clintropolis commented on code in PR #16673:
URL: https://github.com/apache/druid/pull/16673#discussion_r1680120813


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docs/querying/sql-data-types.md:
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@@ -34,12 +34,23 @@ Druid associates each column with a specific data type. 
This topic describes sup
 
 Druid natively supports the following basic column types:
 
-* LONG: 64-bit signed int
-* FLOAT: 32-bit float
-* DOUBLE: 64-bit float
-* STRING: UTF-8 encoded strings and string arrays
-* COMPLEX: non-standard data types, such as nested JSON, hyperUnique and 
approxHistogram, and DataSketches
-* ARRAY: arrays composed of any of these types
+* `LONG`: 64-bit signed int
+* `FLOAT`: 32-bit float
+* `DOUBLE`: 64-bit float
+* `STRING`: UTF-8 encoded strings and string arrays
+* `ARRAY`: arrays composed of any of these types
+
+## Complex types
+
+Druid natively supports the following complex types:
+* `COMPLEX<JSON>`: stores a copy of structured data in JSON format and 
specialized internal columns and indexes for nested basic types. Click here to 
learn more about [`COMPLEX<JSON>`](nested-columns.md)
+* `cardinality`: Data structure to compute the cardinality of Apache Druid 
dimensions using the HyperLogLog algorithm. Click here to learn more about 
[`cardinality`](hll-old.md#cardinality-aggregator)
+* `hyperUnique`: Data structure of aggregated values to estimate count 
distinct using a variant of the HyperLogLog approximation algorithm. Consider 
using HLL sketches for better accuracy in many cases. Click here to learn more 
about [`hyperUnique`](hll-old.md#hyperunique-aggregator)

Review Comment:
   the extension docs primarily describe how to use the extension functions. It 
would make sense to me to list out the types here and link each of them to 
their dedicated docs to learn more about how to create and use these types



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