gaogaotiantian commented on code in PR #56668:
URL: https://github.com/apache/spark/pull/56668#discussion_r3455643213
##########
python/pyspark/pipelines/cli.py:
##########
@@ -325,30 +325,31 @@ def run(
spark_builder = spark_builder.config(key, value)
spark = spark_builder.getOrCreate()
-
- log_with_curr_timestamp("Creating dataflow graph...")
- dataflow_graph_id = create_dataflow_graph(
- spark,
- default_catalog=spec.catalog,
- default_database=spec.database,
- sql_conf=spec.configuration,
- )
-
- log_with_curr_timestamp("Registering graph elements...")
- registry = SparkConnectGraphElementRegistry(spark, dataflow_graph_id)
- register_definitions(spec_path, registry, spec, spark, dataflow_graph_id)
-
- log_with_curr_timestamp("Starting run...")
- result_iter = start_run(
- spark,
- dataflow_graph_id,
- full_refresh=full_refresh,
- full_refresh_all=full_refresh_all,
- refresh=refresh,
- dry=dry,
- storage=spec.storage,
- )
+ # Stop the session even if graph creation, registration, or the run itself
fails, so a failure
Review Comment:
I think the more pythonic way to do this is
```python
with spark_builder.getOrCreate() as spark:
...
```
This will auto-close your spark session when you exit the `with` block, no
matter if it's an exception or a normal exit.
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