add distinct function example 3

Author: XiaoyuMSFT

docs/t-sql/statements/create-materialized-view-as-select-transact-sql.md

@@ -108,7 +108,7 @@ When MIN/MAX aggregates are used in the SELECT list of materialized view definit
 A materialized view in Azure data warehouse is similar to an indexed view in SQL Server.  It shares almost the same restrictions as indexed view (see [Create Indexed Views](/sql/relational-databases/views/create-indexed-views) for details) except that a materialized view supports aggregate functions.   
 
 >[!Note]
->Although CREATE MATERIALIZED VIEW does not support COUNT(), DISTINCT(), COUNT(DISTINCT()), COUNT_BIG(DISTINCT()), or APPROX_COUNT_DISTINCT, SELECT queries with these functions can still benefit from materialized views for faster performance as the Synapse SQL optimizer can automatically re-write those aggregations in the user query to match existing materialized views.  For details, check this article's example section. 
+>Although CREATE MATERIALIZED VIEW does not support COUNT(), DISTINCT, COUNT(DISTINCT expression), or COUNT_BIG (DISTINCT expression), SELECT queries with these functions can still benefit from materialized views for faster performance as the Synapse SQL optimizer can automatically re-write those aggregations in the user query to match existing materialized views.  For details, check this article's example section. 
 
 Only CLUSTERED COLUMNSTORE INDEX is supported by materialized view. 
 
@@ -145,7 +145,7 @@ To find out if a SQL statement can benefit from a new materialized view, run the
 Requires 1) REFERENCES and CREATE VIEW permission OR 2) CONTROL permission on the schema in which the view is being created. 
 
 ## Example
-A. This example shows how Synapse SQL optimizer automatically uses materialized views to execute a query for better performance even when the query uses functions un-supported in CREATE MATERIALIZED VIEW, such as COUNT (DISTINCT()). The query execution time got reduced from 176 seconds to <1 second without any change in the user query.  
+A. This example shows how Synapse SQL optimizer automatically uses materialized views to execute a query for better performance even when the query uses functions un-supported in CREATE MATERIALIZED VIEW, such as COUNT(DISTINCT expression). The query execution time got reduced from multiple seconds to sub-second without any change in the user query.  
 
 ``` sql 
 
@@ -161,21 +161,21 @@ while (@P < 30)
     select @p +=1;
 end
 
--- A SELECT query with count_big(distinct()) took ~176 seconds and it reads data directly from the base table a. 
+-- A SELECT query with COUNT_BIG (DISTINCT expression) took multiple seconds to complete and it reads data directly from the base table a. 
 select a, count_big(distinct b) from t group by a;
 
--- Create two materialized views, not using COUNT_BIG(DISTINCT()).
+-- Create two materialized views, not using COUNT_BIG(DISTINCT expression).
 create materialized view V1 with(distribution=hash(a)) as select a, b from dbo.t group by a, b;
 
 -- Clear all cache.
 
 DBCC DROPCLEANBUFFERS;
 DBCC freeproccache;
 
--- Check the estimated execution plan in SSMS.  It shows the SELECT query is first step (GET operator) is to read data from the materialized view V1, not from base table a.
+-- Check the estimated execution plan in SQL Server Management Studio.  It shows the SELECT query is first step (GET operator) is to read data from the materialized view V1, not from base table a.
 select a, count_big(distinct b) from t group by a;
 
--- Now run this SELECT query.  This time it took <1 second to complete because Synapse SQL engine automatically matches the query with materialized view V1 and uses it for faster query execution.  There was change in no user query.
+-- Now execute this SELECT query.  This time it took sub-second to complete because Synapse SQL engine automatically matches the query with materialized view V1 and uses it for faster query execution.  There was no change in the user query.
 
 DECLARE @timerstart datetime2, @timerend datetime2;
 SET @timerstart = sysdatetime();