Added scripts for exercise 5
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39
labs/ab-etl-visual-raw-to-processed.py
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39
labs/ab-etl-visual-raw-to-processed.py
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import sys
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from awsglue.transforms import *
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from awsglue.utils import getResolvedOptions
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from pyspark.context import SparkContext
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from awsglue.context import GlueContext
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from awsglue.job import Job
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from awsglue import DynamicFrame
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def sparkSqlQuery(glueContext, query, mapping, transformation_ctx) -> DynamicFrame:
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for alias, frame in mapping.items():
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frame.toDF().createOrReplaceTempView(alias)
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result = spark.sql(query)
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return DynamicFrame.fromDF(result, glueContext, transformation_ctx)
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args = getResolvedOptions(sys.argv, ['JOB_NAME'])
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sc = SparkContext()
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glueContext = GlueContext(sc)
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spark = glueContext.spark_session
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job = Job(glueContext)
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job.init(args['JOB_NAME'], args)
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# Script generated for node AWS Glue Data Catalog
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AWSGlueDataCatalog_node1715504004627 = glueContext.create_dynamic_frame.from_catalog(database="datalake_raw_534534002841_ab_1201680", table_name="crawler_stockdata", transformation_ctx="AWSGlueDataCatalog_node1715504004627")
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# Script generated for node SQL Query
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SqlQuery1825 = '''
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select year(cast(transaction_ts as timestamp)) as year,
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month(cast(transaction_ts as timestamp)) as month,
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day(cast(transaction_ts as timestamp)) as day,
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hour(cast(transaction_ts as timestamp)) as hour,
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transaction_ts, symbol, price, amount, dollar_amount, type
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from myDataSource;
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'''
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SQLQuery_node1715504223461 = sparkSqlQuery(glueContext, query = SqlQuery1825, mapping = {"myDataSource":AWSGlueDataCatalog_node1715504004627}, transformation_ctx = "SQLQuery_node1715504223461")
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# Script generated for node AWS Glue Data Catalog
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AWSGlueDataCatalog_node1716060278270 = glueContext.write_dynamic_frame.from_catalog(frame=SQLQuery_node1715504223461, database="datalake_processed_534534002841_ab_1201680", table_name="processed_stockdata", additional_options={"enableUpdateCatalog": True, "updateBehavior": "UPDATE_IN_DATABASE", "partitionKeys": ["symbol", "year", "month", "day", "hour"]}, transformation_ctx="AWSGlueDataCatalog_node1716060278270")
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job.commit()
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53
labs/ab-visual-etl-proces-transformation.py
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53
labs/ab-visual-etl-proces-transformation.py
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import sys
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from awsglue.transforms import *
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from awsglue.utils import getResolvedOptions
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from pyspark.context import SparkContext
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from awsglue.context import GlueContext
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from awsglue.job import Job
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from awsglue import DynamicFrame
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def sparkSqlQuery(glueContext, query, mapping, transformation_ctx) -> DynamicFrame:
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for alias, frame in mapping.items():
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frame.toDF().createOrReplaceTempView(alias)
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result = spark.sql(query)
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return DynamicFrame.fromDF(result, glueContext, transformation_ctx)
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def sparkUnion(glueContext, unionType, mapping, transformation_ctx) -> DynamicFrame:
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for alias, frame in mapping.items():
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frame.toDF().createOrReplaceTempView(alias)
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result = spark.sql("(select * from source1) UNION " + unionType + " (select * from source2)")
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return DynamicFrame.fromDF(result, glueContext, transformation_ctx)
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args = getResolvedOptions(sys.argv, ['JOB_NAME'])
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sc = SparkContext()
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glueContext = GlueContext(sc)
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spark = glueContext.spark_session
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job = Job(glueContext)
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job.init(args['JOB_NAME'], args)
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# Script generated for node AWS Glue Data Catalog
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AWSGlueDataCatalog_node1716120307832 = glueContext.create_dynamic_frame.from_catalog(database="datalake_processed_534534002841_ab_1201680", table_name="agg_stockdata", transformation_ctx="AWSGlueDataCatalog_node1716120307832")
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# Script generated for node AWS Glue Data Catalog
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AWSGlueDataCatalog_node1716061298505 = glueContext.create_dynamic_frame.from_catalog(database="datalake_processed_534534002841_ab_1201680", table_name="processed_stockdata", transformation_ctx="AWSGlueDataCatalog_node1716061298505")
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# Script generated for node Change Schema
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ChangeSchema_node1716120318123 = ApplyMapping.apply(frame=AWSGlueDataCatalog_node1716120307832, mappings=[("total_volume", "double", "total_volume", "double"), ("total_dollars", "double", "total_dollars", "double"), ("total_cnt_of_transactions", "int", "total_cnt_of_transactions", "int"), ("type", "string", "type", "string"), ("symbol", "string", "symbol", "string"), ("year", "int", "year", "int"), ("month", "int", "month", "int"), ("day", "int", "day", "int")], transformation_ctx="ChangeSchema_node1716120318123")
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# Script generated for node SQL Query
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SqlQuery1998 = '''
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select ROUND(SUM(amount), 2) as total_volume,
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ROUND(SUM(dollar_amount), 2) as total_dollars,
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COUNT(transaction_ts) as total_cnt_of_transactions,
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type, symbol, year, month, day
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from datalake_processed_534534002841_ab_1201680.processed_stockdata
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group by symbol, year, month, day, type
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order by symbol, day, type
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'''
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SQLQuery_node1716061397564 = sparkSqlQuery(glueContext, query = SqlQuery1998, mapping = {"myDataSource":AWSGlueDataCatalog_node1716061298505}, transformation_ctx = "SQLQuery_node1716061397564")
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# Script generated for node Union
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Union_node1716065407070 = sparkUnion(glueContext, unionType = "DISTINCT", mapping = {"source1": ChangeSchema_node1716120318123, "source2": SQLQuery_node1716061397564}, transformation_ctx = "Union_node1716065407070")
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# Script generated for node AWS Glue Data Catalog
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AWSGlueDataCatalog_node1716064742210 = glueContext.write_dynamic_frame.from_catalog(frame=Union_node1716065407070, database="datalake_processed_534534002841_ab_1201680", table_name="agg_stockdata", additional_options={"enableUpdateCatalog": True, "updateBehavior": "UPDATE_IN_DATABASE", "partitionKeys": ["symbol", "year", "month", "day"]}, transformation_ctx="AWSGlueDataCatalog_node1716064742210")
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job.commit()
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{
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"version": 4,
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"terraform_version": "1.8.1",
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"serial": 212,
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"serial": 276,
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"lineage": "a77aaaba-b4f8-6adb-0387-8f0b98d722c2",
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"outputs": {},
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"resources": [],
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{
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"version": 4,
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"terraform_version": "1.8.1",
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"serial": 196,
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"serial": 260,
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"lineage": "a77aaaba-b4f8-6adb-0387-8f0b98d722c2",
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"outputs": {},
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"resources": [
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@ -43,7 +43,7 @@
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"id": "development",
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"name": "development",
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"state": "ENABLED",
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"tags": {},
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"tags": null,
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"tags_all": {}
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},
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"sensitive_attributes": [],
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@ -82,8 +82,8 @@
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"id": "534534002841:datalake_processed_534534002841_ab_1201680",
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"location_uri": "",
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"name": "datalake_processed_534534002841_ab_1201680",
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"parameters": {},
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"tags": {},
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"parameters": null,
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"tags": null,
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"tags_all": {},
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"target_database": []
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},
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@ -120,8 +120,8 @@
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"id": "534534002841:datalake_raw_534534002841_ab_1201680",
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"location_uri": "",
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"name": "datalake_raw_534534002841_ab_1201680",
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"parameters": {},
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"tags": {},
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"parameters": null,
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"tags": null,
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"tags_all": {},
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"target_database": []
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},
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@ -141,7 +141,7 @@
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"attributes": {
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"arn": "arn:aws:glue:us-east-1:534534002841:crawler/gc-raw-534534002841-ab-1201680",
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"catalog_target": [],
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"classifiers": [],
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"classifiers": null,
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"configuration": "",
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"database_name": "datalake_raw_534534002841_ab_1201680",
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"delta_target": [],
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@ -175,7 +175,7 @@
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"connection_name": "",
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"dlq_event_queue_arn": "",
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"event_queue_arn": "",
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"exclusions": [],
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"exclusions": null,
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"path": "s3://datalake-raw-534534002841-ab-1201680/raw-zone/stockdata/",
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"sample_size": 0
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}
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],
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"snowflake_configuration": [],
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"splunk_configuration": [],
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"tags": {},
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"tags": null,
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"tags_all": {},
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"timeouts": null,
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"version_id": "1"
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@ -365,9 +365,9 @@
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"image_uri": "",
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"invoke_arn": "arn:aws:apigateway:us-east-1:lambda:path/2015-03-31/functions/arn:aws:lambda:us-east-1:534534002841:function:etl-post-processing-534534002841-ab-1201680/invocations",
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"kms_key_arn": "",
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"last_modified": "2024-05-12T07:30:33.751+0000",
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"last_modified": "2024-05-19T10:36:30.839+0000",
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"layers": [
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"arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:4"
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"arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:6"
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],
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"logging_config": [
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{
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@ -396,7 +396,7 @@
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"snap_start": [],
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"source_code_hash": "DYklWA51/+hutwYtHutJg59rV7DY0LEgfp+ne8wgiSo=",
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"source_code_size": 884,
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"tags": {},
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"tags": null,
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"tags_all": {},
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"timeout": 300,
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"timeouts": null,
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@ -425,15 +425,15 @@
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{
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"schema_version": 0,
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"attributes": {
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"arn": "arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:4",
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"compatible_architectures": [],
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"arn": "arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:6",
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"compatible_architectures": null,
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"compatible_runtimes": [
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"python3.8"
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],
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"created_date": "2024-05-12T07:30:26.214+0000",
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"created_date": "2024-05-19T10:36:30.504+0000",
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"description": "",
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"filename": "../lambda/awswrangler-layer-2.7.0-py3.8.zip",
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"id": "arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:4",
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"id": "arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680:6",
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"layer_arn": "arn:aws:lambda:us-east-1:534534002841:layer:aws_wrangler_534534002841_ab_1201680",
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"layer_name": "aws_wrangler_534534002841_ab_1201680",
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"license_info": "",
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@ -445,7 +445,7 @@
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"skip_destroy": false,
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"source_code_hash": "C0YX/4auMnBs4J9JCDy1f7uc2GLF0vU7ppQgzffQiN4=",
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"source_code_size": 43879070,
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"version": "4"
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"version": "6"
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},
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"sensitive_attributes": [],
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"private": "bnVsbA=="
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@ -514,25 +514,7 @@
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],
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"hosted_zone_id": "Z3AQBSTGFYJSTF",
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"id": "athena-results-534534002841-ab-1201680",
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"lifecycle_rule": [
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{
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"abort_incomplete_multipart_upload_days": 0,
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"enabled": true,
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"expiration": [
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{
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"date": "",
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"days": 1,
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"expired_object_delete_marker": false
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}
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],
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"id": "standard-expiration",
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"noncurrent_version_expiration": [],
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"noncurrent_version_transition": [],
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"prefix": "",
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"tags": {},
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"transition": []
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}
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],
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"lifecycle_rule": [],
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"logging": [],
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"object_lock_configuration": [],
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"object_lock_enabled": false,
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@ -796,17 +778,7 @@
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"bucket": "datalake-raw-534534002841-ab-1201680",
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"eventbridge": false,
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"id": "datalake-raw-534534002841-ab-1201680",
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"lambda_function": [
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{
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"events": [
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"s3:ObjectCreated:*"
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],
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"filter_prefix": "raw-zone/",
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"filter_suffix": "",
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"id": "tf-s3-lambda-20240512073033855700000001",
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"lambda_function_arn": "arn:aws:lambda:us-east-1:534534002841:function:etl-post-processing-534534002841-ab-1201680"
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}
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],
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"lambda_function": [],
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"queue": [],
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"topic": []
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},
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@ -839,12 +811,12 @@
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"key_id": "",
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"name": "s3_processed_bucket_name",
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"overwrite": null,
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"tags": {},
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"tags": null,
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"tags_all": {},
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"tier": "Standard",
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"type": "String",
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"value": "datalake-processed-534534002841-ab-1201680",
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"version": 3
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"version": 1
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},
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"sensitive_attributes": [
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[
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