General Oracle EBS Database Administration Questions:

 

  1. What is Oracle E-Business Suite (EBS)?

    • Can you describe what Oracle EBS is and its components?
  2. What are the key differences between Oracle EBS 12.1 and 12.2?

    • Highlight any major architectural or functional differences between Oracle EBS 12.1 and 12.2.
  3. What are the system requirements for installing Oracle E-Business Suite 12.2?

  4. What is the concept of Multi-Node in Oracle EBS?

    • Can you explain how multiple nodes are used in Oracle EBS and how you set them up?
  5. What is Rapid Install in Oracle EBS?

    • Describe the process and benefits of using Rapid Install.
  6. Explain the architecture of Oracle EBS 12.2.x.

    • What are the primary components, such as database tier, application tier, and middle-tier?
  7. What is the difference between the Oracle EBS Database Tier and Application Tier?

    • What roles does each tier play in Oracle EBS?
  8. What is Oracle EBS AutoConfig?

    • How do you use AutoConfig in Oracle EBS?
  9. Can you explain the role of Oracle HTTP Server (OHS) in Oracle EBS 12.2?

  10. What are the prerequisites for performing an upgrade from Oracle EBS 12.1 to 12.2?

    • Explain the necessary steps, tools, and validation methods for an upgrade.

How to Stop Concurrent Requests from Executing on New Cloned Environment

 If you do not want concurrent requests scheduled in Source to run on a newly cloned environment, Follow the below steps

1. Run “perl adcfgclone.pl appsTier” as normal.
Before starting the application services, run the below update commands


-Take Backup of fnd_concurrent_requests

create table  fnd_concurrent_requests_bkp as select * from fnd_concurrent_requests;

-Terminate ‘Running’ Requests

UPDATE fnd_concurrent_requests
SET phase_code = ‘C’, status_code = ‘X’
WHERE status_code =’R’
OR phase_code = ‘R’
/

-Set Pending jobs to ‘On Hold’

UPDATE fnd_concurrent_requests
SET hold_flag = ‘Y’
WHERE phase_code = ‘P’
AND status_code in (‘Q’,’I’)
/

How can I confirm Profile Option Settings at all levels for a specified Profile Option?

 Run this script to identify Site, and all Responsibility and User values associated with the selected profile option

SELECT A.LAST_UPDATE_DATE,
T.USER_PROFILE_OPTION_NAME “PROFILE OPTION”,
DECODE(A.LEVEL_ID, 10001, ‘SITE’,
10002, ‘APPLICATION’,
10003, ‘RESPONSIBILITY’,
10004, ‘USER’) “LEVEL”,
DECODE(A.LEVEL_ID, 10001, ‘SITE’,
10002, B.APPLICATION_SHORT_NAME,
10003, C.RESPONSIBILITY_KEY,
10004, D.USER_NAME) “LEVEL VALUE”,
A.PROFILE_OPTION_VALUE “PROFILE VALUE”
FROM FND_PROFILE_OPTION_VALUES A,
FND_APPLICATION B,
FND_RESPONSIBILITY C,
FND_USER D,
FND_PROFILE_OPTIONS E,
FND_PROFILE_OPTIONS_TL T
WHERE A.PROFILE_OPTION_ID = E.PROFILE_OPTION_ID
AND E.PROFILE_OPTION_NAME =’&PROFILE_OPTION_NAME’ —Enter profile option name here
AND A.LEVEL_VALUE = B.APPLICATION_ID(+)
AND A.LEVEL_VALUE = C.RESPONSIBILITY_ID(+)
AND A.LEVEL_VALUE = D.USER_ID(+)
AND T.PROFILE_OPTION_NAME = E.PROFILE_OPTION_NAME
ORDER BY E.PROFILE_OPTION_NAME, A.LEVEL_ID DESC;

Python for Beginners – List of Topics

 Here’s a comprehensive list of topics to learn Python programming for beginners. This roadmap will help you systematically build your skills and progress from basic concepts to more advanced topics:

1. Introduction to Python

2. Python Syntax and Structure

  • Writing and running Python scripts
  • Indentation and the importance of whitespace
  • Python comments (single-line and multi-line)
  • Understanding the Python execution model

3. Variables and Data Types

  • Variables in Python (naming conventions)
  • Primitive Data Types:
    • Strings
    • Integers
    • Floats
    • Booleans
  • Type conversion (casting)
  • Understanding immutability vs mutability

4. Basic Input and Output

  • input() function for user input
  • print() function for displaying output
  • String formatting (using f-strings, .format(), concatenation)

5. Operators

  • Arithmetic operators (+, -, *, /, %, //, **)
  • Comparison operators (==, !=, >, <, >=, <=)
  • Logical operators (and, or, not)
  • Assignment operators (=, +=, -=, etc.)
  • Membership and Identity operators (in, not in, is, is not)

6. Control Flow Statements

  • Conditional statements: if, elif, else
  • Nested conditions
  • Boolean expressions
  • The pass statement

7. Loops

  • for loop
    • Iterating over a range of numbers using range()
    • Iterating over lists, tuples, dictionaries, and strings
  • while loop
  • break, continue, and else in loops
  • Nested loops

8. Functions

  • Defining functions using def
  • Function parameters and return values
  • Default parameters
  • Keyword arguments
  • Variable-length arguments (*args, **kwargs)
  • Scope and Lifetime (Local vs Global variables)
  • Lambda functions (anonymous functions)

9. Data Structures in Python

  • Lists:
    • Creating and accessing lists
    • List operations (indexing, slicing, append, remove, pop)
    • List comprehension
  • Tuples:
    • Creating and accessing tuples
    • Immutable nature of tuples
  • Dictionaries:
    • Key-value pairs, creating and accessing dictionaries
    • Dictionary methods (keys(), values(), items())
    • Iterating over dictionaries
  • Sets:
    • Creating sets
    • Set operations (union, intersection, difference)
  • Strings:
    • String manipulation (slicing, concatenation, repetition)
    • String methods (e.g., .lower(), .upper(), .replace())

10. Error Handling and Exceptions

  • Try-except blocks for error handling
  • else and finally blocks
  • Raising exceptions with raise
  • Common exceptions (ValueError, TypeError, etc.)
  • Custom exceptions

11. File Handling

  • Reading files (open(), read(), readlines())
  • Writing to files (write(), writelines())
  • Closing files (close())
  • Working with file paths and directories
  • Using context managers (with statement)

12. Modules and Libraries

  • Importing built-in Python libraries (e.g., math, random, os)
  • Creating and importing custom modules
  • Exploring Python’s standard library
  • Installing third-party libraries using pip

13. Object-Oriented Programming (OOP) Basics

  • Defining classes and objects
  • Instance variables and methods
  • Constructors (__init__ method)
  • Inheritance
  • Polymorphism
  • Encapsulation
  • Abstraction
  • self keyword

14. Basic Debugging Techniques

  • Using print() for debugging
  • Debugging with IDEs (breakpoints, stepping through code)
  • Understanding stack traces

15. Working with Libraries and Packages

  • Installing and managing packages using pip
  • Introduction to popular Python libraries:
    • numpy for numerical computation
    • pandas for data manipulation
    • matplotlib for plotting
    • requests for HTTP requests

16. Basic Algorithms and Problem Solving

  • Sorting algorithms (e.g., bubble sort, selection sort)
  • Searching algorithms (e.g., linear search, binary search)
  • Simple mathematical problems (factorial, Fibonacci sequence)
  • Introduction to time and space complexity

17. Introduction to Web Development with Python

  • Overview of web frameworks like Flask and Django
  • Creating a simple web application with Flask
  • Understanding HTTP methods (GET, POST)
  • Using templates and rendering HTML

18. Basic Data Analysis and Visualization

  • Introduction to data analysis with pandas
  • Working with data structures in pandas (DataFrames, Series)
  • Basic plotting with matplotlib
  • Introduction to numpy for handling numerical data

19. Introduction to Testing

  • Writing basic tests using the unittest module
  • Assertions and test cases
  • Running tests and interpreting results

20. Working with APIs

  • Introduction to RESTful APIs
  • Sending HTTP requests with requests library
  • Handling JSON data
  • Interacting with public APIs (e.g., OpenWeatherMap, Twitter)

Introduction to Python: A Beginner’s Guide

 Python is one of the most popular programming languages in the world today, thanks to its simplicity, versatility, and a vast ecosystem of libraries and frameworks. Whether you’re a beginner stepping into the world of programming or an experienced developer exploring new technologies, Python offers a great balance between power and ease of use. In this blog post, we’ll explore the basics of Python, its features, and why it has become a go-to language for developers across various domains.

What is Python?

Python is a high-level, interpreted programming language that emphasizes code readability and simplicity. It was created by Guido van Rossum and first released in 1991. Python’s design philosophy promotes clean and easy-to-read code, which makes it a great choice for both beginners and experienced programmers.

Key Features of Python

  1. Simple and Readable Syntax: Python’s syntax is straightforward and closely resembles natural language. This makes it easy to read and write Python code, even for those new to programming.

  2. Interpreted Language: Python is an interpreted language, meaning code is executed line by line, making it easier to test and debug. You don’t need to compile the code before running it.

  3. Dynamically Typed: In Python, you don’t need to explicitly declare the data types of variables. The interpreter automatically determines the type at runtime, which can speed up the development process.

  4. Extensive Standard Library: Python has a large standard library, providing built-in functions and modules for everything from file handling to web development. You can often find tools for your tasks without the need for third-party libraries.

  5. Cross-Platform: Python is cross-platform, meaning it can run on any operating system, including Windows, MacOS, and Linux, without requiring major modifications.

  6. Object-Oriented and Functional: Python supports both object-oriented and functional programming paradigms, offering flexibility for various programming styles.

  7. Open-Source and Community-Driven: Python is open-source, meaning anyone can contribute to its development. The large, active community ensures that Python continues to grow and stay up-to-date.

Why Learn Python?

1. Beginner-Friendly

Python is widely considered one of the best languages for beginners. The syntax is clear and concise, allowing you to focus on learning programming concepts rather than struggling with complex syntax. For newcomers to coding, Python offers an approachable entry point into the world of programming.

2. Versatility and Popularity

Python can be used for a wide range of applications, from simple automation scripts to complex web applications and data analysis. Its popularity spans many fields:

  • Web Development: Frameworks like Django and Flask allow you to build powerful web applications quickly and efficiently.
  • Data Science and Machine Learning: Python has become the go-to language for data analysis, machine learning, and artificial intelligence, thanks to libraries like NumPy, Pandas, TensorFlow, and Scikit-learn.
  • Automation: Python’s simplicity makes it ideal for writing scripts to automate repetitive tasks, such as file organization or web scraping.
  • Game Development: Libraries like Pygame allow for simple game creation and prototyping.
  • DevOps and Systems Programming: Python is widely used in DevOps for automation tasks and managing system processes.

3. Job Opportunities

Python’s demand in the job market is continually growing. Companies across industries seek Python developers for roles in web development, data science, automation, and more. The extensive ecosystem of Python libraries and frameworks also makes developers more productive, further boosting its appeal to businesses.



Python is an excellent choice for beginners, offering an intuitive syntax, versatility, and a large supportive community. Whether you’re interested in web development, data analysis, automation, or game development, Python has the tools you need. With its widespread use and job opportunities, learning Python can be a gateway to a fulfilling career in tech.

By mastering the basics of Python and experimenting with small projects, you’ll be well on your way to becoming a proficient programmer. Happy coding!