases can store data in memory and provide it to users just like you with a blazing fast speed.
Regardless, for the memory storage engine to help you, your tables must run the storage engine in the first place. Also, keep in mind that the memory storage engine isn’t a quick fix to all of your problems either: using SQL and database clients like DbVisualizer is a good choice if you find yourself facing databases issues that you aren’t able to solve yourself. Grab a free trial of DbVisualizer today and we’ll see you in the next blog post.
FAQ
What is the HEAP Data Structure?
The HEAP data structure is like a pile of objects where the biggest or smallest item is always at the top. In the database world, HEAP can be used to refer to any storage engines that store data in memory.
When should I use storage engines like MEMORY?
Consider using storage engines running the heap data structure when you need to store data in memory, access it rapidly, and don’t have to worry about your server going down.
Where can I learn more about data structures and databases?
To learn more about data structures and databases, follow our blog over at TheTable, attend industry conferences and over events, and also consider reading books involving database management systems and explaining their concepts.
