AI Foundation for Beginners

Learning Source: Oracle University (Oracle MyLearn) — OCI AI Foundations Course

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Why I’m Writing This

I’m starting my AI learning journey with Oracle Education through the Oracle Cloud Infrastructure (OCI) AI Foundations course. This post captures my Day 1 notes in a beginner-friendly way, so I can revise quickly and also help others who want to start from zero.

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is the ability of machines to imitate human intelligence and problem-solving capabilities. In simple words: AI helps machines “learn, think, understand, and decide” based on data.

Human-like capabilities AI tries to replicate

• Learning new skills through observation
• Understanding abstract concepts and applying reasoning
• Communicating using language
• Understanding non-verbal cues (facial expressions, tone, body language)
• Handling objections or changes in real time (even in complex situations)
• Planning short-term and long-term tasks
• Creating art, music, or new ideas

AGI vs AI (Beginner Clarity)

When machines can replicate a broad range of human capabilities (sensory + motor skills, learning, reasoning, and intelligence), this is often referred to as Artificial General Intelligence (AGI).

When similar intelligence is applied to solve specific, narrow problems with clear objectives, we call it Artificial Intelligence (AI).

AI is All Around Us (Examples)

• Identifying objects in images (e.g., apple vs orange)
• Classifying emails (spam vs not spam)
• Generating or assisting in writing code
• Predicting values (e.g., used car price prediction)
• Product recommendations (cross-sell / up-sell suggestions)

Why AI Matters Today

The amount of data generated today is far more than what humans can absorb, interpret, and make decisions from. AI helps by improving the speed and effectiveness of human efforts.

Two major reasons we need AI

1. Automate routine tasks: credit card approvals, bank loans, insurance claims, and product recommendations.
2. Intelligent assistance: AI can help create stories, poems, designs, code, music, and even respond with humor.

Major AI Domains (with Examples)

• Language: translation, chatbots
• Vision: image classification, object detection
• Speech: speech-to-text, text-to-speech
• Recommendations: product recommendations, personalization
• Anomaly Detection: fraud detection, suspicious activity alerts
• Reinforcement Learning: learning by reward (e.g., self-driving systems)
• Forecasting: weather forecasting, demand prediction
• Content Generation: creating images or text from prompts

AI vs Machine Learning vs Deep Learning (Quick View)

These terms are often mixed together. Here is the simplest structure:

AI (Broad umbrella)
→ Machine Learning (Learning patterns from data)
→ Deep Learning (ML using neural networks)

Key Takeaways 

• AI = machines imitating human intelligence and decision-making
• AI is important because data volume is too large for humans to handle alone
• AI helps automate routine work and provide intelligent assistance
• AI domains include language, vision, speech, forecasting, and content generation
• AI → ML → Deep Learning (simple hierarchy for beginners)

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Next Post: Deep Learning basics (Neural Networks) and how it connects to modern Generative AI.

Database Automation: The Future of Smart DBA Operations

Database Automation: The Future of Smart DBA Operations

Audience: DBAs, Lead DBAs, Cloud/DevOps Engineers
Reading time: ~7–10 minutes
Tags: Database Automation, DBA, DevOps, CI/CD, Oracle, PostgreSQL, MariaDB, Monitoring

In modern enterprise environments, databases are no longer static systems managed manually through scripts and midnight maintenance windows. With growing cloud adoption, hybrid architectures, and high availability demands, Database Automation has become a strategic necessity — not just a convenience.

Automation is not about replacing DBA expertise — it’s about scaling it. It reduces human error, accelerates delivery, and creates a repeatable operational model across DEV/TEST/PROD and DR.

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What is Database Automation?

Database Automation means using scripts, tools, orchestration platforms, and policies to automatically manage the database lifecycle — from provisioning and patching to backups, monitoring, and performance tuning.

In short: Instead of reactive firefighting, automation enables predictable, repeatable, controlled operations.

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Where Database Automation Matters Most

A) Provisioning & Deployment

Automating database setup ensures consistent builds across environments (DEV, TEST, PROD, DR). This typically includes Infrastructure-as-Code (IaC) and configuration automation.

• IaC: Terraform / CloudFormation for repeatable infra provisioning
• Config automation: Ansible for OS packages, users, kernel params, DB install steps
• Standard images: Golden AMIs / templates for faster, consistent deployments
• Containers: Docker/Kubernetes (where applicable) for standardized environments

Benefit: No more “works in DEV but fails in PROD” surprises due to mismatched builds.

B) Automated Patching & Upgrades

Patching is one of the best candidates for automation because it’s repetitive, high-risk, and time-bound (think quarterly CPU cycles). Automation adds discipline via pre-checks, sequencing, and validation.

• Pre-check validation: space, invalid objects, services, opatch version, conflict checks
• Controlled execution: scripted patch apply + datapatch + recompile steps
• Post-validation: patch inventory, component version checks, smoke tests
• Rollback strategy: clearly documented fallback & restore points

C) Backup & Recovery Automation

Backups are only valuable if they are verified and recoverable. Automation ensures backups run, are retained correctly, and are continuously validated.

• Daily incrementals + weekly full backups
• Automated backup integrity checks (restore validation / RMAN validate)
• DR sync checks (Data Guard lag thresholds / replication status)
• Automated retention enforcement & reporting

Outcome: Reduced dependence on manual intervention during a real incident.

D) Monitoring & Self-Healing Operations

Modern monitoring isn’t just dashboards — it’s automation that triggers actions. With the right controls, alerts can run safe remediation tasks and notify the team with evidence.

• Tablespace usage threshold → auto-add datafile (with guardrails)
• Service down → automated restart attempt + escalation
• Blocking sessions → detection & evidence capture (ASH/AWR/locks) + alert
• Failed jobs → restart workflow + ticket creation

Result: Lower MTTR (Mean Time To Recover) and fewer “late-night surprises”.

E) Performance Automation

Instead of waiting for tickets, proactive automation can detect regressions and produce tuning evidence.

• Automated AWR snapshot analysis & trending
• SQL plan regression detection (baselines/profiles where applicable)
• Scheduled statistics gathering and validation checks
• Index and growth recommendations (with review workflow)

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CI/CD for Databases

Database DevOps integrates schema and data-change deployments into CI/CD pipelines. A common flow looks like this:

Developer → Git Commit → Build/Validate → Schema Check → Deploy → Test → Promote

Tools often used for this include: Liquibase, Flyway, and CI orchestrators like Jenkins / GitHub Actions.

Key value: Version-controlled schema changes with consistent rollouts and rollback options.

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☁️ Automation in Cloud Databases

Cloud platforms provide built-in automation for patching, backups, and scaling. This reduces operational overhead, but still requires governance, monitoring, and change control.

Platform	Automation Examples
AWS (RDS/Aurora)	Automated backups, snapshots, maintenance windows, scaling options
OCI	Autonomous capabilities (where used), patch automation, managed services
Azure	Managed backups, monitoring integrations, scaling patterns

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Benefits of Database Automation

• Reduced human error
• Standardized deployments and maintenance
• Faster provisioning
• Better compliance and auditability
• Predictable maintenance windows
• Improved reliability and availability
• Reduced operational fatigue (less firefighting)

 Challenges (and How to Avoid Them)

• Risk: Poorly written scripts can cause large-scale impact → Mitigation: reviews + testing + approvals
• Risk: “Over-automation” without visibility → Mitigation: logging, dashboards, alert correlation
• Risk: Credential handling issues → Mitigation: vaults/secret managers + least privilege
• Risk: No rollback plan → Mitigation: restore points, backups, and documented fallback steps

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A Practical Automation Roadmap (Lead DBA View)

1. Phase 1 — Identify repetitive tasks
   Backups, validation checks, patch pre-checks, monitoring evidence capture.
2. Phase 2 — Script & standardize
   Central Git repo, naming conventions, logging format, common utility functions.
3. Phase 3 — Integrate monitoring
   Alert → action (safe) → verification → notify team with evidence.
4. Phase 4 — Pipeline integration
   CI/CD for schema changes, patch orchestration pipelines, environment promotion gates.
5. Phase 5 — Predictive operations
   Trend analysis, capacity forecasting, anomaly detection, and proactive remediation.

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The Future of DB Automation

The direction is clear: self-healing platforms, policy-driven operations, and AI-assisted optimization. Even if you don’t run “fully autonomous” databases, adopting automation principles today will significantly increase stability and delivery speed.

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✅ Conclusion

A modern DBA is not just a troubleshooter — but an automation architect. Start small, standardize, add guardrails, and scale automation in phases. Your future self (and your on-call rotation) will thank you.

Quick CTA (optional):
If you liked this post, share it with your DBA/DevOps team and bookmark it as a reference for building a strong automation practice.

Note: This article is written as a practical guide and can be adapted for Oracle, PostgreSQL, MariaDB, and cloud-managed databases.

WebLogic Admin Console access issue: Connection rejected, filter blocked Socket, weblogic.security.net.FilterException: [Security:090220] rule 2 (Oracle EBS 12.2)

Fixing WebLogic Admin Console Access Error in Oracle EBS 12.2

Error Message

The Server is not able to service this request:
[Socket:000445] Connection rejected, filter blocked Socket
weblogic.security.net.FilterException: [Security:090220] rule 2

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Root Cause

In Oracle E-Business Suite 12.2, WebLogic connection filtering is enabled as part of security hardening. If your client IP is not allow-listed, WebLogic blocks the request using a deny rule.

Typical deny rule inside config.xml:

<connection-filter-rule>0.0.0.0/0 * * deny</connection-filter-rule>

If your IP does not match an allow rule, WebLogic applies the deny rule (often rule 2), which results in the error:

[Security:090220] rule 2

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Quick Verification Steps

1. Check AdminServer log:

   cd $EBS_DOMAIN_HOME/servers/AdminServer/logs
   tail -200 AdminServer.log
   

2. Identify the blocked client IP address.
3. Verify whether your IP exists in the trusted host configuration.

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Emergency Recovery (If Completely Locked Out)

Important: This should be used only temporarily to regain access.

Step 1 – Stop Application Tier

adstpall.sh apps/APPS_PASSWORD

Step 2 – Backup and Edit config.xml

cd $EBS_DOMAIN_HOME/config
cp -p config.xml config.xml.bak
vi config.xml

Locate this line:

<connection-filter-rule>0.0.0.0/0 * * deny</connection-filter-rule>

Add allow to it:

<connection-filter-rule>0.0.0.0/0 * * allow</connection-filter-rule>

Temporarily comment or remove it:

<!-- <connection-filter-rule>0.0.0.0/0 * * deny</connection-filter-rule> -->

Step 3 – Start Application Tier

adstrtal.sh apps/APPS_PASSWORD

Now try accessing the WebLogic Admin Console again.

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Permanent Fix (Recommended Solution)

1. Update the EBS context variable for trusted admin nodes (for example: s_wls_admin_console_access_nodes).
2. Add only approved IP addresses (such as bastion host or corporate VPN egress IP).
3. Run AutoConfig:

   adautocfg.sh
   

4. Restart services:

   adstpall.sh apps/APPS_PASSWORD
   adstrtal.sh apps/APPS_PASSWORD
   

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Best Practice

• Use a Bastion or Jump Host with a fixed IP.
• Allow only trusted admin IPs.
• Keep the global deny rule enabled.
• Avoid permanent manual edits in config.xml.

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Conclusion

The error "[Security:090220] rule 2" is not a WebLogic failure. It is a security configuration blocking unauthorized access. Properly maintaining trusted host configuration ensures both security and availability.

OCI Object Storage S3 Compatibility Enhancements – POST Uploads & Virtual Hosted URLs Explained

Oracle Cloud Infrastructure (OCI) continues to improve its S3 Compatibility API for OCI Object Storage, making it easier for teams to integrate OCI Object Storage with AWS S3–compatible tools, SDKs, and applications. In this post, I’m summarizing two key enhancements:

• S3 POST Upload Support – secure, browser-based direct uploads
• Virtual-Hosted Style URLs – improved compatibility for S3 clients and tools

Reference: Oracle blog post – S3 Compatibility API Enhancements for OCI Object Storage

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Why This Update Matters

Many organizations build applications and automation around the AWS S3 ecosystem (SDKs, CLI tools, backup utilities, frameworks). When OCI Object Storage becomes more S3-compatible, it reduces friction for:

• Hybrid / multi-cloud design
• Migrating S3-based apps or tooling to OCI
• Using third-party tools that assume AWS-like URL patterns
• Browser / web application workflows for uploads

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1) S3 POST Upload Support (Secure Direct Browser Uploads)

Traditionally, many S3 integrations rely heavily on PUT requests (single request upload). OCI now supports S3 POST, which is especially useful for browser-based uploads using an HTML form and a pre-signed policy.

What is S3 POST?

S3 POST allows a user’s browser (or client) to upload directly to Object Storage using a signed POST policy generated by the backend. The backend defines upload rules and the client uploads without needing long-lived credentials.

Benefits of S3 POST

• Improved Security: No permanent credentials exposed to the browser/client.
• Fine-Grained Control: You can restrict file size, content-type, key prefix, and policy expiration.
• Reduced Backend Load: Upload traffic doesn’t need to pass through your application server.
• Web-Friendly: Works naturally with HTML forms and modern web apps.

Typical Flow (High Level)

1. User requests upload authorization from the application backend.
2. Backend generates a pre-signed POST policy with conditions (size, type, expiry).
3. User uploads directly to OCI Object Storage using POST form parameters + policy.
4. Application can validate/store metadata, and process the uploaded object.

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2) Virtual-Hosted Style URL Support

OCI Object Storage S3 Compatibility has historically been used widely with path-style addressing. Oracle is enhancing support for virtual-hosted style URLs to align more closely with AWS S3 behavior.

Path-Style vs Virtual-Hosted Style

Path-Style URL (bucket appears in the path):

https://<namespace>.compat.objectstorage.<region>.oraclecloud.com/<bucket-name>/<object-name>

Virtual-Hosted Style URL (bucket appears in the hostname):

https://<bucket-name>.vhcompat.objectstorage.<region>.oraclecloud.com/<object-name>

Why Virtual-Hosted Style is Important

• Better Tool Compatibility: Some SDKs/tools expect virtual-hosted style and may not work correctly with path-style.
• Smoother Migrations: Apps built for AWS S3 often assume this URL format.
• More AWS-Like Experience: Improves “drop-in” compatibility for S3 ecosystem clients.

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Architecture Overview (Simple)

Below is a simple conceptual view of how modern browser uploads and S3-compatible access can look in OCI:

[User Browser]
     |
     | (Request signed POST policy)
     v
[App Backend] ---- generates ----> [Signed POST Policy + Form Fields]
     |
     | (Client uploads directly using POST)
     v
[OCI Object Storage (S3 Compatibility API)]

Once uploaded, applications and tools can access objects using S3-compatible SDKs/clients (now with improved URL handling support).

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Enterprise Benefits Summary

Enhancement	Why It Helps
S3 POST Support	Enables secure direct uploads from browsers/clients without exposing credentials and without backend upload traffic.
Virtual-Hosted Style URLs	Improves compatibility with S3 tools/SDKs that expect AWS-like bucket-in-hostname patterns.
More S3 Compatibility	Reduces friction for multi-cloud deployments and migration of S3-based workloads.

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Final Thoughts

These enhancements are valuable for teams building cloud-native applications, especially if you already use the AWS S3 ecosystem and want an OCI Object Storage option that integrates smoothly. S3 POST enables more secure and scalable direct upload patterns, while virtual-hosted style URL support improves compatibility across tools and SDKs.

I’ll continue exploring OCI + AWS interoperability topics as part of my cloud learning journey, focusing on practical architecture and real-world integration patterns.

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Suggested Labels (Blogger)

• Oracle Cloud
• OCI
• Object Storage
• S3 Compatibility
• Cloud Architecture
• Multi Cloud
• AWS Integration

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Oracle DBA Scripts Collection – A Must-Have Toolkit for Every DBA

Oracle DBA Scripts Collection – A Must-Have Toolkit for Every DBA

As Oracle Database Administrators, we perform repetitive monitoring, troubleshooting, tuning, and maintenance activities daily. Instead of reinventing the wheel every time, having a ready-made, organized script repository can significantly improve productivity and standardization.

In this article, I am sharing a very useful GitHub repository that can serve as a reference toolkit for DBAs:

GitHub Repository:
https://github.com/amanpandey1729/oracle-dba-scripts

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About the Repository

This repository contains categorized Oracle DBA scripts covering monitoring, performance tuning, security checks, backup validation, tablespace management, memory diagnostics, OS checks, and more.

The scripts are well organized into folders, making it easy to locate the required utility based on your task.

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Major Script Categories

• Monitoring – Session checks, blocking sessions, active sessions, resource usage
• Performance Tuning – Slow SQL detection, optimizer statistics, execution plan insights
• Tablespace Management – Tablespace usage, free space monitoring
• Memory Management – SGA, PGA analysis
• Backup and Recovery – Backup validation scripts
• Security – User privileges, roles, security checks
• OS Linux Checks – CPU, disk, memory health scripts
• Jobs and Scheduler – Job monitoring and failure checks

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How to Use These Scripts

Step 1: Clone the repository

git clone https://github.com/amanpandey1729/oracle-dba-scripts.git

Step 2: Navigate to required folder based on your task.

Step 3: Review and customize scripts as per your environment (SID, DB_NAME, paths, etc.).

Step 4: Test in Non-Production before using in Production.

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Why Every DBA Should Bookmark This

• ✔ Saves time during incident troubleshooting
• ✔ Helps standardize health checks across environments
• ✔ Good learning material for junior DBAs
• ✔ Ready reference during audits
• ✔ Can be integrated with cron / scheduler jobs

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Important Note

All credits go to the original repository author. This article is shared as a reference and learning resource for the Oracle DBA community.

Always review scripts before running in production environments.

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My Recommendation

I recommend maintaining your own customized DBA toolkit by combining:

• Open-source script collections like this
• Your internal automation scripts
• Enterprise-specific health check standards

This will help you build a strong, reusable DBA operations framework.

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Happy Learning & Happy DBA Life! 🚀

PostgreSQL DBA Scripts from GitHub

Project POSTGRES

Exploring the postgres_dba GitHub Repository (PostgreSQL DBA Scripts Guide)

As part of my structured learning journey into PostgreSQL administration, focused on practical PostgreSQL DBA skills including monitoring, performance diagnostics, and production best practices.

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Learning Objectives

• Understand how to use Git for DBA script management
• Clone and explore a PostgreSQL DBA repository
• Identify useful monitoring and diagnostic scripts
• Apply scripts safely in real environments

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Repository Details

Repository Name: postgres_dba
Author: Nikolay Samokhvalov
Official GitHub Link:
https://github.com/NikolayS/postgres_dba

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How to Clone the Repository

cd ~/Documents
git clone https://github.com/NikolayS/postgres_dba.git
cd postgres_dba
ls -l

The git clone command downloads the complete repository, including full version history.

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Repository Structure (High-Level View)

After cloning, review the file structure:

find . -type f | sort

The repository contains multiple SQL scripts focused on:

• Active session monitoring
• Long-running query detection
• Index usage analysis
• Vacuum and maintenance monitoring
• Replication diagnostics

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Key DBA Scripts to Start With

1️⃣ Active Session Monitoring

Helps identify currently running queries and wait events.

2️⃣ Long Running Queries

Detects queries running longer than expected.

3️⃣ Index Usage Statistics

Helps identify tables performing sequential scans.

4️⃣ Vacuum / Autovacuum Monitoring

Validates maintenance effectiveness and detects bloat risk.

5️⃣ Replication Status

Monitors replication lag and WAL shipping status.

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Oracle DBA Mapping

• Oracle v$session ↔ PostgreSQL pg_stat_activity
• Oracle ASH ↔ PostgreSQL extensions / Performance Insights
• Oracle wait events ↔ wait_event_type / wait_event

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Best Practices

• Always review scripts before running in production
• Test heavy queries in non-production first
• Capture output for trend analysis
• Integrate useful scripts into your DBA toolkit

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Conclusion

Instead of copying full repositories, the correct approach is: Clone → Analyze → Curate → Learn → Apply.

Project POSTGRES will continue with deeper script analysis and performance diagnostics.

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References & Credits

All original scripts belong to the author: Nikolay Samokhvalov.

Official Repository: https://github.com/NikolayS/postgres_dba

This article is written for educational and knowledge-sharing purposes.

PostgreSQL Active Session History (pg_ash) – Complete DBA Guide

As Oracle DBAs, we are very familiar with Active Session History (ASH) for performance diagnostics. PostgreSQL does not provide built-in ASH like Oracle — but thanks to the open-source project pg_ash, we can implement similar functionality in PostgreSQL environments.

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What is pg_ash?

pg_ash is a PostgreSQL extension that collects and stores Active Session History samples, similar to Oracle ASH. It helps DBAs analyze wait events, long-running queries, blocking sessions, and overall workload behavior.

• Tracks active sessions over time
• Captures wait events
• Stores query execution samples
• Helps in performance troubleshooting
• Provides historical workload visibility

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Installation Steps

# Clone repository
git clone https://github.com/NikolayS/pg_ash.git

cd pg_ash

# Build and install
make
make install

Then connect to PostgreSQL and enable extension:

CREATE EXTENSION pg_ash;

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Sample Queries for Monitoring

1️⃣ View ASH Samples:

SELECT * FROM pg_ash;

2️⃣ Top Queries by Activity:

SELECT queryid, count(*) AS samples
FROM pg_ash
GROUP BY queryid
ORDER BY samples DESC;

3️⃣ Analyze Wait Events:

SELECT wait_event_type, wait_event, count(*)
FROM pg_ash
GROUP BY wait_event_type, wait_event
ORDER BY count(*) DESC;

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Why pg_ash is Important for DBAs

• Provides Oracle-like ASH visibility in PostgreSQL
• Helps identify performance bottlenecks
• Useful for production troubleshooting
• Great learning tool for PostgreSQL internals
• Bridges monitoring gap for hybrid Oracle + PostgreSQL DBAs

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DBA Perspective

For DBAs transitioning from Oracle to PostgreSQL (especially in cloud environments like AWS RDS), pg_ash provides a familiar monitoring model. It helps us analyze workload patterns in a structured way, similar to Oracle ASH/AWR concepts.

This makes it a powerful tool for performance diagnostics in modern PostgreSQL deployments.

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Conclusion

Open-source tools like pg_ash demonstrate the strength of the PostgreSQL ecosystem. Understanding ASH-style monitoring is essential for DBAs working in hybrid Oracle and PostgreSQL environments.

Stay tuned for more PostgreSQL performance deep dives as part of my learning journey.

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References & Credits

This open-source extension is developed by Nikolay Samokhvalov.

Official GitHub Repository:
https://github.com/NikolayS/pg_ash

All credits for the original project belong to the author. This article is written for learning and DBA knowledge-sharing purposes.

Oracle Database Scripts – Full Script Listing

Oracle Database Scripts Repository

This repository contains a large collection of Oracle DBA utility scripts covering performance tuning, monitoring, RMAN, RAC, ASM, Data Guard, AWR, ASH, and general administration.

GitHub Repository:
https://github.com/fatdba/Oracle-Database-Scripts

Download Full Repository:
Click Code → Download ZIP from GitHub.

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Complete Script Listing (Generated from Downloaded ZIP)

Click Here to Expand Full Script List

./++
./+imp_scr_oracle_daily
./+plusenv.sql
./+simplecool.sql
./activesessions_ash.sql
./Admin_General/+login.sql
./Admin_General/+plusenv.sql
./Admin_General/+simplecool.sql
./Admin_General/archive_new.sql
./Admin_General/archive.sql
./Admin_General/Bigtable_fortest.sql
./Admin_General/blocking_local.sql.com
./Admin_General/columns_usage.sql
./Admin_General/create_schedule_job.sql
./Admin_General/current_redologfile_usage.sql
./Admin_General/datafiles_fora_tablespace.sql
./Admin_General/dba_schedulerjobs.sql
./Admin_General/dbgrowth_permonth.sql
./Admin_General/dblink_checker_withJob.sql
./Admin_General/dblink_details.sql
./Admin_General/dbms_jobs_broken.sql
./Admin_General/dbserverdetails.sql
./Admin_General/dbtime.sql
./Admin_General/dbupgdiag.sql
./Admin_General/ddl_schema.sql
./Admin_General/ddl-objects.sql
./Admin_General/Fat200objects.sql
./Admin_General/file_block.sql
./Admin_General/file_border.sql
./Admin_General/find_objects_1.sql
./Admin_General/find_objects_2.sql
./Admin_General/find_objects.sql
./Admin_General/find_x$_basetables.sql
./Admin_General/flashback_main.sql
./Admin_General/get_dependent_ddl.sql
./Admin_General/hidden_params.sql
./Admin_General/hugepages.sh
./Admin_General/iostat_summary.sql
./Admin_General/jobs.sql
./Admin_General/killer.sql
./Admin_General/latest_tab_stats.sql
./Admin_General/logmining.sql
./Admin_General/materializedview.sql
./Admin_General/object_blocks.sql
./Admin_General/object_changes.sql
./Admin_General/object_dependencies.sql
./Admin_General/object_details.sql
./Admin_General/object_growth_trend.sql
./Admin_General/object_username.sql
./Admin_General/objectid.sql
./Admin_General/objects_changed.sql
./Admin_General/objects_matching_pattern.sql
./Admin_General/oem_informationpublishereport.sql
./Admin_General/oracle_license_info.sql
./Admin_General/Oracle_Test1.sql
./Admin_General/params.sql
./Admin_General/partitions_drop_future.sql
./Admin_General/partitions_expimp_stats.sql
./Admin_General/partitions_rowcount_each.sql
./Admin_General/partitions_synopsys_incremental.sql
./Admin_General/privileges_copy.sql
./Admin_General/redostats.sql
./Admin_General/resize-datafiles.sql
./Admin_General/running_jobs.sql
./Admin_General/scheduler_shellscript_dbmsscheduler.sql
./Admin_General/securefile_testdata.sql
./Admin_General/segments_inside_datafile.sql
./Admin_General/sequences.sql
./Admin_General/sessions_active.sql
./Admin_General/sessions_main.sql
./Admin_General/sessionusage_upanddownstats.sql
./Admin_General/setnlsdateformat.sql
./Admin_General/shrink_datafiles.sql
./Admin_General/sid_from_ospid.sql
./Admin_General/smon_rollback_monitoring.sql
./Admin_General/states.sql
./Admin_General/tab_ind_detailsschema.sql
./Admin_General/table_set_preference.sql
./Admin_General/tablespace_boundary.sql
./Admin_General/tablespace_free-sum.sql
./Admin_General/tablespaceinfo.sql
./Admin_General/tmp_stats.sql
./Admin_General/top_ts_segments.sql
./Admin_General/top_workarea.sql
./Admin_General/top10.sql
./Admin_General/trace_all_session_ofauser.sql
./Admin_General/tracking_database_usage.sql
./Admin_General/undo_another.sql
./Admin_General/undo_somemore.sql
./Admin_General/undo_stats.sql
./Admin_General/undomain.sql
./Admin_General/unregister_mview_snap.sql
./Admin_General/unused_space.sql
./Admin_General/what_has_changed.sql
./all_stalestats.sql
./archive_new.sql
./archive.sql
./ash_cachebufferchain.sql
./ash_event_trend.sql
./ash_last_x_mins.sql
./ash_last_x_secs.sql
./ash_latch.sql
./ash_object_enq_contention.sql
./ash_pio_events.sql
./ash_sid.sql
./ash_sqlid_mins.sql
./ash_top_events.sql
./ash_toppga_2mb.sql
./asm_diskdrop.sql
./ASM/+login.sql
./ASM/+plusenv.sql
./ASM/asm_diskdrop.sql
./ASM/asmdiskgroup.sql
./ASM/asmfilevolinfo.sql
./ASM/asmspaceused.sql
./asmdiskgroup.sql
./asmfilevolinfo.sql
./asmspaceused.sql
./autostatsgatherdet.sql
./awr_manualsnap.sql
./awr_modify_topnsql.sql
./awretention.sql
./BackupAndRecovery/+login.sql
./BackupAndRecovery/+plusenv.sql
./BackupAndRecovery/rman_bkpdetails.sql
./BackupAndRecovery/rman_datafile_backup.sql
./BackupAndRecovery/rman_everything.sql
./BackupAndRecovery/rman_fulldb_backupscript.sql
./BackupAndRecovery/rman_incremental_backup.sql
./BackupAndRecovery/rman_main.sql
./BackupAndRecovery/rman_monitoring.sql
./BackupAndRecovery/rman_tablespace_backup.sql
./BackupAndRecovery/rman1.sql
./BackupAndRecovery/rmanbest.sql
./Bigtable_fortest.sql
./bindvariables_fromawr.sql
./blocking_local.sql
./check_dataguard_config.sql
./check_modify_awrretention.sql
./coe_xfr_sql_profile.sql
./columns_usage.sql
./cpu_stats.sql
./cpubusytime_db.sql
./cpuusage.sql
./create_schedule_job.sql
./create_sql_patch.sql
./current_redologfile_usage.sql
./cursor_notsharing_reason.sql
./datampump_monitoring.sql
./datapump_10046trace_process.sql
./datapump_cleanup_orphanedjobs.sql
./datapump_samplescript.sh
./DataPump/data_pump_monitor_core.sql
./DataPump/datampump_monitoring.sql
./DataPump/datapump_10046trace_process.sql
./DataPump/datapump_cleanup_orphanedjobs.sql
./DataPump/datapump_samplescript.sh
./DataPump/partitions_expimp_stats.sql
./db_hang.sql
./dba_hist_snapshot.sql
./dba_hist_sqlbind.sql
./dba_schedulerjobs.sql
./dbgrowth_permonth.sql
./dblink_details.sql
./dbms_jobs_broken.sql
./dbserverdetails.sql
./dbtime.sql
./dbupgdiag.sql
./ddl_schema.sql
./ddl-objects.sql
./disable_resourcemanager.sql
./dop_tablesindexes.sql
./drop_phv_baseline.sql
./drop_sql_baseline.sql
./drop_sql_profile.sql
./drop_sqlplan_baselines.sql
./dynamic_sampling_objects.sql
./enq_tx_indexcontention_split.sql
./exadata_cellperf.sql
./Exadata/+login.sql
./Exadata/+plusenv.sql
./Exadata/exadata_cellperf.sql
./failover_stats.sql
./Fat200objects.sql
./file_block.sql
./file_border.sql
./find_objects_1.sql
./find_objects_2.sql
./find_objects.sql
./find_sql_2.sql
./find_sql_pio_1.sql
./find_sql_pio.sql
./find_sql.sql
./find_x$_basetables.sql
./fklocking.sql
./flashback_main.sql
./flushsql_cursor.sql
./FULL_FILE_LIST.txt
./gather_stats.sql
./generate_set_tablestats.sql
./get_dependent_ddl.sql
./get_optimizer_trace.sql
./getbinds-sqlid.sql
./goldengate_healthcheck.sql
./GoldenGate/+login.sql
./GoldenGate/+plusenv.sql
./GoldenGate/goldengate_healthcheck.sql
./hidden_params.sql
./hidden.sql
./high_version_count.sql
./hints.sql
./hot_librarycache_objects.sql
./hourly_segment_stats.sql
./hugepages.sh
./idx_2.sql
./idx_3.sql
./idx_fragmentation.sql
./idx_main.sql
./idx_split_2.sql
./idx_split_session.sql
./idx_split.sql
./idx_usage.sql
./indexlargerthantable.sql
./iointensive_sql_mem.sql
./iostat_summary.sql
./iousage_tempfiles.sql
./latchdetails.sql
./librarycache_locks.sql
./lockingmother.sql
./logfilesync_lfsdiag.sql
./mismatch.sql
./mutex_sleep.sql
./mypoormanscript_fancy.sql
./mypoormanscript.sh
./mypoormanscript.sql
./mysid.sql
./Nonindexedfkconstraints.sql
./object_dependencies.sql
./objects_waiting_miss_sleep.sql
./OFE_12.1.0.2_in_12.2.0.1.sql
./oracle_license_info.sql
./Oracle_Test1.sql
./outlinedata_for_spmsqlbaselines.sql
./p_ash_blockers.sql
./p_ash_events.sql
./parentchild_rel.sql
./partitions_drop_future.sql
./partitions_expimp_stats.sql
./partitions_rowcount_each.sql
./partitions_synopsys_incremental.sql
./pdhc_v1.2.sql
./PerformanceTuning_Mgmt/+login.sql
./PerformanceTuning_Mgmt/+plusenv.sql
./PerformanceTuning_Mgmt/active_sql_workarea.sql
./PerformanceTuning_Mgmt/activesessions_ash.sql
./PerformanceTuning_Mgmt/all_stalestats.sql
./PerformanceTuning_Mgmt/archive_new.sql
./PerformanceTuning_Mgmt/ash_cachebufferchain.sql
./PerformanceTuning_Mgmt/ash_event_trend.sql
./PerformanceTuning_Mgmt/ash_last_x_mins.sql
./PerformanceTuning_Mgmt/ash_last_x_secs.sql
./PerformanceTuning_Mgmt/ash_latch.sql
./PerformanceTuning_Mgmt/ash_object_enq_contention.sql
./PerformanceTuning_Mgmt/ash_pio_events.sql
./PerformanceTuning_Mgmt/ash_sid.sql
./PerformanceTuning_Mgmt/ash_sqlid_mins.sql
./PerformanceTuning_Mgmt/ash_top_events.sql
./PerformanceTuning_Mgmt/ash_toppga_2mb.sql
./PerformanceTuning_Mgmt/auto_stats_collection.sql
./PerformanceTuning_Mgmt/autostatsgatherdet.sql
./PerformanceTuning_Mgmt/awr_manualsnap.sql
./PerformanceTuning_Mgmt/awr_modify_topnsql.sql
./PerformanceTuning_Mgmt/awretention.sql
./PerformanceTuning_Mgmt/bindvariables_fromawr.sql
./PerformanceTuning_Mgmt/check_modify_awrretention.sql
./PerformanceTuning_Mgmt/coe_xfr_sql_profile.sql
./PerformanceTuning_Mgmt/columns_usage.sql
./PerformanceTuning_Mgmt/cpu_stats.sql
./PerformanceTuning_Mgmt/cpubusytime_db.sql
./PerformanceTuning_Mgmt/cpuusage.sql
./PerformanceTuning_Mgmt/create_sql_patch.sql
./PerformanceTuning_Mgmt/cursor_notsharing_reason.sql
./PerformanceTuning_Mgmt/db_hang.sql
./PerformanceTuning_Mgmt/dba_hist_snapshot.sql
./PerformanceTuning_Mgmt/dba_hist_sqlbind.sql
./PerformanceTuning_Mgmt/dbgrowth_permonth.sql
./PerformanceTuning_Mgmt/dbtime.sql
./PerformanceTuning_Mgmt/disable_resourcemanager.sql
./PerformanceTuning_Mgmt/dop_tablesindexes.sql
./PerformanceTuning_Mgmt/drop_phv_baseline.sql
./PerformanceTuning_Mgmt/drop_sql_baseline.sql
./PerformanceTuning_Mgmt/drop_sql_profile.sql
./PerformanceTuning_Mgmt/drop_sqlplan_baselines.sql
./PerformanceTuning_Mgmt/dynamic_sampling_objects.sql
./PerformanceTuning_Mgmt/enq_tx_indexcontention_split.sql
./PerformanceTuning_Mgmt/find_sql_2.sql
./PerformanceTuning_Mgmt/find_sql_pio_1.sql
./PerformanceTuning_Mgmt/find_sql_pio.sql
./PerformanceTuning_Mgmt/find_sql.sql
./PerformanceTuning_Mgmt/fklocking.sql
./PerformanceTuning_Mgmt/flushsql_cursor.sql
./PerformanceTuning_Mgmt/gather_stats.sql
./PerformanceTuning_Mgmt/generate_set_tablestats.sql
./PerformanceTuning_Mgmt/get_optimizer_trace.sql
./PerformanceTuning_Mgmt/getbinds-sqlid.sql
./PerformanceTuning_Mgmt/high_version_count.sql
./PerformanceTuning_Mgmt/hints.sql
./PerformanceTuning_Mgmt/hot_librarycache_objects.sql
./PerformanceTuning_Mgmt/hourly_segment_stats.sql
./PerformanceTuning_Mgmt/idx_2.sql
./PerformanceTuning_Mgmt/idx_3.sql
./PerformanceTuning_Mgmt/idx_fragmentation.sql
./PerformanceTuning_Mgmt/idx_main.sql
./PerformanceTuning_Mgmt/idx_split_2.sql
./PerformanceTuning_Mgmt/idx_split_session.sql
./PerformanceTuning_Mgmt/idx_split.sql
./PerformanceTuning_Mgmt/idx_usage.sql
./PerformanceTuning_Mgmt/indexlargerthantable.sql
./PerformanceTuning_Mgmt/iointensive_sql_mem.sql
./PerformanceTuning_Mgmt/iousage_tempfiles.sql
./PerformanceTuning_Mgmt/latch_waits.sql
./PerformanceTuning_Mgmt/latchdetails.sql
./PerformanceTuning_Mgmt/latchholder.sql
./PerformanceTuning_Mgmt/libcache_lock_bysid.sql
./PerformanceTuning_Mgmt/libcache_lock_waits.sql
./PerformanceTuning_Mgmt/libcache_pin_waits.sql
./PerformanceTuning_Mgmt/libcache_pins_bysid.sql
./PerformanceTuning_Mgmt/Librarycache_lock_holders.sql
./PerformanceTuning_Mgmt/librarycache_locks.sql
./PerformanceTuning_Mgmt/locked_objects_summary.sql
./PerformanceTuning_Mgmt/locked_objects.sql
./PerformanceTuning_Mgmt/lockedstats.sql
./PerformanceTuning_Mgmt/lockingmother.sql
./PerformanceTuning_Mgmt/logfilesync_lfsdiag.sql
./PerformanceTuning_Mgmt/mismatch.sql
./PerformanceTuning_Mgmt/module_pio.sql
./PerformanceTuning_Mgmt/mutex_sleep.sql
./PerformanceTuning_Mgmt/mutex.sql
./PerformanceTuning_Mgmt/mysid.sql
./PerformanceTuning_Mgmt/Nonindexedfkconstraints.sql
./PerformanceTuning_Mgmt/objects_waiting_miss_sleep.sql
./PerformanceTuning_Mgmt/OFE_12.1.0.2_in_12.2.0.1.sql
./PerformanceTuning_Mgmt/outlinedata_for_spmsqlbaselines.sql
./PerformanceTuning_Mgmt/p_ash_blockers.sql
./PerformanceTuning_Mgmt/p_ash_events.sql
./PerformanceTuning_Mgmt/parentchild_rel.sql
./PerformanceTuning_Mgmt/pga_size_estim.sql
./PerformanceTuning_Mgmt/pgaintensivesql.sql
./PerformanceTuning_Mgmt/pretty_metadata.sql
./PerformanceTuning_Mgmt/procwatcher_prw.sql
./PerformanceTuning_Mgmt/px_query_details.sql
./PerformanceTuning_Mgmt/px_query_monitoring.sql
./PerformanceTuning_Mgmt/PXHCDR.sql
./PerformanceTuning_Mgmt/rat_approx_replayprogress.sql
./PerformanceTuning_Mgmt/rat_blocking_sessions.sql
./PerformanceTuning_Mgmt/rat_replay_divergence.sql
./PerformanceTuning_Mgmt/rat_waitevents.sql
./PerformanceTuning_Mgmt/redundantindex.sql
./PerformanceTuning_Mgmt/segments_stats_daily.sql
./PerformanceTuning_Mgmt/sequenceexhaustion80.sql
./PerformanceTuning_Mgmt/session-wait-by-sid.sql
./PerformanceTuning_Mgmt/sessions_librarycachelock.sql
./PerformanceTuning_Mgmt/sga-details.sql
./PerformanceTuning_Mgmt/share.sql
./PerformanceTuning_Mgmt/shared_sqlcursor_reason.sql
./PerformanceTuning_Mgmt/sharedpool_advisory.sql
./PerformanceTuning_Mgmt/sharedpool_lru.sql
./PerformanceTuning_Mgmt/sharedpool_pinned.sql
./PerformanceTuning_Mgmt/sharedpool_stats.sql
./PerformanceTuning_Mgmt/sharedpool_statssubpool.sql
./PerformanceTuning_Mgmt/sharedpool_subpool.sql
./PerformanceTuning_Mgmt/showlock.sql
./PerformanceTuning_Mgmt/snap-session-waits.sql
./PerformanceTuning_Mgmt/sp-reserved.sql
./PerformanceTuning_Mgmt/sparse_Indexes.sql
./PerformanceTuning_Mgmt/sql_changed_elapsedtime.sql
./PerformanceTuning_Mgmt/sql_from_procedures.sql
./PerformanceTuning_Mgmt/sql_plan_baselines.sql
./PerformanceTuning_Mgmt/sql_planflip_new.sql
./PerformanceTuning_Mgmt/sqlflip_newbetter.sql
./PerformanceTuning_Mgmt/sqlflip1.sql
./PerformanceTuning_Mgmt/sqlflip2.sql
./PerformanceTuning_Mgmt/sqlhistory.sql
./PerformanceTuning_Mgmt/sqlid_info.sql
./PerformanceTuning_Mgmt/sqlid_main.sql
./PerformanceTuning_Mgmt/sqlid_phv.sql
./PerformanceTuning_Mgmt/sqlid_topworkarea.sql
./PerformanceTuning_Mgmt/sqloffload_iosaved.sql
./PerformanceTuning_Mgmt/sqlprofile_hints.sql
./PerformanceTuning_Mgmt/sqls_doing_fulltablescan.sql
./PerformanceTuning_Mgmt/sqlstats_history_sqlid.sql
./PerformanceTuning_Mgmt/sqlstats_main.sql
./PerformanceTuning_Mgmt/STA_SQLID_Cursor.sql
./PerformanceTuning_Mgmt/stale_stats.sql
./PerformanceTuning_Mgmt/stats_delete.sql
./PerformanceTuning_Mgmt/stats_get_preference.sql
./PerformanceTuning_Mgmt/stats_incremental.sql
./PerformanceTuning_Mgmt/stats_lock.sql
./PerformanceTuning_Mgmt/table_ind_pkfkcons_DDL.sql
./PerformanceTuning_Mgmt/table_stats_details.sql
./PerformanceTuning_Mgmt/tempintensivesql.sql
./PerformanceTuning_Mgmt/test.sql
./PerformanceTuning_Mgmt/top_sql_cpu.sql
./PerformanceTuning_Mgmt/top_sqls.sql
./PerformanceTuning_Mgmt/top10activesessions.sql
./PerformanceTuning_Mgmt/trace-onoff.sql
./PerformanceTuning_Mgmt/tracemy_sqlid.sql
./PerformanceTuning_Mgmt/treedump.sql
./PerformanceTuning_Mgmt/wait_Chains.sql
./PerformanceTuning_Mgmt/waiteventcontributors.sql
./PerformanceTuning_Mgmt/waits_lfs.sql
./PerformanceTuning_Mgmt/waits_sum.sql
./PerformanceTuning_Mgmt/waitstats.sql
./PerformanceTuning_Mgmt/whattypeof_histogram.sql
./PerformanceTuning_Mgmt/workarea.sql
./PerformanceTuning_Mgmt/xplan_adv_sqlid.sql
./PerformanceTuning_Mgmt/xplan_awr_phash.sql
./PerformanceTuning_Mgmt/xplan_awr.sql
./PerformanceTuning_Mgmt/xplan_objectname.sql
./PerformanceTuning_Mgmt/xplan_phash.sql
./PerformanceTuning_Mgmt/xplan_sid.sql
./PerformanceTuning_Mgmt/xplan_sqlhash.sql
./PerformanceTuning_Mgmt/xplan_sqlid_incursor.sql
./pgaintensivesql.sql
./privileges_copy.sql
./procwatcher_prw.sql
./px_query_details.sql
./px_query_monitoring.sql
./PXHCDR.sql
./rac_clock_sync.sql
./rac_diag.sql
./rac_longops.sql
./rac_main.sql
./RAC/+login.sql
./RAC/+plusenv.sql
./RAC/rac_clock_sync.sql
./RAC/rac_diag.sql
./RAC/rac_longops.sql
./RAC/rac_main.sql
./RAC/racdbstatus.sql
./racdbstatus.sql
./rat_approx_replayprogress.sql
./rat_blocking_sessions.sql
./rat_replay_divergence.sql
./rat_waitevents.sql
./redostats.sql
./redundantindex.sql
./rman_bkpdetails.sql
./rman_datafile_backup.sql
./rman_fulldb_backupscript.sql
./rman_incremental_backup.sql
./rman_main.sql
./rman_monitoring.sql
./rman_tablespace_backup.sql
./rman1.sql
./rowlocking.sql
./scheduler_shellscript_dbmsscheduler.sql
./segments_inside_datafile.sql
./segments_stats_daily.sql
./sequenceexhaustion80.sql
./sessions_active.sql
./sessions_librarycachelock.sql
./sessions_main.sql
./sessionusage_upanddownstats.sql
./sga-details.sql
./sharedpool_advisory.sql
./showlock.sql
./sid_from_ospid.sql
./smon_rollback_monitoring.sql
./sparse_Indexes.sql
./sql_changed_elapsedtime.sql
./sql_from_procedures.sql
./sql_planflip_new.sql
./sqlflip_newbetter.sql
./sqlflip1.sql
./sqlflip2.sql
./sqlhistory.sql
./sqlid_info.sql
./sqlid_main.sql
./sqlid_phv.sql
./sqloffload_iosaved.sql
./sqls_doing_fulltablescan.sql
./sqlstats_history_sqlid.sql
./STA_SQLID_Cursor.sql
./standby_core_collection.sql
./standby_monitorlag_rac.sql
./standby_single.sql
./Standby/+login.sql
./Standby/+plusenv.sql
./Standby/check_dataguard_config.sql
./Standby/DGDiagnostic.sh
./Standby/failover_stats.sql
./Standby/quick_gap_check.sql
./Standby/srdc_DGlogicalStby_diag.sql
./Standby/srdc_DGPhyStby_diag.sql
./Standby/srdc_DGPrimary_diag.sql
./Standby/standby_core_collection.sql
./Standby/standby_monitor.sql
./Standby/standby_monitorlag_rac.sql
./Standby/standby_single.sql
./Standby/standbygap.sql
./standbygap.sql
./stats_delete.sql
./stats_get_preference.sql
./stats_incremental.sql
./stats_lock.sql
./table_ind_pkfkcons_DDL.sql
./tablespaceinfo.sql
./tempintensivesql.sql
./Tools_And_Monitoring/+login.sql
./Tools_And_Monitoring/+plusenv.sql
./Tools_And_Monitoring/ashtop.sql
./Tools_And_Monitoring/dashtop.sql
./Tools_And_Monitoring/mypoormanscript_fancy.sql
./Tools_And_Monitoring/mypoormanscript.sh
./Tools_And_Monitoring/mypoormanscript.sql
./Tools_And_Monitoring/pdhc_v1.2.sql
./Tools_And_Monitoring/snapper.sql
./top_sqls.sql
./top10activesessions.sql
./trace_all_session_ofauser.sql
./tracemy_sqlid.sql
./tracking_database_usage.sql
./undo_somemore.sql
./undomain.sql
./wait_Chains.sql
./waiteventcontributors.sql
./what_has_changed.sql
./whattypeof_histogram.sql

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Note: This list was generated from the downloaded repository package. All credits belong to the original author of the repository.

ORA-00600 [kqlhdlod-bad-base-objn] in 19c PDB – Dictionary Corruption Repair Using DBMS_DICTIONARY_CHECK

Environment: Oracle 19c Multitenant Database
PDB: FNDEV30
Error Type: ORA-00600 (Internal Error)
Component: Data Dictionary / DBMS_PDB

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🚨 Problem Description

The following error was observed in the alert log:

ORA-00600: internal error code, arguments: [kqlhdlod-bad-base-objn], [1403], [849005], [2081137], [88], [5]
ORA-06512: at "SYS.DBMS_PDB", line 85

Trace file location:

/u01/app/oracle/diag/rdbms/fnutcdb/FNUTCDB/trace/FNUTCDB_j000_2280695.trc

Oracle generated incident files and recommended packaging via ADRCI or Support Workbench.

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🔎 Understanding the Error

The error ORA-00600 [kqlhdlod-bad-base-objn] indicates a problem related to:

• Dictionary metadata inconsistency
• Invalid base object number reference
• Possible orphaned or corrupted dictionary entry
• Failure inside DBMS_PDB package

This is an internal error and typically requires Oracle Support involvement.

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🛠 Oracle Recommended Solution

Oracle Support advised running the dictionary repair procedure using:

Step 1 – Connect to the affected PDB

SQL> ALTER SESSION SET CONTAINER=FNDEV30;

Step 2 – Run Dictionary Repair

SQL> SET SERVEROUTPUT ON SIZE UNLIMITED;
SQL> EXECUTE DBMS_DICTIONARY_CHECK.FULL(repair=>TRUE);

This command scans and repairs dictionary inconsistencies.

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📋 Step 3 – Validate After Repair

SQL> SPOOL dictionary_check_after_repair.log
SQL> SET SERVEROUTPUT ON SIZE UNLIMITED;
SQL> EXECUTE DBMS_DICTIONARY_CHECK.FULL;
SQL> SPOOL OFF;

Review the spool log for remaining issues.

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⚠️ Important Notes

WARNING:

• Always take a valid backup before running dictionary repair.
• Run repair only under Oracle Support guidance.
• Test in lower environment if possible.
• Never manually modify dictionary tables.

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📌 Best Practices

• Monitor alert log regularly
• Package incidents using ADRCI before repair
• Validate dictionary health during PDB clone/upgrade operations
• Keep quarterly patches up to date

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🎯 Conclusion

ORA-00600 errors involving dictionary corruption can look critical, but Oracle provides a supported repair mechanism using DBMS_DICTIONARY_CHECK.

Always involve Oracle Support, perform backups, and validate thoroughly after repair.

Stay proactive. Monitor. Validate. Repair safely.

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Author: Punit – Oracle EBS & Database Specialist