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1. Login in to the mysql client using the login name and password provided by your instructor (if not already logged in). 2. View the existing databases that the MySQL Server is maintaining. SHOW DATABASES; 3. Utilize the photo_album database. USE photo_album; ---- If Need be, recreate the database and load the SQL data in that will be used for this lab CREATE DATABASE photo_album; SOURCE /tmp/photo_album.sql; 4. Query the database to display the active primary customer (email, first and last name) and all the associated active login names associated with that customer. SELECT customers.email_customer, customers.fname, customers.lname, logins.login_name  FROM customers, logins WHERE customers.email_customer = logins.email_customer  AND customers.active_customer = 'True'  AND logins.active_login = 'True';

1. Login in to the mysql client using the login name and password provided by your instructor (if not already logged in). 2. View the existing databases that the MySQL Server is maintaining. SHOW DATABASES; 3. Utilize the photo_album database. USE photo_album; ---- If Need be, recreate the database and load the SQL data in that will be used for this lab CREATE DATABASE photo_album; SOURCE /tmp/photo_album.sql; 4. Calculate how many days ago each person logged into the photo_album system. Note: Difference in dates are returned in microseconds when directly subtracted from each other. SELECT login_name, ROUND((NOW() - last_login)/24/60/60/60) FROM logins; 5. List the actual day name (Monday, Tuesday, etc.) for the last logins to determine if there is a trend in the day of the week for the last time a person logged into the photo_album system. SELECT login_name, DAYNAME(last_login) FROM logins; 6. Modify the statement above by having the output show 'Weeke