Details
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Bug
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Status: Closed (View Workflow)
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Resolution: Fixed
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None
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None
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None
Description
I tested MariaDB 5.5.23 with sysbench.
And that time, Aborted_clients metric value is not much grew up.
But, After I applied MariaDB to production database,
Aborted_clients is growing up ever even though normal close of client side.
So, I tested same code with MySQL 5.5.23 community version. But it's okay.
And, MariaDB(with ThreadPool)'s memory usage is really stable under 2GB(Buffer pool is not including)
when I test with sysbench.
But in real service (java application), memory usage is growing up over 6~7GB(without BufferPool).
I'm not sure Aborted_clients metric is related with this memory usage.
Could you check this out ?
Thanks.
after test status----------------------------------------------------------------------------------
root@localhost:(none) 10:22:10>show global status like 'Aborted_clients';
----------------------+
Variable_name | Value |
----------------------+
Aborted_clients | 100 |
----------------------+
mysql> show global status like 'Aborted_clients';
----------------------+
Variable_name | Value |
----------------------+
Aborted_clients | 0 |
----------------------+
test code --------------------------------------------------------------------------------------------
public class AbortedClientsTester {
public static void main(String[] args) throws Exception {
Connection[] conns = new Connection[100];
for(int idx=0; idx<100; idx++)
{ conns[idx] = getConnection(); }Thread.sleep(1000*10);
for(int idx=0; idx<100; idx++)
{ conns[idx].close(); }}
protected static Connection getConnection() throws Exception
{ String driver = "com.mysql.jdbc.Driver"; String url = "jdbc:mysql://127.0.0.1:3306/sysbench"; String uid = "sysbench"; String pwd = "sysbench"; Class.forName(driver).newInstance(); Connection conn = DriverManager.getConnection(url, uid, pwd); return conn; }}
Re: Aborted_clients metric is growing up even though formal connection close
Hi,
Could you please provide the cnf file which you are using in production (where you observe the excessive memory consumption?
Thank you.