\sql

SET GLOBAL local_infile = 1;

DROP DATABASE IF EXISTS heatwaveml_bench;

CREATE DATABASE heatwaveml_bench;

USE heatwaveml_bench;

CREATE TABLE nyc_taxi_train (VendorID INT, store_and_fwd_flag VARCHAR(255), RatecodeID INT, PULocationID INT, DOLocationID INT, passenger_count FLOAT, extra FLOAT,

mta_tax FLOAT, tip_amount FLOAT, tolls_amount FLOAT, improvement_surcharge FLOAT, trip_type INT, lpep_pickup_datetime_day FLOAT, lpep_pickup_datetime_hour FLOAT, lpep_pickup_datetime_minute FLOAT);

CREATE TABLE nyc_taxi_test LIKE nyc_taxi_train;

\js

util.importTable("nyc_taxi_train.csv",{table: "nyc_taxi_train", dialect: "csv-unix", skipRows:1})

util.importTable("nyc_taxi_test.csv",{table: "nyc_taxi_test", dialect: "csv-unix", skipRows:1})

\sql

CALL sys.ML_TRAIN('heatwaveml_bench.nyc_taxi_train', 'tip_amount', JSON_OBJECT('task', 'regression'), @model_nyc_taxi);

CALL sys.ML_MODEL_LOAD(@model_nyc_taxi, NULL);

CALL sys.ML_SCORE('heatwaveml_bench.nyc_taxi_test', 'tip_amount', @model_nyc_taxi, 'r2', @score_nyc_taxi, null);

SELECT @score_nyc_taxi;

DROP DATABASE heatwaveml_bench;