# HDR percentile aggregation memory footprint

**URL:** <https://discuss.elastic.co/t/hdr-percentile-aggregation-memory-footprint/375297>\
**Category:** Elasticsearch\
**Tags:** aggregations\
**Created:** [March 3, 2025, 7:23am UTC](https://discuss.elastic.co/t/hdr-percentile-aggregation-memory-footprint/375297 "2025-03-03T07:23:33Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![mike123](https://avatars.discourse-cdn.com/v4/letter/m/ecc23a/32.png) [@mike123](https://discuss.elastic.co/u/mike123)\
**Post date:** [March 3, 2025, 7:23am UTC](https://discuss.elastic.co/t/hdr-percentile-aggregation-memory-footprint/375297/1 "2025-03-03T07:23:33Z")

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Hi,

I was facing huge latency in t-digest percentile aggregations, So tried out HDR percentile aggregation. it was fast but in the documentation it is mentioned that " **HDR Percentile aggregation has a larger memory footprint**". As said i went through some online sources on how HDR algorithm works and found that it takes more memory due to pre allocation of fixed size buckets, But i couldn't find any resources related to its performance in elasticsearch. So I have few questions about its performance. Hope someone could help me with it.

### **How much memory is consumed by the coordinating node vs. the data nodes that contain shards while executing HDR percentile aggregations?**

- Do data nodes hold **histogram structures in memory** while processing aggregations, or is the memory usage primarily on the coordinating node?
- How can we monitor and measure memory consumption separately for **coordinating** and **data nodes** in real-time while running percentile queries?

### **What are the some conventions that could be followed to reduce memory overhead when running HDR percentile aggregations at scale?**

- How does `number_of_significant_value_digits` affect memory usage, and what’s the recommended value for large datasets?
- Does increasing shard count help in reducing memory load on individual data nodes?