Hannah

AI_ASSIST.md

@@ -6,16 +6,38 @@ Document one session where you used an LLM to help with a query or a design deci
 
 ## The problem
 
-TODO: What were you trying to solve? Paste the relevant SQL or schema fragment.
+My database was working but the next day it said connection is broken
+Connection to hyf-data-pg.postgres.database.azure.com:5432 refused. Check that the hostname and port are correct and that the postmaster is accepting TCP/IP connections.
+  Connection refused: getsockopt
 
 ## The prompt
 
-TODO: What did you ask the AI? Include the context you provided.
+why is my connection to my database broken with error Connection refused: getsockopt
 
 ## The response
 
-TODO: What did it suggest? Did it work first try?
+refused: getsockopt
+
+"Connection refused: getsockopt" is a very common socket-level error. It means your client tried to open a TCP connection to the database but the target machine actively refused it (or nothing was listening).Most Common Causes (in order)Rank
+Cause
+Why it happens
+1
+Database server is not running
+Service crashed, wasn't started, or was stopped
+2
+Wrong host/port
+You're connecting to localhost:5432 but the DB is on another machine or different port
+3
+DB only listening on localhost
+Many DBs (especially Postgres, MySQL) by default bind to 127.0.0.1 only
+4
+Firewall
+iptables, ufw, firewalld, cloud security groups, etc. blocking the port
+
+IT DIDNT WORK
 
 ## Reflection
 
 TODO: Did you understand *why* the suggestion worked, or did you accept it blindly?
+
+i did not understand ,so i requested help and used a localhost postgres instead of the azure postgres

data_dictionary.md

@@ -4,14 +4,14 @@ Document both views. State the grain in one sentence, identify the keys, and lis
 
 ## vw_fact_trips
 
-- **Grain:** TODO (one sentence, e.g. "One row per ...")
-- **Primary key:** TODO
-- **Foreign keys:** TODO
-- **Measures:** TODO (columns you would SUM or AVG)
+- **Grain:** one row per taxi trip that has fare_amount >=0 
+- **Primary key:** vendor_id
+- **Foreign keys:** pickup_location_id, dropoff_location_id
+- **Measures:** fare_amount,trip_distance,tip_amount,passenger_count
 
 ## vw_dim_zones
 
-- **Grain:** TODO
-- **Primary key:** TODO
-- **Foreign keys:** TODO (or "none")
-- **Measures:** TODO (or "none, descriptive attributes only")
+- **Grain:** one zone per day
+- **Primary key:** location id
+- **Foreign keys:**  ( "none")
+- **Measures:**  "none, descriptive attributes only"

schema_setup.sql

@@ -5,8 +5,12 @@
 -- TODO: complete the SELECT (location_id, zone, borough).
 CREATE OR REPLACE VIEW vw_dim_zones AS
 SELECT
-    -- TODO
-FROM nyc_taxi.raw_zones;
+    rz.location_id,
+    rz.zone,
+    rz.borough
+FROM nyc_taxi.raw_zones ;
+
+;
 
 -- Fact: one row per taxi trip.
 --   - Exclude rows where fare_amount is less than 0.
@@ -15,12 +19,26 @@ FROM nyc_taxi.raw_zones;
 -- TODO: complete the SELECT and the WHERE.
 CREATE OR REPLACE VIEW vw_fact_trips AS
 SELECT
-    -- TODO
+    vendor_id,
+    pickup_datetime::timestamp AS pickup_datetime,
+    dropoff_datetime,
+    passenger_count,
+    pickup_location_id,
+    dropoff_location_id,
+    trip_distance,
+    fare_amount,
+    tip_amount,
+    payment_type
 FROM nyc_taxi.raw_trips
--- TODO: WHERE fare_amount >= 0
-;
+WHERE fare_amount >= 0;
 
 -- Join-readiness test (run after creating the views; it must run without error
 -- and return a count close to the vw_fact_trips row count):
 -- SELECT COUNT(*) FROM vw_fact_trips f
 -- JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id;
+
+select * from vw_fact_trips f
+join vw_dim_zones d on f.pickup_location_id = d.location_id;   
+
+
+

validation_queries.sql

@@ -6,15 +6,38 @@
 -- 1. Duplicate check: are there rows with the same vendor_id, pickup_datetime, dropoff_datetime?
 -- TODO: GROUP BY the three columns and keep only groups with HAVING COUNT(*) > 1.
 
+SELECT vendor_id, pickup_datetime, dropoff_datetime, COUNT(*) AS duplicate_count
+FROM nyc_taxi.raw_trips
+GROUP BY vendor_id, pickup_datetime, dropoff_datetime
+HAVING COUNT(*) > 1
+ORDER BY duplicate_count DESC;    
+
 
 -- 2. Null integrity: how many rows have a NULL pickup_location_id or dropoff_location_id?
 -- TODO: count the NULLs (COUNT(*) FILTER (WHERE ... IS NULL) is handy for several columns at once).
 
+SELECT 
+    COUNT(*) AS total_rows,
+    COUNT(*) FILTER (WHERE pickup_location_id IS NULL) AS null_pickup_location_id,
+    COUNT(*) FILTER (WHERE dropoff_location_id IS NULL) AS null_dropoff_location_id
+FROM nyc_taxi.raw_trips;    
+
 
 -- 3. Range validation: what are the min and max fare_amount? Are there negative values?
 -- TODO: SELECT MIN(fare_amount), MAX(fare_amount), and a count of rows where fare_amount < 0.
 
+SELECT 
+    MIN(fare_amount) AS min_fare_amount,
+    MAX(fare_amount) AS max_fare_amount,
+    COUNT(*) FILTER (WHERE fare_amount < 0) AS negative_fare_count
+FROM nyc_taxi.raw_trips;    
+
 
 -- 4. Relationship check: which pickup_location_id values in nyc_taxi.raw_trips do NOT exist in nyc_taxi.raw_zones?
 -- TODO: LEFT JOIN nyc_taxi.raw_zones ... WHERE z.location_id IS NULL  (or NOT EXISTS).
 -- Do NOT use NOT IN: a single NULL in the subquery hides every orphan.
+
+SELECT t.pickup_location_id
+FROM nyc_taxi.raw_trips t
+LEFT JOIN nyc_taxi.raw_zones z ON t.pickup_location_id = z.location_id
+WHERE z.location_id IS NULL 

verification_results.sql

@@ -3,20 +3,61 @@
 -- Borough and zone names live in vw_dim_zones, so join on pickup_location_id = location_id.
 
 -- 1. Volume: how many total rows in vw_fact_trips? How many rows per borough?
+
+SELECT COUNT(*) AS total_rows FROM vw_fact_trips;
+
+
 --    What is the most common pickup/dropoff location combination?
+
+Select d.borough, COUNT(*) AS rows_per_borough
+from vw_fact_trips f
+join vw_dim_zones d on f.pickup_location_id = d.location_id
+group by d.borough
+order by rows_per_borough desc;
+
+
 -- TODO
 -- (Take a screenshot of the per-borough counts and save it as assets/borough_count.png.)
 
 
+
 -- 2. Revenue: which pickup zone (name, not ID) generated the highest total fare_amount?
+
+SELECT d.zone, SUM(f.fare_amount) AS total_fare
+FROM vw_fact_trips f
+JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id
+GROUP BY d.zone
+ORDER BY total_fare DESC
+LIMIT 1;
 --    Which pickup zone collected the highest total fare_amount on any single day?
 -- TODO
+SELECT d.zone, f.pickup_datetime::date AS pickup_date, SUM(f.fare_amount) AS total_fare
+FROM vw_fact_trips f
+JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id
+GROUP BY d.zone, pickup_date
+ORDER BY total_fare DESC
+LIMIT 1;
 
 
 -- 3. Geospatial: total number of trips and average trip_distance for each borough.
 -- TODO
-
+SELECT d.borough, COUNT(*) AS total_trips, AVG(f.trip_distance) AS avg_trip_distance
+FROM vw_fact_trips f
+JOIN vw_dim_zones d ON f.pickup_location_id = d.location_id
+GROUP BY d.borough
+ORDER BY total_trips DESC;
 
 -- 4. Time patterns: which day of the week had the highest total tip_amount?
+
+SELECT EXTRACT(DOW FROM f.pickup_datetime) AS day_of_week, SUM(f.tip_amount) AS total_tip
+FROM vw_fact_trips f
+GROUP BY day_of_week
+ORDER BY total_tip DESC
+LIMIT 1;
 --    What hour of the day has the highest average tip?
 -- TODO
+SELECT EXTRACT(HOUR FROM f.pickup_datetime) AS hour_of_day, AVG(f.tip_amount) AS avg_tip
+FROM vw_fact_trips f
+GROUP BY hour_of_day
+ORDER BY avg_tip DESC
+LIMIT 1;