Partitioning isn't a bad idea for this however I'm still thinking about your dataset size and possible hardware limitations. It's not likely going to fit into relevant buffers/memory so you're going to be on disk more then you want. You're probably creating temporary tables like crazy and I would bet that there are a good load of them heading to disk too. With your IO performance limited to a small amount of disks as you describe, you're not going to be able to get much more from these queries. Although a dedicated DB server are there other databases been accessed on the server? When looking at the scope of your data, are you capturing more then you need? How often and how far back are the users querying? How many users concurrently performing queries on the 32m record table?
On Thu, Sep 8, 2011 at 8:04 PM, Brandon Phelps <bphe...@gls.com> wrote: > Mihail, > > I have considered this but have not yet determined how best to go about > partitioning the table. I don't think partitioning by dst_address or > src_address would help because most of the queries do not filter on IP > address (except very specific queries where the end-user is searching the > table for history on a particular employee). > > I could potentially partition the table based on the day of week the > connection was opened on which may improve performance for a while since > this would take me from a single 32million record table down to roughly 4.5 > million records per partition (32 / 7) however we are looking to eventually > store up to 2 months worth of data in the table, and so far that 32 million > records is only for 1 month, so I estimate another 32 million-ish before the > month is out, bringing me to roughly 70 million records total (it would be > nice if I could store even more than 2 months, but given my currently > performance dilemma I don't expect that to happen). Also this does not take > into account that the end-user will often be pulling data for multiple days > at a time, meaning that multiple partitions in this scheme will need to be > accessed anyway. > > The only other logical partitioning scheme I can think of would be to > partition based on dst_port (the port the log relates to) but the majority > of records are all to port 80 (standard web traffic) so I don't think this > would be all that helpful. > > I have never messed with partitioning so it is totally possible that I am > not thinking of something, so if you have any ideas on a decent partitioning > scheme based on my criteria and queries below, please let me know. > > Thanks, > Brandon > > > On 09/08/2011 02:47 PM, Mihail Manolov wrote: > >> If you're running version 5.1+ you may wanna take a look at table >> partitioning options you may have. >> >> On Sep 8, 2011, at 2:27 PM, Brandon Phelps wrote: >> >> Thanks for the reply Andy. Unfortunately the users will be selecting >>> varying date ranges and new data is constantly coming in, so I am not sure >>> how I could archive/cache the necessary data that would be any more >>> efficient than simply using the database directly. >>> >>> >>> On 09/08/2011 02:16 PM, Andrew Moore wrote: >>> >>>> Thinking outside the query, is there any archiving that could happen to >>>> make >>>> your large tables kinder in the range scan? >>>> >>>> Andy >>>> >>>> On Thu, Sep 8, 2011 at 7:03 PM, Brandon Phelps<bphe...@gls.com> >>>> wrote: >>>> >>>> On 09/01/2011 01:32 PM, Brandon Phelps wrote: >>>>> >>>>> On 09/01/2011 12:47 PM, Shawn Green (MySQL) wrote: >>>>>> >>>>>> On 9/1/2011 09:42, Brandon Phelps wrote: >>>>>>> >>>>>>> On 09/01/2011 04:59 AM, Jochem van Dieten wrote: >>>>>>>> >>>>>>>>> ... >>>>>>>>>> >>>>>>>>> >>>>>>>> WHERE >>>>>>>>>> (open_dt>= '2011-08-30 00:00:00' OR close_dt>= '2011-08-30 >>>>>>>>>> >>>>>>>>> 00:00:00') >>>>>>>> >>>>>>>>> AND (open_dt<= '2011-08-30 12:36:53' OR close_dt<= '2011-08-30 >>>>>>>>>> >>>>>>>>> 12:36:53') >>>>>>>> >>>>>>>> In that case your logic here simplifies to: >>>>>>>>> WHERE >>>>>>>>> open_dt>= '2011-08-30 00:00:00' >>>>>>>>> AND >>>>>>>>> close_dt<= '2011-08-30 12:36:53' >>>>>>>>> >>>>>>>> >>>>>>>> Now add an index over open_dt and close_dt and see what happens. >>>>>>>>> >>>>>>>> >>>>>>>> Jochem >>>>>>>>> >>>>>>>> >>>>>>>> Jochem, >>>>>>>> >>>>>>>> I can't really use your WHERE logic because I also need to retrieve >>>>>>>> results where the open_dt time is out of the range specified. For >>>>>>>> example, a very large file download might span multiple days so >>>>>>>> given >>>>>>>> your logic if the connection was started 2 days ago and I want to >>>>>>>> pull 1 >>>>>>>> days worth of connections, I would miss that entry. Basically I want >>>>>>>> to >>>>>>>> SELECT all of the records that were opened OR closed during the >>>>>>>> specified time period, ie. if any activity happened between my start >>>>>>>> and >>>>>>>> end dates, I need to see that record. >>>>>>>> >>>>>>>> Any other ideas? >>>>>>>> >>>>>>>> >>>>>>>> I believe Jochem was on the right track but he got his dates >>>>>>> reversed. >>>>>>> >>>>>>> Let's try a little ASCII art to show the situation. I will setup a >>>>>>> query >>>>>>> window with two markers (s) and (e). Events will be marked by |----| >>>>>>> markers >>>>>>> showing their durations. >>>>>>> >>>>>>> a) (s) (e) >>>>>>> b) |---| >>>>>>> c) |---| >>>>>>> d) |---| >>>>>>> e) |--------------------| >>>>>>> f) |---| >>>>>>> g) |---| >>>>>>> >>>>>>> To describe these situations: >>>>>>> a) is the window for which you want to query (s) is the starting time >>>>>>> and >>>>>>> (e) is the ending time for the date range you are interested in. >>>>>>> b) the event starts and stops before your window exists. It won't be >>>>>>> part >>>>>>> of your results. >>>>>>> c) the event starts before the window but ends within the window - >>>>>>> include this >>>>>>> d) the event starts and ends within the window - include this >>>>>>> e) the event starts before the window and ends after the window - >>>>>>> include >>>>>>> this >>>>>>> f) the event starts inside the window but ends beyond the window - >>>>>>> include this. >>>>>>> g) the event starts and ends beyond the window - exclude this. >>>>>>> >>>>>>> In order to get every event in the range of c-f, here is what you >>>>>>> need >>>>>>> for a WHERE clause >>>>>>> >>>>>>> WHERE start<= (ending time) and end>= (starting time) >>>>>>> >>>>>>> Try that and let us know the results. >>>>>>> >>>>>>> >>>>>> Thanks Jochem and Shawn, however the following two queries result in >>>>>> the >>>>>> exact same EXPLAIN output: (I hope the tables don't wrap too early for >>>>>> you) >>>>>> >>>>>> Old method: >>>>>> SELECT >>>>>> sc.open_dt, >>>>>> sc.close_dt, >>>>>> sc.protocol, >>>>>> INET_NTOA(sc.src_address) AS src_address, >>>>>> sc.src_port, >>>>>> INET_NTOA(sc.dst_address) AS dst_address, >>>>>> sc.dst_port, >>>>>> sc.sent, >>>>>> sc.rcvd, >>>>>> spm.desc AS src_port_desc, >>>>>> dpm.desc AS dst_port_desc >>>>>> FROM firewall_connections AS sc >>>>>> LEFT JOIN port_mappings AS spm ON spm.port = sc.src_port >>>>>> LEFT JOIN port_mappings AS dpm ON dpm.port = sc.dst_port >>>>>> WHERE >>>>>> (open_dt>= '2011-08-31 09:53:31' OR close_dt>= '2011-08-31 09:53:31') >>>>>> AND (open_dt<= '2011-09-01 09:53:31' OR close_dt<= '2011-09-01 >>>>>> 09:53:31') >>>>>> ORDER BY rcvd DESC >>>>>> LIMIT 0, 10; >>>>>> >>>>>> New method with BTREE index on open_dt, close_dt (index name is >>>>>> ndx_open_close_dt): >>>>>> SELECT >>>>>> sc.open_dt, >>>>>> sc.close_dt, >>>>>> sc.protocol, >>>>>> INET_NTOA(sc.src_address) AS src_address, >>>>>> sc.src_port, >>>>>> INET_NTOA(sc.dst_address) AS dst_address, >>>>>> sc.dst_port, >>>>>> sc.sent, >>>>>> sc.rcvd, >>>>>> spm.desc AS src_port_desc, >>>>>> dpm.desc AS dst_port_desc >>>>>> FROM firewall_connections AS sc >>>>>> LEFT JOIN port_mappings AS spm ON spm.port = sc.src_port >>>>>> LEFT JOIN port_mappings AS dpm ON dpm.port = sc.dst_port >>>>>> WHERE >>>>>> open_dt<= '2011-09-01 09:53:31' AND close_dt>= '2011-08-31 09:53:31' >>>>>> ORDER BY rcvd DESC >>>>>> LIMIT 0, 10; >>>>>> >>>>>> EXPLAIN output for old method: >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> | id | select_type | table | type | possible_keys | key | key_len | >>>>>> ref | >>>>>> rows | Extra | >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> | 1 | SIMPLE | sc | index | open_dt,ndx_open_close_dt | ndx_rcvd | 4 | >>>>>> NULL | 10 | Using where | >>>>>> | 1 | SIMPLE | spm | eq_ref | PRIMARY | PRIMARY | 2 | >>>>>> syslog.sc.src_port | >>>>>> 1 | | >>>>>> | 1 | SIMPLE | dpm | eq_ref | PRIMARY | PRIMARY | 2 | >>>>>> syslog.sc.dst_port | >>>>>> 1 | | >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> >>>>>> EXPLAIN output for new method with new index: >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> | id | select_type | table | type | possible_keys | key | key_len | >>>>>> ref | >>>>>> rows | Extra | >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> | 1 | SIMPLE | sc | index | open_dt,ndx_open_close_dt | ndx_rcvd | 4 | >>>>>> NULL | 10 | Using where | >>>>>> | 1 | SIMPLE | spm | eq_ref | PRIMARY | PRIMARY | 2 | >>>>>> syslog.sc.src_port | >>>>>> 1 | | >>>>>> | 1 | SIMPLE | dpm | eq_ref | PRIMARY | PRIMARY | 2 | >>>>>> syslog.sc.dst_port | >>>>>> 1 | | >>>>>> +----+-------------+-------+--****------+---------------------**--** >>>>>> ----+----------+---------+----****----------------+------+----** >>>>>> --**-------+ >>>>>> >>>>>> SHOW INDEX: >>>>>> +----------------------+------****------+-------------------+-**--** >>>>>> -----------+-------------+----****-------+-------------+------**--** >>>>>> --+--------+------+-----------****-+---------+ >>>>>> | Table | Non_unique | Key_name | Seq_in_index | Column_name | >>>>>> Collation | >>>>>> Cardinality | Sub_part | Packed | Null | Index_type | Comment | >>>>>> +----------------------+------****------+-------------------+-**--** >>>>>> -----------+-------------+----****-------+-------------+------**--** >>>>>> --+--------+------+-----------****-+---------+ >>>>>> | firewall_connections | 1 | ndx_open_close_dt | 1 | open_dt | A | >>>>>> 1342691 >>>>>> | NULL | NULL | | BTREE | | >>>>>> | firewall_connections | 1 | ndx_open_close_dt | 2 | close_dt | A | >>>>>> 6377783 | NULL | NULL | | BTREE | | >>>>>> +----------------------+------****------+-------------------+-**--** >>>>>> -----------+-------------+----****-------+-------------+------**--** >>>>>> --+--------+------+-----------****-+---------+ >>>>>> >>>>>> >>>>>> Although right now the queries do seem to be executing much faster, >>>>>> although I'm not quite sure why. And I'm not sure why the new >>>>>> ndx_open_close_dt isn't being used either. >>>>>> >>>>>> -Brandon >>>>>> >>>>>> >>>>>> I am still having a big issue with my query as seen above. The table >>>>> is up >>>>> to around 32 million records at the moment and either of the two SELECT >>>>> queries above take a very long time to run. Is there anything at all I >>>>> can >>>>> do to speed things up? It seems that changing the format of the WHERE >>>>> clause did not help at all, as the EXPLAIN output is exactly the same >>>>> for >>>>> both version. I also tried adding an index on (open_dt, close_dt, >>>>> rcvd) but >>>>> that index does not get used. >>>>> >>>>> Any other ideas? >>>>> >>>>> Thanks in advance, >>>>> >>>>> >>>>> Brandon >>>>> >>>>> -- >>>>> MySQL General Mailing List >>>>> For list archives: http://lists.mysql.com/mysql >>>>> To unsubscribe: >>>>> http://lists.mysql.com/mysql?****<http://lists.mysql.com/mysql?**> >>>>> unsub=eroomy...@gmail.com<http**://lists.mysql.com/mysql?** >>>>> unsub=eroomy...@gmail.com<http://lists.mysql.com/mysql?unsub=eroomy...@gmail.com> >>>>> > >>>>> >>>>> >>>>> >>>> >>> -- >>> MySQL General Mailing List >>> For list archives: http://lists.mysql.com/mysql >>> To unsubscribe: http://lists.mysql.com/mysql?** >>> unsub=mmano...@liquidation.com<http://lists.mysql.com/mysql?unsub=mmano...@liquidation.com> >>> >>> >> >> > -- > MySQL General Mailing List > For list archives: http://lists.mysql.com/mysql > To unsubscribe: http://lists.mysql.com/mysql?** > unsub=eroomy...@gmail.com<http://lists.mysql.com/mysql?unsub=eroomy...@gmail.com> > >
