Json格式对于现在所有的软件开发者都不陌生,很多数据格式都用他来存储,我们来看一下vertica是怎么处理json数据的。这就是vertica的flex table! 首先创建一个json文件: 1 2 3 4 5 {"name" : "Everest" , "type" :"mountain" , "height" :29029 , "hike_safety" : 34.1 } {"name" : "Mt St Helens" , "type" :"volcano" , "height" :29029 , "hike_safety" : 15.4 } {"name" : "Denali" , "type" :"mountain" , "height" :17000 , "hike_safety" : 12.2 } {"name" : "Kilimanjaro" , "type" :"mountain" , "height" :14000 } {"name" : "Mt Washington" , "type" :"mountain" , "hike_safety" : 50.6 }
然后我们创建一个flex table: 1 2 dbadmin=> CREATE FLEX TABLE start_json(); CREATE TABLE
然后把数据copy进去: 1 2 3 4 5 dbadmin=> COPY start_json FROM '/home/dbadmin/qcfData/*json*' PARSER fjsonparser(); Rows Loaded ------------- 5 (1 row)
查询结果: 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 dbadmin => select * from start_json();ERROR 4256: Only relations and subqueries are allowed in the FROM clausedbadmin => SELECT maptostring(__raw__) FROM start_json; maptostring ---------------------------------------------------------------------------------------------------------- { "height" : "29029" , "hike_safety" : "34.1" , "name" : "Everest" , "type" : "mountain" } { "height" : "29029" , "hike_safety" : "15.4" , "name" : "Mt St Helens" , "type" : "volcano" } { "height" : "17000" , "hike_safety" : "12.2" , "name" : "Denali" , "type" : "mountain" } { "height" : "14000" , "name" : "Kilimanjaro" , "type" : "mountain" } { "hike_safety" : "50.6" , "name" : "Mt Washington" , "type" : "mountain" } (5 rows)
发现很好的解析了json文件,并且格式化了文件。 查询json数据: 1 2 3 4 5 6 7 8 9 dbadmin => SELECT start_json.type,start_json.name FROM start_json; type | name ----------+--------------- mountain | Everest volcano | Mt St Helens mountain | Denali mountain | Kilimanjaro mountain | Mt Washington (5 rows)
此时如果使用 * 查询 会出现乱码:
1 SELECT * FROM start_json;
需要使用函数 compute_flextable_keys
select compute_flextable_keys(‘start_json’);
然后查询就可以有结果
综上,flex table 对json格式的数据提供了很好的存储于展示。