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MongoDBDatabaseAggregationNoSQL

MongoDB Aggregation Pipeline Guide

Master MongoDB aggregation. From basic stages to complex pipelines to performance optimization.

B
Bootspring Team
Engineering
September 17, 2021
7 min read

MongoDB's aggregation pipeline processes documents through stages. Here's how to use it effectively.

Basic Stages#

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Grouping and Accumulation#

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Lookups (Joins)#

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Array Operations#

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Date Operations#

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Conditional Logic#

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Output Stages#

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Performance#

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Best Practices#

Pipeline Order: ✓ $match early to filter ✓ $project early to reduce size ✓ $sort after $match for index use ✓ $limit after $sort Performance: ✓ Create indexes for $match fields ✓ Use $project to limit fields ✓ Avoid $unwind when possible ✓ Use allowDiskUse for large data Design: ✓ Break complex pipelines into steps ✓ Test each stage independently ✓ Use explain() to analyze ✓ Consider $merge for materialized views

Conclusion#

MongoDB's aggregation pipeline is powerful for data transformation and analysis. Structure pipelines with filtering first, use indexes effectively, and break complex operations into readable stages. For production, always analyze with explain() and consider creating materialized views for frequently-run aggregations.

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