Nomination Evidence: cloud-fan

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

Summary

cloud-fan reviews 81x more PRs than they author (81 reviews, 1 PRs), with a strong focus on welcoming newcomers (65 first-timer PR reviews).

Highlights

4 commits, 81 PRs reviewed, 76 review comments | https://github.com/apache/spark/commits?author=cloud-fan
Drove PR #54247 ([SPARK-55024][SQL][FOLLOWUP] Delay namespace length check to v1 identifier creation), 6 review rounds: https://github.com/apache/spark/pull/54247
Review on PR #54297 ([SPARK-55501][SQL] Fix listagg distinct + within group order by bug): "I don't like this approach as it's unclear what happens next if we don't fail he......" https://github.com/apache/spark/pull/54297
Review comment on PR #54297 ([SPARK-55501][SQL] Fix listagg distinct + within group order by bug): "I don't like this approach as it's unclear what happens next if we don't fail here. Does the DISTINCT execution path sav..." https://github.com/apache/spark/pull/54297

Contribution statistics

Code contributions (GitHub)

PRs opened: 1
PRs merged: 0
Lines added: 89
Lines deleted: 134
Commits: 4

Code review

PRs reviewed: 81
Review comments given: 76
Issue comments: 17
- APPROVED: 8 (9%)
- CHANGES_REQUESTED: 0 (0%)
- COMMENTED: 73 (90%)

Composite score

Dimension	Score	Notes
Complexity	5.0/10	0 high-complexity PRs of 1 scored
Stewardship	5.2/10	11% maintenance work, 50% consistency
Review depth	6.8/10	1.1 comments/review, 47% questions, 16 contributors
Composite	5.7/10	out of 66 contributors

Review relationships

People this contributor reviews most

holdenk: 31 reviews
uros-db: 14 reviews
ksbeyer: 13 reviews
erenavsarogullari: 6 reviews
heyihong: 4 reviews
ericm-db: 4 reviews
Yicong-Huang: 2 reviews
ilicmarkodb: 2 reviews
helioshe4: 2 reviews
zhidongqu-db: 1 reviews

People who review this contributor's PRs most

szehon-ho: 2 reviews
dongjoon-hyun: 1 reviews
pan3793: 1 reviews
allisonwang-db: 1 reviews

Newcomer welcoming

cloud-fan reviewed 65 PRs from contributors with 3 or fewer PRs in the project, including zhidongqu-db, ksbeyer, heyihong, ericm-db, ilicmarkodb and 5 others.

Community health profile

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

Net reviewer ratio: 81.0x
Interaction breadth: 16 unique contributors (concentration: 38%)
Newcomer welcoming: 65 reviews on PRs from contributors with 3 or fewer PRs
- Names: zhidongqu-db, ksbeyer, heyihong, ericm-db, ilicmarkodb, zhengruifeng, erenavsarogullari, holdenk, helioshe4, srielau
Helping ratio: 95% of GitHub comments directed at others' PRs
Review depth: 1.1 comments/review, 47% questions (88 comments on 81 reviews)
Stewardship: 11% of work is maintenance (9/83 PRs: 1 authored, 8 reviewed)
Consistency: 50% (1/2 weeks active)
Feedback responsiveness: 100% iteration rate, 25.5h median turnaround, 100% reply rate (1 PRs with feedback)

Complexity of authored work

PRs scored: 1
High complexity (>= 0.5): 0
Low complexity (< 0.5): 1
Average complexity: 0.320

Quality of review contributions

Probing review comments (expressing uncertainty, challenging assumptions): 4

Most significant probing reviews (on highest-complexity PRs)

PR #54297 ([SPARK-55501][SQL] Fix listagg distinct + within group order by bug, score 0.493)
- Topics: order value
- Comment: "I don't like this approach as it's unclear what happens next if we don't fail he..."
PR #46143 ([SPARK-47672][SQL] Avoid double eval from filter pushDown w/ projection pushdown, score 0.473)
- Comment: "hmm why is this needed if we only push a Filter through a Project?"
PR #54094 ([SPARK-55314][CONNECT] Propagate observed metrics errors to client, score 0.451)
- Comment: "why it's a list? because a query can have many observations?"
PR #54040 ([SPARK-55261][Geo][SQL] Implement Parquet read support for Geo types, score 0.427)
- Comment: "why geo type can't support lazy decoding?"

Highest-judgment review comments (on others' PRs)

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

PR #54297 ([SPARK-55501][SQL] Fix listagg distinct + within group order by bug)
- File: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/analysis/CheckAnalysis.scala
- "I don't like this approach as it's unclear what happens next if we don't fail here. Does the DISTINCT execution path save the order value? Even if we add comments here, it's making an assumption of the physical execution path that is far away from here. I still prefer my previous proposal: we can"
PR #46143 ([SPARK-47672][SQL] Avoid double eval from filter pushDown w/ projection pushdown)
- File: sql/catalyst/src/test/scala/org/apache/spark/sql/catalyst/optimizer/FilterPushdownSuite.scala
- "I get the purpose here is to reduce the input to other expensive functions in the same Project. But splitting a Project has overhead as well (more operator, more overhead), and in most cases the benefit of filter pushdown is to reduce IO for shuffle/scan, shall we defer this optimization? Then the i"
PR #46143 ([SPARK-47672][SQL] Avoid double eval from filter pushDown w/ projection pushdown)
- File: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
- "The new impl looks overly complicated. I think we only need to split the predicates and push down the part that won't trigger double eval. e.g. ``` val (stayUp, pushDown) = splitConjunctivePredicates(condition).partition { predicate => replaceAlias(predicate, aliasMap).expensive } (stayUp, pu"
PR #46143 ([SPARK-47672][SQL] Avoid double eval from filter pushDown w/ projection pushdown)
- File: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
- "It's really hard to review this new optimization, I have a few suggestions: 1. optimizer rules should be orthogonal. I think "push down cheap filters only" and "split project" are two optimizations and should be put in two rules. 2. add some code comments at the beginning to explain the algorithm."
PR #46143 ([SPARK-47672][SQL] Avoid double eval from filter pushDown w/ projection pushdown)
- File: sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/optimizer/Optimizer.scala
- "A different view to look at this problem and design the algorithm: A Project with N named expressions can at most be split into N Projects. e.g. Project(expr1 AS c1, expr2 AS c2, expr3 AS c3) can be split into ``` Project(c1, c2, expr3 AS c2) Project(leaf.output, c1, expr2 AS c2) Pro"