[Thank Goodness It's Search] Building Faceted Navigation - Final part 5 OpenSearch Aggregation best practices

Welcome to Thank Goodness It's Search series—your Friday fix of OpenSearch learnings, feature drops, and real-world solutions. I will keep it short, sharp, and search-focused—so you can end your week with more search knowledge than you started with.

This is the final part to the 5-part series where we discussed aggregations in OpenSearch. We discussed nested field types, building faceted search navigation - top-down and bottom-up and options to improve search experience with multi-select filters. You'll find links to all previous posts at the bottom of this article.

When building aggregations in OpenSearch, it's crucial to follow certain best practices to maintain optimal search performance. Let's explore the top 5 practices that can help you build efficient aggregations! These guidelines are essential for avoiding performance bottlenecks and getting the most out of your search operations. Let's get started! 🚀

1. Use Doc Values Whenever Possible

   • Doc values are on-disk data structures built at index time that store field values in a column-oriented fashion
   • They are optimized for sorting, aggregations, and scripting
   • Enable doc_values during field mapping:

   "my_field": {
     "type": "keyword",
     "doc_values": true
   }

2. Leverage Ordinals for High-Cardinality Fields

   • Ordinals are numeric representations of string values
   • They significantly reduce memory usage when dealing with repeated string values
   • Enable global ordinals for frequently used keyword fields for aggregations:

   "my_field": {
     "type": "keyword",
     "eager_global_ordinals": true
   }

3. Configure Coordinator Node for Complex Aggregations

   • Aggregations are memory intensive
   • Configure general purpose coordinator nodes that are one size larger than the data nodes.
   • Helps prevent memory issues on data nodes

4. Limit Aggregation Results

   • Always set a reasonable size for terms aggregations
   • Use the size parameter to control number of buckets:

   "aggs": {
     "my_terms": {
       "terms": {
         "field": "my_field",
         "size": 100
       }
     }
   }
   

5. Use Filter Aggregations for Better Performance

   • Filter before aggregating to reduce the document set
   • Improves performance by processing fewer documents

   {
     "aggs": {
       "filtered_sales": {
         "filter": {
           "term": { "status": "completed" }
         },
         "aggs": {
           "total_revenue": {
             "sum": {
               "field": "amount"
             }
           }
         }
       }
     }
   }
   

Conclusion

In this 5-part series on aggregations in OpenSearch, we covered essential aspects of building faceted navigation:

👉 Understanding nested field types and their role in aggregations

👉 Implementing top-down faceted navigation approach

👉 Building bottom-up faceted navigation

👉 Improving search experience with multi-select filters

👉 Finally ending our 5-part series with Best practices for optimizing aggregation performance!

The best practices listed here will help you build efficient and performant faceted search experiences. By following these guidelines, you can avoid common pitfalls and ensure your aggregations scale well with your data.

OpenSearch also supports different types of aggregations such as:

• Metric aggregations (avg, sum, min, max, cardinality)
• Bucket aggregations (terms, range, date_range, histogram)
• Pipeline aggregations (avg_bucket, sum_bucket, moving_avg)
• Matrix aggregations (matrix_stats)
• Statistical aggregations (extended_stats, percentiles)
• Geo aggregations (geo_centroid, geo_bounds,geo_distance, geohash_grid)
• Composite aggregations are multi-bucket aggregations, for paginating through all buckets

Call for Action

Have you implemented faceted navigation using OpenSearch? Have you tried other aggregation types? Share your experiences and challenges in the comments below! If you found this series helpful, don't forget to:

• 🔔 Follow for more OpenSearch tips every Friday
• 👍 Share this post with your network
• 💡 Try implementing these best practices in your search applications
• ❓ Comment, ask questions if you need help with your implementation

Want to suggest topics for future Thank Goodness It's Search posts? Drop your ideas in the comments!

See you next Friday with another search solution in the Thank Goodness It's Search series! Until then, happy searching! 🔍