MongoDB Performance: Locking Performance, Page Faults, and Database Profiling.
When you are developing a large application there are a lot of transactions that happen within the database.
Before deploying an application for an end user we have to analyze the performance of the database to ensure the speed and concurrency.
When the database is getting populated, we have to face low performance due to high dependent queries. The low performance also depends on the structure of the database, the hardware availability and the number of concurrent connection with the current instance of the database.
As many users start connecting with the database, every new connection gets into the row like a job pool. Every DB instance has a limit of concurrent connections and if it is exceeding, some users have to suffer and that indeed will decrease the efficiency of the application.
MongoDB has an edge by providing the locking system to accommodate the consistency in query execution.
If multiple users are connected with the current instance of the database and executing bulk queries, then it will automatically understand which queries are becoming a cause of locking and it will prevent that query to be executed.
If we start executing long curious then it will consume more Ram and provide less efficiency to multiple users maybe it became a cause of a deadlock due to its high consumable queries execution.
This error is common in a large application. Whenever MongoDB is trying to read and write some information from the physical memory but if there is no physical address available then this error will occur.
It is the same as you are fetching a record from that collection which is not yet created.
There are two main reasons for having this error. The most common and the first reason is memory consumption. When processing large queries, all the memory get consumed and then your request will have to face a page fault error.
The second reason is changing in physical addresses. In simple words, you are calling a table which is getting renamed by another user.
MongoDB provides a database profiler feature, by which we can log the record of each execution of a query. In the large application, at times when reported during the execution of a query, the developers are unable to identify the exact query.
If they have enabled the database profiler, then they can record each execution of the query and easily trace where the exact error occurs.
We can activate database profiler for individuals and all the instances of MongoDB. Remember that whenever you are enabling database profiler for any instance of MongoDB, it will not affect the replicated and shared clustered instance.
The following levels of profiling are available:
- Level 0 – The profiler is off and gathers no data. This is the default level of the profile.
- Level 1 – The profiler collects data for operations which exceed the slown value.
- Level 2 – For all the operations, the profiler collects data.
When you develop an application based on MongoDB and start performing operations with data, it may affect the performance of MongoDB from different perspectives.
Either your queries are taking a lot of memory or your physical memory is getting low due to the high volume of data processing. There are many other factors which can affect the MongoDB performance and we will discuss those in our upcoming tutorials.
We have discussed the most common performance factors in this tutorial. Our upcoming tutorial will explain you the ways to manage MongoDB database profiler.