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RS: Adjusted best practices for scalable Redis query engine & add benchmarks (#1687)
* DOC-4271 RS: Adjusted best practices for scalable Redis query engine & add benchmarks * Style guide fix for indexes * Fixed broken relrefs after AI/search reorg
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‎content/operate/oss_and_stack/stack-with-enterprise/search/scalable-query-best-practices.md

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---
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[Vertical scaling of Redis Query Engine]({{<relref "/operate/oss_and_stack/stack-with-enterprise/search/query-performance-factor">}}) requires configuring query performance factors. With careful crafting of search indices and queries, query performance factors allow throughput scaling up to 16X. The following recommendations help queries avoid accessing the keyspace and enable Redis Query Engine to benefit from additional CPUs allocated by query performance factors.
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[Vertical scaling of Redis Query Engine]({{<relref "/operate/oss_and_stack/stack-with-enterprise/search/query-performance-factor">}}) requires configuring query performance factors. With careful crafting of search indexes and queries, query performance factors allow throughput scaling up to 16X. The following recommendations can help optimize your indexes and queries to maximize the performance benefits from additional CPUs allocated by query performance factors.
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## Best candidates for query performance factor improvements
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- [Vector]({{<relref "/develop/ai/search-and-query/query/vector-search">}})
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- Result set types:
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- [Numeric]({{<relref "/develop/ai/search-and-query/query/range">}})
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- [Geo]({{<relref "/develop/ai/search-and-query/query/geo-spatial">}})
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- Result set types:
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- Small result sets
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- Document subsets that are indexed in their [non-normalized]({{<relref "/develop/ai/search-and-query/advanced-concepts/sorting#normalization-unf-option">}}) form
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## Indexing best practices
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## Best practices
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If query performance factors have not boosted the performance of your queries as much as expected:
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1. Verify your index includes all queried and returned fields.
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1. Identify and avoid query [anti-patterns]({{<relref "/develop/ai/search-and-query/best-practices/scalable-query-best-practices#anti-patterns">}}) that limit scalability.
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1. Follow best practices to [improve indexing](#improve-indexing).
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1. Follow best practices to [improve queries](#improve-queries).
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### Improve indexing
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Follow these best practices for [indexing]({{<relref "/develop/ai/search-and-query/indexing">}}):
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- Use the `NOSTEM` option for `TEXT` fields.
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## Query best practices
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### Improve queries
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Follow these best practices for [queries]({{<relref "/develop/ai/search-and-query/query">}}):
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Follow these best practices to optimize [queries]({{<relref "/develop/ai/search-and-query/query">}}):
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- Specify the result set fields in the `RETURN` or `LOAD` clauses and include them in the index definition. Don’t just return the default result set from [`FT.SEARCH`]({{< relref "commands/ft.search/" >}}) or `LOAD *` from [`FT.AGGREGATE`]({{< relref "commands/ft.aggregate/" >}}).
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```
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## Performance results
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The following benchmarks show the performance improvements for different query types achieved with query performance factors. Vector, tag, and text queries strongly benefit, while numeric and geographic queries show more limited improvements.
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### Vector schema type
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#### Vector ingest
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| Shards | Threads per shard | CPUs | Speedup factor |
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|--------|-------------------|------|----------------|
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| 1 | 0 | 1 | 0 |
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| 6 | 0 | 6 | 6.6 |
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| 1 | 6 | 6 | 2.5 |
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| 2 | 6 | 12 | 6.1 |
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| 4 | 6 | 24 | 24.3 |
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#### Vector query
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| Shards | Threads per shard | CPUs | Speedup factor |
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|--------|-------------------|------|----------------|
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| 1 | 0 | 1 | 0 |
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| 6 | 0 | 6 | 0.8 |
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| 1 | 6 | 6 | 4.7 |
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| 2 | 6 | 12 | 5.1 |
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| 4 | 6 | 24 | 5.6 |
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### Tag schema type
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| Worker threads | % change |
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|----------------|----------|
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| 0 | 0 |
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| 6 | 135.88 |
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### Text schema type
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#### Two-word union queries
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 188 | 0 |
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| 6 | 1,072 | 470 |
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| 12 | 1,995 | 961 |
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| 18 | 2,834 | 1,407 |
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#### Two-word intersection queries
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 2,373 | 0 |
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| 6 | 12,396 | 422 |
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| 12 | 17,506 | 638 |
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| 18 | 19,764 | 733 |
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#### Simple one-word match
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 476 | 0 |
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| 6 | 2,837 | 496 |
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| 12 | 5,292 | 1,012 |
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| 18 | 7,512 | 1,478 |
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### Numeric schema type
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 33,584 | 0 |
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| 1 | 36,993 | 10.15 |
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| 3 | 36,504 | 8.69 |
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| 6 | 36,897 | 9.86 |
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### Geo schema type
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#### Geo queries without UNF
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 48 | 0 |
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| 6 | 96 | 100 |
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| 12 | 96 | 100 |
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| 18 | 98 | 104 |
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#### Geo queries with UNF
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| Worker threads | Queries per second | % change |
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|----------------|--------------------|----------|
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| 0 | 61 | 0 |
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| 6 | 227 | 272 |
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| 12 | 217 | 256 |
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| 18 | 217 | 256 |

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