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tascomi snapshot - change the daysBuffer and clean the partition before writing the data #2187

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Merged
Tian-2017 merged 1 commit into from
Mar 19, 2025
Merged

tascomi snapshot - change the daysBuffer and clean the partition before writing the data #2187

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28 changes: 27 additions & 1 deletion scripts/jobs/planning/tascomi_create_daily_snapshot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -82,6 +82,29 @@ def loadIncrementsSinceDate(increment_table_name, name_space, date):
return increment_df


def purge_today_partition(
glueContext: GlueContext, target_destination: str, retentionPeriod: int = 0
) -> None:
"""
Purges (delete) only today's partition under the given target destination.
Parameters:
glueContext: GlueContext instance.
target_destination: Base S3 path (e.g., "s3://your-bucket/path").
retentionPeriod: Retention period in hours (default 0, meaning delete all files immediately).
Returns:
partition_path: The S3 partition path that was purged.
"""
now = datetime.now()
snapshot_year = str(now.year)
snapshot_month = str(now.month).zfill(2)
snapshot_day = str(now.day).zfill(2)
snapshot_date = snapshot_year + snapshot_month + snapshot_day

partition_path = f"{target_destination}/snapshot_year={snapshot_year}/snapshot_month={snapshot_month}/snapshot_day={snapshot_day}/snapshot_date={snapshot_date}"

glueContext.purge_s3_path(partition_path, {"retentionPeriod": retentionPeriod})


# dict containing parameters for DQ checks
dq_params = {
"appeals": {"unique": ["id"]},
Expand Down Expand Up @@ -189,7 +212,7 @@ def loadIncrementsSinceDate(increment_table_name, name_space, date):
# snapshot table in glue catalogue
else:
pushDownPredicate = create_pushdown_predicate(
partitionDateColumn="snapshot_date", daysBuffer=3
partitionDateColumn="snapshot_date", daysBuffer=30
)
# load latest snpashot
snapshot_ddf = glueContext.create_dynamic_frame.from_catalog(
Expand Down Expand Up @@ -318,6 +341,9 @@ def loadIncrementsSinceDate(increment_table_name, name_space, date):
snapshot_df, glueContext, "resultDataFrame"
)
target_destination = s3_bucket_target + table_name

# Clean up today's partition before writing
purge_today_partition(glueContext, target_destination)
parquetData = glueContext.write_dynamic_frame.from_options(
frame=resultDataFrame,
connection_type="s3",
Expand Down