Hi again,

> What can I do to analyze/fix this?

would it be possible/reasonable to clean up all the "accurate mode"
information and start from zero? If yes, how can I do this?
Unfortunately I'm not that much experienced with mySQL databases...

Thanks for your support and many greets
Stephan


Am 25.02.2018 um 00:49 schrieb Stephan Hermann:
> Hi,
> 
> it seems that I run into this issue, too.
> I just upgraded from 16.2.7 to 17.2.5 (from subscription repo) and
> updated the database scheme from 2004 to 2171.
> 
> Since then incremental backups with a lot of files hang at 'Sending
> Accurate information.' There is one mysql process at 100% cpu, but I
> can't see any relevant disk activity (iotop -o).
> 
> Killing the queries inside mySQL allow me to continue the jobs, but the
> result looks like a full job, not an incremental.
> 
> Some outputs:
> 
> mysql> analyze table File;
> +-------------+---------+----------+----------+
> | Table       | Op      | Msg_type | Msg_text |
> +-------------+---------+----------+----------+
> | bareos.File | analyze | status   | OK       |
> +-------------+---------+----------+----------+
> 1 row in set (0.04 sec)
> 
> mysql> optimize table File;
> +-------------+----------+----------+-------------------------------------------------------------------+
> | Table       | Op       | Msg_type | Msg_text
>                                |
> +-------------+----------+----------+-------------------------------------------------------------------+
> | bareos.File | optimize | note     | Table does not support optimize,
> doing recreate + analyze instead |
> | bareos.File | optimize | status   | OK
>                                |
> +-------------+----------+----------+-------------------------------------------------------------------+
> 2 rows in set (4 min 35.79 sec)
> 
> What can I do to analyze/fix this?
> 
> Thanks a lot and many greets
> Stephan
> 
> 
> Am 23.01.2018 um 22:26 schrieb Stephan Duehr:
>> Hi,
>>
>> that looks like the query being run for accurate backup.
>> I wonder why it's slower after the upgrade, as it's one table less for the 
>> join.
>> This kind of problem with accurate has also been seen with the Bareos 16.2 
>> DB schema
>> in MySQL.
>>
>> Please check if the indexes on the File table match the ones defined in
>> /usr/lib/bareos/scripts/ddl/creates/mysql.sql
>>
>> May be do
>> ANALYZE TABLE File;
>> in mysql again.
>>
>> If that does not help, disabling accurate for that job meanwhile may be 
>> better
>> than killing the query.
>>
>> Regards,
>>
>> Stephan
>>
>> On 01/22/2018 02:30 PM, [email protected] wrote:
>>> Hi, After the upgrade to 17.2.4 (21 Sep 2017) I noticed the following sql 
>>> query:
>>>
>>> SELECT Path.Path, T1.Name, T1.FileIndex, T1.JobId, LStat, DeltaSeq , 
>>> Fhinfo, Fhnode FROM ( SELECT FileId, Job.JobId AS JobId, FileIndex, 
>>> File.PathId AS PathId, File.Name AS Name, LStat , DeltaSeq, Fhinfo, Fhnode, 
>>> Job.JobTDate AS JobTDate FROM Job, File, (SELECT MAX(JobTDate) AS JobTDate, 
>>> PathId, FileName FROM (SELECT JobTDate, PathId, File.Name AS FileName FROM 
>>> File JOIN Job USING (JobId) WHERE File.JobId IN 
>>> (2897,2941,2963,3005,3023,3041) UNION ALL SELECT JobTDate, PathId, 
>>> File.Name AS FileName FROM BaseFiles JOIN File USING (FileId) JOIN Job ON 
>>> (BaseJobId = Job.JobId) WHERE BaseFiles.JobId IN 
>>> (2897,2941,2963,3005,3023,3041) ) AS tmp GROUP BY PathId, FileName) AS T1 
>>> WHERE (Job.JobId IN (SELECT DISTINCT BaseJobId FROM BaseFiles WHERE JobId 
>>> IN (2897,2941,2963,3005,3023,3041)) OR Job.JobId IN 
>>> (2897,2941,2963,3005,3023,3041)) AND T1.JobTDate = Job.JobTDate AND 
>>> Job.JobId = File.JobId AND T1.PathId = File.PathId AND T1.FileName = 
>>> File.Name ) AS T1 JOIN Path ON (Path.PathId = T1.PathId) WHERE FileIndex > 
>>> 0 ORDER BY T1.JobTDate, FileIndex ASC
>>>
>>> This query is taking a very long time to complete. Now it's been running 
>>> over 13 hours and it is still running and taking 100% CPU.
>>>
>>> I'm using mysql 5.5, and the schema was upgraded when upgrading from 16.2 
>>> to 17.2.
>>>
>>> For the last few days I had to kill the queries, but it would be great to 
>>> have this fixed.
>>>
>>> Any idea what is wrong here ?
>>>
>>> Thank you.
>>>
>>
> 

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