doc: add a few sample query for user metric doc (#774)

* doc: add a few sample query for user metric doc
Signed-off-by: feng-tao <fengtao04@gmail.com>

* doc: fix index
Signed-off-by: feng-tao <fengtao04@gmail.com>

docs/tutorials/how-to-track-user-metric.md

 # How to track Amundsen user metric
 
-After you have deployed Amundsen into production, you want to track how user interacts with Amundsen for various reasons. 
+After you have deployed Amundsen into production, you want to track how user interacts with Amundsen for various reasons.
 
 The easier way is to leverage [Google Analytics](https://analytics.google.com/analytics/web/) for basic user tracking. You could first
 get the analytics token for your domain and put it as the [frontend config](https://github.com/amundsen-io/amundsenfrontendlibrary/blob/54de01bdc574665316f0517aefbd55cf7ca37ef0/amundsen_application/static/js/config/config-default.ts#L22)
 
 
-Besides implementing Google Analytics, we provide a way called `action_logging` to do fine grained user action tracking. 
+Besides implementing Google Analytics, we provide a way called `action_logging` to do fine grained user action tracking.
 The `action_logging` is a decorator to allow you to integrate user info and pipe it to your inhouse event tracking system(e.g Kafka).
 
-You need to put the custom method into entry_points following this 
+You need to put the custom method into entry_points following this
 [example](https://github.com/amundsen-io/amundsenfrontendlibrary/blob/54de01bdc574665316f0517aefbd55cf7ca37ef0/docs/configuration.md#action-logging).
 
 And here is the IDL proto we used at Lyft to send the event message:
@@ -40,20 +40,145 @@ Once you have the event in your data warehouse, you could start building differe
 
 1. WAU
 
+Sample query if the event table named as `default.event_amundsenfrontend_user_action`
+```
+SELECT date_trunc('week', CAST("ds" AS TIMESTAMP)) AS "__timestamp",
+   COUNT(DISTINCT user_value) AS "count_distinct_active_users"
+FROM
+(SELECT *
+FROM default.event_amundsenfrontend_user_action
+WHERE ds > '2019-09-01') AS "expr_qry"
+WHERE "ds" >= '2020-04-21 00:00:00.000000'
+AND "ds" <= '2020-10-21 05:31:14.000000'
+GROUP BY date_trunc('week', CAST("ds" AS TIMESTAMP))
+ORDER BY "count_distinct_active_users" DESC
+LIMIT 10000
+```
+
 2. DAU
 
-3. Top 50 active user
+Sample query if the event table named as `default.event_amundsenfrontend_user_action`
+```
+SELECT date_trunc('day', CAST("ds" AS TIMESTAMP)) AS "__timestamp",
+   COUNT(DISTINCT user_value) AS "count_distinct_active_users"
+FROM
+(SELECT *
+FROM default.event_amundsenfrontend_user_action
+WHERE ds > '2019-09-01') AS "expr_qry"
+WHERE "ds" >= '2020-07-21 00:00:00.000000'
+AND "ds" <= '2020-10-21 00:00:00.000000'
+GROUP BY date_trunc('day', CAST("ds" AS TIMESTAMP))
+ORDER BY "count_distinct_active_users" DESC
+LIMIT 50000
+```
+
+You could also exclude weekends:
+```
+SELECT date_trunc('day', CAST("ds" AS TIMESTAMP)) AS "__timestamp",
+   COUNT(DISTINCT user_value) AS "count_distinct_active_users"
+FROM
+(SELECT *
+FROM default.event_amundsenfrontend_user_action
+WHERE ds > '2019-09-01') AS "expr_qry"
+WHERE "ds" >= '2020-04-21 00:00:00.000000'
+AND "ds" <= '2020-10-21 05:33:11.000000'
+AND day_of_week(logged_at) NOT IN (6,
+                                 7)
+GROUP BY date_trunc('day', CAST("ds" AS TIMESTAMP))
+ORDER BY "count_distinct_active_users" DESC
+LIMIT 50000
+```
+
+3. User Penetration per role
+
+Sample query if the event table named as `default.event_amundsenfrontend_user_action` and a table for user:
+```
+SELECT "title" AS "title",
+   COUNT(DISTINCT email) * 100 / MAX(role_count) AS "penetration_percent"
+FROM
+(SELECT e.occurred_at,
+      u.email,
+      u.title,
+      tmp.role_count
+FROM default.family_user u
+JOIN default.event_amundsenfrontend_user_action e ON u.email = e.user_value
+JOIN
+ (SELECT title,
+         count(*) role_count
+  FROM default.family_user
+  GROUP BY 1) as tmp ON u.title = tmp.title
+where ds is not NULL) AS "expr_qry"
+WHERE "occurred_at" >= from_iso8601_timestamp('2020-10-14T00:00:00.000000')
+AND "occurred_at" <= from_iso8601_timestamp('2020-10-21T00:00:00.000000')
+AND "role_count" > 20
+GROUP BY "title"
+ORDER BY "penetration_percent" DESC
+LIMIT 100
+```
+
+4. Usage breakdown per role_count
+
+sample query:
+```
+SELECT "title" AS "title",
+   count("email") AS "COUNT(email)"
+FROM
+(SELECT e.occurred_at,
+      u.email,
+      u.title,
+      tmp.role_count
+FROM default.family_user u
+JOIN default.event_amundsenfrontend_user_action e ON u.email = e.user_value
+JOIN
+ (SELECT title,
+         count(*) role_count
+  FROM default.family_user
+  GROUP BY 1) as tmp ON u.title = tmp.title
+where ds is not NULL) AS "expr_qry"
+WHERE "occurred_at" >= from_iso8601_timestamp('2020-10-14T00:00:00.000000')
+AND "occurred_at" <= from_iso8601_timestamp('2020-10-21T00:00:00.000000')
+GROUP BY "title"
+ORDER BY "COUNT(email)" DESC
+LIMIT 15
+```
+
+5. search click through rate
+
+sample query:
+```
+SELECT date_trunc('day', CAST("occurred_at" AS TIMESTAMP)) AS "__timestamp",
+   SUM(CASE
+           WHEN CAST(json_extract_scalar(keyword_args_json, '$.index') AS BIGINT) <= 3 THEN 1
+           ELSE 0
+       END) * 100 / COUNT(*) AS "click_through_rate"
+FROM
+(SELECT *
+FROM default.event_amundsenfrontend_user_action
+WHERE ds > '2019-09-01') AS "expr_qry"
+WHERE "occurred_at" >= from_iso8601_timestamp('2020-09-21T00:00:00.000000')
+AND "occurred_at" <= from_iso8601_timestamp('2020-10-21T00:00:00.000000')
+AND "command" IN ('_get_table_metadata',
+                '_get_dashboard_metadata',
+                '_log_get_user')
+AND json_extract_scalar(keyword_args_json, '$.source') IN ('search_results',
+                                                         'inline_search')
+GROUP BY date_trunc('day', CAST("occurred_at" AS TIMESTAMP))
+ORDER BY "click_through_rate" DESC
+LIMIT 10000
+```
+
+6. Top 50 active user
 
-4. Top search term
+7. Top search term
 
-5. Top popular tables
+8. Top popular tables
 
-6. Search click index
+9. Search click index
 
-7. Metadata edits
+10. Metadata edits
 
-8. Metadata edit leaders
+11. Metadata edit leaders
 
-9. Amundsen user per role (by joining with employee data)
+12. Amundsen user per role (by joining with employee data)
 
-10. ...
+13. ...