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https://github.com/nish1013/query-optimization

query optimization in databases
https://github.com/nish1013/query-optimization

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query optimization in databases

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README 

        
# query-optimization

query optimization in databases



## Examples of optimized MongoDB queries using TypeScript for each case:



1. Choose the Right Data Model:



```typescript

import { MongoClient, Db } from "mongodb";



async function connectToDatabase(): Promise {

  const uri = "mongodb://localhost:27017";

  const dbName = "mydb";



  const client = await MongoClient.connect(uri, { useUnifiedTopology: true });

  const db = client.db(dbName);



  console.log("Connected to MongoDB");

  return db;

}

```

- Design your data model to fit your application's specific use cases and query patterns.

- Avoid embedding large amounts of data in a single document, as it can impact query performance.



2. Use Indexes:



```typescript

import { Db, Collection } from "mongodb";



async function createIndexes(collection: Collection): Promise {

  await collection.createIndex({ name: 1 }); // Index on the 'name' field

  await collection.createIndex({ age: 1 }); // Index on the 'age' field

}

```

  - Identify the most frequently used fields in your queries and create indexes on those fields.

  - Compound indexes can be beneficial for queries that involve multiple fields.

  - Use sparse indexes for fields that have a high number of missing values.

3. Explain and Analyze Queries:



```typescript

import { Db, Collection } from "mongodb";



async function explainQuery(collection: Collection): Promise {

  const query = { name: "John" };

  const explainResult = await collection.find(query).explain("executionStats");

  console.log(explainResult);

}

```

 - Use the `explain()` method to analyze how queries are executed and identify potential performance bottlenecks.

 - Review the query execution plan to ensure that indexes are being used efficiently.



4. Limit the Data Returned:



```typescript

import { Db, Collection } from "mongodb";



async function getSpecificFields(collection: Collection): Promise {

  const query = { age: { $gt: 20 } };

  const projection = { name: 1, age: 1 }; // Include only 'name' and 'age' fields

  const result = await collection.find(query).project(projection).toArray();

  console.log(result);

}

```

- Use the `projection` parameter in queries to retrieve only the necessary fields, reducing data transfer and improving performance.



5. Use Covered Queries:



```typescript

import { Db, Collection } from "mongodb";



async function coveredQuery(collection: Collection): Promise {

  const query = { name: "John" };

  const projection = { _id: 0, name: 1 }; // Only include 'name' field (excluding '_id')

  const result = await collection.find(query).project(projection).toArray();

  console.log(result);

}

```

 - Covered queries are queries where the index contains all the fields needed, and MongoDB can fulfill the query from the index without examining the actual documents.

- Covered queries can significantly reduce query execution time.



6. Utilize Aggregation Pipeline:



```typescript

import { Db, Collection } from "mongodb";



async function aggregationPipeline(collection: Collection): Promise {

  const pipeline = [

    { $match: { age: { $gt: 25 } } }, // Filter documents with age greater than 25

    { $group: { _id: "$name", count: { $sum: 1 } } }, // Group by 'name' and count occurrences

  ];

  const result = await collection.aggregate(pipeline).toArray();

  console.log(result);

}

```

 - For complex data manipulation and analysis, use the aggregation pipeline, which can perform multiple stages of data processing in a single query.



7. Use `sort()` and `limit()` Efficiently:



```typescript

import { Db, Collection } from "mongodb";



async function sortedLimitedQuery(collection: Collection): Promise {

  const query = { age: { $gt: 20 } };

  const sortCriteria = { age: 1 }; // Sort by 'age' in ascending order

  const limitValue = 10; // Limit to 10 results

  const result = await collection.find(query).sort(sortCriteria).limit(limitValue).toArray();

  console.log(result);

}

```

- When sorting large result sets, use indexes that support the sorting order to avoid in-memory sorting.



8. Regularly Monitor and Analyze Performance:



```typescript

// Monitor performance metrics using MongoDB's built-in monitoring tools or third-party monitoring solutions.

// Analyze slow query logs and take necessary actions to optimize queries.

```



9. Index Maintenance:



```typescript

// Regularly check for index fragmentation and perform index rebuilding or reorganization as needed.

```



10. Test Queries with Real Data:



```typescript

// Use a realistic dataset to test queries and analyze their performance under real-world conditions.

```



Please note that these examples demonstrate the concept of optimized MongoDB queries using TypeScript. The actual implementation and data model will depend on the specific requirements and use cases of your application.



# References

1. [Query Optimization](https://www.mongodb.com/docs/manual/core/query-optimization/#:~:text=A%20covered%20query%20is%20a,are%20in%20the%20same%20index.)