How to Perform MongoDB Performance Tuning

Any database can be affected in one way or another causing slow response and performance. Factors which can cause this problem are attributed but not limited to query structure, application design, index use and data models. Other database performance determiners include system configuration and structural design. Therefore, it becomes necessary to optimize application performance using various methods. One of the most preferred is the MongoDB performance tuning option.

How to analyze and optimize the MongoDB performance

Developing and operating applications requires analysis of the database performance. In case there is a degraded performance, it is often caused by open database connections, access strategies and hardware availability. Troubleshooting any of these will fix the problem.

It is also common for users to experience limited performance due to inappropriate indexing or results of poor design patterns with the schema. All this factors have an impact on MongoDB inter-locking.

In some instances, the issue may be due to database capacity operating process. At this stage, the user has to add extra capacity to the database. To optimize this feature, it is necessary to fit the working set in the complete physical storage.

It is worth noting that some of the database problems may be related to traffic overload. This should be considered as temporally and scaling should solve high and excessive traffic.

With the availability of MMAPv1 storage, MongoDB utilizes the memory-mapped files to carryout all the storage functions. Allocating sufficient and specific data set, mongod process will use all the available memory to optimize its use. This deliberate process improves performance but the mapped files prevent further determination of data set for sufficient RAM. Inspecting mem.mapped will determine the amount of mapped memory in use by mongod. If the results shows greater value than system memory, page faults will be required to perform some operations and read data disk.

There are currently a number of other complex procedures used for MongoDB performance tuning. The choice is determined by level of technical skills and the type of performance optimization expected from the errors. Much emphasis while inspecting the database should be put on:

  • Page Faults
  • Number of Server Connections and
  • Database Profiling

For advanced users, the above procedure may not be enough and additional procedures may be necessary. The following suggestions may be of help:

A. Evaluation of current operations performance

This will include database profiling to evaluate mongodg operations.

B. Query optimization performance.

This mainly involves creating indexes for commonly used queries. For multiple data query, consider having a compound index. This is because indexes are much smaller compared to documents. It becomes faster to scan indexed data than a collection.