I want to split strings into columns.
My columns should be:
account_id, resource_type, resource_name
I have a JSON file source that I have been trying to parse via ADF data flow. That hasn't worked for me, hence I flattened the data and brought it into SQL Server (I am open to parsing values via ADF or SQL if anyone can show me how). Please check the JSON file at the bottom.
Use this code to query the data I am working with.
CREATE TABLE test.test2
(
resource_type nvarchar(max) NULL
)
INSERT INTO test.test2 ([resource_type])
VALUES
('account_id:224526257458,resource_type:buckets,resource_name:camp-stage-artifactory'),
('account_id:535533456241,resource_type:buckets,resource_name:tni-prod-diva-backups'),
('account_id:369798452057,resource_type:buckets,resource_name:369798452057-s3-manifests'),
('account_id:460085747812,resource_type:buckets,resource_name:vessel-incident-report-nonprod-accesslogs')
The output that I should be able to query in SQL Server should like this:
account_id
resource_type
resource_name
224526257458
buckets
camp-stage-artifactory
535533456241
buckets
tni-prod-diva-backups
and so forth.
Please help me out and ask for clarification if needed. Thanks in advance.
EDIT:
Source JSON Format:
{
"start_date": "2021-12-01 00:00:00+00:00",
"end_date": "2021-12-31 23:59:59+00:00",
"resource_type": "all",
"records": [
{
"directconnect_connections": [
"account_id:227148359287,resource_type:directconnect_connections,resource_name:'dxcon-fh40evn5'",
"account_id:401311080156,resource_type:directconnect_connections,resource_name:'dxcon-ffxgf6kh'",
"account_id:401311080156,resource_type:directconnect_connections,resource_name:'dxcon-fg5j5v6o'",
"account_id:227148359287,resource_type:directconnect_connections,resource_name:'dxcon-fgvfo1ej'"
]
},
{
"virtual_interfaces": [
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:'dxvif-fgvj25vt'",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:'dxvif-fgbw5gs0'",
"account_id:401311080156,resource_type:virtual_interfaces,resource_name:'dxvif-ffnosohr'",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:'dxvif-fg18bdhl'",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:'dxvif-ffmf6h64'",
"account_id:390251991779,resource_type:virtual_interfaces,resource_name:'dxvif-fgkxjhcj'",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:'dxvif-ffp6kl3f'"
]
}
]
}
Since you don't have a valid JSON string and not wanting to get in the business of string manipulation... perhaps this will help.
Select B.*
From test2 A
Cross Apply ( Select account_id = max(case when value like 'account_id:%' then stuff(value,1,11,'') end )
,resource_type = max(case when value like 'resource_type:%' then stuff(value,1,14,'') end )
,resource_name = max(case when value like 'resource_name:%' then stuff(value,1,14,'') end )
from string_split(resource_type,',')
)B
Results
account_id resource_type resource_name
224526257458 buckets camp-stage-artifactory
535533456241 buckets tni-prod-diva-backups
369798452057 buckets 369798452057-s3-manifests
460085747812 buckets vessel-incident-report-nonprod-accesslogs
Unfortunately, the values inside the arrays are not valid JSON. You can patch them up by adding {} to the beginning/end, and adding " on either side of : and ,.
DECLARE #json nvarchar(max) = N'{
"start_date": "2021-12-01 00:00:00+00:00",
"end_date": "2021-12-31 23:59:59+00:00",
"resource_type": "all",
"records": [
{
"directconnect_connections": [
"account_id:227148359287,resource_type:directconnect_connections,resource_name:''dxcon-fh40evn5''",
"account_id:401311080156,resource_type:directconnect_connections,resource_name:''dxcon-ffxgf6kh''",
"account_id:401311080156,resource_type:directconnect_connections,resource_name:''dxcon-fg5j5v6o''",
"account_id:227148359287,resource_type:directconnect_connections,resource_name:''dxcon-fgvfo1ej''"
]
},
{
"virtual_interfaces": [
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:''dxvif-fgvj25vt''",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:''dxvif-fgbw5gs0''",
"account_id:401311080156,resource_type:virtual_interfaces,resource_name:''dxvif-ffnosohr''",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:''dxvif-fg18bdhl''",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:''dxvif-ffmf6h64''",
"account_id:390251991779,resource_type:virtual_interfaces,resource_name:''dxvif-fgkxjhcj''",
"account_id:227148359287,resource_type:virtual_interfaces,resource_name:''dxvif-ffp6kl3f''"
]
}
]
}';
SELECT
j4.account_id,
j4.resource_type,
TRIM('''' FROM j4.resource_name) resource_name
FROM OPENJSON(#json, '$.records') j1
CROSS APPLY OPENJSON(j1.value) j2
CROSS APPLY OPENJSON(j2.value) j3
CROSS APPLY OPENJSON('{"' + REPLACE(REPLACE(j3.value, ':', '":"'), ',', '","') + '"}')
WITH (
account_id bigint,
resource_type varchar(20),
resource_name varchar(100)
) j4;
db<>fiddle
The first three calls to OPENJSON have no schema, so the resultset is three columns: key value and type. In the case of arrays (j1 and j3), key is the index into the array. In the case of single objects (j2), key is each property name.
Related
I am looking for a solution to convert the table results to a JSON path.
I have a table with two columns as below. Column 1 Will always have normal values, but column 2 will have values up to 15 separated by ';' (semicolon).
ID Column1 Column2
--------------------------------------
1 T1 Re;BoRe;Va
I want to convert the above column data in to below JSON Format
{
"services":
[
{ "service": "T1"}
],
"additional_services":
[
{ "service": "Re" },
{ "service": "BoRe" },
{ "service": "Va" }
]
}
I have tried creating something like the below, but cannot get to the exact format that I am looking for
SELECT
REPLACE((SELECT d.Column1 AS services, d.column2 AS additional_services
FROM Table1 w (nolock)
INNER JOIN Table2 d (nolock) ON w.Id = d.Id
WHERE ID = 1
FOR JSON PATH), '\/', '/')
Please let me know if this is something we can achieve using T-SQL
As I mention in the comments, I strongly recommend you fix your design and normalise your design. Don't store delimited data in your database; Re;BoRe;Va should be 3 rows, not 1 delimited one. That doesn't mean you can't achieve what you want with your denormalised data, just that your design is flawed, and thus it needs being brought up.
One way to achieve what you're after is with some nested FOR JSON calls:
SELECT (SELECT V.Column1 AS service
FOR JSON PATH) AS services,
(SELECT SS.[value] AS service
FROM STRING_SPLIT(V.Column2,';') SS
FOR JSON PATH) AS additional_services
FROM (VALUES(1,'T1','Re;BoRe;Va'))V(ID,Column1,Column2)
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER;
This results in the following JSON:
{
"services": [
{
"service": "T1"
}
],
"additional_services": [
{
"service": "Re"
},
{
"service": "BoRe"
},
{
"service": "Va"
}
]
}
I'm trying to retrieve the health value from Snowflake semi structured data in a variant column called extra from table X.
An example of the code can be seen below:
[
{
"party":
"[{\"class\":\"Farmer\",\"gender\":\"Female\",\"ethnicity\":\"NativeAmerican\",\"health\":2},
{\"class\":\"Adventurer\",\"gender\":\"Male\",\"ethnicity\":\"White\",\"health\":3},
{\"class\":\"Farmer\",\"gender\":\"Male\",\"ethnicity\":\"White\",\"health\":0},
{\"class\":\"Banker\",\"gender\":\"Female\",\"ethnicity\":\"White\",\"health\":0}
}
]
I have tried reading the Snowflake documentation from https://community.snowflake.com/s/article/querying-semi-structured-data
I have also tried the following queries to flatten the query:
SELECT result.value:health AS PartyHealth
FROM X
WHERE value = 'Trail'
AND name = 'Completed'
AND PartyHealth > 0,
TABLE(FLATTEN(X, 'party')) result
AND
SELECT [0]['party'][0]['health'] AS Health
FROM X
WHERE value = 'Trail'
AND name = 'Completed'
AND PH > 0;
I am trying to retrieve the health value from table X from column extra which contains the the variant party, which has 4 repeating values [0-3]. Im not sure how to do this is someone able to tell me how to query semi structured data in Snowflake, considering the documentation doesn't make much sense?
First, the JSON value you posted seems wrong formatted (might be a copy paste issue).
Here's an example that works:
first your JSON formatted:
[{ "party": [ {"class":"Farmer","gender":"Female","ethnicity":"NativeAmerican","health":2}, {"class":"Adventurer","gender":"Male","ethnicity":"White","health":3}, {"class":"Farmer","gender":"Male","ethnicity":"White","health":0}, {"class":"Banker","gender":"Female","ethnicity":"White","health":0} ] }]
create a table to test:
CREATE OR REPLACE TABLE myvariant (v variant);
insert the JSON value into this table:
INSERT INTO myvariant SELECT PARSE_JSON('[{ "party": [ {"class":"Farmer","gender":"Female","ethnicity":"NativeAmerican","health":2}, {"class":"Adventurer","gender":"Male","ethnicity":"White","health":3}, {"class":"Farmer","gender":"Male","ethnicity":"White","health":0}, {"class":"Banker","gender":"Female","ethnicity":"White","health":0} ] }]');
now, to select a value you start from column name, in my case v, and as your JSON is an array inside, I specify first value [0], and from there expand, so something like this:
SELECT v[0]:party[0].health FROM myvariant;
Above gives me:
For the other rows you can simply do:
SELECT v[0]:party[1].health FROM myvariant;
SELECT v[0]:party[2].health FROM myvariant;
SELECT v[0]:party[3].health FROM myvariant;
Another option might be to make the data more like a table ... I find it easier to work with than the JSON :-)
Code at bottom - just copy/paste and it runs in Snowflake returning screenshot below.
Key Doco is Lateral Flatten
SELECT d4.path, d4.value
from
lateral flatten(input=>PARSE_JSON('[{ "party": [ {"class":"Farmer","gender":"Female","ethnicity":"NativeAmerican","health":2}, {"class":"Adventurer","gender":"Male","ethnicity":"White","health":3}, {"class":"Farmer","gender":"Male","ethnicity":"White","health":0}, {"class":"Banker","gender":"Female","ethnicity":"White","health":0} ] }]') ) as d ,
lateral flatten(input=> value) as d2 ,
lateral flatten(input=> d2.value) as d3 ,
lateral flatten(input=> d3.value) as d4
I have a query like (simplified):
SELECT
JSON_QUERY(r.SerializedData, '$.Values') AS [Values]
FROM
<TABLE> r
WHERE ...
The result is like this:
{ "2019":120, "20191":120, "201902":121, "201903":134, "201904":513 }
How can I remove the entries with a key length less then 6.
Result:
{ "201902":121, "201903":134, "201904":513 }
One possible solution is to parse the JSON and generate it again using string manipulations for keys with desired length:
Table:
CREATE TABLE Data (SerializedData nvarchar(max))
INSERT INTO Data (SerializedData)
VALUES (N'{"Values": { "2019":120, "20191":120, "201902":121, "201903":134, "201904":513 }}')
Statement (for SQL Server 2017+):
UPDATE Data
SET SerializedData = JSON_MODIFY(
SerializedData,
'$.Values',
JSON_QUERY(
(
SELECT CONCAT('{', STRING_AGG(CONCAT('"', [key] ,'":', [value]), ','), '}')
FROM OPENJSON(SerializedData, '$.Values') j
WHERE LEN([key]) >= 6
)
)
)
SELECT JSON_QUERY(d.SerializedData, '$.Values') AS [Values]
FROM Data d
Result:
Values
{"201902":121,"201903":134,"201904":513}
Notes:
It's important to note, that JSON_MODIFY() in lax mode deletes the specified key if the new value is NULL and the path points to a JSON object. But, in this specific case (JSON object with variable key names), I prefer the above solution.
I'm looking for the number 2 here... array_size appears to work on a variant list but is not doing so well on this json. Is there a clever way to do this? I don't know/probably can't trust the structure will only go this deep, and am hoping to use this as just another field on a query where I'm pulling out a bunch of other values out of the json; so ideally a solution allows this as well.
select dict, array_size(dict)
from (select parse_json('{
"partition": [
"partition_col"
],
"sample_weight": [
"sample_weight"
]
}') as dict)
In that case you can create a small Javascript UDF:
create or replace function count_keys(MYVAR variant)
returns float
language javascript
as '
return (Object.entries(MYVAR)).length
'
;
To call it:
select count_keys(parse_json(
'{
"partition": [
"partition_col"
],
"sample_weight": [
"sample_weight"
]
}')
)
;
Use flatten:
with dict as (
select parse_json('{
"partition": [
"partition_col"
],
"sample_weight": [
"sample_weight"
]
}') val
)
select val, count(*)
from dict,
lateral flatten(input => val)
group by val
;
I have the below array of an HTTP request, in JSON format:
[
{
"Code":"856956645",
"Type":"Colet",
"MeasuredWeight":0.0,
"VolumetricWeight":0.0,
"ConfirmationName":null,
"Observation":" 100 DE SFATURI OASELE",
"ResponseCode":null,
"Event":
[
{
"Date":"2018-11-16T16:22:29.397",
"EventId":73,
"Description":"Ridicare din comanda client",
"LocalityName":"BUCURESTI"
},
{
"Date":"2018-11-17T08:55:06.14",
"EventId":5,
"Description":"Spre destinatar ",
"LocalityName":"BUCURESTI"
}
]
}
]
How could I extract the value of Description element, within the second set of values. I tried with OPENJSON but I couldn't do it:
SELECT *
FROM OPENJSON(#json)
WITH (
Description nvarchar(100) '$.Event.Description'
);
Try nesting instead. Nor sure why your attempt didn't work; I've not had much use for OPENJSON as yet apart from when playing around, however, this works:
SELECT J.Code, J.[Type], E.[Description]
FROM OPENJSON(#json)
WITH (Code bigint '$.Code',
[Type] varchar(10) '$.Type',
[Event] nvarchar(MAX) AS JSON) J
CROSS APPLY OPENJSON([Event])
WITH ([Description] varchar(100) '$.Description',
EventID int '$.EventId') E
WHERE E.EventID = 5;
Edit: Worked out why your attempt wasn't working. The JSON you have has a new JSON object in the Event node, they're not simply properties, like in the documentation's second example here. The entities are wrapped in further brackets ([]), not just braces ({}), and hence why you have to parse the next layer again as a separate JSON object.