review-comet-pr

Reviewing Spark compatibility in a pull request involves extracting PR metadata via GitHub CLI, reading changed files, and comparing Comet expression implementations against canonical Spark source behavior to catch correctness regressions early.

Validating Spark expression behavior in a Comet PR requires reading the authoritative Spark source for eval and null handling, verifying serde registration, and running Comet SQL test suites to catch behavioral mismatches.

Serde integration impacts Spark compatibility checks by requiring verification of serde registration and support levels to ensure Comet correctly maps Spark expression behavior and prevents correctness regressions.

Yes, checking ANSI mode differences is necessary when reviewing Comet SQL tests because ANSI mode variations between Spark and Comet can cause subtle behavioral mismatches and correctness regressions in expression evaluation.

When validating null semantics for Spark compatibility, look for limitations in how Comet handles null inputs compared to authoritative Spark source behavior, ensuring edge cases are covered by Comet SQL tests.

You can automate CI checks and performance validation for DataFusion Comet PRs by summarizing CI considerations and verifying that new expressions include performance evidence to ensure implementation correctness and Spark compatibility.