[infra] Require CI status checks to merge (main + branch-0.4) - #848
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[infra] Require CI status checks to merge (main + branch-0.4)#848vinishjail97 wants to merge 1 commit into
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.asf.yaml branch protection is read only from the default branch, and
previously configured no required_status_checks, so green CI was not
gating merges. Add required checks:
- main: Maven CI Build, License Check
- branch-0.4: Maven CI Build, License Check, and both
Spark Runtime Bundle Validation matrix legs (3.4.3, 3.5.9)
The two workflows that shared an ambiguous "build" job context now set
unique job names (Maven CI Build, License Check) so each can be required
distinctly. A matching branch-0.4 change renames the same jobs there.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Both workflows used a job named "build", so both reported the same status-check context and could not be required distinctly. Set unique job names so branch protection (see apache#848) can require each on branch-0.4. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Jul 21, 2026
…k 3.4 + 3.5) (#843) * [836] xtable-spark-runtime: thin drop-in Spark bundle (Hudi 0.x) Ports the xtable-spark-runtime packaging slice onto the Hudi 0.x line (main-hudi-0x, Hudi 0.14 / Spark 3.4). New thin, relocated bundle that runs an incremental XTable sync inside a Spark job; engines are provided by the cluster, never bundled. Module: - xtable-spark-runtime_${scala.binary.version}: xtable-core compile; Spark/Hadoop and the engines (Hudi/Iceberg/Delta) provided. Curated shade allowlist (xtable modules + guava/protobuf/commons-cli relocated); avro/parquet/jackson NOT relocated (exchanged with the engines). Thin ~3.7 MB bundle. - XTableSparkSync: standalone spark-submit entry point (Apache Commons CLI). - XTableSyncService / TableSyncSpec: build an INCREMENTAL ConversionConfig and run ConversionController.sync; target metadata path = source data path (required by Hudi; Iceberg data lives under <basePath>/data). Hudi 0.14 specifics (vs the Hudi 1.x variant on main): - No hudi-hadoop-common (that split is 1.x); hudi-common provides FSUtils. - Engine classpath uses the hudi-spark bundle (its regenerated Avro model classes link on Avro 1.12, which Iceberg 1.9.2 requires) plus hudi-java-client for the Hudi target's Java write client, with the raw hudi-common excluded so the bundle's clean DecimalWrapper wins. ConversionTargetFactory: make ServiceLoader discovery resilient so a subset of engines works when others are absent (warn + skip on LinkageError/ServiceConfigurationError; name-based Delta-Kernel check). ITXTableSparkRuntimeBundle: spark-submits the shaded jar for one case per direction across Hudi, Iceberg and Delta (source and target), engines on a flat classpath, asserting data-equivalence over comparable scalar columns. Requires a Spark 3.4 SPARK_HOME; skipped otherwise. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * [836] xtable-spark-runtime: address review feedback (packaging, licensing, RFC) Publish the shaded jar as the MAIN artifact with a dependency-reduced POM (shadedArtifactAttached=false, createDependencyReducedPom=true), matching iceberg-spark-runtime / hudi-spark-bundle. Resolving the coordinate via a Maven dependency or --packages now yields the relocated bundle and pulls no un-relocated transitive deps; --jars is equivalent. The thin main jar + separate -bundle classifier (which re-introduced the cluster guava clash) is gone. IT findBundleJar() now picks the shaded main jar. Pass release/scripts/validate_shaded_license_coverage.sh (the existing allowlist gate): the shade <includes> must equal the runtime dependency tree, so jackson / scala-library / log4j-1.2-api - which every Spark runtime supplies - are declared provided (dropped from the tree, kept off the shaded jar) and excluded from the IT's flat engine classpath so Spark's own copies win. avro/parquet stay on the flat classpath (the engine's newer avro must win over Spark 3.4's). Bundled-dependency licensing: add META-INF/LICENSE-bundled and NOTICE-bundled (wired via IncludeResourceTransformer) attributing the only bundled third-party - guava's closure (Apache-2.0) and commons-cli (Apache-2.0), plus checker-qual (MIT). Remove the dead protobuf-java allowlist entry and relocation: protobuf resolves as provided and was never bundled. RFC-3: scope v1 to the CLI (XTableSparkSync); mark the config-only XTableSyncListener on-ramp (and XTableSparkConfig / PlanTargetResolver) as a deferred follow-up. Fix the activation example to the shipped CLI and document the required engine Avro version + flat-classpath placement. XTableSyncService: normalize sourceFormat with Locale.ROOT. Root pom: exclude the shade-generated dependency-reduced-pom.xml from spotless (no license header; CI runs clean install). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * [836] xtable-spark-runtime: trim duplicated pom comments Consolidate repeated rationale in the bundle pom (no functional change): - Tell the hudi-common DecimalWrapper / Avro-1.8-1.9 story once (on the hudi-spark bundle dep); the hudi-java-client exclusion just points to it. - State "engine Avro must win on a flat classpath" once (engine-classpath plugin); the avro dep and excludeGroupIds comments reference it. - Explain jackson/scala-library are Spark-supplied once. - Fix a stale "Spark 3.5" reference to Spark 3.4 (this is the Hudi 0.x line). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * [836] ci: trigger Maven CI + License Check on main-hudi-0x Add main-hudi-0x to the push and pull_request branch filters of both workflows (same change as #841) so CI runs on PRs targeting the Hudi 0.x release line, including this one. A pull_request workflow's branch filter takes effect from the PR's own branch, so this makes CI fire on #843. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * Address review feedback: guard ServiceLoader.hasNext() and drain spark-submit stdout off-thread - ConversionTargetFactory: hasNext() resolves provider classes lazily and can throw ServiceConfigurationError too, so move it inside the existing ServiceConfigurationError|LinkageError guard alongside next(). - ITXTableSparkRuntimeBundle: drain spark-submit stdout on a background thread so a hung process is caught by waitFor(10min) instead of blocking forever on readOutput() reading until EOF. * [836] ci: point Maven CI + License Check triggers at branch-0.4 main-hudi-0x was deleted and replaced by branch-0.4 (the 0.4.0 release line), so update the push/pull_request branch filters accordingly. * [836] ci: validate xtable-spark-runtime bundle against a real Spark distro ITXTableSparkRuntimeBundle spark-submits the shaded bundle jar and self-skips unless SPARK_HOME is set, so the main CI never runs it. Add a path-filtered workflow that installs a matching Spark 3.4 distribution from the Apache archive, sets SPARK_HOME, and runs the failsafe IT. * [836] ci: run spark-runtime validation on every branch PR (drop path filter) The workflow is intended to be a required status check on branch-0.4. A required check whose workflow is skipped by a path filter never reports, leaving PRs blocked on a pending check, so run it unconditionally on the covered branches. The Spark distro is cached, so the added cost is the reactor build plus the ~20s IT. * [836] xtable-spark-runtime: address review feedback (CLI validation, unix flags, docs) - XTableSparkSync: validate --sourceformat/--targets up front and fail fast (before SparkSession creation) on empty or unsupported values. Split the allowed sets: sources are Hudi/Iceberg/Delta/Paimon/Parquet, targets are Hudi/Iceberg/Delta (Paimon/Parquet are read-only, no ConversionTarget). - XTableSyncService.sourceProviderFor: wire Paimon and Parquet source providers (previously threw UnsupportedOperationException); engines remain cluster-provided. - Rename CLI long-opts to unix-style lowercase (--basepath, --sourceformat, --tablename, --datapath, --partitionspec); update javadoc, IT and RFC example. - basePathToName -> basePathToTableName: handle "/", trailing slashes and null by throwing with a "pass --tablename" hint instead of an empty table name. - Add XTableSparkSyncTest covering table-name derivation and source/target format validation. - ConversionTargetFactory: log the skipped provider's error class/message so operators can distinguish an intentionally-absent engine from a linkage error. - spark-runtime-validation.yml: add a workflow_dispatch spark_version input and document why the Spark 3.4 line is pinned (Delta 2.4.0 is Spark-3.4-only). - RFC-3: add a supported-formats/engine-versions section, "from application code" (Scala/Java + PySpark) activation examples, and list @vinothchandar as an approver. * [836] xtable-spark-runtime: support Spark 3.5 via Delta Kernel Delta source/target now auto-switch from delta-core to the Spark-free Delta Kernel implementation on Spark 3.5+ (where the bundled delta-core does not run), controlled by a single --usedeltakernel toggle that is auto-enabled by Spark version. Hudi/Iceberg sync was already Spark-free. Also runs the spark-runtime bundle IT on both Spark 3.4.3 and 3.5.9 via a CI matrix. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * [836] Give Maven CI Build and License Check unique job names Both workflows used a job named "build", so both reported the same status-check context and could not be required distinctly. Set unique job names so branch protection (see #848) can require each on branch-0.4. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * [836] xtable-spark-runtime: add --datasetconfig for multi-table sync XTableSparkSync accepts a --datasetconfig YAML (sourceFormat, targetFormats, datasets[]) to sync multiple tables in one run, mutually exclusive with the single-table --basepath/--sourceformat/--targets flags. The config is read through the Spark Hadoop config, so it may live on a local or cloud (s3/gcs/abfs) path, and reuses the same schema as the RunSync utility. Parsed with SnakeYAML's SafeConstructor (plain maps/lists only, no arbitrary type instantiation). SnakeYAML is bundled and relocated to org.apache.xtable.shaded (like guava/commons-cli) because Spark ships its own version (1.33 on 3.4, 2.0 on 3.5) that would otherwise clash; its multi-release classes are filtered out so no un-relocated org.yaml classes remain. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Is there a way to use a wildcard so we don't need the versions listed here?
the-other-tim-brown
approved these changes
Jul 25, 2026
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What
Makes CI green a hard requirement to merge.
.asf.yamlbranch protection is read only from the default branch (main) and previously declared norequired_status_checks, so passing builds were informational, not gating — andbranch-0.4had no protection at all.Required checks added:
main:Maven CI Build,License Checkbranch-0.4:Maven CI Build,License Check,validate-spark-runtime-bundle (3.4.3),validate-spark-runtime-bundle (3.5.9)(The Spark checks are
branch-0.4-only — there is no spark-runtime module onmain.)Job rename
Maven CI BuildandLicense Checkboth used a job namedbuild, so both reported the same status contextbuildand couldn't be required distinctly. Each now sets a unique jobname, giving contextsMaven CI BuildandLicense Check. A companion PR applies the same rename onbranch-0.4so those contexts exist there too.Merge order
Merge after #843 lands on
branch-0.4(it adds thespark-runtime-validationworkflow and its matrix). INFRA applies.asf.yamlwholesale on merge here, so if these rules land first, newbranch-0.4PRs would block on Spark contexts that aren't running yet. Also merge thebranch-0.4job-rename PR before/with this so theMaven CI Build/License Checkcontexts are produced there.🤖 Generated with Claude Code