Example: Updating Rows
CREATE TABLE People (
id INTEGER,
info JSON,
PRIMARY KEY(id))
INSERT INTO People VALUES (
0,
{
"firstName":"John",
"lastName":"Doe",
"profession":"software engineer",
"income":200000,
"address": {
"city" : "San Fransisco",
"state" : "CA",
"phones" : [
{ "areacode":415, "number":2840060, "kind":"office" },
{ "areacode":650, "number":3789021, "kind":"mobile" },
{ "areacode":415, "number":6096010, "kind":"home" }
]
},
"children": {
"Anna" : {
"age" : 10,
"school" : "school_1",
"friends" : ["Anna", "John", "Maria"]
},
"Ron" : { "age" : 2 },
"Mary" : {
"age" : 7,
"school" : "school_3",
"friends" : ["Anna", "Mark"]
}
}
}
)
The following update statement updates various fields in the above row:
UPDATE People p
SET p.info.profession = "surfing instructor",
SET p.info.address.city = "Santa Cruz",
SET p.info.income = p.info.income / 10,
SET p.info.children.values().age = $ + 1,
ADD p.info.address.phones
0 { "areacode":831, "number":5294368, "kind":"mobile" },
REMOVE p.info.address.phones [$element.kind = "office"],
PUT p.info.children.Ron { "friends" : ["Julie"] },
ADD p.info.children.values().friends seq_concat("Ada", "Aris")
WHERE id = 0
RETURNING *
After the update, the row looks like this:
{
"id":0,
"info":{
"firstName":"John",
"lastName":"Doe",
"profession":"surfing instructor",
"income":20000,
"address":{
"city":"Santa Cruz",
"phones":[
{"areacode":831,"kind":"mobile","number":5294368},
{"areacode":650,"kind":"mobile","number":3789021},
{"areacode":415,"kind":"home","number":6096010}
],
"state":"CA"
},
"children":{
"Anna":{
"age":11,
"friends":["Anna","John","Maria","Ada","Aris"],
"school":"school_1"
},
"Ron":{
"age":3,
"friends":["Julie","Ada","Aris"]
},
"Mary":{
"age":8,
"friends":["Anna","Mark","Ada","Aris"],
"school":"school_3"
}
}
}
}
The first two SET clauses change the profession and city of John Doe. The third SET reduces his income to one-tenth. The fourth SET increases the age of his children by 1. Notice the use of the $ variable here: the expression p.info.children.values().age returns 3 ages; The SET will iterate over these ages, bind the $ variable to each age in turn, compute the expression $ + 1 for each age, and update the age with the new value. Notice that the income update could (and can) also have used a $ variable: set p.info.income = $ / 10. This would have saved the re-evaluation of the p.info.income path on the right-hand side or the "=".
The ADD clause adds a new phone at position 0 inside the phones array. The REMOVE removes all the office phones (only one in this example). The PUT clause adds a friend for Ron. In this clause, the expression p.info.children.Ron returns the value associated with the Ron child. This value is a map (the json object { "age" : 3 }) and becomes the target of the update. The 2nd expression in the PUT ({ "friends" : ["Julie"] }) constructs and returns a new map. The fields of this map are added to the target map. Finally, the last ADD clause adds the same two new friends to each child. See seq_concat function function.
Notice that the update query in this example would have been exactly the same if instead of type JSON, the info column had the following RECORD type:
RECORD(
firstName STRING,
lastName STRING,
profession STRING,
income INTEGER,
address RECORD(
city STRING,
state STRING,
phones ARRAY(
RECORD(
areacode INTEGER,
number INTEGER,
kind STRING
)
)
),
children MAP(
RECORD(
age INTEGER,
school STRING,
friends ARRAY(STRING)
)
)
)