From a50c4ead3c903eefd59fc8bd7e62b77cabc9e414 Mon Sep 17 00:00:00 2001
From: Tian Chen <38001883+Tian-2017@users.noreply.github.com>
Date: Mon, 9 Jun 2025 16:55:16 +0100
Subject: [PATCH] restore parking_copy_ringgo_sftp_data_to_raw

---
 .../parking_copy_ringgo_sftp_data_to_raw.py   | 79 +++++++++++++++++++
 1 file changed, 79 insertions(+)
 create mode 100644 scripts/jobs/parking/parking_copy_ringgo_sftp_data_to_raw.py

diff --git a/scripts/jobs/parking/parking_copy_ringgo_sftp_data_to_raw.py b/scripts/jobs/parking/parking_copy_ringgo_sftp_data_to_raw.py
new file mode 100644
index 000000000..5446546b2
--- /dev/null
+++ b/scripts/jobs/parking/parking_copy_ringgo_sftp_data_to_raw.py
@@ -0,0 +1,79 @@
+import sys
+
+import boto3
+from awsglue.context import GlueContext
+from awsglue.job import Job
+from awsglue.transforms import *
+from awsglue.utils import getResolvedOptions
+from pyspark.context import SparkContext
+from pyspark.sql import SparkSession
+from pyspark.sql.functions import col, concat, lit, when
+from pyspark.sql.types import IntegerType
+
+from scripts.helpers.helpers import (
+    PARTITION_KEYS,
+    add_import_time_columns,
+    clean_column_names,
+    get_glue_env_var,
+    get_latest_partitions,
+    get_s3_subfolders,
+)
+
+s3_client = boto3.client("s3")
+sc = SparkContext.getOrCreate()
+spark = SparkSession.builder.getOrCreate()
+glue_context = GlueContext(sc)
+
+logger = glue_context.get_logger()
+
+
+def data_source_landing_to_raw(bucket_source, bucket_target, s3_prefix):
+    logger.info("bucket_target" + bucket_target)
+    logger.info("s3_prefix" + s3_prefix)
+    data_source = spark.read.option("header", "true").csv(
+        bucket_source + "/" + s3_prefix
+    )
+    latest_data = get_latest_partitions(data_source)
+    logger.info(f"latest_data: {latest_data}")
+
+    logger.info(f"Retrieved data source from s3 path {bucket_source}/{s3_prefix}")
+
+    data_frame = clean_column_names(latest_data)
+    logger.info("Using Columns: " + str(data_frame.columns))
+
+    date_partition_formatted = (
+        data_frame.withColumn("import_month", col("import_month").cast(IntegerType()))
+        .withColumn("import_day", col("import_day").cast(IntegerType()))
+        .withColumn(
+            "import_month",
+            when(
+                col("import_month") < 10, concat(lit("0"), col("import_month"))
+            ).otherwise(col("import_month")),
+        )
+        .withColumn(
+            "import_day",
+            when(col("import_day") < 10, concat(lit("0"), col("import_day"))).otherwise(
+                col("import_day")
+            ),
+        )
+    )
+
+    date_partition_formatted.write.mode("append").partitionBy(*PARTITION_KEYS).parquet(
+        bucket_target + "/" + s3_prefix
+    )
+
+
+args = getResolvedOptions(sys.argv, ["JOB_NAME"])
+
+job = Job(glue_context)
+job.init(args["JOB_NAME"], args)
+
+s3_bucket_target = get_glue_env_var("s3_bucket_target", "")
+s3_prefix = get_glue_env_var("s3_prefix", "")
+s3_bucket_source = get_glue_env_var("s3_bucket_source", "")
+
+data_source_landing_to_raw(
+    "s3://" + s3_bucket_source, "s3://" + s3_bucket_target, s3_prefix
+)
+
+job.commit()