skamalj / chatgpt Goto Github PK

This is built using serverless Redshift and needs following environment variables.

REDSHIFT_WORKGROUP_NAME
AWS_REGION
OPENAPI_API_KEY
REDSHIFT_DATABASE

Your aws profile must be set and should have sufficient permissions to query/connect to Redshift

This uses sample database as described over here

• list categories
• list cities sorted by total number of tickets sold for Pop events
• finds the top five sellers in San Diego, based on the total number of tickets sold in 2008, use date table
• • finds the top five sellers in San Diego, based on the number of tickets sold in 2008, use date table, use sales not listing, show full username
• list top 5 categories based on number of events
• which venue had most events hosted
• write sql to rank venues within the city based on number of events hosted, select venue city, venue name and rank , sort the result on city and rank
• who are top 5 sellers based on number of tickets sold
• • get seller full name as well ( qualify tablenames with schema )

• how many users have attended events in multiple cities
• • Solution: how many users have attended events in multiple cities, use subquery
• what was revenue each month , select top 5 months, pricepaid is price per ticket, listing is not sales

bq --location=asia-south1 load --source_format=CSV -F "|" tickit.category category_pipe.txt bq --location=asia-south1 load --source_format=CSV -F "|" tickit.users allusers_pipe.txt bq --location=asia-south1 load --source_format=CSV -F "|" tickit.venue venue_pipe.txt bq --location=asia-south1 load --source_format=CSV -F "|" tickit.date date2008_pipe.txt bq --location=asia-south1 load --source_format=CSV -F "|" tickit.event allevents_pipe.txt bq --location=asia-south1 load --source_format=CSV -F "|" tickit.listing listings_pipe.txt bq --location=asia-south1 load --autodetect --source_format=CSV -F "\t" tickit.sales_temp sales_tab.txt bq query --use_legacy_sql=false 'insert into tickit.sales select * from tickit.sales_temp'