Nomination Evidence: pan3793

Project: apache/spark Period: 2026-02-14 to 2026-02-21

Summary

pan3793 reviews 5x more PRs than they author (10 reviews, 2 PRs), interacting with 10 contributors, 1 of 4 authored PRs scored as high-complexity.

Highlights

Contribution statistics

Code contributions (GitHub)

  • PRs opened: 2
  • PRs merged: 0
  • Lines added: 138
  • Lines deleted: 141
  • Commits: 11

Code review

  • PRs reviewed: 10
  • Review comments given: 22
  • Issue comments: 5
    • APPROVED: 2 (20%)
    • CHANGES_REQUESTED: 0 (0%)
    • COMMENTED: 7 (70%)

Composite score

DimensionScoreNotes
Complexity3.2/101 high-complexity PRs of 4 scored
Stewardship4.8/1040% maintenance work, 50% consistency
Review depth6.0/101.1 comments/review, 44% questions, 10 contributors
Composite4.7/10out of 66 contributors

Review relationships

People this contributor reviews most

  • parthchandra: 4 reviews
  • robreeves: 2 reviews
  • cloud-fan: 1 reviews
  • dongjoon-hyun: 1 reviews
  • jzhuge: 1 reviews
  • ever4Kenny: 1 reviews

People who review this contributor's PRs most

  • dongjoon-hyun: 3 reviews
  • zhengruifeng: 2 reviews
  • srowen: 2 reviews
  • LuciferYang: 1 reviews
  • luhenry: 1 reviews

Net reviewer

pan3793 reviews 5.0x more PRs than they author (10 reviews, 2 PRs), interacting with 10 different contributors.

Community health profile

Relational metrics: how this contributor strengthens the community beyond code output.

  • Net reviewer ratio: 5.0x
  • Interaction breadth: 10 unique contributors (concentration: 40%)
  • Newcomer welcoming: 9 reviews on PRs from contributors with 3 or fewer PRs
    • Names: cloud-fan, parthchandra, jzhuge, robreeves, ever4Kenny
  • Helping ratio: 41% of GitHub comments directed at others' PRs
  • Review depth: 1.1 comments/review, 44% questions (11 comments on 10 reviews)
  • Stewardship: 40% of work is maintenance (6/15 PRs: 4 authored, 2 reviewed)
  • Consistency: 50% (1/2 weeks active)
  • Feedback responsiveness: 100% iteration rate, 5312.2h median turnaround, 157% reply rate (2 PRs with feedback)

Complexity of authored work

  • PRs scored: 4
  • High complexity (>= 0.5): 1
  • Low complexity (< 0.5): 3
  • Average complexity: 0.209

Highest-complexity authored PRs

  • PR #49986 ([SPARK-51243][CORE][ML] Configurable allow native BLAS)
    • Complexity score: 0.633
    • Probing ratio: 50.0%
    • Review rounds: 16
    • Probing topics: assemble a java

Quality of review contributions

Probing review comments (expressing uncertainty, challenging assumptions): 3

Most significant probing reviews (on highest-complexity PRs)

  • PR #49986 ([SPARK-51243][CORE][ML] Configurable allow native BLAS, score 0.633)
    • Comment: "libopenblas-base is removed in Debian 12 and Ubuntu 24.04, libopenblas-dev s..."
  • PR #49986 ([SPARK-51243][CORE][ML] Configurable allow native BLAS, score 0.633)
    • Topics: assemble a java
    • Comment: "> Do other resource managers like k8s need this? not sure K8s does not need t..."
  • PR #54380 ([SPARK-55605][BUILD][DOCS] Bump dev.ludovic.netlib 3.1.1 and update docs, score 0.090)
    • Comment: "libopenblas-base is removed in Debian 12 and Ubuntu 24.04, libopenblas-dev s..."

Highest-judgment review comments (on others' PRs)

(Selected by length, technical content, and presence of questions)

  • PR #53657 ([SPARK-54879][CORE] Add final status to Spark History Server for failed executions)
    • File: core/src/main/scala/org/apache/spark/ui/jobs/AllJobsPage.scala
    • "should it be - Succeeded - Failed (exit code: $code) ? displaying "Succeeded" status helps the user to distinguish the running/crashed app (no SparkListenerApplicationEnd event) from normally finished app"
  • PR #54133 ([SPARK-55353][SQL] Add config to disable SQLAppStatusListener)
    • File: sql/catalyst/src/main/scala/org/apache/spark/sql/internal/StaticSQLConf.scala
    • "Spark currently under 4.2 development cycle so version should be "4.2.0". I agree appStatusListener should keep enabled by default. But could you disable it and tigger a round CI, to help us evaluate the impact?"
  • PR #53840 ([SPARK-55075][K8S] Track executor pod creation errors with ExecutorFailureTracker)
    • File: resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocator.scala
    • "As I said previously, I prefer not to have additional failure threshold check mechanisms outside the failureTracker. The simplest approach to solve your current problem is just propagate the pod creation failure to lifecycleManager, like you did, via registerPodCreationFailure()"
  • PR #53840 ([SPARK-55075][K8S] Track executor pod creation errors with ExecutorFailureTracker)
    • File: resource-managers/kubernetes/core/src/test/scala/org/apache/spark/scheduler/cluster/k8s/ExecutorPodsAllocatorSuite.scala
    • "as we discussed before, the retry mechanism does not help here, we don't need to mention that, the case name might be suggestion test("Pod creation failures are tracked by ExecutorFailureTracker") { "
  • PR #53840 ([SPARK-55075][K8S] Track executor pod creation errors with ExecutorFailureTracker)
    • File: resource-managers/kubernetes/core/src/main/scala/org/apache/spark/scheduler/cluster/k8s/KubernetesClusterManager.scala
    • "Method setExecutorPodsLifecycleManager is added in AbstractPodsAllocator, not the derived class. Is reflection really required here?"

Area focus

Files touched (authored PRs)

  • mllib/src/main (5 files)
  • dev/deps/spark-deps-hadoop-3-hive-2.3 (4 files)
  • pom.xml (4 files)
  • core/src/main (3 files)
  • project/SparkBuild.scala (3 files)
  • docs/ml-linalg-guide.md (2 files)
  • common/network-common/pom.xml (2 files)
  • common/network-shuffle/pom.xml (2 files)

Areas reviewed (from PR titles)

  • testing (1 PRs)
  • config (1 PRs)

Want this for your private team?

Canopy generates digests like this for private engineering teams. Connect your GitHub, Jira, and Slack.

Get started
Canopy

Engineering digests, not dashboards.