docs: Update version to 0.19.1, enhance foreign key features, and imp…

[pflooky]

…rove documentation

• Bump version in various files to 0.19.1.
• Introduce cardinality and nullability controls for foreign key relationships.
• Add new documentation for foreign key enhancements and update existing links.
• Improve logging levels for better debugging.
• Update Dockerfile and example configurations to reflect the new version.
• Add feature catalog for standardized documentation of all features.

---

Note

Medium Risk
Touches plan execution option-merging and Spark defaults, which can change runtime behavior for YAML-based runs and Spark environments. Most other changes are docs/CI/version bumps, but the new defaults should be validated in real deployments.

Overview
Bumps the project and published artifacts to 0.19.1 (Gradle version, docs/examples/Docker image references) and switches CI Java distribution from Oracle to Temurin.

Improves runtime/build stability by merging service files in the shaded JAR (to avoid Hadoop provider conflicts) and disabling several Spark metrics/UI settings by default (and in test configs).

Updates YAML plan processing so each step’s options automatically includes format inferred from the step type when missing (avoiding misconfigured sinks), and tweaks logging verbosity/diagnostics around plan preprocessing.

Adds substantial documentation updates: expanded foreign key docs (cardinality, generation modes, nullability, reference tables), fixes/updates many doc links, adds 0.19.1 release notes, and introduces a new misc/feature-catalog (generated docs + scripts) for standardized feature documentation.

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[claude]

Code Review - PR #130

Summary

This PR bumps the version to 0.19.1 and includes important bug fixes, documentation improvements, and a new feature catalog. The code changes are relatively small but address critical runtime issues.

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Positive Findings

1. Critical Bug Fix: Shadow JAR Service Merging

• Location: app/build.gradle.kts:546
• Added mergeServiceFiles() to fix Hadoop provider conflicts
• Excellent fix for a production issue

2. Improved Logging Verbosity Control

• Location: ForeignKeyUniquenessProcessor.scala:43
• Reduced log level from INFO to DEBUG
• Good practice - aligns with CLAUDE.md guidance

3. Enhanced Task Name Visibility

• Location: PlanProcessor.scala:121
• Added task names to post-processor logging
• Very helpful for troubleshooting auto-generated tasks

4. Documentation Improvements

• Extensive foreign-key.md updates
• New feature catalog infrastructure
• Fixed numerous broken links

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CRITICAL CONCERN: Auto-Inferring format from type

Location: PlanProcessor.scala:362-367, 396-401

This change automatically sets format = step.type when format is missing and type != json.

Issues:

• Breaking change with no test coverage
• Previously missing format would use Spark defaults or fail
• No validation that step.type is a valid Spark format
• Edge cases not handled (custom types)

Recommendations:

1. Add integration tests for format auto-inference
2. Document this behavior change in changelog
3. Add validation that step.type is in SUPPORTED_CONNECTION_FORMATS
4. Add WARN log when auto-inferring format

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Test Data Changes Need Explanation

Location: csv-transaction-task.yaml:41

Changed from weighted distribution oneOf: [1->0.8, 2->0.1, 3->0.1] to uniform oneOf: [1, 2, 3]

Please explain why this was changed and ensure weighted oneOf still works elsewhere.

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Test Coverage

Missing:

• Integration test for auto-format inference
• Test for shadow JAR service merging
• Test validating weighted oneOf still works

Recommendation: Add at least one integration test in app/src/integrationTest validating the format auto-inference.

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Code Quality

Follows CLAUDE.md conventions:

• Uses immutable data structures
• Appropriate use of Option types
• Logging at appropriate levels

Style suggestion: Duplicated logic in YamlPlanRun and UnifiedPlanRun could be extracted to shared helper.

---

Overall Assessment

Quality: 7/10

Fixes critical production issues but the format auto-inference change needs better test coverage and documentation. With recommended tests added, this would be 9/10.

Recommendation: Request changes to add integration tests before merging.

---

Review conducted following CLAUDE.md project conventions.

[claude]

Pull Request Review: v0.19.1 - Foreign Key Enhancements & Bug Fixes

Overall Assessment

This is a well-structured release that introduces important foreign key cardinality features and fixes critical runtime issues. The code quality is generally strong, but there are a few areas that warrant attention before merging.

✅ Strengths

1. Architecture & Design

• Excellent separation of concerns: The new MutatingPrePlanProcessor trait cleanly separates mutating vs. read-only processors
• Proper processor ordering: ForeignKeyUniquenessProcessor runs before CardinalityCountAdjustmentProcessor - this ordering is critical and well-documented
• Smart format inference: The automatic format detection from step type (lines 362-366, 396-400 in PlanProcessor.scala) elegantly fixes the YAML configuration issue

2. Code Quality

• Comprehensive documentation: The processor classes have excellent class-level docs explaining the problem, solution, and benefits
• Defensive validation: CardinalityCountAdjustmentProcessor.validateForeignKeyConfigurations() prevents configuration conflicts upfront
• Logging improvements: Changing ForeignKeyUniquenessProcessor from INFO to DEBUG reduces noise (line 43)

3. Bug Fixes

• ShadowJar mergeServiceFiles() (app/build.gradle.kts:546): Critical fix for Hadoop filesystem provider conflicts in production deployments
• Spark executor metrics disabled: Good workaround for known Spark metrics issues

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⚠️ Issues & Recommendations

🔴 CRITICAL: Potential NPE in PlanProcessor.scala

Location: PlanProcessor.scala:321 (YamlPlanRun constructor)

val dataSourceName = yamlPlan.tasks.find(ts => ts.name.equalsIgnoreCase(t.name)).get.dataSourceName

Problem: Using .get on Option without checking if the task exists will throw NoSuchElementException if a task in yamlTasks doesn't match any task in yamlPlan.tasks.

Recommendation:

val dataSourceName = yamlPlan.tasks
  .find(ts => ts.name.equalsIgnoreCase(t.name))
  .map(_.dataSourceName)
  .getOrElse {
    LOGGER.warn(s"Task '${t.name}' not found in plan tasks, skipping metadata options")
    t.name  // fallback to task name
  }

This same pattern appears at line 356 in the same file - both instances should be addressed.

---

🟡 MEDIUM: Unnecessary Object Instantiation

Location: PlanProcessor.scala:32

cls.getDeclaredConstructor().newInstance()  // <-- Unused result
val tryScalaPlan = Try(cls.getDeclaredConstructor().newInstance().asInstanceOf[PlanRun])

Problem: Line 32 creates an instance that's immediately discarded, then lines 33-34 create new instances.

Recommendation: Remove line 32 entirely - it serves no purpose and wastes resources.

---

🟡 MEDIUM: Overly Broad Exception Handling

Location: PlanProcessor.scala:126-128

} catch {
  case ex: Exception => throw ex
}

Problem: This catch block catches and immediately re-throws all exceptions, providing no value while adding complexity.

Recommendation: Remove this try-catch entirely, or add actual error handling/cleanup logic if needed.

---

🟡 MEDIUM: Unsafe File Operations

Location: PlanProcessor.scala:206

val matchingFiles = planDir.listFiles()
  .filter(f => f.isFile && f.getName.endsWith(".yaml"))

Problem: listFiles() can return null if the directory doesn't exist or isn't readable, causing NPE.

Recommendation:

val matchingFiles = Option(planDir.listFiles())
  .getOrElse(Array.empty)
  .filter(f => f.isFile && f.getName.endsWith(".yaml"))

---

🟠 LOW: Code Duplication in PlanProcessor

Location: Lines 362-366 and 396-400 in PlanProcessor.scala

The format inference logic is duplicated in both YamlPlanRun and UnifiedPlanRun:

val optionsWithFormat = if (!mergedOptions.contains(FORMAT) && step.`type` != DEFAULT_STEP_TYPE) {
  mergedOptions + (FORMAT -> step.`type`)
} else {
  mergedOptions
}

Recommendation: Extract to a helper method:

private def inferFormatFromStepType(step: Step, options: Map[String, String]): Map[String, String] = {
  if (!options.contains(FORMAT) && step.`type` != DEFAULT_STEP_TYPE) {
    options + (FORMAT -> step.`type`)
  } else {
    options
  }
}

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🟠 LOW: Logging Enhancement Opportunity

Location: CardinalityCountAdjustmentProcessor.scala:59

The debug log doesn't show which FKs have cardinality vs. which don't, making debugging harder.

Recommendation:

val fksWithCardinality = enhancedForeignKeys.count(_.generate.exists(_.cardinality.isDefined))
LOGGER.debug(s"Processing ${enhancedForeignKeys.size} foreign key(s), $fksWithCardinality with cardinality configurations")

---

🔍 Testing Concerns

Missing Test Coverage

Based on the files changed, I don't see new unit tests for:

1. CardinalityCountAdjustmentProcessor - Complex logic with multiple branches (ratio vs. min/max, perField handling, validation)
2. MutatingPrePlanProcessor application order - Critical that uniqueness runs before cardinality
3. Format inference logic - Edge cases where step.type != DEFAULT_STEP_TYPE
4. NPE scenarios - The .get calls mentioned above

Recommendation: Add unit tests in app/src/test for these components, particularly:

• Cardinality calculation with ratio (line 227)
• Cardinality calculation with min/max (line 222)
• Validation logic preventing conflicts (lines 249-293)
• Processor ordering in applyMutatingPrePlanProcessors (lines 255-304)

---

🔒 Security Review

✅ No security concerns identified:

• No SQL injection vectors (using Spark DataFrames)
• No command injection (file operations use proper validation)
• No credential exposure in new code
• Logging doesn't expose sensitive data

---

📊 Performance Considerations

Positive

• SQL-based regex generation - Already implemented in previous versions, good foundation
• Bounded buffer optimization - Referenced in memory profiling docs, addresses streaming concerns

Watch

• File system operations in findYamlPlanFile (lines 195-225): Parses YAML files in a loop - could be slow for large plan directories
  • Recommendation: Consider caching parsed plan names or using a more efficient lookup strategy

---

📝 Documentation Review

Excellent

• Release notes (0.19.1.md) are comprehensive and well-organized
• Foreign key documentation rewrite (referenced in changelog) - major improvement
• Feature catalog additions provide good reference material

Missing

• No inline code comments explaining why processor order matters (only in class docs)
• The mergeServiceFiles() fix (build.gradle.kts:546) lacks a comment explaining which Hadoop providers conflict

Recommendation: Add brief comments:

// Merge META-INF/services files to resolve conflicts between hadoop-common's
// FileSystem implementations and platform-specific providers
mergeServiceFiles()

---

✅ CLAUDE.md Compliance

The PR adheres to project conventions:

• ✅ Uses ModifyPimp for immutable updates (in processors)
• ✅ Follows package structure under io.github.datacatering.datacaterer
• ✅ Uses Option[T] instead of null (mostly - see NPE issues above)
• ✅ Case classes have proper JSON annotations
• ✅ Logging follows established patterns

---

🎯 Recommendations Before Merge

Must Fix (Blocking)

1. Fix NPE risk: Replace .get calls in PlanProcessor.scala lines 321 and 356
2. Add null check: Handle listFiles() potentially returning null (line 206)

Should Fix (Strongly Recommended)

3. Remove dead code: Delete unnecessary instantiation (line 32) and useless try-catch (lines 126-128)
4. Add unit tests: At minimum, test CardinalityCountAdjustmentProcessor validation logic

Nice to Have

5. Extract duplicated format inference logic into helper method
6. Add explanatory comments for mergeServiceFiles() and processor ordering
7. Enhance logging in cardinality processor to show counts

---

📋 Summary

This is a solid release with important features and critical bug fixes. The foreign key cardinality implementation is well-architected and the Hadoop fix addresses real production issues.

However, the NPE risks must be addressed before merging - they could cause runtime failures in production when YAML configurations don't perfectly match plan definitions.

Recommendation: Address the two critical NPE issues, then this is ready to merge. The other improvements can be handled in follow-up PRs if needed.

---

Great work on the comprehensive foreign key enhancements and documentation improvements! 🎉

[claude]

Pull Request Review: v0.19.1 Release

Overview

This PR introduces version 0.19.1 with foreign key enhancements, documentation improvements, and runtime stability improvements. The changes span 46 files with significant additions in documentation and a new feature catalog system.

Code Quality & Best Practices

✅ Strengths

1. Comprehensive Documentation: Excellent expansion of foreign key documentation (525 lines added) with clear examples for cardinality, nullability, and generation modes.

2. Feature Catalog System: Well-structured Python scripts for feature extraction and documentation generation. The modular design with utils.py separation is clean.

3. Spark Configuration Improvements: Disabling unnecessary Spark metrics and UI in test configurations improves test performance and reduces overhead.

4. Build Stability: Adding mergeServiceFiles() to shadowJar configuration prevents Hadoop provider conflicts - good defensive practice.

⚠️ Issues & Concerns

1. Critical: Missing Test Coverage for Format Auto-Injection

Location: app/src/main/scala/io/github/datacatering/datacaterer/core/plan/PlanProcessor.scala:362-366

The new logic that automatically adds format to step options when missing is a behavioral change that could impact existing deployments. This duplicates identical code in both YamlPlanRun (line 362) and UnifiedPlanRun (line 396) - DRY violation.

Concerns:

• No integration tests verify this behavior
• Could break existing configurations where type and format intentionally differ
• The PR description mentions avoiding misconfigured sinks but does not explain when this would occur

Recommendation:

• Add integration tests verifying the format auto-injection for various step types
• Document when type != format is valid vs. when auto-injection should apply
• Consider extracting this logic into a shared helper method to avoid duplication

2. Test Configuration Changes Need Documentation

Multiple Spark settings were added to test configurations and production defaults in Constants.scala. The PR description mentions disabling several Spark metrics/UI settings by default as a stability improvement, but:

• No performance benchmarks are provided
• No discussion of what monitoring/observability is lost
• Could make debugging production issues harder

Recommendation: Document these changes in the release notes with guidance on when users might want to re-enable them.

Test Coverage

Missing Tests

1. No integration tests for the format auto-injection behavior
2. No tests for the enhanced logging changes
3. The findYamlPlanFile method added in PlanProcessor.scala:195-225 has no tests despite being new logic

Recommendation: Add integration tests to verify format auto-injection for various step types, behavior when format is already specified, and behavior for DEFAULT_STEP_TYPE steps.

Summary & Recommendations

Must Address Before Merge

1. Add integration tests for format auto-injection behavior
2. Document behavioral changes in release notes (format injection, Spark defaults)
3. Clarify the Java distribution change rationale (oracle to temurin)

Should Address

1. Refactor duplicated code for format injection into shared method
2. Add tests for findYamlPlanFile method
3. Document production implications of disabling Spark metrics/UI

Verdict

Conditional Approval - This PR contains valuable enhancements (foreign key features, documentation) but has several untested behavioral changes that could impact production deployments. The code quality is generally good, but test coverage gaps and missing documentation for behavioral changes need to be addressed.

The foreign key documentation and feature catalog work is excellent and ready to merge. The runtime changes need more validation and documentation.