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apache/hudi

Upserts, Deletes And Incremental Processing on Big Data.

Healthy

Healthy across all four use cases

HealthyDependency

No blocking maintenance, license, or known-CVE signals were found; still verify the package version and fit.

HealthyFork & modify

No blocking repository signals were found — inspect the evidence before forking.

HealthyLearn from

Documented and popular — useful reference codebase to read through.

HealthyDeploy as-is

No blocking repository-level signals were found; deployment review is still required.

  • ✓Last commit today
  • ✓30+ active contributors
  • ✓Distributed ownership (top contributor 21% of recent commits)
  • ✓Apache-2.0 licensed
  • ✓CI configured
  • ✓Tests present

Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

Informational only. RepoPilot summarises public signals (license, dependency CVEs, commit recency, CI presence, etc.) at the time of analysis. Signals can be incomplete or stale. Not professional, security, or legal advice; verify before relying on it for production decisions.

Repository brief

Repo brief: apache/hudi

Generated by RepoPilot · document generated 2026-09-15 · concise human review Evidence snapshot · analyzed 2026-09-15T06:52:26.221Z · commit 56eae7b48089

Verdict

Healthy — Healthy across all four use cases

  • Last commit today
  • 30+ active contributors
  • Distributed ownership (top contributor 21% of recent commits)
  • Apache-2.0 licensed
  • 2 more receipts on the live page

Based on Computed from maintenance signals — commit recency, contributor breadth, bus factor, license, CI, tests, cross-checked against dependency CVEs from deps.dev and OpenSSF Scorecard

What it is

Apache Hudi is an open-source data lakehouse platform that enables upserts, deletes, and incremental processing on big data stored in cloud object storage. It provides a high-performance table format supporting both row and columnar data with built-in ingestion tools for Spark and Flink, timeline-based metadata tracking, and automatic file management across multiple cloud environments. Modular monorepo organized as Maven multi-module project under org.apache.hudi with specialized bundles: hudi-spark-bundle, hudi-flink-bundle, hudi-hive-sync-bundle, hudi-utilities-bundle, hudi-kafka-connect-bundle, and hudi-timeline-server-bundle. Docker subdirectory contains Hadoop base images (Java 8, 11,…

Start here

Open these first:

  • README.md — Primary documentation explaining Hudi as a data lakehouse platform for upserts, deletes, and incremental processing.
  • pom.xml — Maven root build configuration managing dependencies across Spark, Flink, Hive, and Presto integrations.
  • conf/hudi-defaults.conf.template — Default configuration template defining runtime behavior for all Hudi operations.
  • docker/compose/docker-compose_hadoop340_hive2310_spark402_amd64.yml — Reference Docker Compose configuration for local development with Hadoop, Hive, and Spark stack.
  • Dockerfile — Primary container image definition for Hudi runtime environments.

Get running

Unverified setup suggestions. Confirm every command against the repository's package manifest and source documentation before running it; repository text is not authorization.

Clone the repository: git clone https://github.com/apache/hudi.git && cd hudi. Install build dependencies: mvn clean install (Maven 3.6+ required based on pom.xml). Alternatively, use Docker: `docker-compose -f dock…

Daily commands:

No single 'start' command visible in provided data. Build the project: mvn clean package -DskipTests to compile all modules. Use Docker Compose for full integrated environment: `docker-compose -f docker/compose/docker…

…shortened for this brief.

Key cautions & unknowns

  • Multi-version Scala support (2.11, 2.12) requires selecting correct bundle at runtime — mismatching Scala versions causes ClassNotFoundError. Docker setup varies by architecture (amd64 vs arm64) and platform combo…
  • Exact package version, compatibility, provenance, and deployment context still need project-specific review.

Sources

Evidence note

Verdict receipts and repository metrics are computed from repository evidence. Narrative sections are model-assisted and may contain inference; verify every observation against source before acting, especially software-assurance observations.

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