Merge pull request ClickHouse#82542 from ClickHouse/Blargian-patch-16

Docs: embed videos on dictionaries in dictionaries page

Author: Blargian

ci/jobs/scripts/check_style/aspell-ignore/en/aspell-dict.txt

@@ -1894,12 +1894,14 @@ geoToS
 geobase
 geobases
 geocode
+geocoding
 geohash
 geohashDecode
 geohashEncode
 geohashes
 geohashesInBox
 geoip
+geolocation
 geospatial
 getClientHTTPHeader
 getMacro

docs/en/sql-reference/dictionaries/index.md

@@ -800,7 +800,9 @@ This type of storage is for use with composite [keys](#dictionary-key-and-fields
 
 ### ip_trie {#ip_trie}
 
-This type of storage is for mapping network prefixes (IP addresses) to metadata such as ASN.
+This dictionary is designed for IP address lookups by network prefix. It stores IP ranges in CIDR notation and allows fast determination of which prefix (e.g. subnet or ASN range) a given IP falls into, making it ideal for IP-based searches like geolocation or network classification.
+
+<iframe width="1024" height="576" src="https://www.youtube.com/embed/4dxMAqltygk?si=rrQrneBReK6lLfza" title="IP based search with the ip_trie dictionary" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
 **Example**
 
@@ -2139,8 +2141,9 @@ For our example, the structure of dictionary can be the following:
 
 ## Polygon dictionaries {#polygon-dictionaries}
 
-Polygon dictionaries allow you to efficiently search for the polygon containing specified points.
-For example: defining a city area by geographical coordinates.
+This dictionary is optimized for point-in-polygon queries, essentially “reverse geocoding” lookups. Given a coordinate (latitude/longitude), it efficiently finds which polygon/region (from a set of many polygons, such as country or region boundaries) contains that point. It’s well-suited for mapping location coordinates to their containing region.
+
+<iframe width="1024" height="576" src="https://www.youtube.com/embed/FyRsriQp46E?si=Kf8CXoPKEpGQlC-Y" title="Polygon Dictionaries in ClickHouse" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
 Example of a polygon dictionary configuration:
 
@@ -2270,7 +2273,9 @@ Result:
 
 ## Regular Expression Tree Dictionary {#regexp-tree-dictionary}
 
-Regular expression tree dictionaries are a special type of dictionary which represent the mapping from key to attributes using a tree of regular expressions. There are some use cases, e.g. parsing of [user agent](https://en.wikipedia.org/wiki/User_agent) strings, which can be expressed elegantly with regexp tree dictionaries.
+This dictionary lets you map keys to values based on hierarchical regular-expression patterns. It’s optimized for pattern-match lookups (e.g. classifying strings like user agent strings by matching regex patterns) rather than exact key matching.
+
+<iframe width="1024" height="576" src="https://www.youtube.com/embed/ESlAhUJMoz8?si=sY2OVm-zcuxlDRaX" title="An intro to ClickHouse regex tree dictionaries" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>
 
 ### Use Regular Expression Tree Dictionary in ClickHouse Open-Source {#use-regular-expression-tree-dictionary-in-clickhouse-open-source}