I have an application which do mysql reads intensively and usually it needs to read lots of data from mysql(e.g. ~100K rows one time); but i found it's very slow, especially when read it to pandas. here is what i tried:
option-1: pure sql+Sequel=~38ms
select all the 100K rows using pure sql
select * FROM thetable
in a db workbench(Sequel) which cost about 38ms;
option-2: MySQLdb connector + fetchall()
= ~1.6s
option-3: MySQLdb connector + pandas.read_sql(sql, conn)
= ~1.7s
option-3: pymysql connector + pandas.read_sql(sql, conn)
= ~4.3s
It seems that use MySQLdb rather than pymysql can speed about 3X, but how can I achieve the performance as pure SQL does?