Creating a Table With a JSON Column

4 Creating a Table With a JSON Column

You can create a table that has JSON columns. You use SQL condition is json as a check constraint to ensure that data inserted into a column is (well-formed) JSON data. Oracle recommends that you always use an is_json check constraint when you create a column intended for JSON data.

Example 4-1 and Example 4-2 illustrate this. They create and fill a table that holds data used in examples elsewhere in this documentation.

For brevity, only two rows of data (one JSON document) are inserted in Example 4-2.

Note:

SQL/JSON conditions IS JSON and IS NOT JSON return true or false for any non-NULL SQL value. But they both return unknown (neither true nor false) for SQL NULL. When used in a check constraint, they do not prevent a SQL NULL value from being inserted into the column. (But when used in a SQL WHERE clause, SQL NULL is never returned.)

It is true that a check constraint can reduce performance for data insertion. If you are sure that your application inserts only well-formed JSON data into a particular column, then consider disabling the check constraint, but do not drop the constraint.

See Also:

Loading External JSON Data for the creation of the full table j_purchaseorder
Oracle Database SQL Language Reference for information about CREATE TABLE

Example 4-1 Using IS JSON in a Check Constraint to Ensure JSON Data is Well-Formed

CREATE TABLE j_purchaseorder
  (id          VARCHAR2 (32) NOT NULL PRIMARY KEY,
   date_loaded TIMESTAMP (6) WITH TIME ZONE,
   po_document VARCHAR2 (23767)
   CONSTRAINT ensure_json CHECK (po_document IS JSON));

Example 4-2 Inserting JSON Data Into a VARCHAR2 JSON Column

INSERT INTO j_purchaseorder
  VALUES (
    SYS_GUID(),
    to_date('30-DEC-2014'),
    '{"PONumber"             : 1600,
      "Reference"            : "ABULL-20140421",
      "Requestor"            : "Alexis Bull",
      "User"                 : "ABULL",
      "CostCenter"           : "A50",
      "ShippingInstructions" :
        {"name"    : "Alexis Bull",
         "Address" : {"street"  : "200 Sporting Green",
                      "city"    : "South San Francisco",
                      "state"   : "CA",
                      "zipCode" : 99236,
                      "country" : "United States of America"},
         "Phone"   : [{"type" : "Office", "number" : "909-555-7307"},
                      {"type" : "Mobile", "number" : "415-555-1234"}]},
      "Special Instructions" : null,
      "AllowPartialShipment" : true,
        [{"ItemNumber" : 1,
          "Part"       : {"Description" : "One Magic Christmas",
                          "UnitPrice"   : 19.95,
                          "UPCCode"     : 13131092899},
          "Quantity"   : 9.0},
         {"ItemNumber" : 2,
          "Part"       : {"Description" : "Lethal Weapon",
                          "UnitPrice"   : 19.95,
                          "UPCCode"     : 85391628927},
          "Quantity"   : 5.0}]}');

INSERT INTO j_purchaseorder
  VALUES (
    SYS_GUID(),
    to_date('30-DEC-2014'),
    '{"PONumber"             : 672,
      "Reference"            : "SBELL-20141017",
      "Requestor"            : "Sarah Bell",
      "User"                 : "SBELL",
      "CostCenter"           : "A50",
      "ShippingInstructions" : {"name"    : "Sarah Bell",
                                "Address" : {"street"  : "200 Sporting Green",
                                             "city"    : "South San Francisco",
                                             "state"   : "CA",
                                             "zipCode" : 99236,
                                             "country" : "United States of America"},
                                "Phone"   : "983-555-6509"},
      "Special Instructions" : "Courier",
      "LineItems"            :
        [{"ItemNumber" : 1,
          "Part"       : {"Description" : "Making the Grade",
                          "UnitPrice"   : 20,
                          "UPCCode"     : 27616867759},
          "Quantity"   : 8.0},
         {"ItemNumber" : 2,
          "Part"       : {"Description" : "Nixon",
                          "UnitPrice"   : 19.95,
                          "UPCCode"     : 717951002396},
          "Quantity"   : 5},
         {"ItemNumber" : 3,
          "Part"       : {"Description" : "Eric Clapton: Best Of 1981-1999",
                          "UnitPrice"   : 19.95,
                          "UPCCode"     : 75993851120},
          "Quantity"   : 5.0}]}');

Determining Whether a Column Necessarily Contains JSON Data
How can you tell whether a given column of a table or view is well-formed JSON data? Whenever this is the case, the column is listed in the following static data dictionary views: DBA_JSON_COLUMNS, USER_JSON_COLUMNS, and ALL_JSON_COLUMNS.

Parent topic: Store and Manage JSON Data

4.1 Determining Whether a Column Necessarily Contains JSON Data

How can you tell whether a given column of a table or view is well-formed JSON data? Whenever this is the case, the column is listed in the following static data dictionary views: DBA_JSON_COLUMNS, USER_JSON_COLUMNS, and ALL_JSON_COLUMNS.

Each of these views lists the column name, data type, and format (TEXT or BINARY); the table or view name (column TABLE_NAME); and whether the object is a table or a view (column OBJECT_TYPE).

For a table column to be considered JSON data it must have an is json check constraint. But in the case of a view, any one of the following criteria suffices for a column to be considered JSON data:

The underlying data has an is json check constraint.
The column results from the use of SQL/JSON function json_query.
The column results from the use of a JSON generation function, such as json_object.
The column results from the use of SQL function treat with keywords AS JSON.

If an is json check constraint determines that a table column is JSON data, and if that constraint is later deactivated, the column remains listed in the views. If the check constraint is dropped then the column is removed from the views.

Note:

If a check constraint combines condition is json with another condition using logical condition OR, then the column is not listed in the views. In this case, it is not certain that data in the column is JSON data. For example, the constraint jcol is json OR length(jcol) < 1000 does not ensure that the data in column jcol is JSON data.