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Posted to notifications@superset.apache.org by "john-bodley (via GitHub)" <gi...@apache.org> on 2023/02/02 08:12:34 UTC
[GitHub] [superset] john-bodley opened a new pull request, #22957: chore(datasets): Refactor DatasetDAO with bulk operations
john-bodley opened a new pull request, #22957:
URL: https://github.com/apache/superset/pull/22957
<!---
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Example:
fix(dashboard): load charts correctly
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### SUMMARY
Somewhat akin to https://github.com/apache/superset/pull/22413, this PR optimizes the PUT operation for the RESTful API `/api/v1/dataset/{pk}` endpoint.
Though updates are sparse in nature, i.e., per [here](https://github.com/apache/superset/blob/21a2e7bc91125ffab2ddc62d6cee7a7e9a51840d/superset/dao/base.py#L166-L167) where only the specified properties are updated, from a dataset perspective all the columns and metrics must be specified—even if updating a subset—otherwise the undefined (unseen) columns and metrics will be deleted per [here](https://github.com/apache/superset/blob/21a2e7bc91125ffab2ddc62d6cee7a7e9a51840d/superset/datasets/dao.py#L221-L222) and [here](https://github.com/apache/superset/blob/21a2e7bc91125ffab2ddc62d6cee7a7e9a51840d/superset/datasets/dao.py#L262-L263) respectively.
For large datasets (like Airbnb's uber virtual dataset—comprising of thousands of columns and metrics) these updates are rather expensive given that the create, update, and delete operations work on a single entity and thus the PUT operation for the RESTful API `/api/v1/dataset/{pk}` endpoint (even for sparely defined entities) the request timed out after five minutes.
The proposed fix is to use bulk logic for the create, update, and delete operations which reduces the request to well under 60 seconds.
### BEFORE/AFTER SCREENSHOTS OR ANIMATED GIF
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### TESTING INSTRUCTIONS
CI, i.e., existing unit/integration tests.
### ADDITIONAL INFORMATION
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<!--- HINT: Include "Fixes #nnn" if you are fixing an existing issue -->
- [ ] Has associated issue:
- [ ] Required feature flags:
- [ ] Changes UI
- [ ] Includes DB Migration (follow approval process in [SIP-59](https://github.com/apache/superset/issues/13351))
- [ ] Migration is atomic, supports rollback & is backwards-compatible
- [ ] Confirm DB migration upgrade and downgrade tested
- [ ] Runtime estimates and downtime expectations provided
- [ ] Introduces new feature or API
- [ ] Removes existing feature or API
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[GitHub] [superset] john-bodley commented on a diff in pull request #22957: chore(datasets): Refactor DatasetDAO with bulk operations
Posted by "john-bodley (via GitHub)" <gi...@apache.org>.
john-bodley commented on code in PR #22957:
URL: https://github.com/apache/superset/pull/22957#discussion_r1094170324
##########
superset/datasets/dao.py:
##########
@@ -241,26 +252,36 @@ def update_metrics(
then we delete.
"""
- metric_by_id = {metric.id: metric for metric in model.metrics}
- seen = set()
-
- for properties in property_metrics:
- if "id" in properties:
- seen.add(properties["id"])
+ metrics_by_id = {metric.id: metric for metric in model.metrics}
Review Comment:
metrics (plural) and not metric (singular).
##########
superset/datasets/dao.py:
##########
@@ -241,26 +252,36 @@ def update_metrics(
then we delete.
"""
- metric_by_id = {metric.id: metric for metric in model.metrics}
- seen = set()
-
- for properties in property_metrics:
- if "id" in properties:
- seen.add(properties["id"])
+ metrics_by_id = {metric.id: metric for metric in model.metrics}
+
+ property_metrics_by_id = {
+ properties["id"]: properties
+ for properties in property_metrics
+ if "id" in properties
+ }
+
+ db.session.bulk_insert_mappings(
+ SqlMetric,
+ [
+ {**properties, "table_id": model.id}
+ for properties in property_metrics
+ if not "id" in properties
+ ],
+ )
- DatasetDAO.update_metric(
- metric_by_id[properties["id"]],
- properties,
- commit=False,
- )
- else:
- DatasetDAO.create_metric(
- {**properties, "table_id": model.id},
- commit=False,
- )
+ db.session.bulk_update_mappings(
+ SqlMetric,
+ [
+ {**metrics_by_id[properties["id"]].__dict__, **properties}
+ for properties in property_metrics_by_id.values()
+ ],
+ )
- for id_ in {obj.id for obj in model.metrics} - seen:
- DatasetDAO.delete_column(metric_by_id[id_], commit=False)
+ db.session.query(SqlMetric).filter(
+ SqlMetric.id.in_(
+ {metric.id for metric in model.metrics} - property_metrics_by_id.keys()
+ )
+ ).delete(synchronize_session="fetch")
Review Comment:
Using the same `synchronize_session` as the `bulk_delete` method for deleting multiple datasets.
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[GitHub] [superset] codecov[bot] commented on pull request #22957: chore(datasets): Refactor DatasetDAO update to leverage bulk logic for create, update, and delete operations
Posted by "codecov[bot] (via GitHub)" <gi...@apache.org>.
codecov[bot] commented on PR #22957:
URL: https://github.com/apache/superset/pull/22957#issuecomment-1413327649
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[GitHub] [superset] john-bodley merged pull request #22957: chore(datasets): Refactor DatasetDAO update to leverage bulk logic for create, update, and delete operations
Posted by "john-bodley (via GitHub)" <gi...@apache.org>.
john-bodley merged PR #22957:
URL: https://github.com/apache/superset/pull/22957
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