21.13 Import After Conversion with useFlexFields=false

After trying to import, error-log tables are created and queried to show import errors and imported documents.

The process of creating error logs and importing the input document sets (in tables student_tab, teacher_tab, and course_tab) into the duality views created in Using the Converter with useFlexFields=false is exactly the same as in the simplified recipe case: see the example "Creating Error Logs for No Outlier Use Case" and "Importing Document Sets, for No Outlier Use Case" in Migrating To Duality, Simplified Recipe. But checking the error logs for the default case tells a different story.

Example 21-33 Checking Error Logs from Import, for useFlexFields = false Case

As with the default case (see "Checking Error Logs from Import, for Default Case" in Import After Default Conversion), import into the student duality view logs an error for the type-occurrence outlier for field age with value "Nineteen", and no error is logged for the teacher view.

But unlike the default case, import also logs an error for the missing Notes field. Field Notes is not mapped to any column, and since there are no flex columns, the field is not supported by the duality view.

ORA_ERR_NUMBER$
---------------
ORA_ERR_MESG$
-------------
ORA_ERR_TAG$
------------
42555

ORA-42555: Cannot insert into JSON Relational Duality View 'COURSE': The input JSON document is invalid.
JZN-00651: field 'Notes' is unknown or undefined

Import Error

Select that culprit course document from the input course table:

SELECT * FROM "JANUS".course_tab
  WHERE ROWID IN (SELECT ora_err_rowid$ FROM course_err_log);

DATA
----
{"courseId":"MATH101","name":"Algebra","creditHours":3,"students":[{"studentId":
1,"name":"Donald P."},{"studentId":5,"name":"Hye E."}],"teacher":{"teacherId":10
1,"name":"Abdul J."},"Notes":"Prerequisite for Advanced Algebra"}

We next use DBMS_JSON_DUALITY.validate_import_report to report on any problems with documents that have been imported successfully. Unlike the default case and the simplified recipe case, for the conversion with useFlexFields = false, there are validation problems for imported student and course documents. (There are no validation problems for imported teacher documents.)

Example 21-34 VALIDATE_IMPORT_REPORT for useFlexFields = false Case

There are no validation problems for imported teacher documents.

For imported student data, the problematic document with age having a string value is reported.

SELECT * FROM DBMS_JSON_DUALITY.validate_import_report(
                                  table_name => 'STUDENT_TAB',
                                  view_name  => 'STUDENT');

DATA
----
{"studentId":9,"name":"Luis F.","age":"Nineteen","advisorId":101,"courses":[{"co
urseNumber":"CS101","name":"Algorithms","avgGrade":75},{"courseNumber":"MATH102"
,"name":"Calculus","avgGrade":95},{"courseNumber":"MATH103","name":"Advanced Alg
ebra","avgGrade":82}],"dormitory":{"dormId":201,"dormName":"ABC"}}

ERRORS
------
[{"op":"replace","path":"/age","value":null}]

PL/SQL function validate_import_report compares input documents with documents imported into the duality views, ignoring any additional fields added by the converter (_id, _metadata, ora$map*, ora$*_flex). It uses the format of JSON Patch to identify the problematic fields and specify editing operations you can perform on the input data to resolve the problems (differences).

• Field path specifies the location — the syntax of its value is that of JSON Pointer, not that of a SQL/JSON path expression. In this case, the path value /age targets the age field at the top level of the document.

• Field op specifies the editing operation. For the problematic student document, the operation is to replace the value of its top-level field age with JSON null. (That may or may not be the resolution you want.)

The problematic student document fails to import into the student duality view. However, it is still "supported" by that view. It is present in the view because importing to views course and teacher causes a row to be added to underlying table student_root for that document (with student_id = 9).

The value of field age in that document has value (JSON) null, however, because there's no field in the other two document sets that maps to column student_root.age, so that the value of that column is SQL NULL. And that NULL column value maps to JSON null in the student documents.

For imported course data, the problematic document containing field Notes is reported.

SELECT * FROM DBMS_JSON_DUALITY.validate_import_report(
                                  table_name => 'COURSE_TAB',
                                  view_name  => 'COURSE');

DATA
----
{"courseId":"MATH101","name":"Algebra","creditHours":3,"students":[{"studentId": [{"op":"remove","path":"/Notes"},{"op":"remove","path":"/creditHours"}]
1,"name":"Donald P."},{"studentId":5,"name":"Hye E."}],"teacher":{"teacherId":10
1,"name":"Abdul J."},"Notes":"Prerequisite for Advanced Algebra"}

ERRORS
------
[{"op":"remove","path":"/Notes"},{"op":"remove","path":"/creditHours"}]

The problematic course document fails to import into the course duality view.

For that document there are two error operations reported: remove its top-level fields Notes and creditHours. (This may or may not be the resolution you want.)

Import of the problematic course document fails because of its field Notes, which was pruned because, as an occurrence outlier it wasn't mapped to any column. And as an unmapped field the importer can't store it in a flex column because there are no flex columns (the input data was converted with useFlexFields = false).

But the course view's underlying table course_root anyway gets a row that corresponds to that problematic document (where field courseId has value MATH101), because of importing the student and teacher data, that is, populating the student and teacher views. Importing to those views populates columns course_id and name of table course_root, which are used by student and teacher documents. It does not, however, populate field Notes or creditHours.

The examples that follow, "Student Duality View Document Collection (useFlexFields = False)" and "Course Duality View Document Collection (useFlexFields = false) ", show the student and course document collections supported by the duality views, that is, the result of importing into those views, respectively.

The teacher duality-view collection is the same as for conversion with useFlexFields = true — see the example "Teacher Duality View Document Collection (useFlexFields = true)" in Import After Default Conversion.

Example 21-35 Student Duality View Document Collection (useFlexFields = false)

Compare this with the input student document set, "Student Document Set (Migrator Input)" in School Administration Example, Migrator Input Documents, which (with conversion using minFieldFrequency = 25 and minTypeFrequency = 15) has only one outlier field: age (with a type-occurrence frequency of 10%).

These are the only differences (ignoring field order, which is irrelevant):

• Document identifier field _id and document-state field _metadata have been added. (Every document supported by a duality view has these fields.)

• Fields ora$mapCourseId and ora$mapStudentId have been added. These correspond to the identifying columns (primary-key columns in this case) for underlying mapping table map_table_course_root_to_student_root. Their values are the same as the values of fields courseNumber and studentId, respectively.

• Even though the document for student Luis F. (studentId = 9) failed import into the student duality view (because field age has the string value "Nineteen", and its 10% occurrence is a type-occurrence outlier), that document is nevertheless present in the duality view. When we import documents into the course and teacher duality views, a row is added to table student_root that has 9 as the value for column student_root.student_id, because studentId with value 9 is present in both input tables course_tab and teacher_tab.

  The age field value for that student document for Luis F. is (JSON) null, however (not "Nineteen" and not 19). No age field exists in either of the course or teacher input document sets, so importing their student data for Luis F. into the course and teacher views stores SQL NULL in the age column in table student_root. And that NULL column value maps to JSON null in the student documents.

There are no other differences. In particular, mixed-type field avgGrade is unchanged from the input data, as it is not an outlier: each of its types occurs in more than 15% of the documents.

{
  "_id" : 1,
  "_metadata" :
  {
    "etag" : "4F39C8B86F4295AD2958B18A77B0AACC",
    "asof" : "00000000004DB839"
  },
  "age" : 20,
  "name" : "Donald P.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 1,
      "name" : "Algorithms",
      "avgGrade" : 75,
      "courseNumber" : "CS101"
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 1,
      "name" : "Data Structures",
      "avgGrade" : "TBD",
      "courseNumber" : "CS102"
    },
    {
      "ora$mapCourseId" : "MATH101",
      "ora$mapStudentId" : 1,
      "name" : "Algebra",
      "avgGrade" : 90,
      "courseNumber" : "MATH101"
    }
  ],
  "advisorId" : 102,
  "dormitory" :
  {
    "dormId" : 201,
    "dormName" : "ABC"
  },
  "studentId" : 1
}

{
  "_id" : 2,
  "_metadata" :
  {
    "etag" : "758A4F3E6EF3152A4FA0892AB38635D4",
    "asof" : "00000000004DB839"
  },
  "age" : 21,
  "name" : "Elena H.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 2,
      "name" : "Algorithms",
      "avgGrade" : 75,
      "courseNumber" : "CS101"
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 2,
      "name" : "Data Structures",
      "avgGrade" : "TBD",
      "courseNumber" : "CS102"
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 2,
      "name" : "Calculus",
      "avgGrade" : 95,
      "courseNumber" : "MATH102"
    }
  ],
  "advisorId" : 103,
  "dormitory" :
  {
    "dormId" : 202,
    "dormName" : "XYZ"
  },
  "studentId" : 2
}

{
  "_id" : 3,
  "_metadata" :
  {
    "etag" : "06905F120EF74124C5985354BBCE5CC1",
    "asof" : "00000000004DB839"
  },
  "age" : 20,
  "name" : "Francis K.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 3,
      "name" : "Advanced Algebra",
      "avgGrade" : 82,
      "courseNumber" : "MATH103"
    }
  ],
  "advisorId" : 103,
  "dormitory" :
  {
    "dormId" : 204,
    "dormName" : "QWE"
  },
  "studentId" : 3
}

{
  "_id" : 4,
  "_metadata" :
  {
    "etag" : "50847D1AB63537118A6133A4CC1B8708",
    "asof" : "00000000004DB839"
  },
  "age" : 19,
  "name" : "Georgia D.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 4,
      "name" : "Algorithms",
      "avgGrade" : 75,
      "courseNumber" : "CS101"
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 4,
      "name" : "Calculus",
      "avgGrade" : 95,
      "courseNumber" : "MATH102"
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 4,
      "name" : "Advanced Algebra",
      "avgGrade" : 82,
      "courseNumber" : "MATH103"
    }
  ],
  "advisorId" : 101,
  "dormitory" :
  {
    "dormId" : 203,
    "dormName" : "LMN"
  },
  "studentId" : 4
}

{
  "_id" : 5,
  "_metadata" :
  {
    "etag" : "FD6E27A868C56D1EF9C7AEB3F08C7F9B",
    "asof" : "00000000004DB839"
  },
  "age" : 21,
  "name" : "Hye E.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 5,
      "name" : "Data Structures",
      "avgGrade" : "TBD",
      "courseNumber" : "CS102"
    },
    {
      "ora$mapCourseId" : "MATH101",
      "ora$mapStudentId" : 5,
      "name" : "Algebra",
      "avgGrade" : 90,
      "courseNumber" : "MATH101"
    }
  ],
  "advisorId" : 103,
  "dormitory" :
  {
    "dormId" : 201,
    "dormName" : "ABC"
  },
  "studentId" : 5
}

{
  "_id" : 6,
  "_metadata" :
  {
    "etag" : "2BDA7862330B0687F22F830F3E314E34",
    "asof" : "00000000004DB839"
  },
  "age" : 21,
  "name" : "Ileana D.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 6,
      "name" : "Advanced Algebra",
      "avgGrade" : 82,
      "courseNumber" : "MATH103"
    }
  ],
  "advisorId" : 102,
  "dormitory" :
  {
    "dormId" : 205,
    "dormName" : "GHI"
  },
  "studentId" : 6
}

{
  "_id" : 7,
  "_metadata" :
  {
    "etag" : "F1EF0CCD54EDFA78D2263D7E742D6CE8",
    "asof" : "00000000004DB839"
  },
  "age" : 20,
  "name" : "Jatin S.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 7,
      "name" : "Algorithms",
      "avgGrade" : 75,
      "courseNumber" : "CS101"
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 7,
      "name" : "Data Structures",
      "avgGrade" : "TBD",
      "courseNumber" : "CS102"
    }
  ],
  "advisorId" : 101,
  "dormitory" :
  {
    "dormId" : 204,
    "dormName" : "QWE"
  },
  "studentId" : 7
}

{
  "_id" : 8,
  "_metadata" :
  {
    "etag" : "9A25A267BC08858E0F754E0C00B32F9E",
    "asof" : "00000000004DB839"
  },
  "age" : 21,
  "name" : "Katie H.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 8,
      "name" : "Data Structures",
      "avgGrade" : "TBD",
      "courseNumber" : "CS102"
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 8,
      "name" : "Advanced Algebra",
      "avgGrade" : 82,
      "courseNumber" : "MATH103"
    }
  ],
  "advisorId" : 102,
  "dormitory" :
  {
    "dormId" : 205,
    "dormName" : "GHI"
  },
  "studentId" : 8
}

{
  "_id" : 10,
  "_metadata" :
  {
    "etag" : "94376DA05B92E47718AF70A31FBE56E7",
    "asof" : "00000000004DB839"
  },
  "age" : 20,
  "name" : "Ming L.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 10,
      "name" : "Calculus",
      "avgGrade" : 95,
      "courseNumber" : "MATH102"
    }
  ],
  "advisorId" : 101,
  "dormitory" :
  {
    "dormId" : 202,
    "dormName" : "XYZ"
  },
  "studentId" : 10
}

{
  "_id" : 9,
  "_metadata" :
  {
    "etag" : "579824C71904C46901BBA605E8539943",
    "asof" : "00000000004DB839"
  },
  "age" : null,
  "name" : "Luis F.",
  "courses" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 9,
      "name" : "Algorithms",
      "avgGrade" : 75,
      "courseNumber" : "CS101"
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 9,
      "name" : "Calculus",
      "avgGrade" : 95,
      "courseNumber" : "MATH102"
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 9,
      "name" : "Advanced Algebra",
      "avgGrade" : 82,
      "courseNumber" : "MATH103"
    }
  ],
  "advisorId" : 101,
  "dormitory" :
  {
    "dormId" : 201,
    "dormName" : "ABC"
  },
  "studentId" : 9
}

Example 21-36 Course Duality View Document Collection (useFlexFields = false)

Compare this with the input course document set in the example "Course Document Set (Migrator Input)" in School Administration Example, Migrator Input Documents, which (with conversion using minFieldFrequency = 25 and minTypeFrequency = 15) has only one outlier field: Notes (with an occurrence frequency of 20%).

These are the only differences (ignoring field order, which is irrelevant):

• Document identifier field _id and document-state field _metadata have been added. (Every document supported by a duality view has these fields.)

• Fields ora$mapCourseId and ora$mapStudentId have been added. These correspond to the identifying columns (primary-key columns in this case) for underlying mapping table map_table_course_root_to_student_root. Their values are the same as the values of fields courseNumber and studentId, respectively.

• Even though the document with courseId = "MATH101") failed import into the course duality view (because field Notes occurs in only 20% of the documents and is thus an occurrence outlier), that document is present in the duality view, but without field Notes (it was not mapped to any column by the converter, and there is no flex column in which to store its value because useFlexFields was false) and without field creditHours.

  The problematic document is supported by the view, because when we import documents into the student and teacher duality views, a row is added to table course_root that has "MATH101" as the value for column course_root.course_id. This is because column course_id with value "MATH101" is present in both input tables student_tab and teacher_tab.

  Because the course document with field Notes failed to import, that input document's field creditHours is also missing from the document supported by the view. Field creditHours isn't provided for that document by importing any documents into the student or teacher view. Only table course_tab contains column credit_hours.

{
  "_id" : "CS101",
  "_metadata" :
  {
    "etag" : "7600B24570B58297702B95B8DE4F1B00",
    "asof" : "00000000004DB847"
  },
  "name" : "Algorithms",
  "teacher" :
  {
    "name" : "Betty Z.",
    "teacherId" : 102
  },
  "students" :
  [
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 1,
      "name" : "Donald P.",
      "studentId" : 1
    },
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 2,
      "name" : "Elena H.",
      "studentId" : 2
    },
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 4,
      "name" : "Georgia D.",
      "studentId" : 4
    },
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 7,
      "name" : "Jatin S.",
      "studentId" : 7
    },
    {
      "ora$mapCourseId" : "CS101",
      "ora$mapStudentId" : 9,
      "name" : "Luis F.",
      "studentId" : 9
    }
  ],
  "creditHours" : 5,
  "courseId" : "CS101"
}

{
  "_id" : "CS102",
  "_metadata" :
  {
    "etag" : "C3813410219036CF0E210FFCE3917FEB",
    "asof" : "00000000004DB847"
  },
  "name" : "Data Structures",
  "teacher" :
  {
    "name" : "Betty Z.",
    "teacherId" : 102
  },
  "students" :
  [
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 1,
      "name" : "Donald P.",
      "studentId" : 1
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 2,
      "name" : "Elena H.",
      "studentId" : 2
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 5,
      "name" : "Hye E.",
      "studentId" : 5
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 7,
      "name" : "Jatin S.",
      "studentId" : 7
    },
    {
      "ora$mapCourseId" : "CS102",
      "ora$mapStudentId" : 8,
      "name" : "Katie H.",
      "studentId" : 8
    }
  ],
  "creditHours" : 3,
  "courseId" : "CS102"
}

{
  "_id" : "MATH101",
  "_metadata" :
  {
    "etag" : "5E24FBF3B13A297A89FE1D4C68C705BE",
    "asof" : "00000000004DB847"
  },
  "name" : "Algebra",
  "teacher" :
  {
    "name" : "Abdul J.",
    "teacherId" : 101
  },
  "students" :
  [
    {
      "ora$mapCourseId" : "MATH101",
      "ora$mapStudentId" : 1,
      "name" : "Donald P.",
      "studentId" : 1
    },
    {
      "ora$mapCourseId" : "MATH101",
      "ora$mapStudentId" : 5,
      "name" : "Hye E.",
      "studentId" : 5
    }
  ],
  "courseId" : "MATH101"
}

{
  "_id" : "MATH102",
  "_metadata" :
  {
    "etag" : "4B55E2EF38E6DDAF6777251168DD07A5",
    "asof" : "00000000004DB847"
  },
  "name" : "Calculus",
  "teacher" :
  {
    "name" : "Abdul J.",
    "teacherId" : 101
  },
  "students" :
  [
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 2,
      "name" : "Elena H.",
      "studentId" : 2
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 4,
      "name" : "Georgia D.",
      "studentId" : 4
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 9,
      "name" : "Luis F.",
      "studentId" : 9
    },
    {
      "ora$mapCourseId" : "MATH102",
      "ora$mapStudentId" : 10,
      "name" : "Ming L.",
      "studentId" : 10
    }
  ],
  "creditHours" : 4,
  "courseId" : "MATH102"
}

{
  "_id" : "MATH103",
  "_metadata" :
  {
    "etag" : "C59E6274FE813279ECC28C73CA4AB121",
    "asof" : "00000000004DB847"
  },
  "name" : "Advanced Algebra",
  "teacher" :
  {
    "name" : "Colin J.",
    "teacherId" : 103
  },
  "students" :
  [
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 3,
      "name" : "Francis K.",
      "studentId" : 3
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 4,
      "name" : "Georgia D.",
      "studentId" : 4
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 6,
      "name" : "Ileana D.",
      "studentId" : 6
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 8,
      "name" : "Katie H.",
      "studentId" : 8
    },
    {
      "ora$mapCourseId" : "MATH103",
      "ora$mapStudentId" : 9,
      "name" : "Luis F.",
      "studentId" : 9
    }
  ],
  "creditHours" : "3",
  "courseId" : "MATH103"
}

Creating data-guide JSON schemas for the duality views is identical to doing so for the useFlexFields = true case. — see the example "Create JSON Data Guides for Document Collections Supported by Duality Views", "" in Import After Default Conversion. And the resulting data guides for the student and teacher views are the same as for that case — see "Student Duality View Data Guide" and "Teacher Duality View Data Guide"in Import After Default Conversion.

But the data guide created for the course view is not the same:

Example 21-37 Course Duality View Data Guide, for useFlexFields = false Case

This data guide JSON schema summarizes the collection of course documents supported by duality view course, for the conversion case where useFlexFields is false. It is identical to the data guide for the conversion case where useFlexFields is true, except that it is missing the Notes field.

{
  "type" : "object",
  "o:frequency" : 100,
  "o:last_analyzed" : "2025-01-15T21:19:03",
  "o:sample_size" : 5,
  "required" : true,
  "properties" :
  {
    "_id" :
    {
      "type" : "string",
      "o:length" : 8,
      "o:preferred_column_name" : "_id",
      "o:frequency" : 100,
      "o:low_value" : "CS101",
      "o:high_value" : "MATH103",
      "o:num_nulls" : 0,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "maxLength" : 7,
      "minLength" : 5
    },
    "name" :
    {
      "type" : "string",
      "o:length" : 16,
      "o:preferred_column_name" : "name",
      "o:frequency" : 100,
      "o:low_value" : "Advanced Algebra",
      "o:high_value" : "Data Structures",
      "o:num_nulls" : 0,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "maxLength" : 16,
      "minLength" : 7
    },
    "teacher" :
    {
      "type" : "object",
      "o:preferred_column_name" : "teacher",
      "o:frequency" : 100,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "properties" :
      {
        "name" :
        {
          "type" : "string",
          "o:length" : 8,
          "o:preferred_column_name" : "name",
          "o:frequency" : 100,
          "o:low_value" : "Abdul J.",
          "o:high_value" : "Colin J.",
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "required" : true,
          "maxLength" : 8,
          "minLength" : 8
        },
        "teacherId" :
        {
          "type" : "number",
          "o:preferred_column_name" : "teacherId",
          "o:frequency" : 100,
          "o:low_value" : 101,
          "o:high_value" : 103,
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "required" : true,
          "maximum" : 103,
          "minimum" : 101
        }
      }
    },
    "courseId" :
    {
      "type" : "string",
      "o:length" : 8,
      "o:preferred_column_name" : "courseId",
      "o:frequency" : 100,
      "o:low_value" : "CS101",
      "o:high_value" : "MATH103",
      "o:num_nulls" : 0,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "maxLength" : 7,
      "minLength" : 5
    },
    "students" :
    {
      "type" : "array",
      "o:preferred_column_name" : "students",
      "o:frequency" : 100,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "items" :
      {
        "properties" :
        {
          "name" :
          {
            "type" : "string",
            "o:length" : 16,
            "o:preferred_column_name" : "name",
            "o:frequency" : 100,
            "o:low_value" : "Donald P.",
            "o:high_value" : "Ming L.",
            "o:num_nulls" : 0,
            "o:last_analyzed" : "2025-01-15T21:19:03",
            "o:sample_size" : 5,
            "required" : true,
            "maxLength" : 10,
            "minLength" : 6
          },
          "studentId" :
          {
            "type" : "number",
            "o:preferred_column_name" : "studentId",
            "o:frequency" : 100,
            "o:low_value" : 1,
            "o:high_value" : 10,
            "o:num_nulls" : 0,
            "o:last_analyzed" : "2025-01-15T21:19:03",
            "o:sample_size" : 5,
            "required" : true,
            "maximum" : 10,
            "minimum" : 1
          },
          "ora$mapCourseId" :
          {
            "type" : "string",
            "o:length" : 8,
            "o:preferred_column_name" : "ora$mapCourseId",
            "o:frequency" : 100,
            "o:low_value" : "CS101",
            "o:high_value" : "MATH103",
            "o:num_nulls" : 0,
            "o:last_analyzed" : "2025-01-15T21:19:03",
            "o:sample_size" : 5,
            "required" : true,
            "maxLength" : 7,
            "minLength" : 5
          },
          "ora$mapStudentId" :
          {
            "type" : "number",
            "o:preferred_column_name" : "ora$mapStudentId",
            "o:frequency" : 100,
            "o:low_value" : 1,
            "o:high_value" : 10,
            "o:num_nulls" : 0,
            "o:last_analyzed" : "2025-01-15T21:19:03",
            "o:sample_size" : 5,
            "required" : true,
            "maximum" : 10,
            "minimum" : 1
          }
        }
      }
    },
    "_metadata" :
    {
      "type" : "object",
      "o:preferred_column_name" : "_metadata",
      "o:frequency" : 100,
      "o:last_analyzed" : "2025-01-15T21:19:03",
      "o:sample_size" : 5,
      "required" : true,
      "properties" :
      {
        "asof" :
        {
          "type" : "binary",
          "o:length" : 8,
          "o:preferred_column_name" : "asof",
          "o:frequency" : 100,
          "o:low_value" : "",
          "o:high_value" : "",
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "required" : true
        },
        "etag" :
        {
          "type" : "binary",
          "o:length" : 16,
          "o:preferred_column_name" : "etag",
          "o:frequency" : 100,
          "o:low_value" : "",
          "o:high_value" : "",
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "required" : true
        }
      }
    },
    "creditHours" :
    {
      "oneOf" :
      [
        {
          "type" : "number",
          "o:preferred_column_name" : "creditHours",
          "o:frequency" : 60,
          "o:low_value" : 3,
          "o:high_value" : 5,
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "maximum" : 5,
          "minimum" : 3
        },
        {
          "type" : "string",
          "o:length" : 1,
          "o:preferred_column_name" : "creditHours",
          "o:frequency" : 20,
          "o:low_value" : "3",
          "o:high_value" : "3",
          "o:num_nulls" : 0,
          "o:last_analyzed" : "2025-01-15T21:19:03",
          "o:sample_size" : 5,
          "maxLength" : 1,
          "minLength" : 1
        }
      ]
    }
  }
}

This is the missing Notes entry (from the useFlexFields = true case):

"Notes" : {"type"                    : "string",
           "o:length"                : 64,
           "o:preferred_column_name" : "Notes",
           "o:frequency"             : 20,
           "o:low_value"             : "Prerequisite for Advanced Algebra",
           "o:high_value"            : "Prerequisite for Advanced Algebra",
           "o:num_nulls"             : 0,
           "o:last_analyzed"         : "2025-01-15T21:11:48",
           "o:sample_size"           : 5,
           "maxLength"               : 33,
           "minLength"              : 33}

See Also:

• DBMS_JSON_DUALITY IN Oracle Database PL/SQL Packages and Types Reference for information about function validate_import_report

• JSON Patch and JSON Pointer for information about the error content reported by DBMS_JSON_DUALITY.validate_import_report