I read all the relevant duplicated questions/answers and I found this to be the most relevant answer:
INSERT IGNORE INTO temp(MAILING_ID,REPORT_ID)
SELECT DISTINCT MAILING_ID,REPORT_IDFROM table_1
;
The problem is that I want to remove duplicates by col1 and col2, but also want to include to the insert all the other fields of table_1.
I tried to add all the relevant columns this way:
INSERT IGNORE INTO temp(M_ID,MAILING_ID,REPORT_ID,
MAILING_NAME,VISIBILITY,EXPORTED) SELECT DISTINCT
M_ID,MAILING_ID,REPORT_ID,MAILING_NAME,VISIBILITY,
EXPORTED FROM table_1
;
M_ID(int,primary),MAILING_ID(int),REPORT_ID(int),
MAILING_NAME(varchar),VISIBILITY(varchar),EXPORTED(int)
But it inserted all rows into temp (including duplicates)
In SQL, some rows contain duplicate entries in multiple columns(>1). For deleting such rows, we need to use the DELETE keyword along with self-joining the table with itself.
By using pandas. DataFrame. drop_duplicates() method you can drop/remove/delete duplicate rows from DataFrame. Using this method you can drop duplicate rows on selected multiple columns or all columns.
The best way to delete duplicate rows by multiple columns is the simplest one:
Add an UNIQUE index:
ALTER IGNORE TABLE your_table ADD UNIQUE (field1,field2,field3);
The IGNORE above makes sure that only the first found row is kept, the rest discarded.
(You can then drop that index if you need future duplicates and/or know they won't happen again).
For Mysql:
DELETE t1 FROM yourtable t1
INNER JOIN yourtable t2 WHERE t1.id < t2.id
AND t1.identField1 = t2.identField1
AND t1.identField2 = t2.identField2;
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