DB2 10.5 for Linux, UNIX, and Windows

JSON documents

JSON documents consist of fields, which are name-value pair objects. The fields can be in any order, and be nested or arranged in arrays.

There is no enforcement of document structures. Other documents in the same collection might therefore have a subset of these fields, extra fields, or different representations of the same field.

The field name is always of String type and serves as key for the field, and, therefore, it must be unique. The values can be any of the supported JSON data types. The first six data types, from java.lang.String to java.util.Date, are recognized by JSON. The types that follow are extensions that can be stored in the JSON store, but need to be represented externally with the MongoDB-defined functions, or in a Java™ language construct.

Table 1. JSON data types
Data type	Example in JSON format
java.lang.String	"string"
java.lang.Integer	3
java.lang.Long	4294967296
java.lang.Double	6.2
java.lang.Byte []	true / false
java.util.Date (millisecond precision, in Coordinated Universal Time)	{ "$binary": "(base64-encoded value)", "$type": "0" }
java.util.regex.Pattern	{ "$date" : "1998-03-11T17:14:12.456Z" }
java.util.regex.Pattern	{ "$regex" : "ab*" , "$options" : "" }
java.util.UUID	{ "$uuid" : "fb46f9a6-13df-41a2-a4e3-c77e85e747dd" }
com.ibm.nosql.bson.types.ObjectId	{ "$oid" : "51d2f200eefac17ea91d6831" }
com.ibm.nosql.bson.types.Code	{ "$code" : "mycode" }
com.ibm.nosql.bson.types.CodeWScope	{ "$code" : "i=i+1", "$scope" : {} }
com.ibm.nosql.json.api.BasicDBObject	{ "a" : 1, "b": { "c" : 2 } }
com.ibm.nosql.json.api.BasicDBList	[1 , 2, "3", "abc", 5]

For Date string values, the client converts the value to Coordinated Universal Time to be stored in DB2® databases. It is also retrieved as a Date in Coordinated Universal Time format.

The following example represents a sample JSON document with array values and nested objects:

9
{
	name:"Joe",
	age:25,
	phone:["555-666-7777", "444-789-1234"],
	homeAddress:
		{street:"Sycamore Avenue",
		city: “Gilroy”,
		zipcode:"95046"
		}
	businessAddress:
		{
		street:"Bailey Avenue",
		City: “San Jose”,
		zipcode:"95141"
		}
}