1
def load_data(redshift_conn_params):
2
    """ Executes a query on the designated Redshift cluster and returns a dataframe"""
3
	query=f"""select activeday, 
4
                datacenter, 
5
                pid, 
6
                brand, 
7
                dcinternaluserid, 
8
                ipcountrycode, 
9
                jurisdictioncode, 
10
                regcountrycode, 
11
                gameid, 
12
                channel, 
13
                isfreegame, 
14
                currency, 
15
                exchangerate, 
16
                avgrtp, 
17
                sum(rounds) as "rounds", 
18
                sum(basebet) as "basebet", 
19
                sum(basewin) as "basewin", 
20
                sum(basejploss) as "basejploss", 
21
                sum(basejpwin) as "basejpwin", 
22
                sum(baseggr) as "baseggr", 
23
                sum(baseggrjpinlc) as "baseggrjpinlc", 
24
                y, m, d
25
        FROM "etl_dev"."transactions_daily_aggregation"
26
        WHERE activeday >= '2022-01-01' and activeday < '2022-02-01'
27
        GROUP BY activeday, datacenter, pid, brand, dcinternaluserid, ipcountrycode, jurisdictioncode, regcountrycode, gameid, channel, isfreegame, currency, exchangerate, avgrtp, y, m, d
28
    """
29
    conn = redshift_connector.connect(**redshift_conn_params)
30
    cursor = conn.cursor()
31
    # Query and receive result set
32
    cursor.execute(query)
33
    result: pd.DataFrame = cursor.fetch_dataframe()
34
    return result