[Python] Optimize BigQuery copy jobs in file loads using multi-source copy#38983
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stankiewicz wants to merge 4 commits into
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[Python] Optimize BigQuery copy jobs in file loads using multi-source copy#38983stankiewicz wants to merge 4 commits into
stankiewicz wants to merge 4 commits into
GitHub Actions / Python 3.13 Test Results (ubuntu-latest)
failed
Jun 16, 2026 in 0s
17 errors, 12 skipped, 1 pass in 11m 38s
Annotations
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_invalid_write_on_missing_primary_key_in_entity (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 33s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_invalid_write_on_non_existent_collection (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 0s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_invalid_write_on_non_existent_partition (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 0s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_write_on_auto_id_primary_key (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 0s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_write_on_existent_collection_with_default_schema (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 0s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_write_with_batching (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 0s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_write_with_custom_column_specifications (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 1s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f2762a14e90>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f2762a08550>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_vector_search_with_inner_product_similarity (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 35s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f048194c050>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f0481803d90>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_invalid_query_on_non_existent_collection (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 33s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f64a696b360>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f64a685c2d0>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_empty_input_chunks (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 33s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7fc3aaf5b5c0>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7fc3aaeb8050>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_invalid_query_on_non_existent_field (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 1s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f64a696b360>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f64a685c2d0>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_filtered_search_with_bm25_full_text_and_batching (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 1s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7fc3aaf5b5c0>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7fc3aaeb8050>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_idempotent_write (apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 6s]
Raw output
failed on setup with "TimeoutError: container did not become running"
cls = <class 'apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/ingestion/milvus_search_it_test.py:180:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:217: in start_db_container
raise e
apache_beam/ml/rag/test_utils.py:189: in start_db_container
port = running_container.get_exposed_port(service_container_port)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/container.py:331: in get_exposed_port
C().wait_until_ready(self)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <testcontainers.core.wait_strategies.ContainerStatusWaitStrategy object at 0x7f04819e3df0>
container = <apache_beam.ml.rag.test_utils.CustomMilvusContainer object at 0x7f04819a8cb0>
def wait_until_ready(self, container: WaitStrategyTarget) -> None:
result = self._poll(lambda: self.running(self.get_status(container)))
if not result:
> raise TimeoutError("container did not become running")
E TimeoutError: container did not become running
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/testcontainers/core/wait_strategies.py:672: TimeoutError
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_keyword_search_with_inner_product_sparse_embedding (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 10m 0s]
Raw output
failed on setup with "Failed: Timeout (>600.0s) from pytest-timeout."
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7fa94482c7d0>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
> grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:231:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:160: in result
self._block(timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <grpc._utilities._ChannelReadyFuture object at 0x7fa9448a1770>
timeout = 10
def _block(self, timeout: Optional[float]) -> None:
until = None if timeout is None else time.time() + timeout
with self._condition:
while True:
if self._cancelled:
raise grpc.FutureCancelledError()
if self._matured:
return
if until is None:
self._condition.wait()
else:
remaining = until - time.time()
if remaining < 0:
> raise grpc.FutureTimeoutError()
E grpc.FutureTimeoutError
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:105: FutureTimeoutError
The above exception was the direct cause of the following exception:
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7fa946c3a660>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
> result = operation()
^^^^^^^^^^^
apache_beam/ml/rag/utils.py:200:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:147: in list_collections_probe
client = MilvusClient(uri=uri)
^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/milvus_client/milvus_client.py:89: in __init__
self._handler = self._manager.get_or_create(
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:500: in get_or_create
return self._create_shared(config, client, timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:524: in _create_shared
handler._wait_for_channel_ready(timeout=timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7fa94482c7d0>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
self._setup_identifier_interceptor(self._user, timeout=effective_timeout)
except grpc.FutureTimeoutError as e:
self.close()
> raise MilvusException(
code=Status.CONNECT_FAILED,
message=f"Fail connecting to server on {self._address}, illegal connection params or server unavailable",
) from e
E pymilvus.exceptions.MilvusException: <MilvusException: (code=2, message=Fail connecting to server on localhost:50535, illegal connection params or server unavailable)>
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:235: MilvusException
During handling of the above exception, another exception occurred:
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:191: in start_db_container
MilvusTestHelpers._wait_for_milvus_grpc(info.uri)
apache_beam/ml/rag/test_utils.py:153: in _wait_for_milvus_grpc
retry_with_backoff(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7fa946c3a660>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
result = operation()
_LOGGER.info(
"Successfully completed %s on attempt %d",
operation_name,
attempt + 1)
return result
except exception_types as e:
last_exception = e
if attempt < max_retries:
delay = retry_delay * (retry_backoff_factor**attempt)
_LOGGER.warning(
"%s attempt %d failed: %s. Retrying in %.2f seconds...",
operation_name,
attempt + 1,
e,
delay)
> time.sleep(delay)
E Failed: Timeout (>600.0s) from pytest-timeout.
apache_beam/ml/rag/utils.py:216: Failed
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_filtered_search_with_cosine_similarity_and_batching (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 10m 0s]
Raw output
failed on setup with "Failed: Timeout (>600.0s) from pytest-timeout."
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7f0418e90050>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
> grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:231:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:160: in result
self._block(timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <grpc._utilities._ChannelReadyFuture object at 0x7f0418eb14f0>
timeout = 10
def _block(self, timeout: Optional[float]) -> None:
until = None if timeout is None else time.time() + timeout
with self._condition:
while True:
if self._cancelled:
raise grpc.FutureCancelledError()
if self._matured:
return
if until is None:
self._condition.wait()
else:
remaining = until - time.time()
if remaining < 0:
> raise grpc.FutureTimeoutError()
E grpc.FutureTimeoutError
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:105: FutureTimeoutError
The above exception was the direct cause of the following exception:
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7f0579862200>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
> result = operation()
^^^^^^^^^^^
apache_beam/ml/rag/utils.py:200:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:147: in list_collections_probe
client = MilvusClient(uri=uri)
^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/milvus_client/milvus_client.py:89: in __init__
self._handler = self._manager.get_or_create(
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:500: in get_or_create
return self._create_shared(config, client, timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:524: in _create_shared
handler._wait_for_channel_ready(timeout=timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7f0418e90050>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
self._setup_identifier_interceptor(self._user, timeout=effective_timeout)
except grpc.FutureTimeoutError as e:
self.close()
> raise MilvusException(
code=Status.CONNECT_FAILED,
message=f"Fail connecting to server on {self._address}, illegal connection params or server unavailable",
) from e
E pymilvus.exceptions.MilvusException: <MilvusException: (code=2, message=Fail connecting to server on localhost:34955, illegal connection params or server unavailable)>
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:235: MilvusException
During handling of the above exception, another exception occurred:
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:191: in start_db_container
MilvusTestHelpers._wait_for_milvus_grpc(info.uri)
apache_beam/ml/rag/test_utils.py:153: in _wait_for_milvus_grpc
retry_with_backoff(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7f0579862200>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
result = operation()
_LOGGER.info(
"Successfully completed %s on attempt %d",
operation_name,
attempt + 1)
return result
except exception_types as e:
last_exception = e
if attempt < max_retries:
delay = retry_delay * (retry_backoff_factor**attempt)
_LOGGER.warning(
"%s attempt %d failed: %s. Retrying in %.2f seconds...",
operation_name,
attempt + 1,
e,
delay)
> time.sleep(delay)
E Failed: Timeout (>600.0s) from pytest-timeout.
apache_beam/ml/rag/utils.py:216: Failed
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_vector_search_with_euclidean_distance (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 1s]
Raw output
failed on setup with "Failed: Timeout (>600.0s) from pytest-timeout."
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7fa94482c7d0>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
> grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:231:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:160: in result
self._block(timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <grpc._utilities._ChannelReadyFuture object at 0x7fa9448a1770>
timeout = 10
def _block(self, timeout: Optional[float]) -> None:
until = None if timeout is None else time.time() + timeout
with self._condition:
while True:
if self._cancelled:
raise grpc.FutureCancelledError()
if self._matured:
return
if until is None:
self._condition.wait()
else:
remaining = until - time.time()
if remaining < 0:
> raise grpc.FutureTimeoutError()
E grpc.FutureTimeoutError
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:105: FutureTimeoutError
The above exception was the direct cause of the following exception:
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7fa946c3a660>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
> result = operation()
^^^^^^^^^^^
apache_beam/ml/rag/utils.py:200:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:147: in list_collections_probe
client = MilvusClient(uri=uri)
^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/milvus_client/milvus_client.py:89: in __init__
self._handler = self._manager.get_or_create(
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:500: in get_or_create
return self._create_shared(config, client, timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:524: in _create_shared
handler._wait_for_channel_ready(timeout=timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7fa94482c7d0>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
self._setup_identifier_interceptor(self._user, timeout=effective_timeout)
except grpc.FutureTimeoutError as e:
self.close()
> raise MilvusException(
code=Status.CONNECT_FAILED,
message=f"Fail connecting to server on {self._address}, illegal connection params or server unavailable",
) from e
E pymilvus.exceptions.MilvusException: <MilvusException: (code=2, message=Fail connecting to server on localhost:50535, illegal connection params or server unavailable)>
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:235: MilvusException
During handling of the above exception, another exception occurred:
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:191: in start_db_container
MilvusTestHelpers._wait_for_milvus_grpc(info.uri)
apache_beam/ml/rag/test_utils.py:153: in _wait_for_milvus_grpc
retry_with_backoff(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7fa946c3a660>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
result = operation()
_LOGGER.info(
"Successfully completed %s on attempt %d",
operation_name,
attempt + 1)
return result
except exception_types as e:
last_exception = e
if attempt < max_retries:
delay = retry_delay * (retry_backoff_factor**attempt)
_LOGGER.warning(
"%s attempt %d failed: %s. Retrying in %.2f seconds...",
operation_name,
attempt + 1,
e,
delay)
> time.sleep(delay)
E Failed: Timeout (>600.0s) from pytest-timeout.
apache_beam/ml/rag/utils.py:216: Failed
github-actions / Python 3.13 Test Results (ubuntu-latest)
test_hybrid_search (apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment) with error
sdks/python/test-suites/tox/py313/build/srcs/sdks/python/pytest_py313-ml.xml [took 1s]
Raw output
failed on setup with "Failed: Timeout (>600.0s) from pytest-timeout."
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7f0418e90050>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
> grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:231:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:160: in result
self._block(timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <grpc._utilities._ChannelReadyFuture object at 0x7f0418eb14f0>
timeout = 10
def _block(self, timeout: Optional[float]) -> None:
until = None if timeout is None else time.time() + timeout
with self._condition:
while True:
if self._cancelled:
raise grpc.FutureCancelledError()
if self._matured:
return
if until is None:
self._condition.wait()
else:
remaining = until - time.time()
if remaining < 0:
> raise grpc.FutureTimeoutError()
E grpc.FutureTimeoutError
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/grpc/_utilities.py:105: FutureTimeoutError
The above exception was the direct cause of the following exception:
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7f0579862200>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
> result = operation()
^^^^^^^^^^^
apache_beam/ml/rag/utils.py:200:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:147: in list_collections_probe
client = MilvusClient(uri=uri)
^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/milvus_client/milvus_client.py:89: in __init__
self._handler = self._manager.get_or_create(
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:500: in get_or_create
return self._create_shared(config, client, timeout)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/connection_manager.py:524: in _create_shared
handler._wait_for_channel_ready(timeout=timeout)
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <pymilvus.client.grpc_handler.GrpcHandler object at 0x7f0418e90050>
timeout = None
def _wait_for_channel_ready(self, timeout: Optional[float] = 10):
if self._channel is None:
raise MilvusException(
code=Status.CONNECT_FAILED,
message="No channel in handler, please setup grpc channel first",
)
# grpc.Future.result(timeout=None) blocks indefinitely. Normalise None
# to the default 10 s so that an unreachable URI raises MilvusException
# instead of hanging forever (mirrors async ensure_channel_ready behaviour).
effective_timeout = timeout if timeout is not None else 10
try:
grpc.channel_ready_future(self._channel).result(timeout=effective_timeout)
self._setup_identifier_interceptor(self._user, timeout=effective_timeout)
except grpc.FutureTimeoutError as e:
self.close()
> raise MilvusException(
code=Status.CONNECT_FAILED,
message=f"Fail connecting to server on {self._address}, illegal connection params or server unavailable",
) from e
E pymilvus.exceptions.MilvusException: <MilvusException: (code=2, message=Fail connecting to server on localhost:34955, illegal connection params or server unavailable)>
target/.tox-py313-ml/py313-ml/lib/python3.13/site-packages/pymilvus/client/grpc_handler.py:235: MilvusException
During handling of the above exception, another exception occurred:
cls = <class 'apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment'>
@classmethod
def setUpClass(cls):
> cls._db = MilvusTestHelpers.start_db_container()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
apache_beam/ml/rag/enrichment/milvus_search_it_test.py:242:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
apache_beam/ml/rag/test_utils.py:191: in start_db_container
MilvusTestHelpers._wait_for_milvus_grpc(info.uri)
apache_beam/ml/rag/test_utils.py:153: in _wait_for_milvus_grpc
retry_with_backoff(
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
operation = <function MilvusTestHelpers._wait_for_milvus_grpc.<locals>.list_collections_probe at 0x7f0579862200>
max_retries = 25, retry_delay = 2.0, retry_backoff_factor = 1.2
operation_name = 'Milvus client connection after container start'
exception_types = (<class 'pymilvus.exceptions.MilvusException'>,)
def retry_with_backoff(
operation: Callable[[], Any],
max_retries: int = 3,
retry_delay: float = 1.0,
retry_backoff_factor: float = 2.0,
operation_name: str = "operation",
exception_types: tuple[type[BaseException], ...] = (Exception, )
) -> Any:
"""Executes an operation with retry logic and exponential backoff.
This is a generic retry utility that can be used for any operation that may
fail transiently. It retries the operation with exponential backoff between
attempts.
Note:
This utility is designed for one-time setup operations and complements
Apache Beam's RequestResponseIO pattern. Use retry_with_backoff() for:
* Establishing client connections in __enter__() methods (e.g., creating
MilvusClient instances, database connections) before processing elements
* One-time setup/teardown operations in DoFn lifecycle methods
* Operations outside of per-element processing where retry is needed
For per-element operations (e.g., API calls within Caller.__call__),
use RequestResponseIO which already provides automatic retry with
exponential backoff, failure handling, caching, and other features.
See: https://beam.apache.org/documentation/io/built-in/webapis/
Args:
operation: Callable that performs the operation to retry. Should return
the result of the operation.
max_retries: Maximum number of retry attempts. Default is 3.
retry_delay: Initial delay in seconds between retries. Default is 1.0.
retry_backoff_factor: Multiplier for the delay after each retry. Default
is 2.0 (exponential backoff).
operation_name: Name of the operation for logging purposes. Default is
"operation".
exception_types: Tuple of exception types to catch and retry. Default is
(Exception,) which catches all exceptions.
Returns:
The result of the operation if successful.
Raises:
The last exception encountered if all retry attempts fail.
Example:
>>> def connect_to_service():
... return service.connect(host="localhost")
>>> client = retry_with_backoff(
... connect_to_service,
... max_retries=5,
... retry_delay=2.0,
... operation_name="service connection")
"""
last_exception = None
for attempt in range(max_retries + 1):
try:
result = operation()
_LOGGER.info(
"Successfully completed %s on attempt %d",
operation_name,
attempt + 1)
return result
except exception_types as e:
last_exception = e
if attempt < max_retries:
delay = retry_delay * (retry_backoff_factor**attempt)
_LOGGER.warning(
"%s attempt %d failed: %s. Retrying in %.2f seconds...",
operation_name,
attempt + 1,
e,
delay)
> time.sleep(delay)
E Failed: Timeout (>600.0s) from pytest-timeout.
apache_beam/ml/rag/utils.py:216: Failed
Check notice on line 0 in .github
github-actions / Python 3.13 Test Results (ubuntu-latest)
12 skipped tests found
There are 12 skipped tests, see "Raw output" for the full list of skipped tests.
Raw output
apache_beam.ml.inference.anthropic_inference_it_test
apache_beam.ml.inference.anthropic_inference_test
apache_beam.ml.inference.onnx_inference_test
apache_beam.ml.inference.tensorrt_inference_test
apache_beam.ml.inference.xgboost_inference_test
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_both_dense_and_sparse
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_dense_embeddings_only
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_sparse_embeddings_only
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_with_batching
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_with_byte_size_limit
apache_beam.ml.transforms.handlers_test
apache_beam.ml.transforms.tft_test
Check notice on line 0 in .github
github-actions / Python 3.13 Test Results (ubuntu-latest)
30 tests found
There are 30 tests, see "Raw output" for the full list of tests.
Raw output
apache_beam.ml.inference.anthropic_inference_it_test
apache_beam.ml.inference.anthropic_inference_test
apache_beam.ml.inference.onnx_inference_test
apache_beam.ml.inference.tensorrt_inference_test
apache_beam.ml.inference.xgboost_inference_test
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_empty_input_chunks
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_filtered_search_with_bm25_full_text_and_batching
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_filtered_search_with_cosine_similarity_and_batching
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_hybrid_search
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_invalid_query_on_non_existent_collection
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_invalid_query_on_non_existent_field
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_keyword_search_with_inner_product_sparse_embedding
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_vector_search_with_euclidean_distance
apache_beam.ml.rag.enrichment.milvus_search_it_test.TestMilvusSearchEnrichment ‑ test_vector_search_with_inner_product_similarity
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_idempotent_write
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_invalid_write_on_missing_primary_key_in_entity
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_invalid_write_on_non_existent_collection
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_invalid_write_on_non_existent_partition
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_write_on_auto_id_primary_key
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_write_on_existent_collection_with_default_schema
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_write_with_batching
apache_beam.ml.rag.ingestion.milvus_search_it_test.TestMilvusVectorWriterConfig ‑ test_write_with_custom_column_specifications
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_both_dense_and_sparse
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_dense_embeddings_only
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_on_non_existent_collection
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_sparse_embeddings_only
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_with_batching
apache_beam.ml.rag.ingestion.qdrant_it_test.TestQdrantIngestion ‑ test_write_with_byte_size_limit
apache_beam.ml.transforms.handlers_test
apache_beam.ml.transforms.tft_test
Loading