Merge pull request #7 from knaufk/staging-21

Day 21

21_map.md

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+# Advent of Flink - Day #21 `MAP`
+
+Another day, another data type. `MAP`s. Let's start by creating a `MAP`. 
+
+```sql
+SELECT MAP['Java', 5, 'SQL', 4, 'Python', 3] AS my_map;
+```
+returns
+```
+{Java=5, Python=3, SQL=4}
+```
+You can retrieve a specific value from a map via square brackets. 
+```
+CREATE VIEW maps AS SELECT MAP['Java', 5, 'SQL', 4, 'Python', 3] AS my_map;
+```
+and 
+```
+SELECT my_map['Java'] FROM maps;
+```
+which retunrs
+```
+EXPR$0
+5
+```
+Flink has a couple of related built-in functions, too. First, there are three functions to retrieve the content of a map as an array: 
+
+* `MAP_ENTRIES` returns an `ARRAY` of `ROW`s with the key and value as the two columns of these rows.
+* `MAP_VALUES` returns an `ARRAY` of the values of the map.
+* `MAP_KEY` returns an `ARRAY` of the keys of the map.
+
+The other way around, you can use `MAP_FROM_ARRAYS` to create a map from two arrays: one for the keys, one for the arrays. Or you can use
+`STR_TO_MAP` to create a `MAP` from `STRING` `MAP_UNION` you can use to merge two maps. As an example, in the following I use `MAP_FROM_ARRAYS` 
+to get to table that contains user_id and for each user_id a map from urls to the number of clicks from this user on that url. 
+```sql
+SELECT 
+ user_id, 
+ MAP_FROM_ARRAYS(ARRAY_AGG(url), ARRAY_AGG(cnt))
+FROM 
+( 
+  SELECT 
+    user_id, 
+    url,
+    COUNT(*) cnt
+  FROM `examples`.`marketplace`.`clicks`
+  GROUP BY user_id, url
+)
+GROUP BY user_id;
+```
+As always (so far), the examples in here are runnable out of the box on [Confluent Cloud](https://confluent.cloud).
+
+
+