Andrew,
Generally there is only 1 user performing the complicated SELECT query at a time, however
the background process that fills the table is constantly doing a fast SELECT (0.00003
seconds) and a subsequent UPDATE. Basically whenever a connection is closed on the
firewall, the bg process SELECTS from the table the last record that was opened (and
hasn't already been closed) for a given source IP, source port, dest ip, and protocol.
So for example whenever the firewall logs a "CONNECTION CLOSED" message, the bg
process does:
select id from sonicwall_connections where src_address = w.x.y.z and src_port =
x and dst_address = w.x.y.z and protocol = x ORDER BY open_dt LIMIT 0, 1
then it UPDATES the close_dt column for the record with the selected ID. These
select/update statements being run by the background process generally take
0.000x seconds each.
The only slowdown we see is with the complicated SELECT I have below, and this
is only executed once in a while throughout the day. For example, if an IT
manager sees a huge bandwidth spike on the network, he may access the web gui
to determine what the source IP is so he can determine who is downloading a
large file, etc.
I think what I will try to do is create 60 partitions for the table in question
based on month and day. This way each day will go into it's own partition and
if someone runs the query for a date range such as 01/01/2011 - 01/07/2011 it
will only need to access 7 partitions instead of the entire table.
My only question with this is how would I go about creating the table with 60
partitions in such a way that I won't need to constantly add/remove new/old
partitions every day? Is there any partitioning function I can use that would
not require me to update the partitions schema every day? I already plan to
have a cron run each night to purge records older than 60 days from the
database.
On 09/08/2011 03:26 PM, Andrew Moore wrote:
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
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