fix: respect customer artifact prefix everywhere #702
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Co-authored-by: Thomas Chow <[email protected]>
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WalkthroughThe changes refactor GCS path handling in the Changes
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api/python/ai/chronon/repo/gcp.py(6 hunks)
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api/python/ai/chronon/repo/gcp.py (1)
api/python/ai/chronon/repo/utils.py (2)
JobType(20-22)extract_filename_from_path(60-61)
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🔇 Additional comments (8)
api/python/ai/chronon/repo/gcp.py (8)
36-37: Appropriate instance variable storageProperly stores the artifact prefix for class-wide use.
215-215: Well-structured parameter additionExplicitly requiring the customer artifact prefix improves function design.
220-222: Clean URI parsing implementationGood use of
urlparseto extract bucket and path components.
230-231: Correct GCS path constructionProperly uses parsed components for file uploads.
Also applies to: 235-235
295-296: Correctly passes instance variableProperly uses stored prefix in method call.
339-340: Consistent prefix usageCorrectly passes the stored prefix parameter.
385-386: Consistent prefix usageMaintains pattern of using stored prefix.
414-415: Consistent prefix usageCompletes consistent usage throughout class.
Co-authored-by: Thomas Chow <[email protected]>
Co-authored-by: Thomas Chow <[email protected]>
Co-authored-by: Thomas Chow <[email protected]>
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🧹 Nitpick comments (1)
api/python/ai/chronon/repo/gcp.py (1)
240-240: Remove unnecessary f-strings.-release_prefix = os.path.join(customer_artifact_prefix, f"release", f"{version}", "jars") +release_prefix = os.path.join(customer_artifact_prefix, "release", version, "jars")🧰 Tools
🪛 Ruff (0.8.2)
240-240: f-string without any placeholders
Remove extraneous
fprefix(F541)
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api/python/ai/chronon/repo/gcp.py(6 hunks)
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api/python/ai/chronon/repo/gcp.py (1)
api/python/ai/chronon/repo/utils.py (2)
JobType(20-22)extract_filename_from_path(60-61)
🪛 Ruff (0.8.2)
api/python/ai/chronon/repo/gcp.py
240-240: f-string without any placeholders
Remove extraneous f prefix
(F541)
⏰ Context from checks skipped due to timeout of 90000ms (19)
- GitHub Check: cloud_aws_tests
- GitHub Check: service_tests
- GitHub Check: hub_tests
- GitHub Check: cloud_gcp_tests
- GitHub Check: online_tests
- GitHub Check: service_commons_tests
- GitHub Check: flink_tests
- GitHub Check: cloud_gcp_tests
- GitHub Check: api_tests
- GitHub Check: cloud_aws_tests
- GitHub Check: aggregator_tests
- GitHub Check: service_tests
- GitHub Check: online_tests
- GitHub Check: hub_tests
- GitHub Check: api_tests
- GitHub Check: flink_tests
- GitHub Check: orchestration_tests
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🔇 Additional comments (10)
api/python/ai/chronon/repo/gcp.py (10)
36-40: Constructor now requires artifact_prefix.Storage and validation of the required prefix field is clean and well-implemented.
219-222: GCS URI parsing logic properly extracts bucket and path.The implementation correctly handles parsing the GCS URI into bucket name and blob path components.
229-233: File upload path construction is correctly implemented.Uploads now properly use the prefix structure from the customer_artifact_prefix.
236-237: Bucket name usage is consistent with the parsed URI.
243-243: JAR URI construction fixed without leading slash.Path joining works correctly now without a leading slash that would cause the first argument to be ignored.
251-251: Flink JAR URI construction fixed without leading slash.Path joining works correctly without a leading slash, as previously suggested.
297-299: Method call updated to use stored artifact prefix.Consistent usage of the stored prefix parameter.
341-342: Method call updated to use stored artifact prefix.
387-388: Method call updated to use stored artifact prefix.
416-417: Method call updated to use stored artifact prefix.
Co-authored-by: Thomas Chow <[email protected]>
Co-authored-by: Thomas Chow <[email protected]>
<-----------------------------------------------------------------------------------
------------------------------------------------------------------------------------
DATAPROC LOGS
------------------------------------------------------------------------------------
------------------------------------------------------------------------------------>
INFO:ai.chronon.logger:Running command: gcloud dataproc jobs wait 0e68feda-fcef-421b-842e-845dcfcd7e73 --region=us-central1 --project=canary-443022
Waiting for job output...
25/04/29 23:43:47 WARN SparkConf: The configuration key 'spark.yarn.executor.failuresValidityInterval' has been deprecated as of Spark 3.5 and may be removed in the future. Please use the new key 'spark.executor.failuresValidityInterval' instead.
25/04/29 23:43:47 WARN SparkConf: The configuration key 'spark.yarn.executor.failuresValidityInterval' has been deprecated as of Spark 3.5 and may be removed in the future. Please use the new key 'spark.executor.failuresValidityInterval' instead.
25/04/29 23:43:48 INFO MetadataDirWalker: Uploading Chronon configs from purchases.v1_dev
25/04/29 23:43:51 INFO MetadataStore: Creating dataset: CHRONON_METADATA
25/04/29 23:43:52 INFO BigTableKVStoreImpl: Table CHRONON_METADATA already exists
25/04/29 23:43:52 INFO MetadataStore: Successfully created dataset: CHRONON_METADATA
25/04/29 23:43:52 INFO MetadataStore: Creating dataset: CHRONON_ENTITY_BY_TEAM
25/04/29 23:43:52 INFO BigTableKVStoreImpl: Table CHRONON_ENTITY_BY_TEAM already exists
25/04/29 23:43:52 INFO MetadataStore: Successfully created dataset: CHRONON_ENTITY_BY_TEAM
25/04/29 23:43:52 INFO MetadataStore: Putting metadata for
dataset: CHRONON_METADATA
key: group_bys/gcp.purchases.v1_dev
conf: List({"metaData":{"name":"gcp.purchases.v1_dev","team":"gcp","outputNamespace":"data","online":1,"sourceFile":"group_bys/gcp/purchases.py","customJson":"{\"airflowDependencies\": [{\"name\": \"wf_data_purchases\", \"spec\": \"data.purchases/ds={{ ds }}\"}]}","executionInfo":{"env":{"common":{"VERSION":"latest","JOB_MODE":"local[*]","HADOOP_DIR":"[STREAMING-TODO]/path/to/folder/containing","CHRONON_ONLINE_CLASS":"[ONLINE-TODO]your.online.class","CHRONON_ONLINE_ARGS":"[ONLINE-TODO]args prefixed with -Z become constructor map for your implementation of ai.chronon.online.Api, -Zkv-host=<YOUR_HOST> -Zkv-port=<YOUR_PORT>","PARTITION_COLUMN":"ds","PARTITION_FORMAT":"yyyy-MM-dd","CUSTOMER_ID":"dev","GCP_PROJECT_ID":"canary-443022","GCP_REGION":"us-central1","GCP_DATAPROC_CLUSTER_NAME":"zipline-canary-cluster","GCP_BIGTABLE_INSTANCE_ID":"zipline-canary-instance","CLOUD_PROVIDER":"gcp"}},"conf":{"common":{"spark.chronon.partition.column":"ds","spark.chronon.cloud_provider":"gcp","spark.chronon.table.format_provider.class":"ai.chronon.integrations.cloud_gcp.GcpFormatProvider","spark.chronon.partition.format":"yyyy-MM-dd","spark.chronon.table.gcs.temporary_gcs_bucket":"zipline-warehouse-canary","spark.chronon.table.gcs.connector_output_dataset":"data","spark.chronon.table.gcs.connector_output_project":"canary-443022","spark.chronon.table_write.prefix":"gs://zipline-warehouse-canary/data/tables/","spark.chronon.table_write.format":"iceberg","spark.sql.catalog.spark_catalog.warehouse":"gs://zipline-warehouse-canary/data/tables/","spark.sql.catalog.spark_catalog.gcp_location":"us-central1","spark.sql.catalog.spark_catalog.gcp_project":"canary-443022","spark.sql.catalog.spark_catalog.catalog-impl":"org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog","spark.sql.catalog.spark_catalog":"ai.chronon.integrations.cloud_gcp.DelegatingBigQueryMetastoreCatalog","spark.sql.catalog.spark_catalog.io-impl":"org.apache.iceberg.io.ResolvingFileIO","spark.sql.catalog.default_iceberg.warehouse":"gs://zipline-warehouse-canary/data/tables/","spark.sql.catalog.default_iceberg.gcp_location":"us-central1","spark.sql.catalog.default_iceberg.gcp_project":"canary-443022","spark.sql.catalog.default_iceberg.catalog-impl":"org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog","spark.sql.catalog.default_iceberg":"ai.chronon.integrations.cloud_gcp.DelegatingBigQueryMetastoreCatalog","spark.sql.catalog.default_iceberg.io-impl":"org.apache.iceberg.io.ResolvingFileIO","spark.sql.defaultUrlStreamHandlerFactory.enabled":"false","spark.kryo.registrator":"ai.chronon.integrations.cloud_gcp.ChrononIcebergKryoRegistrator","spark.chronon.coalesce.factor":"10","spark.default.parallelism":"10","spark.sql.shuffle.partitions":"10"}},"scheduleCron":"@daily","historicalBackfill":0}},"sources":[{"events":{"table":"data.purchases","query":{"selects":{"user_id":"user_id","purchase_price":"purchase_price"},"timeColumn":"ts"}}}],"keyColumns":["user_id"],"aggregations":[{"inputColumn":"purchase_price","operation":7,"argMap":{},"windows":[{"length":3,"timeUnit":1},{"length":14,"timeUnit":1},{"length":30,"timeUnit":1}]},{"inputColumn":"purchase_price","operation":6,"argMap":{},"windows":[{"length":3,"timeUnit":1},{"length":14,"timeUnit":1},{"length":30,"timeUnit":1}]},{"inputColumn":"purchase_price","operation":8,"argMap":{},"windows":[{"length":3,"timeUnit":1},{"length":14,"timeUnit":1},{"length":30,"timeUnit":1}]},{"inputColumn":"purchase_price","operation":13,"argMap":{"k":"10"}}],"backfillStartDate":"2023-11-01"})
25/04/29 23:43:52 INFO MetadataStore: Putting 1 configs to KV Store, dataset=CHRONON_METADATA
25/04/29 23:43:52 INFO MetadataStore: Putting metadata for
dataset: CHRONON_ENTITY_BY_TEAM
key: group_bys/gcp
conf: List(group_bys/gcp.purchases.v1_dev)
25/04/29 23:43:52 INFO MetadataStore: Putting 1 configs to KV Store, dataset=CHRONON_ENTITY_BY_TEAM
25/04/29 23:43:52 INFO Driver$MetadataUploader$: Uploaded Chronon Configs to the KV store, success count = 2, failure count = 0
Job [0e68feda-fcef-421b-842e-845dcfcd7e73] finished successfully.
done: true
driverControlFilesUri: gs://dataproc-staging-us-central1-703996152583-lxespibx/google-cloud-dataproc-metainfo/4c97ca31-f67f-4f8c-8aee-1df7877ee18e/jobs/0e68feda-fcef-421b-842e-845dcfcd7e73/
driverOutputResourceUri: gs://dataproc-staging-us-central1-703996152583-lxespibx/google-cloud-dataproc-metainfo/4c97ca31-f67f-4f8c-8aee-1df7877ee18e/jobs/0e68feda-fcef-421b-842e-845dcfcd7e73/driveroutput
jobUuid: 0e68feda-fcef-421b-842e-845dcfcd7e73
placement:
clusterName: zipline-canary-cluster
clusterUuid: 4c97ca31-f67f-4f8c-8aee-1df7877ee18e
reference:
jobId: 0e68feda-fcef-421b-842e-845dcfcd7e73
projectId: canary-443022
sparkJob:
args:
- metadata-upload
- --conf-path=purchases.v1_dev
- --online-jar=cloud_gcp_lib_deploy.jar
- --online-class=ai.chronon.integrations.cloud_gcp.GcpApiImpl
- --conf-type=group_bys
- --is-gcp
- --gcp-project-id=canary-443022
- --gcp-bigtable-instance-id=zipline-canary-instance
fileUris:
- gs://zipline-artifacts-dev/metadata/purchases.v1_dev
jarFileUris:
- gs://zipline-artifacts-dev/release/0.1.0+dev.thomaschow/jars/cloud_gcp_lib_deploy.jar
mainClass: ai.chronon.spark.Driver
properties:
spark.chronon.cloud_provider: gcp
spark.chronon.coalesce.factor: '10'
spark.chronon.partition.column: ds
spark.chronon.partition.format: yyyy-MM-dd
spark.chronon.table.format_provider.class: ai.chronon.integrations.cloud_gcp.GcpFormatProvider
spark.chronon.table.gcs.connector_output_dataset: data
spark.chronon.table.gcs.connector_output_project: canary-443022
spark.chronon.table.gcs.temporary_gcs_bucket: zipline-warehouse-canary
spark.chronon.table_write.format: iceberg
spark.chronon.table_write.prefix: gs://zipline-warehouse-canary/data/tables/
spark.default.parallelism: '10'
spark.kryo.registrator: ai.chronon.integrations.cloud_gcp.ChrononIcebergKryoRegistrator
spark.sql.catalog.default_iceberg: ai.chronon.integrations.cloud_gcp.DelegatingBigQueryMetastoreCatalog
spark.sql.catalog.default_iceberg.catalog-impl: org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog
spark.sql.catalog.default_iceberg.gcp_location: us-central1
spark.sql.catalog.default_iceberg.gcp_project: canary-443022
spark.sql.catalog.default_iceberg.io-impl: org.apache.iceberg.io.ResolvingFileIO
spark.sql.catalog.default_iceberg.warehouse: gs://zipline-warehouse-canary/data/tables/
spark.sql.catalog.spark_catalog: ai.chronon.integrations.cloud_gcp.DelegatingBigQueryMetastoreCatalog
spark.sql.catalog.spark_catalog.catalog-impl: org.apache.iceberg.gcp.bigquery.BigQueryMetastoreCatalog
spark.sql.catalog.spark_catalog.gcp_location: us-central1
spark.sql.catalog.spark_catalog.gcp_project: canary-443022
spark.sql.catalog.spark_catalog.io-impl: org.apache.iceberg.io.ResolvingFileIO
spark.sql.catalog.spark_catalog.warehouse: gs://zipline-warehouse-canary/data/tables/
spark.sql.defaultUrlStreamHandlerFactory.enabled: 'false'
spark.sql.shuffle.partitions: '10'
status:
state: DONE
stateStartTime: '2025-04-29T23:43:52.871799Z'
statusHistory:
- state: PENDING
stateStartTime: '2025-04-29T23:43:41.434675Z'
- state: SETUP_DONE
stateStartTime: '2025-04-29T23:43:41.456995Z'
- details: Agent reported job success
state: RUNNING
stateStartTime: '2025-04-29T23:43:41.666276Z'
INFO:ai.chronon.logger:Running command: gcloud dataproc jobs describe 0e68feda-fcef-421b-842e-845dcfcd7e73 --region=us-central1 --project=canary-443022 --format=json
<<<<<<<<<<<<<<<<-----------------JOB STATUS----------------->>>>>>>>>>>>>>>>>
Job 0e68feda-fcef-421b-842e-845dcfcd7e73 is in DONE state.
+ fail_if_bash_failed
+ '[' 0 -ne 0 ']'
+ echo -e '\033[0;32m<<<<<.....................................FETCH.....................................>>>>>\033[0m'
<<<<<.....................................FETCH.....................................>>>>>
+ touch tmp_fetch.out
+ [[ dev == \c\a\n\a\r\y ]]
+ zipline run --repo=/Users/thomaschow/zipline-ai/chronon/api/python/test/canary --version 0.1.0+dev.thomaschow --mode fetch --conf=compiled/group_bys/gcp/purchases.v1_dev -k '{"user_id":"5"}' --name gcp.purchases.v1_dev
+ tee tmp_fetch.out
+ grep -q purchase_price_average_14d
+ fail_if_bash_failed
+ '[' 0 -ne 0 ']'
+ cat tmp_fetch.out
+ grep purchase_price_average_14d
2025/04/29 16:44:23 INFO SawtoothOnlineAggregator.scala:60 - purchase_price_average_14d -> Some(2023-11-18 00:00:00)
"purchase_price_average_14d" : 72.5,
+ '[' 0 -ne 0 ']'
+ echo -e '\033[0;32m<<<<<.....................................SUCCEEDED!!!.....................................>>>>>\033[0m'
<<<<<.....................................SUCCEEDED!!!.....................................>>>>> |
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This reverts commit 918b4a4.
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kumar-zlai
pushed a commit
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## Summary
## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Refactor**
- Improved handling of Google Cloud Storage (GCS) artifact locations by
requiring a full artifact prefix URI instead of relying on internal
customer ID logic. All GCS interactions now use this provided prefix,
allowing for more flexible and centralized configuration.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
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Co-authored-by: Thomas Chow <[email protected]>
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chewy-zlai
pushed a commit
that referenced
this pull request
May 15, 2025
## Summary
## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Refactor**
- Improved handling of Google Cloud Storage (GCS) artifact locations by
requiring a full artifact prefix URI instead of relying on internal
customer ID logic. All GCS interactions now use this provided prefix,
allowing for more flexible and centralized configuration.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
<!-- av pr metadata
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the status of stacks when using Aviator. Please do not delete or edit
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---------
Co-authored-by: Thomas Chow <[email protected]>
chewy-zlai
pushed a commit
that referenced
this pull request
May 15, 2025
## Summary
## Checklist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Refactor**
- Improved handling of Google Cloud Storage (GCS) artifact locations by
requiring a full artifact prefix URI instead of relying on internal
customer ID logic. All GCS interactions now use this provided prefix,
allowing for more flexible and centralized configuration.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
<!-- av pr metadata
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Co-authored-by: Thomas Chow <[email protected]>
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May 16, 2025
## Summary
## Cheour clientslist
- [ ] Added Unit Tests
- [ ] Covered by existing CI
- [ ] Integration tested
- [ ] Documentation update
<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit
- **Refactor**
- Improved handling of Google Cloud Storage (GCS) artifact locations by
requiring a full artifact prefix URI instead of relying on internal
customer ID logic. All GCS interactions now use this provided prefix,
allowing for more flexible and centralized configuration.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->
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Co-authored-by: Thomas Chow <[email protected]>
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