support aggregate,time,column function

Author: camilesing

README.md

@@ -5,7 +5,7 @@ This extension provides Flink SQL support for VSCode. It also provides some basi
 
 ## Features
 
-Enables syntax highlighting and formatting for Flink SQL, including user-defined functions.
+Enables syntax highlighting and formatting for Flink SQL(v1.16.0), including user-defined functions.
 
 
 ## How use
@@ -16,8 +16,5 @@ Enable the extension on your file, either name the file with a extension:
 Or press F1, type 'Change Language Mode', and then choose FlinkSQL.
 
 # TODO List
-## UDF 
-- Support `Conditional Functions`：`CASE value WHEN value1_1 [, value1_2]* THEN RESULT1 (WHEN value2_1 [, value2_2 ]* THEN result_2)* (ELSE result_z) END`
-- Support `Aggregate Function`
-- Support `Time Interval and Point Unit Specifiers`
-- Support `Column Functions`
+- Support grammer:`Conditional Functions`：`CASE value WHEN value1_1 [, value1_2]* THEN RESULT1 (WHEN value2_1 [, value2_2 ]* THEN result_2)* (ELSE result_z) END`
+- Error grammer highlight 

package.json

@@ -1,6 +1,6 @@
 {
     "name": "flink-sql",
-    "version": "0.1.0",
+    "version": "1.0.0",
     "displayName": "Flink SQL",
     "description": "Adds support for Flink's variant of the SQL language",
     "publisher": "CamileSing",

syntaxes/flink.tmLanguage.json

@@ -150,11 +150,19 @@
     },
     {
       "name" : "support.function.udaf.flink",
-      "match" : "\\b(?i:count|sum|avg|min|max|variance|var_pop|var_samp|stddev_pop|stddev_samp|covar_pop|covar_samp|corr|percentile|percentile_approx|histogram_numeric|collect_set|collect_list|ntile|lead|lag|first_value|last_value|rank|row_number|dense_rank|cume_dist|percent_rank)\\b"
+      "match" : "\\b(?i:count|count(1)|sum|avg|min|max|variance|var_pop|var_samp|collect|variance|rank()|dense_rank()|row_number()|lead|lag|first_value|last_value|list_agg|cume_dist|percent_rank|ntile)\\b"
     },
     {
-      "name" : "support.function.udtf.flink",
-      "match" : "\\b(?i:inline|explode|json_tuple|parse_url_tuple|stack|posexplode)\\b"
+      "name" : "support.function.udf.aggregate.flink",
+      "match" : "\\b(?i:count|distinct|avg|parse_url_tuple|stack|posexplode)\\b"
+    },
+    {
+      "name" : "support.function.udf.time.flink",
+      "match" : "\\b(?i:miliennium|century|decade|year|year_to_month|week|day|day_to_hour|day_to_minute|day_to_second|hour|hour_to_minute|hour_to_second|minute|minute_to_second|second|millisecond|nanosecond|epoch|doy|dow|isodow|epoch|isoyear)\\b"
+    },
+    {
+      "name" : "support.function.udf.column.flink",
+      "match" : "\\b(?i:withColumns|withoutColumns)\\b"
     },
     {
       "begin": "(?i)^\\s*((?:set)\\s+(?:[^\\=]+))\\s*=\\s*",