My question is somewhat similar to this ( Athena/Presto - UNNEST MAP to columns ). But in my case, I know what columns I need before hand.
My use case is this
I have a json blob which contains the following structures
{
"reqId" : "1234",
"clientId" : "client",
"response" : [
{
"name" : "Susan",
"projects" : [
{
"name" : "project1",
"completed" : true
},
{
"name" : "project2",
"completed" : false
}
]
},
{
"name" : "Adams",
"projects" : [
{
"name" : "project1",
"completed" : true
},
{
"name" : "project2",
"completed" : false
}
]
}
]
}
I need to create a view which will return output something like this
name | project | Completed |
----------+-------------+------------+
Susan | project1 | true |
Susan | project2 | false |
Adams | project1 | true |
Adams | project2 | false |
I tried the following and other approaches. This one was the closest I can get
WITH dataset AS (
SELECT 'Susan' as name, transform(filter(CAST(json_extract('{
"projects": [{"name":"project1", "completed":false}, {"name":"project3", "completed":false},
{"name":"project2", "completed":true}]}', '$.projects') AS ARRAY<MAP<VARCHAR, VARCHAR>>), p -> (p['name'] != 'project1')), p -> ROW(map_values(p))) AS projects
)
SELECT * from dataset
CROSS JOIN UNNEST(projects)
This is the output I am getting
name projects _col2
1 Susan [{field0=[project3, false]}, {field0=[project2, true]}] {field0=[project3, false]}
2 Susan [{field0=[project3, false]}, {field0=[project2, true]}] {field0=[project2, true]}
I basically want to unnest the key-value pairs of my map as separate columns. How do I do this in presto / Athena?
Your JSON example seems to be invalid, it misses a ,
after "name": "Susan"
and "name": "Adams"
. Besides that, you can achieve your expected output by this query, you need to UNNEST two times and also requires some casting:
with dataset as
(
select json_parse('{"reqId" : "1234","clientId" : "client","response" : [{"name" : "Susan","projects" : [{"name" : "project1","completed" : true},{"name" : "project2","completed" : false}]},{"name" : "Adams","projects" : [{"name" : "project1","completed" : true},{"name" : "project2","completed" : false}]}]}') as json_col
)
,unnest_response as
(
select *
from dataset
cross join UNNEST(cast(json_extract(json_col, '$.response') as array<JSON>)) as t (response)
)
select
json_extract_scalar(response, '$.name') name,
json_extract_scalar(project, '$.name') project_name,
json_extract_scalar(project, '$.completed') project_completed
from unnest_response
cross join UNNEST(cast(json_extract(response, '$.projects') as array<JSON>)) as t (project);
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