kfaraz commented on code in PR #12768:
URL: https://github.com/apache/druid/pull/12768#discussion_r918938093


##########
docs/querying/granularities.md:
##########
@@ -38,10 +38,27 @@ You can specify a time period as a 
[simple](#simple-granularities) string, as a
 
 Simple granularities are specified as a string and bucket timestamps by their 
UTC time (e.g., days start at 00:00 UTC).
 
-Supported granularity strings are: `all`, `none`, `second`, `minute`, 
`fifteen_minute`, `thirty_minute`, `hour`, `day`, `week`, `month`, `quarter` 
and `year`.
-
-* `all` buckets everything into a single bucket
-* `none` does not bucket data (it actually uses the granularity of the index - 
minimum here is `none` which means millisecond granularity). Using `none` in a 
[TimeseriesQuery](../querying/timeseriesquery.md) is currently not recommended 
(the system will try to generate 0 values for all milliseconds that didn’t 
exist, which is often a lot).
+Supported granularity strings are: 
+  - `all`
+  - `none`
+  - `second`
+  - `minute`
+  - `five_minute`
+  - `ten_minute`
+  - `fifteen_minute`
+  - `thirty_minute`
+  - `hour`
+  - `six_hour`
+  - `eight_hour`
+  - `day`
+  - `week`
+  - `month`
+  - `quarter` 
+  - `year`
+
+> NOTE
+> * `all` buckets everything into a single bucket

Review Comment:
   The basic behaviour of `all` and `none` should probably not be a side-note. 
   
   We could maybe break this into two parts:
   ```
   The supported simple granularity strings are as under. Each of these divide 
data into buckets of the respective size.
   - `second`
   - `minute`
   - ...
   - `year`
   
   Special granularity strings:
   - `all`: Puts everything into a single bucket
   - `none`: Does not bucket data at all. Instead, it uses the granularity ...
   ```
   
   It makes sense to make the following part a side note though:
   ```
   Using `none` in a [TimeseriesQuery](../querying/timeseriesquery.md) is 
currently not recommended. This is because the system will try to generate 0 
values for all milliseconds that didn’t exist, which is often a lot.
   ```
   



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