This document discusses indexing, searching, and aggregation in Redis using RediSearch and .NET. It provides an introduction to Redis data structures and building secondary indices. It then covers using RediSearch to define schemas, query data through full text search and filters, and perform aggregations through grouping, reductions, and applying functions. RediSearch provides an easier way to index and query Redis compared to building secondary indices in vanilla Redis.

1. Indexing, Searching, and Aggregation in
Redis with RediSearch and .NET
Presented by: Steve Lorello - Developer Advocate @Redis
Twitter: @slorello

2. Agenda ● Introduction to Redis
● Redis Data Structures
● Secondary Indices
● Building Secondary Indices with any Redis
● Building Secondary Indices with RediSearch
● Writing Queries for Redis
● Writing Aggregations for Redis

3. What is Redis?
● NoSQL Database
● In-Memory Database
● Fundamentally a key-value
store
● Multimodal Database
● Fast
● Simple - Extremely Popular

4. Redis Data
Structures
● Strings
● Sets
● Sorted Sets
● Hashes
● JSON

5. Strings
● Single key retrieves single value
● Value can further be encoded as numeric/string
● Most basic Data Type in Redis
● Many users of Redis never look beyond this data type
SET foo bar

6. ● Set of Redis Strings
● Unordered
● No duplication
● Set Operations
○ Intersection
○ Difference
○ Union
Person:Name:Steve = {Person:1}
Sets
SADD Person:Name:Steve Person:1

7. Sorted Set
● Ordered Sets
● Score Member
● No duplicate members
● Can be Ordered by
○ Score
○ Lexicographically.
Person:Age
Id Score
Person:1 32
Person:2 45
ZADD Person:Age 32 Person:1 45 Person:2

8. Redis Hashes
● Field Value Stores
● Flat Objects
● Field Names are Strings
● Field Values are strings
HSET Person:1 age 32 firstName Steve
Person:1
age 32
firstName Steve

9. Json
● Store objects as JSON
● Access via JSONPath
● Update via JSONPath
● Redis Module
● Source Available License
JSON.SET Person:1 .
‘{“firstName”:”Steve”,”age”:32}’

10. Finding Stuff In Redis

11. SELECT * FROM people
WHERE firstName = ‘Steve’
SELECT * FROM people
WHERE age < 35
You Can’t Just Search for things in Redis
Unless You Build a Secondary Index

12. Secondary Indices
● Efficiently find items in Primary Index
● Redis Primary Index = Keys
● Explicitly Declared
● Separate Maintenance and Updating
Source: https://lethain.com/global-secondary-indexes/

13. Secondary Indices in Redis Vanilla
● Exact Match Text - Unsorted -> Sets
● Exact Match Numeric - Unsorted -> Sets
● Numeric Sorted -> Sorted Sets
● Full Text -> Sorted Sets
Person:Name:Steve = {Person:1}
Person:Age
Id Score
Person:1 32
Person:2 45

14. Exact Match
● Store data in a Hash
● Foreach IndexName:Field:Value create a set
● Query the set for the IndexName:Field:Value then query hashes for
the result
● If you want to run more complicated queries, use set combination
operations to combine queries

15. Range Queries Numeric
● Use Sorted Sets store scores for particular fields
● Use Range Queries

16. Cons
● This can be done on any
Redis Database
● Total control over what you
index and what you don’t
● Excellent for Job Security
● Complicated to do any sort of
complex data modeling
● Impossible to horizontally
scale database and maintain
atomicity when updating data
● Needs regular consistency
updating throughout cluster.
Pros
OSS Redis Indexing Pros and Cons

17. RediSearch

18. What is RediSearch
● Module of Redis maintained by Redis
● Allows you to define schema of index
● Redis will take care of indexing
● Automatically index your data
● Provides Full Text Search Capabilities
● Provides Geo Filtering Capabilities
● Index automatically maintained cross-shards
● Source Available License

19. Spin up RediSearch
docker run -p 6379:6379 redislabs/redisearch

20. Creating Indices
● Indices are declared on types (Hash or JSON)
● Indices may be declared on Prefixes (e.g. Person:)
● Indices contain a schema mapping fields -> index types
● 4 index types
○ Tag (exact match or faceted matches)
○ Text (Full Text Search)
○ Numeric
○ Geo

21. Querying
● FT.SEARCH
● Query Syntax varies by data type
○ Tag -> @FieldName:{search Data}
○ Text -> @FieldName:search Data
○ Geo -> GEOFILTER @fieldName lon lat radius unit
○ Numeric -> @FieldName:[lowerBound upperBound]

22. Aggregations
● Query Data along same syntax as standard querying
● Build Pipelines to Transform indexed data in Redis
● Group like items together and run reductions on them
● Filter Data based off results of aggregations

23. Apply Functions
● Apply functions to your data
○ E.g. “@sales * @sales_regional_adjustment” AS SALES_ADJUSTED
● Use a variety of mathematical, string and timestamp functions
● Store results of apply functions in the pipeline, and use them later for
reductions and further apply functions

24. GroupBy and Reductions
● Records with like fields can be grouped together
● Grouped records can run reduction functions to combine them
○ E.g. SUM, AVERAGE, Stand Deviation etc. .
● Grouped records can be returned or passed further down the pipeline

25. ● Declarative syntax for Index Creation
● Fluent API for Searching and Aggregation
● Object Mapping for mapping objects to Redis Data
Structures

26. Steve Lorello
Developer Advocate
@Redis
@slorello
github.com/slorello89
slorello.com

27. Resources
Redis
https://redis.io
RediSearch
https://redisearch.io
Redis Search Docker Image
https://hub.docker.com/r/redislabs/redisearch/
Redis OM
https://github.com/redis/redis-om-dotnet

28. Come Check Us Out!
Redis University:
https://university.redis.com
Discord:
https://discord.com/invite/redis