-
Notifications
You must be signed in to change notification settings - Fork 2
/
etl.py
61 lines (46 loc) · 2.49 KB
/
etl.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
import configparser
import psycopg2
from sql_queries import copy_table_queries, insert_table_queries
def load_staging_tables(cur, conn):
"""
This function loads the staging tables through execution of COPY comands defined in 'sql_queries' module.
This is the first step of the pipeline in AWS where we transfer the records from JSON files in Amazon S3 to Amazon Redshift cluster.
Args:
cur (:obj:`cursor`): One object of the class cursor.
It allows the execution of PostgreSQL commands in a database session.
All the commands are executed in the context of the database session wrapped by the connection.
conn (:obj:`connection`): One object of the class connection that encapsulates a database session.
It handles the connection to a PostgreSQL database instance.
Since Redshift is compatible with PostgreSQL we can use the same library to connect and manipulate Amazon Redshift.
"""
for query in copy_table_queries:
cur.execute(query)
conn.commit()
def insert_tables(cur, conn):
"""
This function insert the records in the data warehouse in Redshift tables. The data is read from staging tables using SQL statements defined in 'sql_queries' module.
This is the second step of the pipeline in AWS.
Args:
cur (:obj:`cursor`): One object of the class cursor.
It allows the execution of PostgreSQL commands in a database session.
All the commands are executed in the context of the database session wrapped by the connection.
conn (:obj:`connection`): One object of the class connection that encapsulates a database session.
It handles the connection to a PostgreSQL database instance.
Since Redshift is compatible with PostgreSQL we can use the same library to connect and manipulate Amazon Redshift.
"""
for query in insert_table_queries:
cur.execute(query)
conn.commit()
def main():
"""
Main function, used to connect to the data warehouse in Amazon Redshift and execute the data pipeline by calling 'load_staging_tables' and 'insert_tables' functions.
"""
config = configparser.ConfigParser()
config.read('dwh.cfg')
conn = psycopg2.connect("host={} dbname={} user={} password={} port={}".format(*config['CLUSTER'].values()))
cur = conn.cursor()
load_staging_tables(cur, conn)
insert_tables(cur, conn)
conn.close()
if __name__ == "__main__":
main()