Chapter_26

📘 Chapter 26 – Indexing, Aggregations, and Queries in MongoDB

In this chapter, we explore advanced database operations in MongoDB:

• Indexes → Make queries faster
• Queries → Filter data with conditions
• Aggregations → Process and transform data

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🔹 Indexing

An index is like an index in a book:
Instead of reading every page, MongoDB looks up the index to quickly find documents.

coll.create_index("name")

Now queries using name will be much faster.

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🔹 Queries

Queries allow filtering results.

# Find students with age > 20
coll.find({"age": {"$gt": 20}})

# Find students in Kolkata
coll.find({"city": "Kolkata"})

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🔹 Aggregations

Aggregation pipelines allow grouping, filtering, and calculating over data.

pipeline = [
    {"$group": {"_id": "$city", "total": {"$sum": 1}}},
    {"$sort": {"total": -1}}
]
coll.aggregate(pipeline)

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🔹 Visual Diagram

[Collection] ---> [Match/Filter] ---> [Group] ---> [Sort] ---> [Result]

Example:

Students ---> age > 20 ---> group by city ---> sort desc ---> Report

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🧠 Summary

• Indexes = Faster queries
• Queries = Fetch filtered data
• Aggregations = Data analysis inside MongoDB