Related
I have this table which is very simple with this data
CREATE TABLE #Prices
(
ProductId int,
SizeId int,
Price int,
Date date
)
INSERT INTO #Prices
VALUES (1, 1, 100, '2020-01-01'),
(1, 1, 120, '2020-02-01'),
(1, 1, 130, '2020-03-01'),
(1, 2, 100, '2020-01-01'),
(1, 2, 100, '2020-02-01'),
(2, 1, 100, '2020-01-01'),
(2, 1, 120, '2020-02-01'),
(2, 1, 130, '2020-03-01'),
(2, 2, 100, '2020-01-01'),
(2, 2, 100, '2020-02-01')
I would like to format the output to be something like this:
{
"Products": [
{
"Product": 2,
"UnitSizes": [
{
"SizeId": 1,
"PerDate": [
{
"Date": "2020-01-02",
"Price": 870.0
},
{
"Date": "2021-04-29",
"Price": 900.0
}
]
},
{
"SizeId": 2,
"PerDate": [
{
"Date": "2020-01-02",
"Price": 435.0
},
{
"Date": "2021-04-29",
"Price": 450.0
}
]
}
]
},
{
"Product": 4,
"UnitSizes": [
{
"SizeId": 1,
"PerDate": [
{
"Date": "2020-01-02",
"Price": 900.0
}
]
}
]
}
]
}
I almost have it but I don't know how to format to get the array inside 'PerDate'. This is what I have
SELECT
ProductId AS [Product],
SizeId AS 'Sizes.SizeId',
date AS 'Sizes.PerDate.Date',
price AS 'Sizes.PerDate.Price'
FROM
#Prices
ORDER BY
ProductId, [Sizes.SizeId], Date
FOR JSON PATH, ROOT('Products')
I have tried with FOR JSON AUTO and nothing, I've tried with JSON_QUERY() but I was not able to achieve the result I want.
Every help will be very appreciated.
Thanks
Unfortunately, SQL Server does not have the JSON_AGG function, which means you would normally need to use a number of correlated subqueries and keep on rescanning the base table.
However, we can simulate it by using STRING_AGG against single JSON objects generated in an APPLY. This means that we only scan the base table once.
Use of JSON_QUERY with no path prevents double-escaping
WITH PerDate AS (
SELECT
p.ProductId,
p.SizeId,
PerDate = '[' + STRING_AGG(j.PerDate, ',') WITHIN GROUP (ORDER BY p.Date) + ']'
FROM #Prices AS p
CROSS APPLY ( -- This produces multiple rows of single JSON objects
SELECT p.Date, p.Price
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
) j(PerDate)
GROUP BY
p.ProductId,
p.SizeId
),
UnitSizes AS (
SELECT
p.ProductId,
UnitSizes = '[' + STRING_AGG(j.UnitSizes, ',') WITHIN GROUP (ORDER BY p.SizeId) + ']'
FROM PerDate p
CROSS APPLY (
SELECT p.SizeId, PerDate = JSON_QUERY(p.PerDate)
FOR JSON PATH, WITHOUT_ARRAY_WRAPPER
) j(UnitSizes)
GROUP BY
p.ProductId
)
SELECT
Product = p.ProductId,
UnitSizes = JSON_QUERY(p.UnitSizes)
FROM UnitSizes p
ORDER BY p.ProductId
FOR JSON PATH, ROOT('Products');
db<>fiddle
This is one way of doing it
DROP TABLE IF EXISTS #Prices
CREATE TABLE #Prices
(
ProductId INT,
SizeId INT,
Price INT,
Date DATE
)
-- SQL Prompt formatting off
INSERT INTO #Prices
VALUES (1, 1, 100, '2020-01-01'),
(1, 1, 120, '2020-02-01'),
(1, 1, 130, '2020-03-01'),
(1, 2, 100, '2020-01-01'),
(1, 2, 100, '2020-02-01'),
(2, 1, 100, '2020-01-01'),
(2, 1, 120, '2020-02-01'),
(2, 1, 130, '2020-03-01'),
(2, 2, 100, '2020-01-01'),
(2, 2, 100, '2020-02-01')
-- SQL Prompt formatting on
SELECT m.ProductId AS Product,
(
SELECT s.SizeId,
(
SELECT p.Date,
p.Price
FROM #Prices AS p
WHERE p.SizeId = s.SizeId
GROUP BY p.Date,
p.Price
ORDER BY p.Date
FOR JSON PATH
) AS PerDate
FROM #Prices AS s
WHERE s.ProductId = m.ProductId
GROUP BY s.SizeId
ORDER BY s.SizeId
FOR JSON PATH
) AS UnitSizes
FROM #Prices AS m
GROUP BY m.ProductId
ORDER BY m.ProductId
FOR JSON PATH, ROOT('Products')
Output:
{
"Products":
[
{
"Product": 1,
"UnitSizes":
[
{
"SizeId": 1,
"PerDate":
[
{
"Date": "2020-01-01",
"Price": 100
},
{
"Date": "2020-02-01",
"Price": 120
},
{
"Date": "2020-03-01",
"Price": 130
}
]
},
{
"SizeId": 2,
"PerDate":
[
{
"Date": "2020-01-01",
"Price": 100
},
{
"Date": "2020-02-01",
"Price": 100
}
]
}
]
},
{
"Product": 2,
"UnitSizes":
[
{
"SizeId": 1,
"PerDate":
[
{
"Date": "2020-01-01",
"Price": 100
},
{
"Date": "2020-02-01",
"Price": 120
},
{
"Date": "2020-03-01",
"Price": 130
}
]
},
{
"SizeId": 2,
"PerDate":
[
{
"Date": "2020-01-01",
"Price": 100
},
{
"Date": "2020-02-01",
"Price": 100
}
]
}
]
}
]
}
Is there a way to create a treetable dynamically in a way to have a dynamic number of columns and rows? Lets say the attributes in the model are called 'ColX' where X stands for a counter. For every such attribute I want to create a column.
An example for a model that I found is working with a treetable looks like and would produce 3 columns and 2 first level rows:
{
"Nodes": [
{
"NodeID": 1,
"HierarchyLevel": 0,
"Description": "Level1Node1",
"ParentNodeID": null,
"DrillState": "expanded",
"Col1": "col1-val1",
"Col2": "col1-val2",
"Col3": "col1-val3",
"data": [
{
"NodeID": 11,
"HierarchyLevel": 2,
"Description": "11",
"ParentNodeID": 1,
"DrillState": "leaf",
"Col1": "col11-val1",
"Col2": "col11-val2",
"Col3": "col11-val3"
},
{
"NodeID": 12,
"HierarchyLevel": 2,
"Description": "12",
"ParentNodeID": 1,
"DrillState": "leaf",
"Col1": "col12-val1",
"Col2": "col12-val2",
"Col3": "col12-val3"
},
{
"NodeID": 16,
"HierarchyLevel": 2,
"Description": "1x",
"ParentNodeID": 1,
"DrillState": "leaf",
"Col1": "col13-val1",
"Col2": "col13-val2",
"Col3": "col13-val3"
}
]
},
{
"NodeID": 2,
"HierarchyLevel": 0,
"Description": "Level1Node2",
"ParentNodeID": null,
"DrillState": "expanded",
"Col1": "col2-val1",
"Col2": "col2-val2",
"Col3": "col2-val3",
"data": [
{
"NodeID": 17,
"HierarchyLevel": 2,
"Description": "21",
"ParentNodeID": 2,
"DrillState": "leaf",
"Col1": "col21-val1",
"Col2": "col21-val2",
"Col3": "col21-val3"
}
]
}
]
}
I have a Json like this (it is contained in a clob variable):
{"id": "33", "type": "abc", "val": "2", "cod": "", "sg1": "1", "sg2": "1"}
{"id": "359", "type": "abcef", "val": "52", "cod": "aa", "sg1": "", "sg2": "0"}
…
I need to remove " from values of: id, val, sg1, sg2
Is it possibile?
For example, I need to obtain this:
{"id": 33, "type": "abc", "val": 2, "cod": "", "sg1": 1, "sg2": 1}
{"id": 359, "type": "abcef", "val": 52, "cod": "aa", "sg1": , "sg2": 0}
…
If you are using Oracle 12 (R2?) or later then you can convert your JSON to the appropriate data types and then convert it back to JSON.
Oracle 18 Setup:
CREATE TABLE test_data ( value CLOB );
INSERT INTO test_data ( value )
VALUES ( '{"id": "33", "type": "abc", "val": "2", "cod": "", "sg1": "1", "sg2": "1"}' );
INSERT INTO test_data ( value )
VALUES ( '{"id": "359", "type": "abcef", "val": "52", "cod": "aa", "sg1": "", "sg2": "0"}' );
Query:
SELECT JSON_OBJECT(
'id' IS j.id,
'type' IS j.typ,
'val' IS j.val,
'cod' IS j.cod,
'sg1' IS j.sg1,
'sg2' IS j.sg2
) AS JSON
FROM test_data t
CROSS JOIN
JSON_TABLE(
t.value,
'$'
COLUMNS
id NUMBER(5,0) PATH '$.id',
typ VARCHAR2(10) PATH '$.type',
val NUMBER(5,0) PATH '$.val',
cod VARCHAR2(10) PATH '$.cod',
sg1 NUMBER(5,0) PATH '$.sg1',
sg2 NUMBER(5,0) PATH '$.sg2'
) j
Output:
| JSON |
| :--------------------------------------------------------------- |
| {"id":33,"type":"abc","val":2,"cod":null,"sg1":1,"sg2":1} |
| {"id":359,"type":"abcef","val":52,"cod":"aa","sg1":null,"sg2":0} |
Or, if you want to use regular expressions (you shouldn't if you have the choice and should use a proper JSON parser instead) then:
Query 2:
SELECT REGEXP_REPLACE(
REGEXP_REPLACE(
value,
'"(id|val|sg1|sg2)": ""',
'"\1": "null"'
),
'"(id|val|sg1|sg2)": "(\d+|null)"',
'"\1": \2'
) AS JSON
FROM test_data
Output:
| JSON |
| :-------------------------------------------------------------------------- |
| {"id": 33, "type": "abc", "val": 2, "cod": "", "sg1": 1, "sg2": 1} |
| {"id": 359, "type": "abcef", "val": 52, "cod": "aa", "sg1": null, "sg2": 0} |
db<>fiddle here
I want to use the create_coco_tf_record-script provided by tensorflow, to convert the following simple label definition in coco json format to TFRecord:
"info": {
"year": 2018,
"version": null,
"description": "TransferLearningTest",
"contributor": "ralph#r4robotics.com.au",
"url": "labelbox.io",
"date_created": "2018-03-25T08:30:27.427851+00:00"
},
"images": [{
"id": "cjf6gxqjw2fho01619gre5j0y",
"width": 615,
"height": 409,
"file_name": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles1.jpg?alt=media&token=b381c976-da30-49d7-8e95-eb4ae8588354",
"license": null,
"flickr_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles1.jpg?alt=media&token=b381c976-da30-49d7-8e95-eb4ae8588354",
"coco_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles1.jpg?alt=media&token=b381c976-da30-49d7-8e95-eb4ae8588354",
"date_captured": null
}, {
"id": "cjf6gyhtl55sv01385xtqjrqi",
"width": 259,
"height": 194,
"file_name": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles2.jpg?alt=media&token=9b274e2e-c541-4e80-8f3d-b198f3ba9b4d",
"license": null,
"flickr_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles2.jpg?alt=media&token=9b274e2e-c541-4e80-8f3d-b198f3ba9b4d",
"coco_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles2.jpg?alt=media&token=9b274e2e-c541-4e80-8f3d-b198f3ba9b4d",
"date_captured": null
}, {
"id": "cjf6gzj9v2g1h0161bwh18chv",
"width": 277,
"height": 182,
"file_name": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles3.jpg?alt=media&token=3cfc13ca-432d-4501-b574-00d3874a4682",
"license": null,
"flickr_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles3.jpg?alt=media&token=3cfc13ca-432d-4501-b574-00d3874a4682",
"coco_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles3.jpg?alt=media&token=3cfc13ca-432d-4501-b574-00d3874a4682",
"date_captured": null
}, {
"id": "cjf6h0p9n55wz0178pg79lc3c",
"width": 301,
"height": 167,
"file_name": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles4.jpg?alt=media&token=d2660bc4-d576-45f0-8de6-557270fc683d",
"license": null,
"flickr_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles4.jpg?alt=media&token=d2660bc4-d576-45f0-8de6-557270fc683d",
"coco_url": "https://firebasestorage.googleapis.com/v0/b/labelbox-193903.appspot.com/o/cjf6gtsr950sr0125idy65yiy%2Ff245e964-d756-4c01-98de-b6e5a9070588%2Fbottles4.jpg?alt=media&token=d2660bc4-d576-45f0-8de6-557270fc683d",
"date_captured": null
}],
"annotations": [{
"id": 1,
"image_id": "cjf6gxqjw2fho01619gre5j0y",
"category_id": 1,
"segmentation": [
[118.39765618513167, 313.457848898712, 179.7169976455091, 299.1734470204843, 294.6908226914901, 310.3222212573321, 337.1962867729657, 334.7101881586143, 366.4623832276035, 338.89097185223864, 372.03689297966736, 385.5765403887654, 332.31863061175864, 389.75732408238974, 282.84505592143563, 406.48051201843583, 215.9512047089942, 408.5708772844735, 192.2596180064203, 390.4541125044023, 151.8445552101198, 403.6933051688366, 105.1582353958287, 376.51813141795526, 118.39765618513167, 313.457848898712]
],
"area": 22106.876283900496,
"bbox": [105.1582353958287, 0.42912271552648545, 266.8786575838387, 109.39743026398922],
"iscrowd": 0
}, {
"id": 2,
"image_id": "cjf6gxqjw2fho01619gre5j0y",
"category_id": 1,
"segmentation": [
[160.20631983821562, 142.04523900617488, 195.04687288245222, 131.24488556110788, 308.62704390918475, 134.03209241070698, 356.01021731433246, 152.1488571907783, 381.7922053020817, 150.75522718520426, 384.57951334057844, 186.64038911511503, 349.7389071338769, 187.68559832890833, 317.6856089656722, 202.3183678373679, 159.50946624735892, 195.3503772941444, 160.20631983821562, 142.04523900617488]
],
"area": 13123.705213053147,
"bbox": [159.50946624735892, 206.6816321626321, 225.07004709321953, 71.07348227626002],
"iscrowd": 0
}, {
"id": 3,
"image_id": "cjf6gyhtl55sv01385xtqjrqi",
"category_id": 1,
"segmentation": [
[80.06035395893144, 68.18619344603749, 119.11342792196902, 74.69491256085784, 131.84812313721997, 72.14801308536389, 177.97602777539703, 78.09078572494903, 187.59778022105084, 91.67421361042045, 203.1624077063576, 93.37213939731716, 201.18146375358646, 112.04938782407424, 184.76784795099502, 111.200414135477, 169.20322046568833, 122.51994816851872, 128.16920254987957, 117.42614921753086, 114.86852951688535, 114.03029764373744, 93.07803808305403, 114.31328167650393, 70.43857992260781, 103.2767316762287, 80.06035395893144, 68.18619344603749]
],
"area": 4995.907009222967,
"bbox": [70.43857992260781, 71.48005183148128, 132.7238277837498, 54.33375472248123],
"iscrowd": 0
}, {
"id": 4,
"image_id": "cjf6gzj9v2g1h0161bwh18chv",
"category_id": 1,
"segmentation": [
[173.46162883883662, 160.28013107383993, 255.65715601241382, 148.2998138472238, 266.2728180897869, 177.11325728633884, 184.68389092165103, 182.8759506021435, 159.20627416758742, 180.1462513325615, 154.35340470313542, 170.74397441725296, 175.28142885516084, 167.7109803710303, 173.46162883883662, 160.28013107383993]
],
"area": 2509.1082874191734,
"bbox": [154.35340470313542, -0.8759506021434983, 111.91941338665146, 34.576136754919716],
"iscrowd": 0
}, {
"id": 5,
"image_id": "cjf6gzj9v2g1h0161bwh18chv",
"category_id": 1,
"segmentation": [
[37.58112185203197, 87.03332022958155, 45.16373762158412, 93.40262623857566, 94.90570169790779, 106.44448675338808, 106.73458692647054, 87.03332022958155, 46.680260775494574, 73.08155224493905, 40.31086815713212, 74.901344044691, 33.63817553604898, 74.901344044691, 27.875382923127926, 80.9673321371363, 37.58112185203197, 87.03332022958155]
],
"area": 1386.09176276128,
"bbox": [27.875382923127926, 75.55551324661192, 78.85920400334261, 33.36293450844903],
"iscrowd": 0
}, {
"id": 6,
"image_id": "cjf6gzj9v2g1h0161bwh18chv",
"category_id": 1,
"segmentation": [
[200.7590456092244, 136.92608617388885, 181.95412147624396, 120.09295996138994, 234.4258318576678, 85.2135284298296, 255.05055600697247, 103.71478748380605, 200.7590456092244, 136.92608617388885]
],
"area": 1614.301579806095,
"bbox": [181.95412147624396, 45.073913826111145, 73.09643453072852, 51.71255774405926],
"iscrowd": 0
}, {
"id": 7,
"image_id": "cjf6h0p9n55wz0178pg79lc3c",
"category_id": 1,
"segmentation": [
[17.847508506087518, 28.63952607163654, 66.60858665657888, 24.08859036914734, 77.98617155836023, 14.986669362689923, 145.27644948557162, 14.49906202292621, 147.5519565454611, 51.881911126804255, 75.0605019090974, 56.10780833710362, 64.0079859014193, 47.98110201017366, 24.3489855928197, 53.34473314609532, 17.847508506087518, 28.63952607163654]
],
"area": 4189.730491764894,
"bbox": [17.847508506087518, 110.89219166289638, 129.7044480393736, 41.60874631417741],
"iscrowd": 0
}, {
"id": 8,
"image_id": "cjf6h0p9n55wz0178pg79lc3c",
"category_id": 1,
"segmentation": [
[223.94433711573117, 23.27591973645434, 257.10186033759857, 27.82685543894354, 261.32783036444124, 48.306165303102944, 179.73427308501883, 104.86804629868364, 145.27644948557162, 113.3198159185429, 128.37261898053467, 122.42173692500033, 111.46876367433086, 108.76885541531423, 131.29826382863067, 96.09118858515549, 137.14960312715638, 77.56230808005091, 223.94433711573117, 23.27591973645434]
],
"area": 6031.236484118768,
"bbox": [111.46876367433086, 44.57826307499967, 149.85906669011038, 99.14581718854599],
"iscrowd": 0
}, {
"id": 9,
"image_id": "cjf6h0p9n55wz0178pg79lc3c",
"category_id": 1,
"segmentation": [
[26.299423758605975, 125.34733136210352, 40.60267830965016, 111.53193060632253, 117.97024076106304, 72.6862842838929, 133.57379568968702, 80.81299061082292, 132.59856420621048, 93.16559414805232, 111.46876367433086, 115.2702204768582, 64.33305479552251, 138.67514957886033, 46.128923912905776, 139.65033945764822, 23.37375410934314, 148.75226046410563, 8.095292875989244, 141.11316147693933, 26.299423758605975, 125.34733136210352]
],
"area": 3857.6591542480846,
"bbox": [8.095292875989244, 18.24773953589436, 125.47850281369777, 76.06597618021274],
"iscrowd": 0
}],
"licenses": [],
"categories": [{
"supercategory": "Bottle",
"id": 1,
"name": "Bottle"
}]
}
But when I run the script using
with open('coco_labels.json') as json_data:
label_info = json.load(json_data)
IMAGE_FOLDER = "coco_images"
with tf.python_io.TFRecordWriter("training.record") as writer:
for i,image in enumerate(label_info["images"]):
img_data = requests.get(image["file_name"]).content
image_name = "image"+str(i)+".jpg"
image_path = os.path.join(IMAGE_FOLDER,image_name)
with open(image_path, 'wb') as handler:
handler.write(img_data)
image["file_name"] = image_name
tf_example = create_coco_tf_record.create_tf_example(image,
label_info["annotations"][i],
IMAGE_FOLDER,
label_info["categories"]
)
writer.write(tf_example.SerializeToString())
I get the error
(image, annotations_list, image_dir, category_index, include_masks)
124 num_annotations_skipped = 0
125 for object_annotations in annotations_list:
--> 126 (x, y, width, height) = tuple(object_annotations['bbox'])
127 if width <= 0 or height <= 0:
128 num_annotations_skipped += 1
TypeError: string indices must be integers
What could be the problem?
Each image is supposed to receive a list of annotations, and you are providing a single one. Making it a single element list should solve your error.
Ideally, make each item of images in your json be a list itself. As a quick fix, embrace label_info["annotations"][i] in brackets:
[label_info["annotations"][i]]
Say I have the following product schema which has common properties like title etc, as well as variants in an array.
How would I go about ordering the products by price lowest to highest?
drop table if exists product;
create table product (
id int,
data jsonb
);
insert into product values (1, '
{
"product_id": 10000,
"title": "product 10000",
"variants": [
{
"variantId": 100,
"price": 9.95,
"sku": 100,
"weight": 388
},
{
"variantId": 101,
"price": 19.95,
"sku": 101,
"weight": 788
}
]
}');
insert into product values (2, '
{
"product_id": 10001,
"title": "product 10001",
"variants": [
{
"variantId": 200,
"price": 89.95,
"sku": 200,
"weight": 11
},
{
"variantId": 201,
"price": 99.95,
"sku": 201,
"weight": 22
}
]
}');
insert into product values (3, '
{
"product_id": 10002,
"title": "product 10002",
"variants": [
{
"variantId": 300,
"price": 1.00,
"sku": 300,
"weight": 36
}
]
}');
select * from product;
1;"{"title": "product 10000", "variants": [{"sku": 100, "price": 9.95, "weight": 388, "variantId": 100}, {"sku": 101, "price": 19.95, "weight": 788, "variantId": 101}], "product_id": 10000}"
2;"{"title": "product 10001", "variants": [{"sku": 200, "price": 89.95, "weight": 11, "variantId": 200}, {"sku": 201, "price": 99.95, "weight": 22, "variantId": 201}], "product_id": 10001}"
3;"{"title": "product 10002", "variants": [{"sku": 300, "price": 1.00, "weight": 36, "variantId": 300}], "product_id": 10002}"
Use jsonb_array_elements() to unnest variants, e.g.:
select
id, data->'product_id' product_id,
var->'sku' as sku, var->'price' as price
from
product, jsonb_array_elements(data->'variants') var
order by 4;
id | product_id | sku | price
----+------------+-----+-------
3 | 10002 | 300 | 1.00
1 | 10000 | 100 | 9.95
1 | 10000 | 101 | 19.95
2 | 10001 | 200 | 89.95
2 | 10001 | 201 | 99.95
(5 rows)