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Practical MongoDB Aggregations

You're reading from  Practical MongoDB Aggregations

Product type Book
Published in Mar 2024
Publisher Packt
ISBN-13 9781835884362
Pages 278 pages
Edition 1st Edition
Languages
Author (1):
Paul Done Paul Done
Profile icon Paul Done

Table of Contents (20) Chapters

Preface 1. Chapter 1: MongoDB Aggregations Explained 2. Part 1: Guiding Tips and Principles
3. Chapter 2: Optimizing Pipelines for Productivity 4. Chapter 3: Optimizing Pipelines for Performance 5. Chapter 4: Harnessing the Power of Expressions 6. Chapter 5: Optimizing Pipelines for Sharded Clusters 7. Part 2: Aggregations by Example
8. Chapter 6: Foundational Examples: Filtering, Grouping, and Unwinding 9. Chapter 7: Joining Data Examples 10. Chapter 8: Fixing and Generating Data Examples 11. Chapter 9: Trend Analysis Examples 12. Chapter 10: Securing Data Examples 13. Chapter 11: Time-Series Examples 14. Chapter 12: Array Manipulation Examples 15. Chapter 13: Full-Text Search Examples 16. Afterword
17. Index 18. Other books you may enjoy Appendix

Performance tips for sharded aggregations

All the recommended aggregation optimization outlined in Chapter 3, Optimizing Pipelines for Performance, equally apply to a sharded cluster. In fact, in most cases, these same recommendations, repeated as follows, become even more important when executing aggregations on sharded clusters:

  • Sorting – use index sort: When the runtime has to split on a $sort stage, the shards part of the split pipeline running on each shard in parallel will avoid an expensive in-memory sort operation.
  • Sorting – use limit with sort: The runtime has to transfer fewer intermediate records over the network, from each shard performing the shards part of a split pipeline to the location that executes the pipeline's merger part.
  • Sorting – reduce records to sort: If you cannot adopt point 1 or 2, moving a $sort stage to as late as possible in a pipeline will typically benefit performance in a sharded cluster. Wherever the $sort...
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