fix tascomi snapshot timeout again

scripts/jobs/planning/tascomi_create_daily_snapshot.py

@@ -83,13 +83,13 @@ def loadIncrementsSinceDate(
 ) -> DataFrame:
     """
     Loads increments from the specified catalog table starting from a given date.
-    If the provided date is None, it defaults to 30 days ago.
+    If the provided date is None, it defaults to 60 days ago.
 
     Returns:
         DataFrame: A Spark DataFrame containing the loaded increments.
     """
     if date is None:
-        date = (datetime.now() - timedelta(days=30)).strftime("%Y%m%d")  # default date
+        date = (datetime.now() - timedelta(days=60)).strftime("%Y%m%d")  # default date
     increment_ddf = glueContext.create_dynamic_frame.from_catalog(
         name_space=name_space,
         table_name=increment_table_name,
@@ -149,6 +149,32 @@ def loadIncrementsSinceDate(
     "enforcement_breach_details": {"unique": ["id"]},
 }
 
+
+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})
+
+
 if __name__ == "__main__":
     args = getResolvedOptions(sys.argv, ["JOB_NAME"])
 
@@ -208,14 +234,18 @@ def loadIncrementsSinceDate(
             # snapshot table in glue catalogue
             else:
                 pushDownPredicate = create_pushdown_predicate(
-                    partitionDateColumn="snapshot_date", daysBuffer=3
+                    partitionDateColumn="snapshot_date", daysBuffer=60
                 )
                 #   load latest snpashot
                 snapshot_ddf = glueContext.create_dynamic_frame.from_catalog(
                     name_space=source_catalog_database,
                     table_name=snapshot_table_name,
-                    # push_down_predicate=pushDownPredicate
+                    push_down_predicate=pushDownPredicate,
                 )
+                if snapshot_ddf.count() == 0:
+                    logger.error(
+                        f"No data returned for table {snapshot_table_name} using push_down_predicate: {pushDownPredicate}. "
+                    )
                 snapshot_df = snapshot_ddf.toDF()
                 snapshot_df = get_latest_snapshot(snapshot_df)
                 last_snapshot_date = snapshot_df.select(max("snapshot_date")).first()[0]
@@ -248,6 +278,7 @@ def loadIncrementsSinceDate(
                         # apply COU
                         logger.info(f"Applying increment {increment_table_name}")
                         snapshot_df = apply_increments(snapshot_df, increment_df)
+
                 else:
                     logger.info(
                         f"Couldn't find table {increment_table_name} in database {source_catalog_database}, saving same snapshot as yesterday"
@@ -337,6 +368,9 @@ def loadIncrementsSinceDate(
                     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",
@@ -346,6 +380,7 @@ def loadIncrementsSinceDate(
                         "partitionKeys": PARTITION_KEYS,
                     },
                 )
+
         job.commit()
     finally:
         if len(dq_errors) > 0:

terraform/etl/24-aws-glue-tascomi-data.tf

@@ -53,7 +53,7 @@ locals {
     "complaint_sources",
     "file_closure_reasons",
     "enforcement_case_statuses"
-]
+  ]
 
   table_list = join(",", concat(local.tascomi_table_names, local.tascomi_static_tables))
 
@@ -264,7 +264,7 @@ module "tascomi_create_daily_snapshot" {
   job_name                       = "${local.short_identifier_prefix}tascomi_create_daily_snapshot_planning"
   glue_version                   = "2.0"
   glue_job_worker_type           = "G.2X"
-  number_of_workers_for_glue_job = 12
+  number_of_workers_for_glue_job = 6
   helper_module_key              = data.aws_s3_object.helpers.key
   pydeequ_zip_key                = data.aws_s3_object.pydeequ.key
   spark_ui_output_storage_id     = module.spark_ui_output_storage_data_source.bucket_id