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Optimizing MongoDB 3.2 and above: How to Limit RAM Memory Usage

Jasser Mark Arioste

Jasser Mark Arioste

Optimizing MongoDB 3.2 and above: How to Limit RAM Memory Usage

Managing memory usage is crucial for optimizing the performance of MongoDB. While MongoDB 3.2 is quite an old version (released in 2015), the general principles for limiting RAM memory usage remain relevant. Here's a guide on how to limit RAM memory usage for MongoDB 3.2.

Introduction #

MongoDB is a popular NoSQL database known for its flexibility and scalability. However, it's essential to manage its memory usage efficiently to ensure optimal performance. In this article, we'll explore techniques to limit RAM memory usage for MongoDB 3.2.

1. Configure WiredTiger Cache Size #

MongoDB 3.2 introduced the WiredTiger storage engine as the default engine. WiredTiger efficiently uses memory for caching data. To limit RAM usage, adjust the WiredTiger cache size by modifying the wiredTiger.engineConfig.cacheSizeGB parameter in the MongoDB configuration file.

The MongoDB configuration file is usually located in /etc folder. For example: /etc/mongod.conf.

# mongod.conf

# for documentation of all options, see:
#   http://docs.mongodb.org/manual/reference/configuration-options/

# Where and how to store data.
storage:
  dbPath: /var/lib/mongodb
  journal:
    enabled: true
  engine:
    wiredTiger:
      engineConfig:
         cacheSizeGB: 1
12345678910111213

This example sets the cache size to 1 GB. Adjust this value based on your available RAM and system requirements.

2. Adjust the System File Cache #

MongoDB relies on the operating system's file system cache for additional caching. You can control the amount of memory allocated to the file cache by tuning the vm.dirty_background_ratio and vm.dirty_ratio kernel parameters. Edit the /etc/sysctl.conf file to persist these changes across reboots.

vm.dirty_background_ratio = 5
vm.dirty_ratio = 10
1

These values represent the percentage of system memory before the kernel starts writing dirty pages to disk. Lower values allocate less memory to file caching.

3. Set WiredTiger Cache Pressure Threshold #

The wiredTiger.cache_pressure parameter determines how aggressively WiredTiger releases memory when under pressure. Adjust this setting in the MongoDB configuration file:

# mongod.conf

# for documentation of all options, see:
#   http://docs.mongodb.org/manual/reference/configuration-options/

# Where and how to store data.
storage:
  dbPath: /var/lib/mongodb
  journal:
    enabled: true
  engine:
    wiredTiger:
      cachePressure: 50
      engineConfig:
         cacheSizeGB: 1
1234567891011121314

This example sets the cache pressure threshold to 50. Experiment with different values to find the optimal balance between memory usage and performance.

4. Monitor and Analyze #

Regularly monitor MongoDB's performance using tools like MongoDB's built-in profiler or external monitoring tools. Keep an eye on metrics such as cache utilization, page faults, and query performance. Adjust your configuration based on the observed behavior and workload.

5. Consider Shard Key Design #

If your MongoDB deployment includes sharding, carefully choose the shard key. An inappropriate shard key can lead to increased memory usage. Choose a shard key that distributes the data evenly across shards, avoiding hotspots.

Conclusion #

Effectively managing RAM memory usage is crucial for maintaining MongoDB's performance. By tuning WiredTiger cache settings, adjusting system file cache parameters, and monitoring the system, you can optimize MongoDB 3.2 for your specific environment. Regularly analyze your deployment to ensure it continues to meet performance expectations as your data and workload evolve

Credits: Image by Hoàng Phùng from Pixabay

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