⚡ Optimize namespace component grouping using Union-Find

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

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[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

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---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.

[akutuva21]

💡 What: Replaced the highly inefficient O(N^3) repeated nested loop inside findOverlappingNamespace with a Disjoint Set Union (Union-Find) algorithm. It maps annotation and annotationName references efficiently to unify overlapping clusters in O(N * α(N)) time.
🎯 Why: The prior approach utilized a nested loop checking subset intersections inside a while loop that threw exceptions and fully restarted whenever an overlap was detected, causing severe algorithmic complexity and catastrophic slow downs when finding heavily overlapping graph relationships.
📊 Measured Improvement: Under the benchmark simulating 500 nodes with random overlap probability, the original nested loop took ~4.76s to execute. The refactored Union-Find method completed the exact same clustering on the same structure in <0.01s (0.0087s), correctly matching identical node sets.

---

PR created automatically by Jules for task 16539731179192652333 started by @akutuva21

[google-labs-jules]

👋 Jules, reporting for duty! I'm here to lend a hand with this pull request.

When you start a review, I'll add a 👀 emoji to each comment to let you know I've read it. I'll focus on feedback directed at me and will do my best to stay out of conversations between you and other bots or reviewers to keep the noise down.

I'll push a commit with your requested changes shortly after. Please note there might be a delay between these steps, but rest assured I'm on the job!

For more direct control, you can switch me to Reactive Mode. When this mode is on, I will only act on comments where you specifically mention me with @jules. You can find this option in the Pull Request section of your global Jules UI settings. You can always switch back!

New to Jules? Learn more at jules.google/docs.

---

For security, I will only act on instructions from the user who triggered this task.

[akutuva21]

Superseded by #108 namingDatabase batching optimization.

[google-labs-jules]

Superseded by #108 namingDatabase batching optimization.

Understood. Acknowledging that this work is superseded by #108 and stopping work on this task.