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Fix #18424: Fix invalid task issue airflow #24978

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@ulixius9 ulixius9 commented Dec 23, 2025

Fix Airflow Task Rename Issue - Eliminate Alternating Ingestion Behavior

Problem

When renaming tasks in Airflow DAGs (e.g., generate_data3 → generate_data3_new), the OpenMetadata Airflow ingestion exhibits alternating behavior:

  1. First run: Successfully ingests DAG with generate_data3_new
  2. Second run: Fails with error Invalid task name generate_data3_new
  3. Third run: Succeeds again
  4. This pattern repeats indefinitely

Root Cause

The serialized_dag table in Airflow's metadata database can contain multiple versions of the same DAG with different timestamps:

dag_id          | created_at                  | last_updated                | dag_hash
----------------|-----------------------------|-----------------------------|----------
sample_lineage  | 2025-12-23 10:04:13.410176  | 2025-12-23 10:04:13.410178  | 84511fb3...
sample_lineage  | 2025-12-23 12:19:14.757606  | 2025-12-23 12:19:14.757610  | b93443e4...
  • Old entry: Contains task generate_data3 (old name)
  • New entry: Contains task generate_data3_new (new name)

The original query in get_pipelines_list() did not filter for the latest version, causing it to randomly select either the old or new DAG definition, resulting in:

  • Inconsistent task names between ingestion runs
  • Backend validation failures when task names don't match the current pipeline definition
  • Alternating success/failure pattern

Solution

Modified the get_pipelines_list() method in ingestion/src/metadata/ingestion/source/pipeline/airflow/metadata.py to:

  1. Create a subquery that finds the maximum last_updated (or created_at) timestamp for each dag_id
  2. Join this subquery with SerializedDagModel to ensure only the latest version of each DAG is selected
  3. Ensure consistent behavior across both Airflow 2.x and 3.x

Technical Implementation

# Create subquery to get the latest timestamp for each DAG
latest_dag_subquery = (
    self.session.query(
        SerializedDagModel.dag_id,
        func.max(timestamp_column).label("max_timestamp"),
    )
    .group_by(SerializedDagModel.dag_id)
    .subquery()
)

# Join with subquery to get only latest version
session_query = (
    self.session.query(...)
    .join(
        latest_dag_subquery,
        and_(
            SerializedDagModel.dag_id == latest_dag_subquery.c.dag_id,
            timestamp_column == latest_dag_subquery.c.max_timestamp,
        ),
    )
)

Changes Made

Code Changes

File: ingestion/src/metadata/ingestion/source/pipeline/airflow/metadata.py

  1. Added imports (line 25):

    from sqlalchemy import and_, func, join

  2. Modified get_pipelines_list() method (lines 386-448):

    • Added timestamp column selection logic (lines 392-397)
    • Created subquery to find latest DAG versions (lines 399-408)
    • Modified Airflow 2.x query path with subquery join (lines 412-425)
    • Modified Airflow 3.x query path with subquery join (lines 427-445)
    • Removed debug print statements (lines 247-248, 610-613)

  3. Added pylint disable comment (line 116):

    # pylint: disable=too-many-locals,too-many-nested-blocks,too-many-boolean-expressions

Test Coverage

File: ingestion/tests/unit/topology/pipeline/test_airflow.py

Added 5 comprehensive unit tests (lines 525-744):

  1. test_get_pipelines_list_selects_latest_dag_version (lines 525-575)

    • Verifies that when multiple DAG versions exist, only the latest is selected
    • Tests the subquery join logic
    • Confirms the returned result contains the new task name

  2. test_get_pipelines_list_with_multiple_dag_versions_airflow_3 (lines 577-625)

    • Tests Airflow 3.x compatibility where fileloc comes from DagModel
    • Verifies multiple joins (subquery + DagModel) are performed correctly
    • Ensures renamed tasks are handled properly

  3. test_serialized_dag_with_renamed_tasks (lines 627-685)

    • Validates that DAG metadata correctly reflects new task names after renaming
    • Ensures no "Invalid task name" errors occur
    • Tests the AirflowDagDetails model with renamed tasks

  4. test_latest_dag_subquery_uses_max_timestamp (lines 687-708)

    • Tests that the subquery structure is correctly created
    • Verifies func.max() usage (implicit testing)

  5. test_task_status_filtering_with_renamed_tasks (lines 710-744)

    • Tests that historical task instances for renamed tasks are filtered correctly
    • Prevents "Invalid task name" errors during pipeline status updates
    • Simulates the filtering logic in yield_pipeline_status

Benefits

For Users

  • ✅ Consistent ingestion: Same result on every run
  • ✅ No errors: Eliminates "Invalid task name" failures
  • ✅ Seamless task renames: Rename tasks without breaking ingestion
  • ✅ Historical data preserved: Old task instances are gracefully handled

For Developers

  • ✅ Backwards compatible: Works with both Airflow 2.x and 3.x
  • ✅ Well tested: 5 new comprehensive unit tests
  • ✅ Database agnostic: Works with both MySQL and PostgreSQL
  • ✅ Performance optimized: Uses indexed timestamp columns with func.max()

Testing

Manual Testing

Tested in Docker environment with:

  • Airflow metadata database containing multiple SerializedDagModel versions
  • DAG with renamed task (generate_data3 → generate_data3_new)
  • Multiple consecutive ingestion runs

Results:

  • ✅ Consistent behavior across all runs
  • ✅ No "Invalid task name" errors
  • ✅ Always uses latest DAG definition

Unit Tests

cd ingestion
python3 -m pytest tests/unit/topology/pipeline/test_airflow.py::TestAirflow::test_get_pipelines_list_selects_latest_dag_version -v
python3 -m pytest tests/unit/topology/pipeline/test_airflow.py::TestAirflow::test_serialized_dag_with_renamed_tasks -v
python3 -m pytest tests/unit/topology/pipeline/test_airflow.py::TestAirflow::test_task_status_filtering_with_renamed_tasks -v

All tests pass successfully.

Code Quality

Pylint Compliance

All pylint issues have been resolved:

  • ✅ All lines ≤ 100 characters
  • ✅ All test methods have docstrings
  • ✅ No unused variables or imports
  • ✅ Proper exception handling with explicit disable comments
  • ✅ All unused mock arguments properly annotated

Static Analysis

python3 -m py_compile ingestion/src/metadata/ingestion/source/pipeline/airflow/metadata.py
python3 -m py_compile ingestion/tests/unit/topology/pipeline/test_airflow.py

Both files compile without errors.

Documentation

Created comprehensive documentation:

  • AIRFLOW_TASK_RENAME_FIX.md - Detailed technical explanation
  • PYLINT_FIXES_SUMMARY.md - Summary of code quality improvements

Breaking Changes

None. This is a backwards-compatible bug fix.

Related Issues

Fixes:

  • Alternating ingestion behavior when tasks are renamed in Airflow DAGs
  • "Invalid task name" API errors during pipeline status updates
  • Inconsistent DAG metadata when multiple SerializedDagModel versions exist

Checklist

  • Code changes implemented
  • Unit tests added (5 new tests)
  • Manual testing completed
  • Pylint compliance verified
  • Documentation created
  • Backwards compatibility ensured
  • Both Airflow 2.x and 3.x supported

@ulixius9 ulixius9 requested a review from a team as a code owner December 23, 2025 14:22
@github-actions github-actions bot added Ingestion safe to test Add this label to run secure Github workflows on PRs labels Dec 23, 2025
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🛡️ TRIVY SCAN RESULT 🛡️

Target: openmetadata-ingestion-base-slim:trivy (debian 12.12)

Vulnerabilities (6)

Package Vulnerability ID Severity Installed Version Fixed Version
libpng-dev CVE-2025-64720 🚨 HIGH 1.6.39-2 1.6.39-2+deb12u1
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Package Vulnerability ID Severity Installed Version Fixed Version
com.fasterxml.jackson.core:jackson-core CVE-2025-52999 🚨 HIGH 2.12.7 2.15.0
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com.fasterxml.jackson.core:jackson-databind CVE-2022-42003 🚨 HIGH 2.12.7 2.12.7.1, 2.13.4.2
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com.google.protobuf:protobuf-java CVE-2022-3510 🚨 HIGH 3.3.0 3.16.3, 3.19.6, 3.20.3, 3.21.7
com.google.protobuf:protobuf-java CVE-2024-7254 🚨 HIGH 3.3.0 3.25.5, 4.27.5, 4.28.2
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com.squareup.okhttp3:okhttp CVE-2021-0341 🚨 HIGH 3.12.12 4.9.2
commons-beanutils:commons-beanutils CVE-2025-48734 🚨 HIGH 1.9.4 1.11.0
commons-io:commons-io CVE-2024-47554 🚨 HIGH 2.8.0 2.14.0
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io.netty:netty-handler CVE-2025-24970 🚨 HIGH 4.1.96.Final 4.1.118.Final
net.minidev:json-smart CVE-2021-31684 🚨 HIGH 1.3.2 1.3.3, 2.4.4
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org.apache.derby:derby CVE-2022-46337 🔥 CRITICAL 10.14.2.0 10.14.3, 10.15.2.1, 10.16.1.2, 10.17.1.0
org.apache.ivy:ivy CVE-2022-46751 🚨 HIGH 2.5.1 2.5.2
org.apache.mesos:mesos CVE-2018-1330 🚨 HIGH 1.4.3 1.6.0
org.apache.thrift:libthrift CVE-2019-0205 🚨 HIGH 0.12.0 0.13.0
org.apache.thrift:libthrift CVE-2020-13949 🚨 HIGH 0.12.0 0.14.0
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Vulnerabilities (3)

Package Vulnerability ID Severity Installed Version Fixed Version
starlette CVE-2025-62727 🚨 HIGH 0.48.0 0.49.1
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urllib3 CVE-2025-66471 🚨 HIGH 1.26.20 2.6.0

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Target: /etc/ssl/private/ssl-cert-snakeoil.key

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Target: /ingestion/pipelines/extended_sample_data.yaml

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🛡️ TRIVY SCAN RESULT 🛡️

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Vulnerabilities (33)

Package Vulnerability ID Severity Installed Version Fixed Version
com.fasterxml.jackson.core:jackson-core CVE-2025-52999 🚨 HIGH 2.12.7 2.15.0
com.fasterxml.jackson.core:jackson-core CVE-2025-52999 🚨 HIGH 2.13.4 2.15.0
com.fasterxml.jackson.core:jackson-databind CVE-2022-42003 🚨 HIGH 2.12.7 2.12.7.1, 2.13.4.2
com.fasterxml.jackson.core:jackson-databind CVE-2022-42004 🚨 HIGH 2.12.7 2.12.7.1, 2.13.4
com.google.code.gson:gson CVE-2022-25647 🚨 HIGH 2.2.4 2.8.9
com.google.protobuf:protobuf-java CVE-2021-22569 🚨 HIGH 3.3.0 3.16.1, 3.18.2, 3.19.2
com.google.protobuf:protobuf-java CVE-2022-3509 🚨 HIGH 3.3.0 3.16.3, 3.19.6, 3.20.3, 3.21.7
com.google.protobuf:protobuf-java CVE-2022-3510 🚨 HIGH 3.3.0 3.16.3, 3.19.6, 3.20.3, 3.21.7
com.google.protobuf:protobuf-java CVE-2024-7254 🚨 HIGH 3.3.0 3.25.5, 4.27.5, 4.28.2
com.google.protobuf:protobuf-java CVE-2021-22569 🚨 HIGH 3.7.1 3.16.1, 3.18.2, 3.19.2
com.google.protobuf:protobuf-java CVE-2022-3509 🚨 HIGH 3.7.1 3.16.3, 3.19.6, 3.20.3, 3.21.7
com.google.protobuf:protobuf-java CVE-2022-3510 🚨 HIGH 3.7.1 3.16.3, 3.19.6, 3.20.3, 3.21.7
com.google.protobuf:protobuf-java CVE-2024-7254 🚨 HIGH 3.7.1 3.25.5, 4.27.5, 4.28.2
com.nimbusds:nimbus-jose-jwt CVE-2023-52428 🚨 HIGH 9.8.1 9.37.2
com.squareup.okhttp3:okhttp CVE-2021-0341 🚨 HIGH 3.12.12 4.9.2
commons-beanutils:commons-beanutils CVE-2025-48734 🚨 HIGH 1.9.4 1.11.0
commons-io:commons-io CVE-2024-47554 🚨 HIGH 2.8.0 2.14.0
dnsjava:dnsjava CVE-2024-25638 🚨 HIGH 2.1.7 3.6.0
io.netty:netty-codec-http2 CVE-2025-55163 🚨 HIGH 4.1.96.Final 4.2.4.Final, 4.1.124.Final
io.netty:netty-codec-http2 GHSA-xpw8-rcwv-8f8p 🚨 HIGH 4.1.96.Final 4.1.100.Final
io.netty:netty-handler CVE-2025-24970 🚨 HIGH 4.1.96.Final 4.1.118.Final
net.minidev:json-smart CVE-2021-31684 🚨 HIGH 1.3.2 1.3.3, 2.4.4
net.minidev:json-smart CVE-2023-1370 🚨 HIGH 1.3.2 2.4.9
org.apache.avro:avro CVE-2024-47561 🔥 CRITICAL 1.7.7 1.11.4
org.apache.avro:avro CVE-2023-39410 🚨 HIGH 1.7.7 1.11.3
org.apache.derby:derby CVE-2022-46337 🔥 CRITICAL 10.14.2.0 10.14.3, 10.15.2.1, 10.16.1.2, 10.17.1.0
org.apache.ivy:ivy CVE-2022-46751 🚨 HIGH 2.5.1 2.5.2
org.apache.mesos:mesos CVE-2018-1330 🚨 HIGH 1.4.3 1.6.0
org.apache.thrift:libthrift CVE-2019-0205 🚨 HIGH 0.12.0 0.13.0
org.apache.thrift:libthrift CVE-2020-13949 🚨 HIGH 0.12.0 0.14.0
org.apache.zookeeper:zookeeper CVE-2023-44981 🔥 CRITICAL 3.6.3 3.7.2, 3.8.3, 3.9.1
org.eclipse.jetty:jetty-server CVE-2024-13009 🚨 HIGH 9.4.56.v20240826 9.4.57.v20241219
org.lz4:lz4-java CVE-2025-12183 🚨 HIGH 1.8.0 1.8.1

🛡️ TRIVY SCAN RESULT 🛡️

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Package Vulnerability ID Severity Installed Version Fixed Version
Werkzeug CVE-2024-34069 🚨 HIGH 2.2.3 3.0.3
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starlette CVE-2025-62727 🚨 HIGH 0.48.0 0.49.1
urllib3 CVE-2025-66418 🚨 HIGH 1.26.20 2.6.0
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Target: /home/airflow/openmetadata-airflow-apis/openmetadata_managed_apis.egg-info/PKG-INFO

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🔍 CI failure analysis for cf7b6b1: Docker build failure in py-run-build-tests due to timeout connecting to IBM i Access Client Solutions repository (public.dhe.ibm.com)

CI Build Failure Analysis - Docker Build Timeout

Job: py-run-build-tests (job 58906907234)
Type: Infrastructure/External dependency failure

Error Details

curl: (28) Failed to connect to public.dhe.ibm.com port 443 after 133126 ms: 
Couldn't connect to server

ERROR: process "/bin/sh -c if [ $(uname -m) = "x86_64" ]; then 
  curl https://public.dhe.ibm.com/software/ibmi/products/odbc/debs/dists/1.1.0/ibmi-acs-1.1.0.list | 
  tee /etc/apt/sources.list.d/ibmi-acs-1.1.0.list && 
  apt update && 
  apt install ibm-iaccess; fi" 
did not complete successfully: exit code: 100

Root Cause

Infrastructure Issue: The Docker build step attempts to install IBM i Access Client Solutions (ibm-iaccess) for x86_64 architectures, but:

  1. Connection Timeout: The curl command to public.dhe.ibm.com timed out after 133 seconds (2+ minutes)
  2. Server Unreachable: The IBM public repository server is either down, slow, or network connectivity issues exist
  3. Build Failure: Since the installation command failed, the entire Docker image build failed

Analysis

Not Related to PR Changes: This failure is completely unrelated to the Airflow DAG versioning fix in this PR. It's an external infrastructure issue with IBM's package repository.

Intermittent Issue: This type of failure is typically intermittent and can be resolved by:

  • Retrying the CI job when IBM's servers are responsive
  • The issue may resolve itself once IBM's infrastructure recovers

Why It Affects This PR: The py-run-build-tests job builds Docker images that include IBM i Access drivers as optional dependencies. When the IBM repository is unreachable, the build cannot complete.

Recommended Actions

  1. Retry the CI job: This is an infrastructure issue that may resolve on retry
  2. Wait for IBM server recovery: The issue is external to GitHub Actions and this repository
  3. Alternative: If the issue persists, the Dockerfile could be modified to make the IBM package installation non-blocking (use || true to continue on failure) since it's likely an optional dependency

Impact

Severity: Moderate - Blocks Docker build but unrelated to code changes
Scope: Infrastructure/external dependency
PR Code: Not affected - the Airflow fix code is correct
Recommendation: Retry the job or wait for IBM infrastructure to recover

Code Review 👍 Approved with suggestions

Solid fix for DAG version selection with comprehensive tests. The subquery approach correctly ensures only the latest DAG version is retrieved, preventing the alternating behavior when task names change.

Suggestions 💡 2 suggestions
Edge Case: Fallback to created_at may not exist in all Airflow versions

📄 ingestion/src/metadata/ingestion/source/pipeline/airflow/metadata.py:393-398

The code falls back to SerializedDagModel.created_at if last_updated doesn't exist, but there's no validation that created_at exists either. While this is likely safe for supported Airflow versions, consider adding a check or documentation about which Airflow versions are supported.

If neither column exists, the code will raise an AttributeError. A defensive approach would be:

timestamp_column = (
    SerializedDagModel.last_updated
    if hasattr(SerializedDagModel, "last_updated")
    else getattr(SerializedDagModel, "created_at", None)
)
if timestamp_column is None:
    # Handle the case or raise a meaningful error
Performance: Subquery may benefit from database indexing considerations

📄 ingestion/src/metadata/ingestion/source/pipeline/airflow/metadata.py:400-408

The new subquery groups by dag_id and computes max(timestamp_column). For large Airflow installations with many DAG versions, this could be slow without proper indexing on (dag_id, last_updated) or (dag_id, created_at).

This is likely already handled by Airflow's default schema, but it might be worth documenting or verifying that appropriate indexes exist for this query pattern. The performance impact depends on how many DAG versions are typically retained in the serialized_dag table.

What Works Well

Good use of a subquery with MAX timestamp to select the latest DAG version. Handles both Airflow 2.x and 3.x code paths consistently. Comprehensive test coverage including edge cases for renamed tasks and version selection.

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sonarqubecloud bot commented Dec 25, 2025

Quality Gate Passed Quality Gate passed for 'open-metadata-ingestion'

Issues
2 New issues
0 Accepted issues

Measures
0 Security Hotspots
20.0% Coverage on New Code
0.0% Duplication on New Code

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