#冲刺创作新星# openGauss 高级特性 DB4AI 进行 AI 开发 原创

# 镜像搜索
docker search opengauss
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# 镜像拉取
docker pull enmotech/opengauss:3.0.0
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# 镜像查看
docker images
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# 运行镜像
docker run --name opengauss -p 26000:26000 --privileged=true -d -e GS_PASSWORD=Enmo@123 enmotech/opengauss:latest
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# 查看镜像 ID
docker ps
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# 进入容器
docker exec -it 6b4745abb1a2 /bin/bash
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root@6b4745abb1a2:/# su - omm

omm@6b4745abb1a2:~$ gsql
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CREATE TABLE houses (
id INTEGER,
tax INTEGER,
bedroom INTEGER,
bath DOUBLE PRECISION,
price INTEGER,
size INTEGER,
lot INTEGER,
mark text
);
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insert into houses(id, tax, bedroom, bath, price, size, lot, mark) VALUES
(1,590,2,1,50000,770,22100,'a+'),
(2,1050,3,2,85000,1410,12000,'a+'),
(3,20,2,1,22500,1060,3500,'a-'),
(4,870,2,2,90000,1300,17500,'a+'),
(5,1320,3,2,133000,1500,30000,'a+'),
(6,1350,2,1,90500,850,25700,'a-'),
(7,2790,3,2.5,260000,2130,25000,'a+'),
(8,680,2,1,142500,1170,22000,'a-'),
(9,1840,3,2,160000,1500,19000,'a+'),
(10,3680,4,2,240000,2790,20000,'a-'),
(11,1660,3,1,87000,1030,17500,'a+'),
(12,1620,3,2,118500,1250,20000,'a-'),
(13,3100,3,2,140000,1760,38000,'a+'),
(14,2090,2,3,148000,1550,14000,'a-'),
(15,650,3,1.5,65000,1450,12000,'a-');
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CREATE MODEL model_name USING algorithm_name 
[FEATURES { {expression [ [ AS ] output_name ]} [, ...] }]
[TARGET { {expression [ [ AS ] output_name ]} [, ...] }]
FROM { table_name | select_query }
WITH hyperparameter_name = { hyperparameter_value | DEFAULT } [, ...] }
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CREATE MODEL price_model USING logistic_regression
 FEATURES size, lot
 TARGET mark
 FROM HOUSES
 WITH learning_rate=0.88, max_iterations=default;
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SELECT id, PREDICT BY price_model (FEATURES size,lot), price 
FROM houses;
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