# MongoDB # Tuning
MongoDB tuning involves a holistic approach, focusing on **[data modeling](https://www.google.com/search?q=data+modeling&sca_esv=8c1d8b7610d1bcd4&sxsrf=AE3TifOPNGjqgVwR6RtChD-KV8HcaTieLg%3A1765473263891&ei=7_s6aa-QNoqf4-EP7M6ysQY&ved=2ahUKEwj6hoq-hLaRAxV0UGwGHT4HCRsQgK4QegQIARAB&uact=5&oq=mongodb+tuning&gs_lp=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&sclient=gws-wiz-serp&mstk=AUtExfC1bhK_cC3VtrCkupOFWLiaS2u3hqzK1fNG2bk18lYvZhbhAsQ5pUL4y7021iti12YyfLd0oXrrEce642Vd5c57__YTHVy6SSgDFdd_v8C1IY9ultYeDiVo8KmUL0yKGezXndw2ajTrALOg_oZQjfwNbhBGrjVCXcJE380Vd2n1-EWqa_bVKzG_K9oCY-OeNQanuNCID5OM39Mi44xjgoVbJiCa7y_qnwgJT6SlpXQGWhKIIYV9A6Q014ywxurCHdLW4iG4Wy0dy2v7FrvM-Lc8zb1Yxl1fE7jgvXFoATeU-cOBzgl1SOLTPdqpp5eZmo9Nu9MGOQOOjv-H57FPmnod2qNNwKKEGysIYqmSnYbhZjrMJsP7XR9ro6S_2F4iwYgor7rC7V5-DMXl2soWqg&csui=3)** (embedding vs. referencing), **[indexing](https://www.google.com/search?q=indexing&sca_esv=8c1d8b7610d1bcd4&sxsrf=AE3TifOPNGjqgVwR6RtChD-KV8HcaTieLg%3A1765473263891&ei=7_s6aa-QNoqf4-EP7M6ysQY&ved=2ahUKEwj6hoq-hLaRAxV0UGwGHT4HCRsQgK4QegQIARAC&uact=5&oq=mongodb+tuning&gs_lp=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&sclient=gws-wiz-serp&mstk=AUtExfC1bhK_cC3VtrCkupOFWLiaS2u3hqzK1fNG2bk18lYvZhbhAsQ5pUL4y7021iti12YyfLd0oXrrEce642Vd5c57__YTHVy6SSgDFdd_v8C1IY9ultYeDiVo8KmUL0yKGezXndw2ajTrALOg_oZQjfwNbhBGrjVCXcJE380Vd2n1-EWqa_bVKzG_K9oCY-OeNQanuNCID5OM39Mi44xjgoVbJiCa7y_qnwgJT6SlpXQGWhKIIYV9A6Q014ywxurCHdLW4iG4Wy0dy2v7FrvM-Lc8zb1Yxl1fE7jgvXFoATeU-cOBzgl1SOLTPdqpp5eZmo9Nu9MGOQOOjv-H57FPmnod2qNNwKKEGysIYqmSnYbhZjrMJsP7XR9ro6S_2F4iwYgor7rC7V5-DMXl2soWqg&csui=3)** (creating efficient indexes for queries), **[query optimization](https://www.google.com/search?q=query+optimization&sca_esv=8c1d8b7610d1bcd4&sxsrf=AE3TifOPNGjqgVwR6RtChD-KV8HcaTieLg%3A1765473263891&ei=7_s6aa-QNoqf4-EP7M6ysQY&ved=2ahUKEwj6hoq-hLaRAxV0UGwGHT4HCRsQgK4QegQIARAD&uact=5&oq=mongodb+tuning&gs_lp=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&sclient=gws-wiz-serp&mstk=AUtExfC1bhK_cC3VtrCkupOFWLiaS2u3hqzK1fNG2bk18lYvZhbhAsQ5pUL4y7021iti12YyfLd0oXrrEce642Vd5c57__YTHVy6SSgDFdd_v8C1IY9ultYeDiVo8KmUL0yKGezXndw2ajTrALOg_oZQjfwNbhBGrjVCXcJE380Vd2n1-EWqa_bVKzG_K9oCY-OeNQanuNCID5OM39Mi44xjgoVbJiCa7y_qnwgJT6SlpXQGWhKIIYV9A6Q014ywxurCHdLW4iG4Wy0dy2v7FrvM-Lc8zb1Yxl1fE7jgvXFoATeU-cOBzgl1SOLTPdqpp5eZmo9Nu9MGOQOOjv-H57FPmnod2qNNwKKEGysIYqmSnYbhZjrMJsP7XR9ro6S_2F4iwYgor7rC7V5-DMXl2soWqg&csui=3)** (using `explain()` for slow queries, projection), **[server configuration](https://www.google.com/search?q=server+configuration&sca_esv=8c1d8b7610d1bcd4&sxsrf=AE3TifOPNGjqgVwR6RtChD-KV8HcaTieLg%3A1765473263891&ei=7_s6aa-QNoqf4-EP7M6ysQY&ved=2ahUKEwj6hoq-hLaRAxV0UGwGHT4HCRsQgK4QegQIARAE&uact=5&oq=mongodb+tuning&gs_lp=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&sclient=gws-wiz-serp&mstk=AUtExfC1bhK_cC3VtrCkupOFWLiaS2u3hqzK1fNG2bk18lYvZhbhAsQ5pUL4y7021iti12YyfLd0oXrrEce642Vd5c57__YTHVy6SSgDFdd_v8C1IY9ultYeDiVo8KmUL0yKGezXndw2ajTrALOg_oZQjfwNbhBGrjVCXcJE380Vd2n1-EWqa_bVKzG_K9oCY-OeNQanuNCID5OM39Mi44xjgoVbJiCa7y_qnwgJT6SlpXQGWhKIIYV9A6Q014ywxurCHdLW4iG4Wy0dy2v7FrvM-Lc8zb1Yxl1fE7jgvXFoATeU-cOBzgl1SOLTPdqpp5eZmo9Nu9MGOQOOjv-H57FPmnod2qNNwKKEGysIYqmSnYbhZjrMJsP7XR9ro6S_2F4iwYgor7rC7V5-DMXl2soWqg&csui=3)** (memory, storage, concurrency settings like tickets, connection pooling), and **[monitoring](https://www.google.com/search?q=monitoring&sca_esv=8c1d8b7610d1bcd4&sxsrf=AE3TifOPNGjqgVwR6RtChD-KV8HcaTieLg%3A1765473263891&ei=7_s6aa-QNoqf4-EP7M6ysQY&ved=2ahUKEwj6hoq-hLaRAxV0UGwGHT4HCRsQgK4QegQIARAF&uact=5&oq=mongodb+tuning&gs_lp=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&sclient=gws-wiz-serp&mstk=AUtExfC1bhK_cC3VtrCkupOFWLiaS2u3hqzK1fNG2bk18lYvZhbhAsQ5pUL4y7021iti12YyfLd0oXrrEce642Vd5c57__YTHVy6SSgDFdd_v8C1IY9ultYeDiVo8KmUL0yKGezXndw2ajTrALOg_oZQjfwNbhBGrjVCXcJE380Vd2n1-EWqa_bVKzG_K9oCY-OeNQanuNCID5OM39Mi44xjgoVbJiCa7y_qnwgJT6SlpXQGWhKIIYV9A6Q014ywxurCHdLW4iG4Wy0dy2v7FrvM-Lc8zb1Yxl1fE7jgvXFoATeU-cOBzgl1SOLTPdqpp5eZmo9Nu9MGOQOOjv-H57FPmnod2qNNwKKEGysIYqmSnYbhZjrMJsP7XR9ro6S_2F4iwYgor7rC7V5-DMXl2soWqg&csui=3)** (profiler, Atlas tools) to ensure optimal performance, scalability, and resource usage for your specific application needs.
This video provides an overview of the MongoDB architecture for query performance:
![Related video thumbnail](https://articles.ravapps.com/uploads/images/gallery/2025-12/gPtT9sQ0bb9n9n53-embedded-image-o6jwigho.jpeg)
06:26
[
MongoDB
YouTube • 9 Jul 2025
](https://www.youtube.com/watch?v=s1_55jY0Amw)
Key Areas for Tuning
1. **Data Modeling & Indexing:** - **Embed vs. Reference:** Model data for common access patterns, embedding related data for fewer reads, but referencing when data is shared or grows large (minimizing document size). - **Index Strategically:** Create indexes on fields used in `find()`, `sort()`, and `aggregate()` stages. Use compound indexes for multi-field queries. - **Avoid Collection Scans:** Use `explain()` to ensure queries use index scans, not full collection scans.
This video explains the importance of indexes for performance:
![Related video thumbnail](https://articles.ravapps.com/uploads/images/gallery/2025-12/6ZVbyQLduetlZbm5-embedded-image-wsnjijal.jpeg)
58s
[
solarwindsinc
YouTube • 12 Oct 2021
](https://www.youtube.com/watch?v=eWBjIHfMWWc&t=1797)
2. **Query & Aggregation Optimization:** - **Use the Profiler:** Enable the database profiler to find slow queries exceeding a threshold. - **`explain()` Plan:** Analyze `explain()` output to see if indexes are used, how many documents are examined, and identify bottlenecks. - **Projection:** Use `projection` to return only needed fields, reducing network traffic and memory. - **Aggregation Pipelines:** Optimize stages, push filters down, and use appropriate operators for complex data processing.
This video demonstrates how to use the profiler and analyze query plans:
![Related video thumbnail](https://articles.ravapps.com/uploads/images/gallery/2025-12/BsedwK0vTjJm15OO-embedded-image-piu09esc.jpeg)
1m
[
CodeLucky
YouTube • 30 Aug 2025
](https://www.youtube.com/watch?v=h0vWdePFTFc&t=337)
3. **Server & Storage Engine Tuning:** - **WiredTiger Tickets:** Adjust `wiredTigerTicketValues` for read/write concurrency if operations queue up (tickets hit 0). - **Memory:** Configure `storage.wiredTiger.engineConfig.cacheSizeGB` for optimal WiredTiger cache size. - **Compression:** Enable compression (e.g., Snappy, zlib) to reduce I/O and storage, often improving performance.
This video discusses memory settings and their impact on performance:
![Related video thumbnail](https://articles.ravapps.com/uploads/images/gallery/2025-12/DlckaE0ATJQLJJHD-embedded-image-phlxxzrd.jpeg)
47s
[
Percona
YouTube • 19 Jan 2021
](https://www.youtube.com/watch?v=LEUtqqG6qhc&t=138)
4. **Connection Management:** - **Connection Pooling:** Tune `minPoolSize`, `maxPoolSize`, and `socketTimeoutMS` in your drivers to match application load and network conditions.
This video explores patterns for tuning MongoDB performance and scalability:
![Related video thumbnail](https://articles.ravapps.com/uploads/images/gallery/2025-12/fhfXubGFMDtm8dze-embedded-image-c25qy8xe.jpeg)
1m
[
MongoDB
YouTube • 21 Nov 2022
](https://www.youtube.com/watch?v=xpHjnFXICh8&t=700)
5. **Hardware & OS (Advanced):** - **NUMA Settings:** Configure BIOS/OS settings (like `iommu=pt`) for optimal CPU/memory interaction on NUMA systems.
General Approach
- **Monitor:** Use MongoDB Atlas metrics or tools like `mongostat`, `mongotop`, and the profiler. - **Methodical Changes:** Apply changes one at a time and measure the impact. - **Balance:** Indexing speeds up reads but slows writes; find the right balance for your workload. # Laboriosam pariatur sed sequi aut est adipisci et quos. Doloribus perspiciatis nesciunt ipsam assumenda delectus sit. Qui id soluta libero voluptates corporis placeat. Nam veritatis aut aut debitis. Consectetur et optio ullam reprehenderit accusantium sunt. Rerum illo saepe dolor et quia minus consequatur. Dolores hic autem delectus aspernatur sequi qui.Eius voluptas beatae voluptas ut doloremque cumque rerum. Ab asperiores dicta necessitatibus aut voluptatem.Vel commodi quo est beatae. Cumque adipisci quos vitae officiis.Omnis deleniti illo quae ut aut nemo earum. Sit qui sapiente velit qui molestiae. Distinctio enim tempora temporibus incidunt corporis. # Nesciunt laudantium sint ut iusto nisi distinctio. Molestias minus doloremque voluptatum id saepe dolor. Sed sint officia ut. Recusandae distinctio voluptas ut natus cum eligendi et. Placeat magni velit veniam ex labore. Ab reprehenderit voluptatem ipsam temporibus esse. Et dolor et maxime aut voluptas consectetur expedita. Sapiente pariatur hic tempora. Hic aut assumenda quis velit accusantium dolore perferendis.Dolorum nesciunt ut sint in rerum nisi. Qui quas officiis dolore incidunt nisi facere. Enim libero explicabo optio libero ut voluptatem quos sit. Doloribus cupiditate dignissimos et molestias.Ea aut enim expedita eos voluptatum perferendis et. Sequi natus sed qui exercitationem iusto quia. Sunt quos qui voluptatem corrupti. Et soluta molestiae eum assumenda enim impedit iste inventore.Modi ipsam aut aut maiores. Sint eaque sit non sunt autem neque dicta. # MongoDB: average value of field
To calculate the average value of a field in MongoDB using the shell, the aggregation framework with the `$avg` operator is utilized.
Example 1: Calculating the average of a field across the entire collection
Assume a collection named `products` with documents like:
Code
``` { "_id": 1, "item": "A", "price": 10 } { "_id": 2, "item": "B", "price": 15 } { "_id": 3, "item": "C", "price": 20 } { "_id": 4, "item": "D", "price": 12 } ```
To find the average `price` of all products:
JavaScript
``` db.products.aggregate([ { $group: { _id: null, // Group all documents into a single group averagePrice: { $avg: "$price" } // Calculate the average of the 'price' field } } ]) ```
This query would return a result similar to:
Code
``` { "_id": null, "averagePrice": 14.25 } ```
Example 2: Calculating the average of a field grouped by another field
To find the average `price` grouped by `item`:
JavaScript
``` db.products.aggregate([ { $group: { _id: "$item", // Group documents by the 'item' field averagePrice: { $avg: "$price" } // Calculate the average of 'price' for each group } } ]) ```
If the `products` collection contains:
Code
``` { "_id": 1, "item": "A", "price": 10 } { "_id": 2, "item": "B", "price": 15 } { "_id": 3, "item": "A", "price": 20 } { "_id": 4, "item": "B", "price": 12 } ```
This query would return a result similar to:
Code
``` [ { "_id": "B", "averagePrice": 13.5 }, { "_id": "A", "averagePrice": 15 } ] ```
# MongoDB : sorting documents by multiple fields
To sort documents by multiple fields in the MongoDB shell, use the `sort()` method after your `find()` query. The `sort()` method accepts a document where keys are the field names and values are either `1` for ascending order or `-1` for descending order. The order of fields within the `sort()` document determines the sorting priority.
Here's an example:
Assume a collection named `students` with documents like:
Code
``` { "name": "Alice", "grade": "A", "age": 18 } { "name": "Bob", "grade": "B", "age": 19 } { "name": "Charlie", "grade": "A", "age": 17 } { "name": "David", "grade": "B", "age": 18 } ```
To sort these documents first by `grade` in ascending order, and then by `age` in descending order for students with the same grade:
JavaScript
``` db.students.find().sort({ grade: 1, age: -1 }); ```
Explanation:
- `db.students.find()`: This retrieves all documents from the `students` collection. - `.sort({ grade: 1, age: -1 })`: This applies the sorting criteria. - `grade: 1`: Documents are primarily sorted by the `grade` field in ascending order (e.g., "A" before "B"). - `age: -1`: For documents that have the same `grade`, they are then sorted by the `age` field in descending order (e.g., 19 before 18).
Example Output (based on the sample data):
Code
``` { "name": "Charlie", "grade": "A", "age": 17 } { "name": "Alice", "grade": "A", "age": 18 } { "name": "Bob", "grade": "B", "age": 19 } { "name": "David", "grade": "B", "age": 18 } ``` # MongoDB: shell commands examples
Here are examples of common operations within the MongoDB Shell (mongosh):
1. Database Management:
show databases.
JavaScript
``` show dbs ```
- **Switch to a database (or create if it doesn't exist):**
JavaScript
``` use myDatabase ```
Show current database.
JavaScript
``` db ```
2. Collection Management:
Show collections in the current database.
JavaScript
``` show collections ```
Create a new collection.
JavaScript
``` db.createCollection("myCollection") ```
3. Data Manipulation (CRUD Operations):
Insert a single document.
JavaScript
``` db.myCollection.insertOne({ name: "Alice", age: 30, city: "New York" }) ```
Insert multiple documents.
JavaScript
``` db.myCollection.insertMany([ { name: "Bob", age: 25, city: "London" }, { name: "Charlie", age: 35, city: "Paris" } ]) ```
Find all documents in a collection.
JavaScript
``` db.myCollection.find() ```
Find documents with specific criteria.
JavaScript
``` db.myCollection.find({ age: { $gt: 28 } }) // Find documents where age is greater than 28 ```
Find documents and project specific fields.
JavaScript
``` db.myCollection.find({}, { name: 1, city: 1, _id: 0 }) // Include name and city, exclude _id ```
Update a single document.
JavaScript
``` db.myCollection.updateOne({ name: "Alice" }, { $set: { age: 31 } }) ```
Update multiple documents.
JavaScript
``` db.myCollection.updateMany({ city: "London" }, { $set: { status: "active" } }) ```
Delete a single document.
JavaScript
``` db.myCollection.deleteOne({ name: "Bob" }) ```
Delete multiple documents.
JavaScript
``` db.myCollection.deleteMany({ status: "inactive" }) ```
4. Utility Commands:
Clear the shell screen.
JavaScript
``` cls ```
exit the shell.
JavaScript
``` exit ``` # MongoDB: find documents matching regular expression
To find documents matching a regular expression in the MongoDB shell, use the `find()` method with the `$regex` operator or a regex literal.
Using a Regex Literal:
JavaScript
``` db.collectionName.find({ fieldName: /pattern/options }); ```
Example: Find documents in the `users` collection where the `name` field contains "john" (case-insensitive).
JavaScript
``` db.users.find({ name: /john/i }); ```
Using the `$regex` Operator:
JavaScript
``` db.collectionName.find({ fieldName: { $regex: "pattern", $options: "options" } }); ```
Example: Find documents in the `products` collection where the `description` field contains "eco-friendly" (case-insensitive).
JavaScript
``` db.products.find({ description: { $regex: "eco-friendly", $options: "i" } }); ```
Explanation:
- `collectionName`: The name of the collection to query. - `fieldName`: The field within the documents to apply the regular expression to. - `pattern`: The regular expression pattern to match. - `options`: Optional flags to modify the regex behavior. Common options include: - `i`: Case-insensitive matching. - `m`: Multi-line matching. - `s`: Allows the dot (`.`) to match newline characters. - `x`: Ignores whitespace characters in the pattern unless escaped.