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Aggregation Concepts

MongoDB provides the three approaches to aggregation, each with its own strengths and purposes for a given situation. This section describes these approaches and also describes behaviors and limitations specific to each approach. See also the chart that compares the approaches.

Aggregation Pipeline

The aggregation pipeline is a framework for performing aggregation tasks, modeled on the concept of data processing pipelines. Using this framework, MongoDB passes the documents of a single collection through a pipeline. The pipeline transforms the documents into aggregated results, and is accessed through the aggregate database command.

Map-Reduce

Map-reduce is a generic multi-phase data aggregation modality for processing quantities of data. MongoDB provides map-reduce with the mapReduce database command.

Single Purpose Aggregation Operations

MongoDB provides a collection of specific data aggregation operations to support a number of common data aggregation functions. These operations include returning counts of documents, distinct values of a field, and simple grouping operations.

Aggregation Mechanics

Details internal optimization operations, limits, support for sharded collections, and concurrency concerns.

• Aggregation Pipeline
• Map-Reduce
• Single Purpose Aggregation Operations
• Aggregation Mechanics
  • Aggregation Pipeline Optimization
  • Aggregation Pipeline Limits
  • Aggregation Pipeline and Sharded Collections
  • Map-Reduce and Sharded Collections
  • Map Reduce Concurrency

←   Aggregation Introduction Aggregation Pipeline  →

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