Shannon-Data/ShannonBase - Open Source PR Review Scorecard

The Next-Gen Database for AI—an infrastructure designed for data and AI. As the MySQL of the AI era.

C-Rank Grade: A (Welcoming) - 57/100

External PR Merge Rate: 92%

Response Time: 9d

First Timer Success: 50%

Frequently Asked Questions

Is Shannon-Data/ShannonBase welcoming to first-time open-source contributors?

Shannon-Data/ShannonBase has a recorded first-timer success rate of 50.0%. Repositories ranked A typically provide actionable feedback during code reviews and actively nurture new community contributors.

How fast can I expect code review feedback on my pull request?

Maintainers in Shannon-Data/ShannonBase respond to incoming external pull requests in approximately 209.8 hours on average. Keeping PRs focused on single tasks and ensuring tests pass helps maintainers review faster.

What does the 56.8 C-Rank™ score (A Tier) represent?

The C-Rank™ system evaluates GitHub projects on a 0–100 scale using real data: PR merge rates, review turnaround time, active maintainer presence, and first-time contributor success. A score of 56.8 places Shannon-Data/ShannonBase in the A tier.

What is the external contributor pull request merge rate for Shannon-Data/ShannonBase?

The external contributor pull request merge rate for Shannon-Data/ShannonBase is 92.1%, based on public PR activity from non-core contributors.

Are there Good First Issues available in Shannon-Data/ShannonBase?

Shannon-Data/ShannonBase currently has 5 active issue(s) tagged with beginner-friendly labels like "good first issue", "beginner", or "up-for-grabs".

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Shannon-Data/ShannonBase

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InactiveA•Welcoming(57/100)C++

The Next-Gen Database for AI—an infrastructure designed for data and AI. As the MySQL of the AI era.

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AI Maintainer Review Guidelines

Review Persona

Empathetic Technical Mentor

Warmth Score
8.3/10
Patience Score
8.6/10
Nitpick Rate
20%

Highly welcoming maintainers in Shannon-Data/ShannonBase. Prompt code reviews with positive guidance for new contributors.

Top PR Submission Do's

  • •Ensure code complies with the project coding style
  • •Keep PRs scoped to a single concern
  • •Include context and link to the related issue

Top PR Friction Pitfalls (Don'ts)

  • •Do not submit PRs without linking an issue
  • •Do not break existing tests without fixing them
  • •Do not mix unrelated refactors in a single PR
Response Velocity
8 days+
Standard maintainer review cycle

Average Response Latency

Tracks hours until a maintainer leaves a review, comment, or PR response.

Merge Efficiency
92.1%
High acceptance rate for external PRs

External Acceptance Rate

Percentage of community pull requests successfully merged into main.

First-Timer Success
50.0%
Accepts new contributor PRs

First PR Conversion

Rate at which developers submitting their first repository PR succeed.

Active Maintainers
1 core
Single maintainer review bottleneck
Diagnostic Health HUD
92.1%
Merge Gauge
50.0%
1st-Timer
Community Vibe52/100

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GetMerged C-Rank badge for Shannon-Data/ShannonBase
[![GetMerged C-Rank](https://getmerged.abhishekco.de/api/badge/Shannon-Data/ShannonBase)](https://getmerged.abhishekco.de/Shannon-Data/ShannonBase?utm_source=github&utm_medium=badge)

Active Good First Issues (5)

View on GitHub

Summary HeatWave-style guidance: low-cardinality string columns used as JOIN / GROUP BY keys should be compared and hashed as dictionary codes (fixed-width integers) rather than as decoded strings, because it shrinks the working set, replaces string ops with integer ops, and vectorizes far better. This issue tracks closing that gap in the rapid engine. Audit result: neither the hash join nor the hash aggregate exploits dictionary codes today. Both deliberately fall back to a decoded-string path. Audited at 9294ff340d4a36d95ada87d4c597c6a89433d48a (branch main). Current state of string encoding (differs from HeatWave's model) HeatWave ShannonBase today Encoding choice VARLEN or DICTIONARY, per column CHAR/VARCHAR are always dictionary-encoded; there is no raw-VARLEN option RAPID_COLUMN=ENCODING=SORTED|VARLEN selects the storage form only selects the dictionary-entry compressor (SORTED→ZSTD, VARLEN→LZ4), and only for entries ≥ 64 B CU slot width variable / fixed-width c

📅 Opened Sep 29, 2026💬 0 comments
Quality: 75/100Contribute

Summary Seven of the 22 TPC-H queries execute with zero vectorized operators. The cause is not the join shape: it is that AccessPath::STREAM is always translated to a MySQLNative node, and MySQLNative::ToAccessPath() discards the translated subtree and walks the entire original subtree clearing vectorized. One Stream results node anywhere in the plan therefore takes everything below it native. Measurement Counting Vectorized in EXPLAIN FORMAT=TREE against Stream results, TPC-H SF0.2, hypergraph on, use_secondary_engine=FORCED: query vectorized ops Stream results q3, q5, q10, q11, q13, q16, q21 0 1 q1, q4, q12, q18 1 0 q6, q15, q19, q20 2 0 q14, q17 4 0 q22 6 0 q9 7 0 q2 8 0 q7 9 0 q8 0 0 The correlation is exact: every query containing a STREAM node vectorizes nothing, every query without one vectorizes something. (q8 is 0/0 — a separate cause, not covered here.) Mechanism Optimizer::translate_access_path(), case AccessPath::STREAM translates the child and t

📅 Opened Sep 25, 2026💬 0 comments
Quality: 60/100Contribute

Summary Description for this feature. The core version of mysql has been upgraded from 8.x to 9.7.x LTS. And ShannonBase also should do this upgrade opers.

📅 Opened Sep 14, 2026💬 0 comments
Quality: 35/100Contribute

Summary Description for this feature. in order to increase the converage, we should add more MTR cases to cover all workload scenarios.

📅 Opened Sep 14, 2026💬 0 comments
Quality: 35/100Contribute

Summary Description for this feature. Ingest Files into a Vector Store CALL sys.VECTOR_STORE_LOAD("oci://BucketName@Namespace/Path/Filename", @options); ref : https://dev.mysql.com/doc/heatwave/en/mys-hw-genai-vector-store-load.html

📅 Opened Jun 30, 2026💬 0 comments
Quality: 25/100Contribute
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Contributor Compatibility & Review Speed Analysis for Shannon-Data/ShannonBase

When evaluating whether to contribute to Shannon-Data/ShannonBase, response velocity and maintainer engagement are crucial. GetMerged continuously tracks pull request trajectories, first-comment latency, and code review rounds to help developers avoid submitting pull requests to backlogged repositories.

Currently, maintainers of Shannon-Data/ShannonBase acknowledge new external contributions in approximately 8 days+. Out of all submitted pull requests from non-core authors in the last 180-day window, 92.1% were successfully merged into the primary branch.

Frequently Asked Questions - Contributing to Shannon-Data/ShannonBase

01

Is Shannon-Data/ShannonBase welcoming to first-time open-source contributors?

Shannon-Data/ShannonBase has a recorded first-timer success rate of 50.0%. Repositories ranked Welcoming typically provide actionable feedback during code reviews and actively nurture new community contributors.

02

How fast can I expect code review feedback on my pull request?

The initial maintainer response time averages ~8 days+. Keeping PRs scoped to single concerns and ensuring CI checks succeed will optimize review turnaround.

03

What does the 56.8 C-Rank™ score represent?

The C-Rank™ index scores repositories on a 0 to 100 scale using an objective formula: external PR merge rates, initial response speed, active maintainer count, and first-time contributor retention. A score of 56.8 places Shannon-Data/ShannonBase in the Welcoming tier.

04

What is the external contributor pull request merge rate for Shannon-Data/ShannonBase?

The external pull request merge rate is 92.1%. GetMerged isolates non-core community contributions so external developers get an accurate benchmark of PR acceptance probability.

05

Are there beginner Good First Issues open in Shannon-Data/ShannonBase?

Yes, Shannon-Data/ShannonBase currently has 5 active issue(s) tagged with beginner-friendly labels. You can inspect these directly from the repository issues tab.

GetMerged C-Rank™ Indexing Standard

All metrics displayed for Shannon-Data/ShannonBase are automatically retrieved via the public GitHub API and recalculated daily. Insider pull requests submitted by repository owners or organization members are excluded from merge rate calculations to preserve objective external contributor statistics.