I have been using Python to perform a SQL query and retrieve data from the previous date every day since June and load it into a Postgres database which is local. Each date has about 2 million rows and 75 columns or so, so it is fairly large and it takes a while to pull.
Can someone give me an example bcp code which will generate a CSV (comma) file? How much data would I be able to pull at once or can I loop through each calendar date in the SELECT statement? I am hoping this will be a faster way to kind of replicate the tables I am interested in.
My Python code essentially boils down to SELECT * FROM table_name WHERE report_date = {}. The report date is typically yesterday.
Here is my final working result if anyone else every stumbles upon this. The subprocess.run executes the string which contains the BCP query. In the code below, there are a few variables such as the table_name, database name, and query date since I am looping through different tables and databases on different dates.
path = 'C:/raw/'
filename = '{}_{}.csv'.format(database, select_database(database)[table_int])
query = '"SELECT * FROM {}.dbo.{} WHERE row_date = \'{}\'"'.format(database, select_database(database)[table_int], query_date)
command = 'BCP {} queryout \"{}\" -t, -c -S "server_name" -T'.format(query, os.path.join(path, filename))
table_name = 'raw_{}_{}'.format(select_database(database)[table_int], database)
logger.info(command)
subprocess.run(command)