Optimizing MongoDB Configuration for 100GB Database and High Query Load on 4 vCPU, 8GB RAM, 1TB SSD Server

Ensuring fast data retrieval and seamless user experiences is crucial for databases of all sizes, especially when dealing with high query loads. In this guide, we’ll provide detailed instructions on configuring MongoDB, its cache, and sort settings to optimize performance for a 100GB database handling 10,000 concurrent queries on a server with 4 vCPUs, 8GB RAM, and a 1TB SSD.

1. MongoDB Configuration:

WiredTiger Storage Engine:

• wiredTigerCacheSizeGB: Set to 2GB – 4GB to allocate sufficient memory for the WiredTiger cache, which stores frequently accessed data.
• wiredTigerCollectionCacheSizeGB: Set to 1GB – 2GB to allocate memory for the collection cache, which stores frequently accessed collections.

Background Operations:

• backgroundIndexBuild: Set to false to disable background index builds, reducing CPU usage during high query load.
• backgroundCompaction: Set to false to disable background compactions, reducing I/O usage during high query load.

Journaling:

• journalCommitInterval: Set to 500 or 1000 milliseconds to reduce the frequency of journal commits, improving write performance.
• journalSync: Set to false to disable synchronous journaling, further enhancing write performance but increasing the risk of data loss in case of a crash.

Query Caching:

• queryCacheSize: Set to 1GB – 2GB to allocate memory for the query cache, which stores frequently executed queries for faster retrieval.

2. Sort Settings:

• sort.memoryLimit: Set to 1GB – 2GB to provide adequate memory for sorting operations.
• sort.useSorted: Set to true to enable sorted memory maps for efficient sorting.

3. mongod.conf Configuration File Content:

# WiredTiger Storage Engine
wiredTigerCacheSizeGB: 4
wiredTigerCollectionCacheSizeGB: 2

# Background Operations
backgroundIndexBuild: false
backgroundCompaction: false

# Journaling
journalCommitInterval: 500
journalSync: false

# Query Caching
queryCacheSize: 2

# Sort Settings
sort.memoryLimit: 2
sort.useSorted: true

4. Considerations:

• Fine-tune the configuration values based on specific workload characteristics and performance requirements.
• Monitor and adjust settings as needed to maintain optimal performance under varying query loads.
• Utilize performance analysis tools like MongoDB Cloud Manager or dbstats to identify and address performance bottlenecks.