Data Warehouse Service GaussDB (DWS) -1

vim /home/user/Desktop/product_info0.csv

100,XHDK-A,2017-09-01,A,2017 Shirt Women,red,M,328,2017-09-04,715,good!
205,KDKE-B,2017-09-01,A,2017 T-shirt Women,pink,L,584,2017-09-05,40,very good!
300,JODL-X,2017-09-01,A,2017 T-shirt men,red,XL,15,2017-09-03,502,Bad.
310,QQPX-R,2017-09-02,B,2017 jacket women,red,L,411,2017-09-05,436,It's nice.
150,ABEF-C,2017-09-03,B,2017 Jeans Women,blue,M,123,2017-09-06,120,good.

200,BCQP-E,2017-09-04,B,2017 casual pants men,black,L,997,2017-09-10,301,good quality.
250,EABE-D,2017-09-10,A,2017 dress women,black,S,841,2017-09-15,299,This dress fits well.
108,CDXK-F,2017-09-11,A,2017 dress women,red,M,85,2017-09-14,22,It's really amazing to buy.
450,MMCE-H,2017-09-11,A,2017 jacket women,white,M,114,2017-09-14,22,very good.
260,OCDA-G,2017-09-12,B,2017 woolen coat women,red,L,2004,2017-09-15,826,Very comfortable.

980,"ZKDS-J",2017-09-13,"B","2017 Women's Cotton Clothing","red","M",112,,,
98,"FKQB-I",2017-09-15,"B","2017 new shoes men","red","M",4345,2017-09-18,5473
50,"DMQY-K",2017-09-21,"A","2017 pants men","red","37",28,2017-09-25,58,"good","good","good"
80,"GKLW-l",2017-09-22,"A","2017 Jeans Men","red","39",58,2017-09-25,72,"Very comfortable."
30,"HWEC-L",2017-09-23,"A","2017 shoes women","red","M",403,2017-09-26,607,"good!"
40,"IQPD-M",2017-09-24,"B","2017 new pants Women","red","M",35,2017-09-27,52,"very good."
50,"LPEC-N",2017-09-25,"B","2017 dress Women","red","M",29,2017-09-28,47,"not good at all."
60,"NQAB-O",2017-09-26,"B","2017 jacket women","red","S",69,2017-09-29,70,"It's beautiful."
70,"HWNB-P",2017-09-27,"B","2017 jacket women","red","L",30,2017-09-30,55,"I like it so much"
80,"JKHU-Q",2017-09-29,"C","2017 T-shirt","red","M",90,2017-10-02,82,"very good."


cd /home/user/Desktop/

ll

cat /home/user/Downloads/credentials.csv|grep -w user

CREATE FOREIGN TABLE product_info_ext
(
product_price integer not null,
product_id char(30) not null,
product_time date,
product_level char(10),
product_name varchar(200),
product_type1 varchar(20),
product_type2 char(10),
product_monthly_sales_cnt integer,
product_comment_time date,
product_comment_num integer,
product_comment_content varchar(200) 
) 
SERVER gsmpp_server 
OPTIONS(
LOCATION'obs://OBS_bucket_name/input_data/',
FORMAT 'CSV' ,
DELIMITER ',',
ENCODING 'utf8',
HEADER 'false',
ACCESS_KEY'AK',
SECRET_ACCESS_KEY'SK',
FILL_MISSING_FIELDS 'true',
IGNORE_EXTRA_DATA 'true'
)
READ ONLY 
LOG INTO product_info_err 
PER NODE REJECT LIMIT 'unlimited';

CREATE TABLE product_info
(
product_price integer not null,
product_id char(30) not null,
product_time date ,
product_level char(10) ,
product_name varchar(200) ,
product_type1 varchar(20) ,
product_type2 char(10) ,
product_monthly_sales_cnt integer ,
product_comment_time date ,
product_comment_num integer ,
product_comment_content varchar(200) 
) 
WITH (
orientation = column,
compression=middle
) 
DISTRIBUTE BY hash (product_id);

INSERT INTO product_info SELECT * FROM product_info_ext;

VACUUM FULL product_info;
ANALYZE product_info;

SELECT * FROM product_info;

INSERT INTO product_info VALUES (200,'ARCP-E','2016-05-04','B','2016 casual pants men','black','L',997,'2016-09-10',301,'good quality.');

INSERT INTO product_info VALUES (500,'JYXL-E','2017-06-04','B','2017 casual pants men','black','M',990,'2016-11-10',302,'good quality.');

UPDATE product_info SET product_price = 185 WHERE product_id = 'KDKE-B';

DELETE product_info WHERE product_id ='KDKE-B';

SELECT COUNT(*) FROM product_info;