# Why are Range Queries on Nested Docs Slow?

**URL:** <https://discuss.elastic.co/t/why-are-range-queries-on-nested-docs-slow/271825>\
**Category:** Elasticsearch\
**Created:** [April 30, 2021, 6:43pm UTC](https://discuss.elastic.co/t/why-are-range-queries-on-nested-docs-slow/271825 "2021-04-30T18:43:50Z")\
**Posts on this page:** 2\
**Page:** 1

<div class="post-metadata">

**Author:** ![mserrato](https://sea2.discourse-cdn.com/elastic/user_avatar/discuss.elastic.co/mserrato/32/88036_2.png) [@mserrato](https://discuss.elastic.co/u/mserrato)\
**Post date:** [April 30, 2021, 6:43pm UTC](https://discuss.elastic.co/t/why-are-range-queries-on-nested-docs-slow/271825/1 "2021-04-30T18:43:50Z")

</div>

Hello,

I was wondering if I could get some insight and possibly some explanation on some search performance I've noticed when using range queries with nested and non-nested documents.

I've been performing some benchmarking against ES 7.10 on a 3 data node cluster. I ran two types of queries on a 3 shard index that has 5 million documents each having 400 nested documents. The nested documents have a doc\_id property, each document will contain the same set of nested document ids but with different values for `nested_name`. (So every document will have a nested doc with `doc_id`: 2, for instance, with a different value for `nested_name`)

My field mappings look something like this

> **Mappings**
>
> ```auto
> {
> "mappings": {
> "properties": {
> "id": {
> "type": "keyword"
> },
> "name": {
> "type": "keyword"
> },
> "some_nested_doc": {
> "type": "nested",
> "properties": {
> "id": {
> "type": "keyword"
> },
> "doc_id": {
> "type": "keyword"
> },
> "values": {
> "properties": {
> "nested_name": {
> "fields": {
> "raw": {
> "type": "keyword",
> }
> }
> }
> }
> }
> }
> }
> }
> }
> }
> 
> ```

I ran two queries:

1. A range query on the top level property `name`.
2. A range query on the nested property `nested_name`.

Query 2 is part of a larger query, but I narrowed down the slowness of that query to this particular range query.

> **Query 1**
>
> ```auto
> { 
> "query": {
> "bool": {
> "must": [
> {
> "range": {
> "name": {
> "gt": "<value>"
> }
> }
> }
> ]
> }
> }
> }
> 
> ```

> **Query 2**
>
> ```auto
> {
> "query": {
> "bool": {
> "should": [
> {
> "nested": {
> "path": "some_nested_doc",
> "query": {
> "bool": {
> "must": [
> {
> "filter": {
> "term": {
> "some_nested_doc.doc_id": {
> "value": "<some_id>"
> }
> }
> }
> },
> {
> "range": {
> "some_nested_doc.values.nested_name.raw": {
> "gt": "<some_value>"
> }
> }
> }
> ]
> }
> }
> }
> }
> ]
> }
> }
> }
> 
> ```

The search times differ quite a bit where Query 1's p90 is around 450ms and Query 2's is around 6 _seconds_. From looking at profiling traces, I noticed that the majority of the time is spent in the `build_scorer`. As I understand it, this creates an iterator over the matching document so that they can be scored. However, even running Query 2 within a filtered context yields the same performance results!

After searching a bit on possible optimizations, I realized I could put the doc\_id term query inside a `filter` block. As I understand it, a filter should lower the number of matching docs before the `should/must` block in the `bool` block is executed. So in theory, the `must` block in Updated Query 2 should only be performing against 5 Mil documents (since each document should have a nested document with doc\_id=x).

> **Updated Query 2**
>
> ```auto
> {
> "query": {
> "bool": {
> "should": [
> {
> "nested": {
> "path": "some_nested_doc",
> "query": {
> "bool": {
> "filter": {
> "term": {
> "some_nested_doc.doc_id": {
> "value": "<some_id>"
> }
> }
> },
> "must": {
> "range": {
> "some_nested_doc.values.nested_name.raw": {
> "gt": "<some_value>"
> }
> }
> }
> }
> }
> }
> }
> ]
> }
> }
> }
> 
> ```

Updated Query 2 performs exactly the same as Query 2 even though I would assume it performs the search over a smaller nested document set. Why does the performance of Updated Query 2 in this case not match Query 1? (don't they both technically apply a range query over 5 Million documents?) Is there something I'm missing around queries performed within a nested context? Are they inherently slower for some reason?

Thanks!

---

<div class="post-metadata">

**Author:** ![system](https://us1.discourse-cdn.com/elastic/original/3X/1/a/1ac57faf039f6b580b3f104ef42a2a89e41014de.png) [@system](https://discuss.elastic.co/u/system)\
**Post date:** [May 28, 2021, 6:44pm UTC](https://discuss.elastic.co/t/why-are-range-queries-on-nested-docs-slow/271825/2 "2021-05-28T18:44:02Z")

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