List of Examples
- 1-1 A JSON Object (Representation of a JavaScript Object Literal)
- 2-1 Converting Textual JSON Data to JSON Type On the Fly
- 2-2 Adding Time Zone Information to JSON Data
- 2-3 Using JSON_SERIALIZE To Convert JSON type or BLOB Data To Pretty-Printed Text with Ordered Object Members
- 2-4 Using JSON_SERIALIZE To Convert Non-ASCII Unicode Characters to ASCII Escape Codes
- 4-1 Creating a Table with a JSON Type Column
- 4-2 Using IS JSON in a Check Constraint to Ensure Textual JSON Data is Well-Formed
- 4-3 Inserting JSON Data Into a JSON Column
- 5-1 Using IS JSON in a Check Constraint to Ensure Textual JSON Data is Strictly Well-Formed
- 6-1 Creating a JSON Collection Table with Virtual Column and Constraint
- 6-2 Creating a JSON Collection Table
- 7-1 Validating JSON Data Against a JSON Schema with Condition IS JSON
- 7-2 JSON Schema Validation With Type Casting In an IS JSON Check Constraint
- 7-3 Prechecking Column Constraints
- 9-1 JDBC Client: Using the LOB Locator Interface To Retrieve JSON BLOB Data
- 9-2 JDBC Client: Using the LOB Locator Interface To Retrieve JSON CLOB Data
- 9-3 ODP.NET Client: Using the LOB Locator Interface To Retrieve JSON BLOB Data
- 9-4 ODP.NET Client: Using the LOB Locator Interface To Retrieve JSON CLOB Data
- 9-5 JDBC Client: Using the LOB Data Interface To Retrieve JSON BLOB Data
- 9-6 JDBC Client: Using the LOB Data Interface To Retrieve JSON CLOB Data
- 9-7 JDBC Client: Reading Full BLOB Content Directly with getBytes
- 9-8 JDBC Client:Reading Full CLOB Content Directly with getString
- 9-9 ODP.NET Client: Reading Full BLOB Content Directly with getBytes
- 9-10 ODP.NET Client: Reading Full CLOB Content Directly with getString
- 10-1 Creating a Partitioned Collection Table Using a JSON Virtual Column
- 13-1 Updating a JSON Column Using JSON_TRANSFORM
- 13-2 Modifying JSON Data On the Fly With JSON_TRANSFORM
- 13-3 Adding a Field Using JSON_TRANSFORM
- 13-4 Removing a Field Using JSON_TRANSFORM
- 13-5 Creating or Replacing a Field Value Using JSON_TRANSFORM
- 13-6 Replacing an Existing Field Value Using JSON_TRANSFORM
- 13-7 Using FORMAT JSON To Set a JSON Boolean Value
- 13-8 Setting an Array Element Using JSON_TRANSFORM
- 13-9 Appending an Element To an Array Using JSON_TRANSFORM
- 13-10 Appending Multiple Elements To an Array Using JSON_TRANSFORM
- 13-11 Prepending Multiple Elements To an Array Using JSON_TRANSFORM
- 13-12 Removing Array Elements That Satisfy a Predicate Using JSON_TRANSFORM
- 13-13 Sorting Elements In an Array By Field Values Using JSON_TRANSFORM
- 13-14 Updating Each Element of an Array Using JSON_TRANSFORM
- 13-15 Downscoping with NESTED PATH, To Limit JSON_TRANSFORM Pruning by KEEP
- 13-16 JSON_TRANSFORM: Controlling Modifications with SET and CASE
- 14-1 A JSON Merge Patch Document
- 14-2 A Merge-Patched JSON Document
- 14-3 Updating a JSON Column Using JSON_MERGEPATCH
- 14-4 Modifying JSON Data On the Fly With JSON_MERGEPATCH
- 15-1 Creating a Database Directory Object for Purchase Orders
- 15-2 Creating an External Table and Filling It From a File-System File of Textual JSON Data
- 15-3 Creating a Table With a JSON Column for JSON Data
- 15-4 Copying JSON Data From an External Table To a Database Table
- 15-5 Copying JSON Data From an External Table To a JSON Collection Table
- 16-1 JSON Dot-Notation Query Compared With JSON_VALUE
- 16-2 JSON Dot-Notation Query Compared With JSON_QUERY
- 17-1 Aggregating Values of a Field for Each Document
- 17-2 Aggregating Values of a Field Across All Documents
- 18-1 Using Parameter JSON_BEHAVIOR To Provide ERROR ON ERROR Behavior
- 18-2 Using ON MISMATCH Clauses
- 19-1 JSON_EXISTS: Path Expression Without Filter
- 19-2 JSON_EXISTS: Current Item and Scope in Path Expression Filters
- 19-3 JSON_EXISTS: Filter Conditions Depend On the Current Item
- 19-4 JSON_EXISTS: Filter Downscoping
- 19-5 JSON_EXISTS: Path Expression Using Path-Expression exists Condition
- 19-6 JSON_EXISTS Expressed Using JSON_TABLE
- 20-1 JSON_VALUE: Returning a JSON Boolean Value as VARCHAR2
- 20-2 JSON_VALUE: Returning a JSON Boolean Value to SQL as BOOLEAN
- 20-3 JSON_VALUE: Returning a JSON Boolean Value to PL/SQL as BOOLEAN
- 20-4 JSON_VALUE: Returning a JSON Boolean Value to SQL as NUMBER
- 20-5 Instantiate a User-Defined Object Instance From JSON Data with JSON_VALUE
- 20-6 Instantiate a Collection Type Instance From JSON Data with JSON_VALUE
- 20-7 JSON_VALUE Expressed Using JSON_TABLE
- 21-1 Selecting JSON Values Using JSON_QUERY
- 21-2 JSON_QUERY Expressed Using JSON_TABLE
- 22-1 Equivalent JSON_TABLE Queries: Simple and Full Syntax
- 22-2 Equivalent: SQL NESTED and JSON_TABLE with LEFT OUTER JOIN
- 22-3 Using SQL NESTED To Expand a Nested Array
- 22-4 Accessing JSON Data Multiple Times to Extract Data
- 22-5 Using JSON_TABLE to Extract Data Without Multiple Reads
- 22-6 Projecting an Entire JSON Array as JSON Data
- 22-7 Projecting Elements of a JSON Array
- 22-8 Projecting Elements of a JSON Array Plus Other Data
- 22-9 JSON_TABLE: Projecting Array Elements Using NESTED
- 22-10 Creating a View Over JSON Data
- 22-11 Creating a Materialized View Over JSON Data
- 23-1 Full-Text Query of JSON Data with JSON_TEXTCONTAINS
- 23-2 JSON_TEXTCONTAINS: Sorting Query Results By Relevance Using SCORE
- 24-1 Enabling Persistent Support for a JSON Data Guide But Not For Search
- 24-2 Enabling JSON Data-Guide Support For an Existing JSON Search Index
- 24-3 Gathering Statistics on JSON Data Using a JSON Search Index
- 24-4 Specifying Preferred Column Names For Some JSON Fields
- 24-5 Creating a View Using a Hierarchical Data Guide Obtained With JSON_DATAGUIDE
- 24-6 Creating a View That Projects All Scalar Fields
- 24-7 Creating a View That Projects Scalar Fields Targeted By a Path Expression
- 24-8 Creating a View That Projects Scalar Fields Having a Given Frequency
- 24-9 Adding Virtual Columns That Project JSON Fields Using a Data Guide Obtained With JSON_DATAGUIDE
- 24-10 Adding Virtual Columns, Hidden and Visible
- 24-11 Projecting All Scalar Fields Not Under an Array as Virtual Columns
- 24-12 Projecting Scalar Fields With a Minimum Frequency as Virtual Columns
- 24-13 Projecting Scalar Fields With a Minimum Frequency as Hidden Virtual Columns
- 24-14 Dropping Virtual Columns Projected From JSON Fields
- 24-15 Adding Virtual Columns Automatically With Change Trigger ADD_VC
- 24-16 Tracing Data-Guide Updates With a User-Defined Change Trigger
- 24-17 Adding a 2015 Purchase-Order Document
- 24-18 Adding a 2016 Purchase-Order Document
- 24-19 Creating Multiple Data Guides With Aggregate Function JSON_DATAGUIDE
- 24-20 Querying a Data Guide Obtained Using JSON_DATAGUIDE
- 24-21 Querying a Data Guide With Index Data For Paths With Frequency at Least 80%
- 24-22 Flat Data Guide For Purchase Orders
- 24-23 Hierarchical Data Guide For Purchase Orders
- 24-24 Schema Data Guide for Purchase-Order Documents
- 25-1 FORMAT JSON: Declaring an Input SQL Value To Be JSON Data
- 25-2 Using Name–Value Pairs with JSON_OBJECT
- 25-3 Using Column Names with JSON_OBJECT
- 25-4 Using a Wildcard (*) with JSON_OBJECT
- 25-5 Using JSON_OBJECT With ABSENT ON NULL
- 25-6 Using a User-Defined Object-Type Instance with JSON_OBJECT
- 25-7 Using WITH TYPENAME with JSON_OBJECT
- 25-8 Using JSON_ARRAY with Value Arguments to Construct a JSON Array
- 25-9 Using JSON_ARRAY with a Query Argument to Construct a JSON Array
- 25-10 Using JSON_OBJECTAGG to Construct a JSON Object
- 25-11 Using JSON_ARRAYAGG to Construct a JSON Array
- 25-12 Generating JSON Objects with Nested Arrays Using a SQL Subquery
- 25-13 Creating a View That Uses JSON Generation
- 25-14 JSON Document Generated From DEPARTMENT_VIEW
- 27-1 Constructing and Serializing an In-Memory JSON Object
- 27-2 Using Method GET_KEYS() to Obtain a List of Object Fields
- 27-3 Using Method PUT() to Update Parts of JSON Documents
- 28-1 A Table With GeoJSON Data
- 28-2 Selecting a geometry Object From a GeoJSON Feature As an SDO_GEOMETRY Instance
- 28-3 Retrieving Multiple geometry Objects From a GeoJSON Feature As SDO_GEOMETRY
- 28-4 Creating a Spatial Index For Scalar GeoJSON Data
- 28-5 Using GeoJSON Geometry With Spatial Operators
- 28-6 Creating a Materialized View Over GeoJSON Data
- 28-7 Creating a Spatial Index on a Materialized View Over GeoJSON Data
- 30-1 Creating a Bitmap Index for JSON_VALUE
- 30-2 Creating a Function-Based Index for a JSON Field: Dot Notation
- 30-3 Creating a Function-Based Index for a JSON Field: JSON_VALUE
- 30-4 Specifying NULL ON EMPTY for a JSON_VALUE Function-Based Index
- 30-5 Use of a JSON_VALUE Function-Based Index with a JSON_TABLE Query
- 30-6 JSON_EXISTS Query Targeting Field Compared to Literal Number
- 30-7 JSON_EXISTS Query Targeting Field Compared to Variable Value
- 30-8 JSON_EXISTS Query Targeting Field Cast to Number Compared to Variable Value
- 30-9 JSON_EXISTS Query Targeting a Conjunction of Field Comparisons
- 30-10 JSON_VALUE Query with Explicit RETURNING NUMBER
- 30-11 JSON_VALUE Query with Explicit Numerical Conversion
- 30-12 JSON_VALUE Query with Implicit Numerical Conversion
- 30-13 Table PARTS_TAB, for Multivalue Index Examples
- 30-14 Creating a Multivalue Index for JSON_EXISTS
- 30-15 Creating a Composite Multivalue Index for JSON_EXISTS
- 30-16 Creating a Composite Multivalue Index That Can Target Array Positions
- 30-17 JSON_EXISTS Query With Item Method numberOnly()
- 30-18 JSON_EXISTS Query Without Item Method numberOnly()
- 30-19 JSON_EXISTS Query Checking Multiple Fields
- 30-20 JSON_EXISTS Query Checking Array Element Position
- 30-21 Creating a Composite B-tree Index For JSON Object Fields
- 30-22 Querying JSON Data Indexed With a Composite B-tree Index
- 30-23 Creating a JSON Search Index with Default Behavior
- 30-24 Creating a JSON Search Index That Is Synchronized On Commit
- 30-25 Execution Plan Indication that a JSON Search Index Is Used
- 30-26 Some Ad Hoc JSON Queries
- 31-1 Populating JSON Data Into the IM Column Store For Ad Hoc Query Support
- 31-2 Populating a JSON Type Column Into the IM Column Store For Full-Text Query Support
- 32-1 Creating a Materialized View of JSON Data To Support Query Rewrite
- 32-2 Creating an Index Over a Materialized View of JSON Data
- D-1 Locating Problematic JSON Data Reported By DBMS_JSON.JSON_TYPE_CONVERTIBLE_CHECK
- D-2 Using CREATE TABLE AS SELECT (CTAS) to Migrate to JSON Data Type
- D-3 Using INSERT as SELECT (IAS) to Migrate to JSON Data Type
- D-4 Rename New Table To Original Table Name
- D-5 Obtaining Information Needed To Re-Create an Index