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JSON_ARRAYAGG SQL/JSON Function
SQL/JSON function
json_arrayagg
constructs a JSON array by aggregating information from multiple rows of a grouped SQL query as the array elements. The order of array elements reflects the query result order, by default, but you can use the
ORDER BY
clause to impose array element order.
You can use SQL/JSON functions
json_object
,
json_array
,
json_objectagg
, and
json_arrayagg
to construct JSON data from non-JSON data in the database. The JSON data is returned as a SQL value.
These generation functions make it easy to construct JSON data directly from a SQL query. They allow non-JSON data to be represented as JSON objects and JSON arrays. You can generate complex, hierarchical JSON documents by nesting calls to these functions. Nested subqueries can generate JSON collections that represent one-to-many relationships.
Foot 1
The Best Way to Construct JSON Data from Non-JSON Data
Alternatives to using the SQL/JSON generation functions are generally error prone or inefficient.
Using
string concatenation
to generate JSON documents is error prone. In particular, there are a number of complex rules that must be respected concerning when and how to escape special characters, such as double quotation marks (
"
). It is easy to overlook or misunderstand these rules, which can result in generating incorrect JSON data.
Reading non-JSON result sets from the database and using
client-side application code
to generate JSON data is typically quite inefficient, particularly due to network overhead. When representing one-to-many relationships as JSON data, multiple
SELECT
operations are often required, to collect all of the non-JSON data needed. If the documents to be generated represent multiple levels of one-to-many relationships then this technique can be quite costly.
The SQL/JSON generation functions do not suffer from such problems; they are designed for the job of constructing JSON data from non-JSON database data.
They always construct well-formed JSON documents.
By using SQL subqueries with these functions, you can generate an entire set of JSON documents using a single SQL statement, which allows the generation operation to be optimized.
Because only the generated documents are returned to a client, network overhead is minimized: there is at most one round trip per document generated.
Functions
json_object
and
json_array
construct a JSON object or array, respectively, given as arguments SQL name–value pairs and values, respectively. The number of arguments corresponds to the number of object members and array elements, respectively (except when an argument expression evaluates to SQL
NULL
and the
ABSENT ON NULL
clause applies).
Each name must have the syntax of a SQL identifier. Each value can be any SQL value, including a value computed using a scalar SQL (sub)query that returns at most one item (a single row with a single column — an error is raised if such a query argument returns more than one row.)
Functions
json_objectagg
, and
json_arrayagg
are
aggregate
SQL functions. They transform information that is contained in the rows of a grouped SQL query into JSON objects and arrays, respectively. Evaluation of the arguments determines the number of object members and array elements, respectively; that is, the size of the result reflects the current queried data.
For
json_objectagg
and
json_arrayagg
, the order of object members and array elements, respectively, is unspecified. For
json_arrayagg
, you can use an
ORDER BY
clause within the
json_arrayagg
invocation to control the array element order.
Handling of Input Values For SQL/JSON Generation Functions
The generation functions take SQL values as input and render them as JSON values inside the SQL value that is returned. How the input values are rendered as JSON depends on their SQL data type. By default, a SQL
NUMBER
value is rendered in the output as a JSON number, a SQL
VARCHAR2
value is rendered as a JSON string, and so on. For example, by default the
VARCHAR2
value
'{}'
is rendered as the JSON string
"{}"
.
In some cases you know or expect that an input value in fact already represents JSON data, and you want to communicate this to the generation function so that the value is kept as is. For example, if the input is
'{}'
then you might want it interpreted (rendered) as an empty JSON
object
,
{}
, not as a JSON
string
,
"{}"
.
You can do this by adding keywords
FORMAT JSON
after an input expression to declare that the value that results from it is to be considered as already representing JSON data. Equivalently, you can apply SQL function
treat
with keywords
AS JSON
to a generation-function input value — the effect is the same as using
FORMAT JSON
.
In many cases Oracle can determine automatically that an input value is in fact JSON data, in which case the input is treated as if it were followed by an explicit
FORMAT JSON
declaration. This is the case, for instance, if the value expression is itself an invocation of a SQL/JSON generation function or function
json_query
.
If you do
not
specify
FORMAT JSON
for a given input value, and if Oracle
cannot
determine that the value is JSON data, then it is assumed to be ordinary (non-JSON) SQL data. In that case it is serialized as follows (any other SQL value raises an error):
A
VARCHAR2
,
CLOB
, or
NVARCHAR
value is wrapped in double quotation marks (
"
), and characters are escaped when necessary to conform to the JSON standard.
A numeric value (
NUMBER
,
BINARY_DOUBLE
, or
BINARY_FLOAT
) is rendered as a JSON number. (It is not quoted.)
A
RAW
or
BLOB
value is rendered as a hexadecimal JSON string (with double quotation marks,
"
).
A time-related value (
DATE
,
TIMESTAMP
,
TIMESTAMP WITH TIME ZONE
,
TIMESTAMP WITH LOCAL TIME ZONE
,
INTERVAL YEAR TO MONTH
, or
INTERVAL DAY TO SECOND
) is rendered in a supported ISO 8601 format, and the result is enclosed in double quotation marks (
"
).
A
BOOLEAN
PL/SQL value is rendered as JSON
true
or
false
. (It is not quoted.)
A
NULL
value is rendered as JSON
null
, regardless of the
NULL
data type. (It is not quoted.)
Note:
For data types
CLOB
and
BLOB
, an empty instance is distinguished from
NULL
and is rendered as an empty JSON string (
""
). But for data types
VARCHAR2
,
NVARCHAR2
, and
RAW
, Oracle SQL treats an empty (zero-length) value as
NULL
, so do
not
expect such a value to be rendered as a JSON string.
The format of an input argument can affect the format of the data that is returned by the function. In particular, if an input is declared or automatically determined to be of format JSON then it is treated as JSON data when computing the return value.
Example 19-1
illustrates this — it explicitly uses
FORMAT JSON
to interpret the SQL string
"true"
as the JSON Boolean value
true
.
Oracle Database SQL Language Reference
for information about SQL/JSON function
json_array
Oracle Database SQL Language Reference
for information about SQL/JSON function
json_arrayagg
Oracle Database SQL Language Reference
for information about SQL/JSON function
json_object
Oracle Database SQL Language Reference
for information about SQL/JSON function
json_objectagg
Example 19-1 Declaring an Input Value To Be JSON
This example specifies
FORMAT JSON
for SQL string values
'true'
and
'false'
, in order that the JSON Boolean values
true
and
false
are used. Without specifying
FORMAT JSON
, the values of field
hasCommission
would be the JSON
string
values
"true"
and
"false"
, not the JSON
Boolean
values
true
and
false
.
SELECT json_object('name' VALUE first_name || ' ' || last_name,
'hasCommission' VALUE
CASE WHEN commission_pct IS NULL THEN 'false' ELSE 'true'
END FORMAT JSON)
FROM employees WHERE first_name LIKE 'W%';
JSON_OBJECT('NAME'ISFIRST_NAME||''||LAST_NAME,'
-----------------------------------------------
{"name":"William Gietz","hasCommission":false}
{"name":"William Smith","hasCommission":true}
{"name":"Winston Taylor","hasCommission":false}
SQL/JSON function json_object
constructs JSON objects from name–value pairs. Each pair is provided as an explicit argument. Each name of a pair must evaluate to a SQL identifier. Each value of a pair can be any SQL expression. The name and value are separated by keyword VALUE
.
The evaluated arguments you provide to json_object
are explicit object field names and field values. The resulting object has an member for each pair of name–value arguments you provide (except when an value expression evaluates to SQL NULL
and the ABSENT ON NULL
clause applies).
Example 19-2 Using JSON_OBJECT to Construct JSON Objects
This example constructs a JSON object for each employee of table hr.employees
(from standard database schema HR
) whose salary is less than 15000. The object includes, as the value of its field contactInfo
, an object with fields mail
and phone
.
Because the return value of json_object
is JSON data, FORMAT JSON
is deduced for the input format of field contactInfo
— the explicit FORMAT JSON
here is not needed.
SELECT json_object('id' VALUE employee_id,
'name' VALUE first_name || ' ' || last_name,
'hireDate' VALUE hire_date,
'pay' VALUE salary,
'contactInfo' VALUE json_object('mail' VALUE email,
'phone' VALUE phone_number)
FORMAT JSON)
FROM employees
WHERE salary > 15000;
-- The query returns rows such as this (pretty-printed here for clarity):
{"id":101,
"name":"Neena Kochhar",
"hireDate":"21-SEP-05",
"pay":17000,
"contactInfo":{"mail":"NKOCHHAR",
"phone":"515.123.4568"}}
Example 19-3 Using JSON_OBJECT With ABSENT ON NULL
This example queries table hr.locations
from standard database schema HR
to create JSON objects with fields city
and province
.
The default NULL
-handling behavior for json_object is NULL ON NULL
.
In order to prevent the creation of a field with a null
JSON value, the example uses ABSENT ON NULL
. The NULL
SQL value for column state_province
when column city
has value 'Singapore'
means that no province
field is created for that location.
SELECT JSON_OBJECT('city' VALUE city,
'province' VALUE state_province ABSENT ON NULL)
FROM locations
WHERE city LIKE 'S%';
JSON_OBJECT('CITY'ISCITY,'PROVINCE'ISSTATE_PROVINCEABSENTONNULL)
----------------------------------------------------------------
{"city":"Southlake","province":"Texas"}
{"city":"South San Francisco","province":"California"}
{"city":"South Brunswick","province":"New Jersey"}
{"city":"Seattle","province":"Washington"}
{"city":"Sydney","province":"New South Wales"}
{"city":"Singapore"}
{"city":"Stretford","province":"Manchester"}
{"city":"Sao Paulo","province":"Sao Paulo"}
Oracle Database SQL Language Reference for information about SQL/JSON function json_object
Oracle Database SQL Language Reference for SQL identifier syntax
SQL/JSON function json_array
constructs a JSON array from the results of evaluating its argument SQL expressions. Each argument can be any SQL expression. Array element order is the same as the argument order.
The evaluated arguments you provide to json_array
are explicit array element values. The resulting array has an element for each argument you provide (except when an argument expression evaluates to SQL NULL
and the ABSENT ON NULL
clause applies).
An argument expression that evaluates to a SQL number is converted to a JSON number. A non-NULL
and non-number argument value is converted to a JSON string.
Example 19-4 Using JSON_ARRAY to Construct a JSON Array
This example constructs a JSON object for each job in database table hr.jobs
(from standard database schema HR
). The fields of the objects are the job title and salary range. The salary range (field salaryRange
) is an array of two numeric values, the minimum and maximum salaries for the job. These values are taken from SQL columns min_salary
and max_salary
.
SELECT json_object('title' VALUE job_title,
'salaryRange' VALUE json_array(min_salary, max_salary))
FROM jobs;
JSON_OBJECT('TITLE'ISJOB_TITLE,'SALARYRANGE'ISJSON_ARRAY(MIN_SALARY,MAX_SALARY))
--------------------------------------------------------------------------------
{"title":"President","salaryRange":[20080,40000]}
{"title":"Administration Vice President","salaryRange":[15000,30000]}
{"title":"Administration Assistant","salaryRange":[3000,6000]}
{"title":"Finance Manager","salaryRange":[8200,16000]}
{"title":"Accountant","salaryRange":[4200,9000]}
{"title":"Accounting Manager","salaryRange":[8200,16000]}
{"title":"Public Accountant","salaryRange":[4200,9000]}
{"title":"Sales Manager","salaryRange":[10000,20080]}
{"title":"Sales Representative","salaryRange":[6000,12008]}
{"title":"Purchasing Manager","salaryRange":[8000,15000]}
{"title":"Purchasing Clerk","salaryRange":[2500,5500]}
{"title":"Stock Manager","salaryRange":[5500,8500]}
{"title":"Stock Clerk","salaryRange":[2008,5000]}
{"title":"Shipping Clerk","salaryRange":[2500,5500]}
{"title":"Programmer","salaryRange":[4000,10000]}
{"title":"Marketing Manager","salaryRange":[9000,15000]}
{"title":"Marketing Representative","salaryRange":[4000,9000]}
{"title":"Human Resources Representative","salaryRange":[4000,9000]}
{"title":"Public Relations Representative","salaryRange":[4500,10500]}
SQL/JSON function json_objectagg
constructs a JSON object by aggregating information from multiple rows of a grouped SQL query as the object members.
Unlike the case for SQL/JSON function json_object
, where the number of members in the resulting object directly reflects the number of arguments, for json_objectagg
the size of the resulting object reflects the current queried data. It can thus vary, depending on the data that is queried.
Example 19-5 Using JSON_OBJECTAGG to Construct a JSON Object
This example constructs a single JSON object from table hr.departments
(from standard database schema HR
) using field names taken from column department_name
and field values taken from column department_id
.
SELECT json_objectagg(department_name VALUE department_id) FROM departments;
-- The returned object is pretty-printed here for clarity.
-- The order of the object members is arbitrary.
JSON_OBJECTAGG(DEPARTMENT_NAMEISDEPARTMENT_ID)
----------------------------------------------
{"Administration": 10,
"Marketing": 20,
"Purchasing": 30,
"Human Resources": 40,
"Shipping": 50,
"IT": 60,
"Public Relations": 70,
"Sales": 80,
"Executive": 90,
"Finance": 100,
"Accounting": 110,
"Treasury": 120,
"Corporate Tax": 130,
"Control And Credit": 140,
"Shareholder Services": 150,
"Benefits": 160,
"Manufacturing": 170,
"Construction": 180,
"Contracting": 190,
"Operations": 200,
"IT Support": 210,
"NOC": 220,
"IT Helpdesk": 230,
"Government Sales": 240,
"Retail Sales": 250,
"Recruiting": 260,
"Payroll": 270}
SQL/JSON function json_arrayagg
constructs a JSON array by aggregating information from multiple rows of a grouped SQL query as the array elements. The order of array elements reflects the query result order, by default, but you can use the ORDER BY
clause to impose array element order.
Unlike the case for SQL/JSON function json_array
, where the number of elements in the resulting array directly reflects the number of arguments, for json_arrayagg
the size of the resulting array reflects the current queried data. It can thus vary, depending on the data that is queried.
Example 19-6 Using JSON_ARRAYAGG to Construct a JSON Array
This example constructs a JSON object for each employee of table hr.employees
(from standard database schema HR
) who is a manager in charge of at least six employees. The objects have fields for the manager id number, manager name, number of employees reporting to the manager, and id numbers of those employees.
The order of the employee id numbers in the array is determined by the ORDER BY
clause for json_arrayagg
. The default direction for ORDER BY
is ASC
(ascending). The array elements, which are numeric, are in ascending numerical order.
SELECT json_object('id' VALUE mgr.employee_id,
'manager' VALUE (mgr.first_name || ' '|| mgr.last_name),
'numReports' VALUE count(rpt.employee_id),
'reports' VALUE json_arrayagg(rpt.employee_id
ORDER BY rpt.employee_id))
FROM employees mgr, employees rpt
WHERE mgr.employee_id = rpt.manager_id
GROUP BY mgr.employee_id, mgr.last_name, mgr.first_name
HAVING count(rpt.employee_id) > 6;
-- The returned object is pretty-printed here for clarity.
JSON_OBJECT('ID'ISMGR.EMPLOYEE_ID,'MANAGER'VALUE(MGR.FIRST_NAME||''||MGR.LAST_NAME)
-----------------------------------------------------------------------------------
{"id": 100,
"manager": "Steven King",
"numReports": 14,
"reports": [101,102,114,120,121,122,123,124,145,146,147,148,149,201]}
{"id": 120,
"manager": "Matthew Weiss",
"numReports": 8,
"reports": [125,126,127,128,180,181,182,183]}
{"id": 121,
"manager": "Adam Fripp",
"numReports": 8,
"reports": [129,130,131,132,184,185,186,187]}
{"id": 122,
"manager": "Payam Kaufling",
"numReports": 8,
"reports": [133,134,135,136,188,189,190,191]}
{"id": 123,
"manager": "Shanta Vollman",
"numReports": 8,
"reports": [137,138,139,140,192,193,194,195]}
{"id": 124,
"manager": "Kevin Mourgos",
"numReports": 8,
"reports": [141,142,143,144,196,197,198,199]}