解决mysqldb查询大量数据导致内存使用过高的问题

时间:2021-01-06 05:17:03
1.源码
connection=MySQLdb.connect(
host="thehost",user="theuser",
passwd="thepassword",db="thedb")
cursor=connection.cursor()
cursor.execute(query)
for row in cursor.fetchall():
print(row)
2.问题
普通的操作不管是fetchall()还是fetchone()都是先将数据加载到本地再进行计算,大量的数据会导致内存资源消耗光。解决的方法是使用SSCurosr光标来处理。



3.优化后的代码
import MySQLdb.cursors
connection=MySQLdb.connect(
host="thehost",user="theuser",
passwd="thepassword",db="thedb",
cursorclass = MySQLdb.cursors.SSCursor)
cursor=connection.cursor()
cursor.execute(query)
for row in cursor:
print(row)

參考文档:http://mysql-python.sourceforge.net/MySQLdb.html#

关键段落截取:
BaseCursor
The base class for Cursor objects. This does not raise Warnings.
CursorStoreResultMixIn
Causes the Cursor to use the mysql_store_result() function to get the query result. The entire result set is stored on the client side.
CursorUseResultMixIn
Causes the cursor to use the mysql_use_result() function to get the query result. The result set is stored on the server side and is transferred
row by row using fetch operations.
CursorTupleRowsMixIn
Causes the cursor to return rows as a tuple of the column values.

CursorDictRowsMixIn

Causes the cursor to return rows as a dictionary, where the keys are column names and the values are column values. Note that if the column names are not unique, i.e., you are selecting from two tables that share column
names, some of them will be rewritten as table.column. This can be avoided by using the SQL ASkeyword.
(This is yet-another reason not to use * in SQL queries, particularly where JOIN is
involved.)

Cursor
The default cursor class. This class is composed of CursorWarningMixInCursorStoreResultMixInCursorTupleRowsMixIn, and BaseCursor,
i.e. it raises Warning, usesmysql_store_result(), and returns rows as tuples.
DictCursor
Like Cursor except it returns rows as dictionaries.
SSCursor
A "server-side" cursor. Like Cursor but uses CursorUseResultMixIn.
Use only if you are dealing with potentially large result sets.
SSDictCursor
Like SSCursor except it returns rows as dictionaries.