List of Examples
- 2-1 A JSON Object (Representation of a JavaScript Object Literal)
- 4-1 Using IS JSON in a Check Constraint to Ensure JSON Data is Well-Formed
- 4-2 Inserting JSON Data Into a VARCHAR2 JSON Column
- 5-1 Using IS JSON in a Check Constraint to Ensure JSON Data is Strictly Well-Formed (Standard)
- 7-1 Creating a Partitioned Table Using a JSON Virtual Column
- 9-1 Inserting JSON Data Into a BLOB Column
- 10-1 Creating a Database Directory Object for Purchase Orders
- 10-2 Creating an External Table and Filling It From a JSON Dump File
- 10-3 Creating a Table With a BLOB JSON Column
- 10-4 Copying JSON Data From an External Table To a Database Table
- 11-1 A JSON Merge Patch Document
- 11-2 A Merge-Patched JSON Document
- 11-3 Updating a JSON Column Using JSON Merge Patch
- 11-4 Updating Selected JSON Documents On the Fly
- 12-1 JSON Dot-Notation Query Compared With JSON_VALUE
- 12-2 JSON Dot-Notation Query Compared With JSON_QUERY
- 15-1 JSON_EXISTS: Path Expression Without Filter
- 15-2 JSON_EXISTS: Current Item and Scope in Path Expression Filters
- 15-3 JSON_EXISTS: Filter Conditions Depend On the Current Item
- 15-4 JSON_EXISTS: Filter Downscoping
- 15-5 JSON_EXISTS: Path Expression Using Path-Expression exists Condition
- 15-6 JSON_EXISTS Expressed Using JSON_TABLE
- 16-1 JSON_VALUE: Returning a JSON Boolean Value to PL/SQL as BOOLEAN
- 16-2 JSON_VALUE: Returning a JSON Boolean Value to SQL as VARCHAR2
- 16-3 Instantiate a User-Defined Object Instance From JSON Data with JSON_VALUE
- 16-4 Instantiate a Collection Type Instance From JSON Data with JSON_VALUE
- 16-5 JSON_VALUE Expressed Using JSON_TABLE
- 17-1 Selecting JSON Values Using JSON_QUERY
- 17-2 JSON_QUERY Expressed Using JSON_TABLE
- 18-1 Equivalent JSON_TABLE Queries: Simple and Full Syntax
- 18-2 Equivalent: SQL NESTED and JSON_TABLE with LEFT OUTER JOIN
- 18-3 Accessing JSON Data Multiple Times to Extract Data
- 18-4 Using JSON_TABLE to Extract Data Without Multiple Parses
- 18-5 Projecting an Entire JSON Array as JSON Data
- 18-6 Projecting Elements of a JSON Array
- 18-7 Projecting Elements of a JSON Array Plus Other Data
- 18-8 JSON_TABLE: Projecting Array Elements Using NESTED
- 18-9 Creating a View Over JSON Data
- 18-10 Creating a Materialized View Over JSON Data
- 19-1 Using JSON_SERIALIZE To Convert BLOB Data To Pretty-Printed Text
- 19-2 Using JSON_SERIALIZE with Clients
- 20-1 Enabling Persistent Support for a JSON Data Guide But Not For Search
- 20-2 Disabling JSON Data-Guide Support For an Existing JSON Search Index
- 20-3 Gathering Statistics on JSON Data Using a JSON Search Index
- 20-4 Specifying Preferred Column Names For Some JSON Fields
- 20-5 Creating a View Using a Hierarchical Data Guide Obtained With GET_INDEX_DATAGUIDE
- 20-6 Creating a View Using a Hierarchical Data Guide Obtained With JSON_DATAGUIDE
- 20-7 Creating a View That Projects All Scalar Fields
- 20-8 Creating a View That Projects Scalar Fields Targeted By a Path Expression
- 20-9 Creating a View That Projects Scalar Fields Having a Given Frequency
- 20-10 Adding Virtual Columns That Project JSON Fields Using a Data Guide Obtained With GET_INDEX_DATAGUIDE
- 20-11 Adding Virtual Columns, Hidden and Visible
- 20-12 Projecting All Scalar Fields Not Under an Array as Virtual Columns
- 20-13 Projecting Scalar Fields With a Minimum Frequency as Virtual Columns
- 20-14 Projecting Scalar Fields With a Minimum Frequency as Hidden Virtual Columns
- 20-15 Dropping Virtual Columns Projected From JSON Fields
- 20-16 Adding Virtual Columns Automatically With Change Trigger ADD_VC
- 20-17 Tracing Data-Guide Updates With a User-Defined Change Trigger
- 20-18 Adding a 2015 Purchase-Order Document
- 20-19 Adding a 2016 Purchase-Order Document
- 20-20 Creating Multiple Data Guides With Aggregate Function JSON_DATAGUIDE
- 20-21 Querying a Data Guide Obtained Using JSON_DATAGUIDE
- 20-22 Querying a Data Guide With Index Data For Paths With Frequency at Least 80%
- 20-23 Flat Data Guide For Purchase Orders
- 20-24 Hierarchical Data Guide For Purchase Orders
- 21-1 Declaring an Input Value To Be JSON
- 21-2 Using Name–Value Pairs with JSON_OBJECT
- 21-3 Using Column Names with JSON_OBJECT
- 21-4 Using a Wildcard (*) with JSON_OBJECT
- 21-5 Using JSON_OBJECT With ABSENT ON NULL
- 21-6 Using a User-Defined Object-Type Instance with JSON_OBJECT
- 21-7 Using JSON_ARRAY to Construct a JSON Array
- 21-8 Using JSON_OBJECTAGG to Construct a JSON Object
- 21-9 Using JSON_ARRAYAGG to Construct a JSON Array
- 23-1 Constructing and Serializing an In-Memory JSON Object
- 23-2 Using Method GET_KEYS() to Obtain a List of Object Fields
- 23-3 Using Method PUT() to Update Parts of JSON Documents
- 24-1 A Table With GeoJSON Data
- 24-2 Selecting a geometry Object From a GeoJSON Feature As an SDO_GEOMETRY Instance
- 24-3 Retrieving Multiple geometry Objects From a GeoJSON Feature As SDO_GEOMETRY
- 24-4 Creating a Spatial Index For Scalar GeoJSON Data
- 24-5 Using GeoJSON Geometry With Spatial Operators
- 24-6 Creating a Materialized View Over GeoJSON Data
- 24-7 Creating a Spatial Index on a Materialized View Over GeoJSON Data
- 26-1 Creating a Bitmap Index for JSON_EXISTS
- 26-2 Creating a Bitmap Index for JSON_VALUE
- 26-3 Creating a Function-Based Index for a JSON Field: Dot Notation
- 26-4 Creating a Function-Based Index for a JSON Field: JSON_VALUE
- 26-5 Specifying NULL ON EMPTY for a JSON_VALUE Function-Based Index
- 26-6 Use of a JSON_VALUE Function-Based Index with a JSON_TABLE Query
- 26-7 JSON_EXISTS Query Targeting Field Compared to Literal Number
- 26-8 JSON_EXISTS Query Targeting Field Compared to Variable Value
- 26-9 JSON_EXISTS Query Targeting Field Cast to Number Compared to Variable Value
- 26-10 JSON_EXISTS Query Targeting a Conjunction of Field Comparisons
- 26-11 JSON_VALUE Query with Explicit RETURNING NUMBER
- 26-12 JSON_VALUE Query with Explicit Numerical Conversion
- 26-13 JSON_VALUE Query with Implicit Numerical Conversion
- 26-14 Creating Virtual Columns For JSON Object Fields
- 26-15 Creating a Composite B-tree Index For JSON Object Fields
- 26-16 Two Ways to Query JSON Data Indexed With a Composite Index
- 26-17 Creating a JSON Search Index
- 26-18 Execution Plan Indication that a JSON Search Index Is Used
- 26-19 Full-Text Query of JSON Data
- 26-20 Full-Text Query of JSON Data, with Escaped Search Pattern
- 26-21 Some Ad Hoc JSON Queries
- 27-1 Populating JSON Data Into the IM Column Store