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  • Coherence Query Performance in Large Clusters

    - by jpurdy
    Large clusters (measured in terms of the number of storage-enabled members participating in the largest cache services) may introduce challenges when issuing queries. There is no particular cluster size threshold for this, rather a gradually increasing tendency for issues to arise. The most obvious challenges are that a client's perceived query latency will be determined by the slowest responder (more likely to be a factor in larger clusters) as well as the fact that adding additional cache servers will not increase query throughput if the query processing is not compute-bound (which would generally be the case for most indexed queries). If the data set can take advantage of the partition affinity features of Coherence, then the application can use a PartitionedFilter to target a query to a single server (using partition affinity to ensure that all data is in a single partition). If this can not be done, then avoiding an excessive number of cache server JVMs will help, as will ensuring that each cache server has sufficient CPU resources available and is also properly configured to minimize GC pauses (the most common cause of a slow-responding cache server).

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  • Temenos WealthManager: performance benchmark on Exadata

    - by Javier Puerta
    Temenos WealthManager is at work in financial institutions of all sizes. No matter the size, each of Temenos’ customers has one requirement in common: a need for fast technology. This led Temenos to conduct a performance benchmark, running its WealthManager platform on Oracle Exadata Database Machine. During the study, Temenos executed high-intensity financial engines two- to three-times faster than its previous internal benchmarks and/or largest customer throughput. The company also demonstrated greater than two-times the average improvement in response times for six-times the number of users and data volumes. Further, Temenos secured a two-times gain in service-level agreements for batch and user-oriented workloads via dedicated or parallelized processing windows. Last year Temenos also communicated the availability of its T24 core banking system and how the benchmark run demonstrated the ability of Oracle’s Exadata platform to comfortably support the highest banking volumes for T24. Read full story here  

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  • How to prioritize tasks when you have multiple programming projects running in parallel?

    - by Vinko Vrsalovic
    Say you have 5 customers, you develop 2 or 3 different projects for each. Each project has Xi tasks. Each project takes from 2 to 10 man weeks. Given that there are few resources, it is desired to minimize the management overhead. Two questions in this scenario: What tools would you use to prioritize the tasks and track their completion, while tending to minimize the overhead? What criteria would you take into consideration to determine which task to assign to the next available resource given that the primary objective is to increase throughput (more projects finished per time unit, this objective conflicts with starting one project and finishing it and then moving on to the next)? Ideas, management techniques, algorithms are welcome

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  • nicstat update - version 1.92

    - by user12608033
    Another minor nicstat release is now available. Changes for Version 1.92, October 2012 Common Added "-M" option to change throughput statistics to Mbps (Megabits per second). Suggestion from Darren Todd. Fixed bugs with printing extended parseable format (-xp) Fixed man page's description of extended parseable output. Solaris Fixed memory leak associated with g_getif_list Add 2nd argument to dladm_open() for Solaris 11.1 Modify nicstat.sh to handle Solaris 11.1 Linux Modify nicstat.sh to see "x86_64" cputype as "i386". All Linux binaries are built as 32-bit, so we do not need to differentiate these two cpu types. Availability nicstat source and binaries are available from sourceforge. History For more history on nicstat, see my earlier entry

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  • Bacula & Multiple Tape Devices, and so on

    - by Tom O'Connor
    Bacula won't make use of 2 tape devices simultaneously. (Search for #-#-# for the TL;DR) A little background, perhaps. In the process of trying to get a decent working backup solution (backing up 20TB ain't cheap, or easy) at $dayjob, we bought a bunch of things to make it work. Firstly, there's a Spectra Logic T50e autochanger, 40 slots of LTO5 goodness, and that robot's got a pair of IBM HH5 Ultrium LTO5 drives, connected via FibreChannel Arbitrated Loop to our backup server. There's the backup server.. A Dell R715 with 2x 16 core AMD 62xx CPUs, and 32GB of RAM. Yummy. That server's got 2 Emulex FCe-12000E cards, and an Intel X520-SR dual port 10GE NIC. We were also sold Commvault Backup (non-NDMP). Here's where it gets really complicated. Spectra Logic and Commvault both sent respective engineers, who set up the library and the software. Commvault was running fine, in so far as the controller was working fine. The Dell server has Ubuntu 12.04 server, and runs the MediaAgent for CommVault, and mounts our BlueArc NAS as NFS to a few mountpoints, like /home, and some stuff in /mnt. When backing up from the NFS mountpoints, we were seeing ~= 290GB/hr throughput. That's CRAP, considering we've got 20-odd TB to get through, in a <48 hour backup window. The rated maximum on the BlueArc is 700MB/s (2460GB/hr), the rated maximum write speed on the tape devices is 140MB/s, per drive, so that's 492GB/hr (or double it, for the total throughput). So, the next step was to benchmark NFS performance with IOzone, and it turns out that we get epic write performance (across 20 threads), and it's like 1.5-2.5TB/hr write, but read performance is fecking hopeless. I couldn't ever get higher than 343GB/hr maximum. So let's assume that the 343GB/hr is a theoretical maximum for read performance on the NAS, then we should in theory be able to get that performance out of a) CommVault, and b) any other backup agent. Not the case. Commvault seems to only ever give me 200-250GB/hr throughput, and out of experimentation, I installed Bacula to see what the state of play there is. If, for example, Bacula gave consistently better performance and speeds than Commvault, then we'd be able to say "**$.$ Refunds Plz $.$**" #-#-# Alas, I found a different problem with Bacula. Commvault seems pretty happy to read from one part of the mountpoint with one thread, and stream that to a Tape device, whilst reading from some other directory with the other thread, and writing to the 2nd drive in the autochanger. I can't for the life of me get Bacula to mount and write to two tape drives simultaneously. Things I've tried: Setting Maximum Concurrent Jobs = 20 in the Director, File and Storage Daemons Setting Prefer Mounted Volumes = no in the Job Definition Setting multiple devices in the Autochanger resource. Documentation seems to be very single-drive centric, and we feel a little like we've strapped a rocket to a hamster, with this one. The majority of example Bacula configurations are for DDS4 drives, manual tape swapping, and FreeBSD or IRIX systems. I should probably add that I'm not too bothered if this isn't possible, but I'd be surprised. I basically want to use Bacula as proof to stick it to the software vendors that they're overpriced ;) I read somewhere that @KyleBrandt has done something similar with a modern Tape solution.. Configuration Files: *bacula-dir.conf* # # Default Bacula Director Configuration file Director { # define myself Name = backuphost-1-dir DIRport = 9101 # where we listen for UA connections QueryFile = "/etc/bacula/scripts/query.sql" WorkingDirectory = "/var/lib/bacula" PidDirectory = "/var/run/bacula" Maximum Concurrent Jobs = 20 Password = "yourekiddingright" # Console password Messages = Daemon DirAddress = 0.0.0.0 #DirAddress = 127.0.0.1 } JobDefs { Name = "DefaultFileJob" Type = Backup Level = Incremental Client = backuphost-1-fd FileSet = "Full Set" Schedule = "WeeklyCycle" Storage = File Messages = Standard Pool = File Priority = 10 Write Bootstrap = "/var/lib/bacula/%c.bsr" } JobDefs { Name = "DefaultTapeJob" Type = Backup Level = Incremental Client = backuphost-1-fd FileSet = "Full Set" Schedule = "WeeklyCycle" Storage = "SpectraLogic" Messages = Standard Pool = AllTapes Priority = 10 Write Bootstrap = "/var/lib/bacula/%c.bsr" Prefer Mounted Volumes = no } # # Define the main nightly save backup job # By default, this job will back up to disk in /nonexistant/path/to/file/archive/dir Job { Name = "BackupClient1" JobDefs = "DefaultFileJob" } Job { Name = "BackupThisVolume" JobDefs = "DefaultTapeJob" FileSet = "SpecialVolume" } #Job { # Name = "BackupClient2" # Client = backuphost-12-fd # JobDefs = "DefaultJob" #} # Backup the catalog database (after the nightly save) Job { Name = "BackupCatalog" JobDefs = "DefaultFileJob" Level = Full FileSet="Catalog" Schedule = "WeeklyCycleAfterBackup" # This creates an ASCII copy of the catalog # Arguments to make_catalog_backup.pl are: # make_catalog_backup.pl <catalog-name> RunBeforeJob = "/etc/bacula/scripts/make_catalog_backup.pl MyCatalog" # This deletes the copy of the catalog RunAfterJob = "/etc/bacula/scripts/delete_catalog_backup" Write Bootstrap = "/var/lib/bacula/%n.bsr" Priority = 11 # run after main backup } # # Standard Restore template, to be changed by Console program # Only one such job is needed for all Jobs/Clients/Storage ... # Job { Name = "RestoreFiles" Type = Restore Client=backuphost-1-fd FileSet="Full Set" Storage = File Pool = Default Messages = Standard Where = /srv/bacula/restore } FileSet { Name = "SpecialVolume" Include { Options { signature = MD5 } File = /mnt/SpecialVolume } Exclude { File = /var/lib/bacula File = /nonexistant/path/to/file/archive/dir File = /proc File = /tmp File = /.journal File = /.fsck } } # List of files to be backed up FileSet { Name = "Full Set" Include { Options { signature = MD5 } File = /usr/sbin } Exclude { File = /var/lib/bacula File = /nonexistant/path/to/file/archive/dir File = /proc File = /tmp File = /.journal File = /.fsck } } Schedule { Name = "WeeklyCycle" Run = Full 1st sun at 23:05 Run = Differential 2nd-5th sun at 23:05 Run = Incremental mon-sat at 23:05 } # This schedule does the catalog. It starts after the WeeklyCycle Schedule { Name = "WeeklyCycleAfterBackup" Run = Full sun-sat at 23:10 } # This is the backup of the catalog FileSet { Name = "Catalog" Include { Options { signature = MD5 } File = "/var/lib/bacula/bacula.sql" } } # Client (File Services) to backup Client { Name = backuphost-1-fd Address = localhost FDPort = 9102 Catalog = MyCatalog Password = "surelyyourejoking" # password for FileDaemon File Retention = 30 days # 30 days Job Retention = 6 months # six months AutoPrune = yes # Prune expired Jobs/Files } # # Second Client (File Services) to backup # You should change Name, Address, and Password before using # #Client { # Name = backuphost-12-fd # Address = localhost2 # FDPort = 9102 # Catalog = MyCatalog # Password = "i'mnotjokinganddontcallmeshirley" # password for FileDaemon 2 # File Retention = 30 days # 30 days # Job Retention = 6 months # six months # AutoPrune = yes # Prune expired Jobs/Files #} # Definition of file storage device Storage { Name = File # Do not use "localhost" here Address = localhost # N.B. Use a fully qualified name here SDPort = 9103 Password = "lalalalala" Device = FileStorage Media Type = File } Storage { Name = "SpectraLogic" Address = localhost SDPort = 9103 Password = "linkedinmakethebestpasswords" Device = Drive-1 Device = Drive-2 Media Type = LTO5 Autochanger = yes } # Generic catalog service Catalog { Name = MyCatalog # Uncomment the following line if you want the dbi driver # dbdriver = "dbi:sqlite3"; dbaddress = 127.0.0.1; dbport = dbname = "bacula"; DB Address = ""; dbuser = "bacula"; dbpassword = "bbmaster63" } # Reasonable message delivery -- send most everything to email address # and to the console Messages { Name = Standard mailcommand = "/usr/lib/bacula/bsmtp -h localhost -f \"\(Bacula\) \<%r\>\" -s \"Bacula: %t %e of %c %l\" %r" operatorcommand = "/usr/lib/bacula/bsmtp -h localhost -f \"\(Bacula\) \<%r\>\" -s \"Bacula: Intervention needed for %j\" %r" mail = root@localhost = all, !skipped operator = root@localhost = mount console = all, !skipped, !saved # # WARNING! the following will create a file that you must cycle from # time to time as it will grow indefinitely. However, it will # also keep all your messages if they scroll off the console. # append = "/var/lib/bacula/log" = all, !skipped catalog = all } # # Message delivery for daemon messages (no job). Messages { Name = Daemon mailcommand = "/usr/lib/bacula/bsmtp -h localhost -f \"\(Bacula\) \<%r\>\" -s \"Bacula daemon message\" %r" mail = root@localhost = all, !skipped console = all, !skipped, !saved append = "/var/lib/bacula/log" = all, !skipped } # Default pool definition Pool { Name = Default Pool Type = Backup Recycle = yes # Bacula can automatically recycle Volumes AutoPrune = yes # Prune expired volumes Volume Retention = 365 days # one year } # File Pool definition Pool { Name = File Pool Type = Backup Recycle = yes # Bacula can automatically recycle Volumes AutoPrune = yes # Prune expired volumes Volume Retention = 365 days # one year Maximum Volume Bytes = 50G # Limit Volume size to something reasonable Maximum Volumes = 100 # Limit number of Volumes in Pool } Pool { Name = AllTapes Pool Type = Backup Recycle = yes AutoPrune = yes # Prune expired volumes Volume Retention = 31 days # one Moth } # Scratch pool definition Pool { Name = Scratch Pool Type = Backup } # # Restricted console used by tray-monitor to get the status of the director # Console { Name = backuphost-1-mon Password = "LastFMalsostorePasswordsLikeThis" CommandACL = status, .status } bacula-sd.conf # # Default Bacula Storage Daemon Configuration file # Storage { # definition of myself Name = backuphost-1-sd SDPort = 9103 # Director's port WorkingDirectory = "/var/lib/bacula" Pid Directory = "/var/run/bacula" Maximum Concurrent Jobs = 20 SDAddress = 0.0.0.0 # SDAddress = 127.0.0.1 } # # List Directors who are permitted to contact Storage daemon # Director { Name = backuphost-1-dir Password = "passwordslinplaintext" } # # Restricted Director, used by tray-monitor to get the # status of the storage daemon # Director { Name = backuphost-1-mon Password = "totalinsecurityabound" Monitor = yes } Device { Name = FileStorage Media Type = File Archive Device = /srv/bacula/archive LabelMedia = yes; # lets Bacula label unlabeled media Random Access = Yes; AutomaticMount = yes; # when device opened, read it RemovableMedia = no; AlwaysOpen = no; } Autochanger { Name = SpectraLogic Device = Drive-1 Device = Drive-2 Changer Command = "/etc/bacula/scripts/mtx-changer %c %o %S %a %d" Changer Device = /dev/sg4 } Device { Name = Drive-1 Drive Index = 0 Archive Device = /dev/nst0 Changer Device = /dev/sg4 Media Type = LTO5 AutoChanger = yes RemovableMedia = yes; AutomaticMount = yes; AlwaysOpen = yes; RandomAccess = no; LabelMedia = yes } Device { Name = Drive-2 Drive Index = 1 Archive Device = /dev/nst1 Changer Device = /dev/sg4 Media Type = LTO5 AutoChanger = yes RemovableMedia = yes; AutomaticMount = yes; AlwaysOpen = yes; RandomAccess = no; LabelMedia = yes } # # Send all messages to the Director, # mount messages also are sent to the email address # Messages { Name = Standard director = backuphost-1-dir = all } bacula-fd.conf # # Default Bacula File Daemon Configuration file # # # List Directors who are permitted to contact this File daemon # Director { Name = backuphost-1-dir Password = "hahahahahaha" } # # Restricted Director, used by tray-monitor to get the # status of the file daemon # Director { Name = backuphost-1-mon Password = "hohohohohho" Monitor = yes } # # "Global" File daemon configuration specifications # FileDaemon { # this is me Name = backuphost-1-fd FDport = 9102 # where we listen for the director WorkingDirectory = /var/lib/bacula Pid Directory = /var/run/bacula Maximum Concurrent Jobs = 20 #FDAddress = 127.0.0.1 FDAddress = 0.0.0.0 } # Send all messages except skipped files back to Director Messages { Name = Standard director = backuphost-1-dir = all, !skipped, !restored }

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  • Trying to run multiple HTTP requests in parallel, but being limited by Windows (registry)

    - by Nailuj
    I'm developing an application (winforms C# .NET 4.0) where I access a lookup functionality from a 3rd party through a simple HTTP request. I call an url with a parameter, and in return I get a small string with the result of the lookup. Simple enough. The challenge is however, that I have to do lots of these lookups (a couple of thousands), and I would like to limit the time needed. Therefore I would like to run requests in parallel (say 10-20). I use a ThreadPool to do this, and the short version of my code looks like this: public void startAsyncLookup(Action<LookupResult> returnLookupResult) { this.returnLookupResult = returnLookupResult; foreach (string number in numbersToLookup) { ThreadPool.QueueUserWorkItem(lookupNumber, number); } } public void lookupNumber(Object threadContext) { string numberToLookup = (string)threadContext; string url = @"http://some.url.com/?number=" + numberToLookup; WebClient webClient = new WebClient(); Stream responseData = webClient.OpenRead(url); LookupResult lookupResult = parseLookupResult(responseData); returnLookupResult(lookupResult); } I fill up numbersToLookup (a List<String>) from another place, call startAsyncLookup and provide it with a call-back function returnLookupResult to return each result. This works, but I found that I'm not getting the throughput I want. Initially I thought it might be the 3rd party having a poor system on their end, but I excluded this by trying to run the same code from two different machines at the same time. Each of the two took as long as one did alone, so I could rule out that one. A colleague then tipped me that this might be a limitation in Windows. I googled a bit, and found amongst others this post saying that by default Windows limits the number of simultaneous request to the same web server to 4 for HTTP 1.0 and to 2 for HTTP 1.1 (for HTTP 1.1 this is actually according to the specification (RFC2068)). The same post referred to above also provided a way to increase these limits. By adding two registry values to [HKEY_CURRENT_USER\Software\Microsoft\Windows\CurrentVersion\Internet Settings] (MaxConnectionsPerServer and MaxConnectionsPer1_0Server), I could control this myself. So, I tried this (sat both to 20), restarted my computer, and tried to run my program again. Sadly though, it didn't seem to help any. I also kept an eye on the Resource Monitor (see screen shot) while running my batch lookup, and I noticed that my application (the one with the title blacked out) still only was using two TCP connections. So, the question is, why isn't this working? Is the post I linked to using the wrong registry values? Is this perhaps not possible to "hack" in Windows any longer (I'm on Windows 7)? Any ideas would be highly appreciated :) And just in case anyone should wonder, I have also tried with different settings for MaxThreads on ThreadPool (everyting from 10 to 100), and this didn't seem to affect my throughput at all, so the problem shouldn't be there either.

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  • Wireless AAA for a small, bandwidth-limited hotel.

    - by Anthony Hiscox
    We (the tech I work with and myself) live in a remote northern town where Internet access is somewhat of a luxury, and bandwidth is quite limited. Here, overage charges ranging from few hundreds, to few thousands of dollars a month, is not uncommon. I myself incur regular monthly charges just through my regular Internet usage at home (I am allowed 10G for $60CAD!) As part of my work, I have found myself involved with several hotels that are feeling this. I know that I can come up with something to solve this problem, but I am relatively new to system administration and I don't want my dreams to overcome reality. So, I pass these ideas on to you, those with much more experience than I, in hopes you will share some of your thoughts and concerns. This system must be cost effective, yes the charges are high here, but the trust in technology is the lowest I've ever seen. Must be capable of helping client reduce their usage (squid) Allow a limited (throughput and total usage) amount of free Internet, as this is often franchise policy. Allow a user to track their bandwidth usage Allow (optional) higher speed and/or usage for an additional charge. This fee can be obtained at the front desk on checkout and should not require the use of PayPal or Credit Card. Unfortunately some franchises have ridiculous policies that require the use of a third party remote service to authenticate guests to your network. This means WPA is out, and it also means that I do not auth before Internet usage, that will be their job. However, I do require the ABILITY to perform authentication for Internet access if a hotel does not have this policy. I will still have to track bandwidth (under a guest account by default) and provide the same limiting, however the guest often will require a complete 'unlimited' access, in terms of existence, not throughput. Provide firewalling capabilities for hotels that have nothing, Office, and Guest network segregation (some of these guys are running their office on the guest network, with no encryption, and a simple TOS to get on!) Prevent guests from connecting to other guests, however provide a means to allow this to happen. IE. Each guest connects to a page and allows the other guest, this writes a iptables rule (with python-netfilter) and allows two rooms to play a game, for instance. My thoughts on how to implement this. One decent box (we'll call it a router now) with a lot of ram, and 3 NIC's: Internet Office Guests (AP's + In Room Ethernet) Router Firewall Rules Guest can talk to router only, through which they are routed to where they need to go, including Internet services. Office can be used to bridge Office to Internet if an existing solution is not in place, otherwise, it simply works for a network accessible web (webmin+python-webmin?) interface. Router Software: OpenVZ provides virtualization for a few services I don't really trust. Squid, FreeRADIUS and Apache. The only service directly accessible to guests is Apache. Apache has mod_wsgi and django, because I can write quickly using django and my needs are low. It also potentially has the FreeRADIUS mod, but there seems to be some caveats with this. Firewall rules are handled on the router with iptables. Webmin (or a custom django app maybe) provides abstracted control over any features that the staff may need to access. Python, if you haven't guessed it's the language I feel most comfortable in, and I use it for almost everything. And finally, has this been done, is it a overly massive project not worth taking on for one guy, and/or is there some tools I'm missing that could be making my life easier? For the record, I am fairly good with Python, but not very familiar with many other languages (I can struggle through PHP, it's a cosmetic issue there). I am also an avid linux user, and comfortable with config files and command line. Thank you for your time, I look forward to reading your responses. Edit: My apologies if this is not a Q&A in the sense that some were expecting, I'm just looking for ideas and to make sure I'm not trying to do something that's been done. I'm looking at pfSense now as a possible start for what I need.

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  • Fragmented Log files could be slowing down your database

    - by Fatherjack
    Something that is sometimes forgotten by a lot of DBAs is the fact that database log files get fragmented in the same way that you get fragmentation in a data file. The cause is very different but the effect is the same – too much effort reading and writing data. Data files get fragmented as data is changed through normal system activity, INSERTs, UPDATEs and DELETEs cause fragmentation and most experienced DBAs are monitoring their indexes for fragmentation and dealing with it accordingly. However, you don’t hear about so many working on their log files. How can a log file get fragmented? I’m glad you asked. When you create a database there are at least two files created on the disk storage; an mdf for the data and an ldf for the log file (you can also have ndf files for extra data storage but that’s off topic for now). It is wholly possible to have more than one log file but in most cases there is little point in creating more than one as the log file is written to in a ‘wrap-around’ method (more on that later). When a log file is created at the time that a database is created the file is actually sub divided into a number of virtual log files (VLFs). The number and size of these VLFs depends on the size chosen for the log file. VLFs are also created in the space added to a log file when a log file growth event takes place. Do you have your log files set to auto grow? Then you have potentially been introducing many VLFs into your log file. Let’s get to see how many VLFs we have in a brand new database. USE master GO CREATE DATABASE VLF_Test ON ( NAME = VLF_Test, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test.mdf', SIZE = 100, MAXSIZE = 500, FILEGROWTH = 50 ) LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 5MB, MAXSIZE = 250MB, FILEGROWTH = 5MB ); go USE VLF_Test go DBCC LOGINFO; The results of this are firstly a new database is created with specified files sizes and the the DBCC LOGINFO results are returned to the script editor. The DBCC LOGINFO results have plenty of interesting information in them but lets first note there are 4 rows of information, this relates to the fact that 4 VLFs have been created in the log file. The values in the FileSize column are the sizes of each VLF in bytes, you will see that the last one to be created is slightly larger than the others. So, a 5MB log file has 4 VLFs of roughly 1.25 MB. Lets alter the CREATE DATABASE script to create a log file that’s a bit bigger and see what happens. Alter the code above so that the log file details are replaced by LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 1GB, MAXSIZE = 25GB, FILEGROWTH = 1GB ); With a bigger log file specified we get more VLFs What if we make it bigger again? LOG ON ( NAME = VLF_Test_Log, FILENAME = 'C:\Program Files\Microsoft SQL Server\MSSQL10.ROCK_2008\MSSQL\DATA\VLF_Test_log.ldf', SIZE = 5GB, MAXSIZE = 250GB, FILEGROWTH = 5GB ); This time we see more VLFs are created within our log file. We now have our 5GB log file comprised of 16 files of 320MB each. In fact these sizes fall into all the ranges that control the VLF creation criteria – what a coincidence! The rules that are followed when a log file is created or has it’s size increased are pretty basic. If the file growth is lower than 64MB then 4 VLFs are created If the growth is between 64MB and 1GB then 8 VLFs are created If the growth is greater than 1GB then 16 VLFs are created. Now the potential for chaos comes if the default values and settings for log file growth are used. By default a database log file gets a 1MB log file with unlimited growth in steps of 10%. The database we just created is 6 MB, let’s add some data and see what happens. USE vlf_test go -- we need somewhere to put the data so, a table is in order IF OBJECT_ID('A_Table') IS NOT NULL DROP TABLE A_Table go CREATE TABLE A_Table ( Col_A int IDENTITY, Col_B CHAR(8000) ) GO -- Let's check the state of the log file -- 4 VLFs found EXECUTE ('DBCC LOGINFO'); go -- We can go ahead and insert some data and then check the state of the log file again INSERT A_Table (col_b) SELECT TOP 500 REPLICATE('a',2000) FROM sys.columns AS sc, sys.columns AS sc2 GO -- insert 500 rows and we get 22 VLFs EXECUTE ('DBCC LOGINFO'); go -- Let's insert more rows INSERT A_Table (col_b) SELECT TOP 2000 REPLICATE('a',2000) FROM sys.columns AS sc, sys.columns AS sc2 GO 10 -- insert 2000 rows, in 10 batches and we suddenly have 107 VLFs EXECUTE ('DBCC LOGINFO'); Well, that escalated quickly! Our log file is split, internally, into 107 fragments after a few thousand inserts. The same happens with any logged transactions, I just chose to illustrate this with INSERTs. Having too many VLFs can cause performance degradation at times of database start up, log backup and log restore operations so it’s well worth keeping a check on this property. How do we prevent excessive VLF creation? Creating the database with larger files and also with larger growth steps and actively choosing to grow your databases rather than leaving it to the Auto Grow event can make sure that the growths are made with a size that is optimal. How do we resolve a situation of a database with too many VLFs? This process needs to be done when the database is under little or no stress so that you don’t affect system users. The steps are: BACKUP LOG YourDBName TO YourBackupDestinationOfChoice Shrink the log file to its smallest possible size DBCC SHRINKFILE(FileNameOfTLogHere, TRUNCATEONLY) * Re-size the log file to the size you want it to, taking in to account your expected needs for the coming months or year. ALTER DATABASE YourDBName MODIFY FILE ( NAME = FileNameOfTLogHere, SIZE = TheSizeYouWantItToBeIn_MB) * – If you don’t know the file name of your log file then run sp_helpfile while you are connected to the database that you want to work on and you will get the details you need. The resize step can take quite a while This is already detailed far better than I can explain it by Kimberley Tripp in her blog 8-Steps-to-better-Transaction-Log-throughput.aspx. The result of this will be a log file with a VLF count according to the bullet list above. Knowing when VLFs are being created By complete coincidence while I have been writing this blog (it’s been quite some time from it’s inception to going live) Jonathan Kehayias from SQLSkills.com has written a great article on how to track database file growth using Event Notifications and Service Broker. I strongly recommend taking a look at it as this is going to catch any sneaky auto grows that take place and let you know about them right away. Hassle free monitoring of VLFs If you are lucky or wise enough to be using SQL Monitor or another monitoring tool that let’s you write your own custom metrics then you can keep an eye on this very easily. There is a custom metric for VLFs (written by Stuart Ainsworth) already on the site and there are some others there are very useful so take a moment or two to look around while you are there. Resources MSDN – http://msdn.microsoft.com/en-us/library/ms179355(v=sql.105).aspx Kimberly Tripp from SQLSkills.com – http://www.sqlskills.com/BLOGS/KIMBERLY/post/8-Steps-to-better-Transaction-Log-throughput.aspx Thomas LaRock at Simple-Talk.com – http://www.simple-talk.com/sql/database-administration/monitoring-sql-server-virtual-log-file-fragmentation/ Disclosure I am a Friend of Red Gate. This means that I am more than likely to say good things about Red Gate DBA and Developer tools. No matter how awesome I make them sound, take the time to compare them with other products before you contact the Red Gate sales team to make your order.

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  • What's new in Solaris 11.1?

    - by Karoly Vegh
    Solaris 11.1 is released. This is the first release update since Solaris 11 11/11, the versioning has been changed from MM/YY style to 11.1 highlighting that this is Solaris 11 Update 1.  Solaris 11 itself has been great. What's new in Solaris 11.1? Allow me to pick some new features from the What's New PDF that can be found in the official Oracle Solaris 11.1 Documentation. The updates are very numerous, I really can't include all.  I. New AI Automated Installer RBAC profiles have been introduced to enable delegation of installation tasks. II. The interactive installer now supports installing the OS to iSCSI targets. III. ASR (Auto Service Request) and OCM (Oracle Configuration Manager) have been enabled by default to proactively provide support information and create service requests to speed up support processes. This is optional and can be disabled but helps a lot in supportcases. For further information, see: http://oracle.com/goto/solarisautoreg IV. The new command svcbundle helps you to create SMF manifests without having to struggle with XML editing. (btw, do you know the interactive editprop subcommand in svccfg? The listprop/setprop subcommands are great for scripting and automating, but for an interactive property editing session try, for example, this: svccfg -s svc:/application/pkg/system-repository:default editprop )  V. pfedit: Ever wondered how to delegate editing permissions to certain files? It is well known "sudo /usr/bin/vi /etc/hosts" is not the right way, for sudo elevates the complete vi process to admin levels, and the user can "break" out of the session as root with simply starting a shell from that vi. Now, the new pfedit command provides a solution exactly to this challenge - an auditable, secure, per-user configurable editing possibility. See the pfedit man page for examples.   VI. rsyslog, the popular logging daemon (filters, SSL, formattable output, SQL collect...) has been included in Solaris 11.1 as an alternative to syslog.  VII: Zones: Solaris Zones - as a major Solaris differentiator - got lots of love in terms of new features: ZOSS - Zones on Shared Storage: Placing your zones to shared storage (FC, iSCSI) has never been this easy - via zonecfg.  parallell updates - with S11's bootenvironments updating zones was no problem and meant no downtime anyway, but still, now you can update them parallelly, a way faster update action if you are running a large number of zones. This is like parallell patching in Solaris 10, but with all the IPS/ZFS/S11 goodness.  per-zone fstype statistics: Running zones on a shared filesystems complicate the I/O debugging, since ZFS collects all the random writes and delivers them sequentially to boost performance. Now, over kstat you can find out which zone's I/O has an impact on the other ones, see the examples in the documentation: http://docs.oracle.com/cd/E26502_01/html/E29024/gmheh.html#scrolltoc Zones got RDSv3 protocol support for InfiniBand, and IPoIB support with Crossbow's anet (automatic vnic creation) feature.  NUMA I/O support for Zones: customers can now determine the NUMA I/O topology of the system from within zones.  VIII: Security got a lot of attention too:  Automated security/audit reporting, with builtin reporting templates e.g. for PCI (payment card industry) audits.  PAM is now configureable on a per-user basis instead of system wide, allowing different authentication requirements for different users  SSH in Solaris 11.1 now supports running in FIPS 140-2 mode, that is, in a U.S. government security accredited fashion.  SHA512/224 and SHA512/256 cryptographic hash functions are implemented in a FIPS-compliant way - and on a T4 implemented in silicon! That is, goverment-approved cryptography at HW-speed.  Generally, Solaris is currently under evaluation to be both FIPS and Common Criteria certified.  IX. Networking, as one of the core strengths of Solaris 11, has been extended with:  Data Center Bridging (DCB) - not only setups where network and storage share the same fabric (FCoE, anyone?) can have Quality-of-Service requirements. DCB enables peers to distinguish traffic based on priorities. Your NICs have to support DCB, see the documentation, and additional information on Wikipedia. DataLink MultiPathing, DLMP, enables link aggregation to span across multiple switches, even between those of different vendors. But there are essential differences to the good old bandwidth-aggregating LACP, see the documentation: http://docs.oracle.com/cd/E26502_01/html/E28993/gmdlu.html#scrolltoc VNIC live migration is now supported from one physical NIC to another on-the-fly  X. Data management:  FedFS, (Federated FileSystem) is new, it relies on Solaris 11's NFS referring mechanism to join separate shares of different NFS servers into a single filesystem namespace. The referring system has been there since S11 11/11, in Solaris 11.1 FedFS uses a LDAP - as the one global nameservice to bind them all.  The iSCSI initiator now uses the T4 CPU's HW-implemented CRC32 algorithm - thus improving iSCSI throughput while reducing CPU utilization on a T4 Storage locking improvements are now RAC aware, speeding up throughput with better locking-communication between nodes up to 20%!  XI: Kernel performance optimizations: The new Virtual Memory subsystem ("VM2") scales now to 100+ TB Memory ranges.  The memory predictor monitors large memory page usage, and adjust memory page sizes to applications' needs OSM, the Optimized Shared Memory allows Oracle DBs' SGA to be resized online XII: The Power Aware Dispatcher in now by default enabled, reducing power consumption of idle CPUs. Also, the LDoms' Power Management policies and the poweradm settings in Solaris 11 OS will cooperate. XIII: x86 boot: upgrade to the (Grand Unified Bootloader) GRUB2. Because grub2 differs in the configuration syntactically from grub1, one shall not edit the new grub configuration (grub.cfg) but use the new bootadm features to update it. GRUB2 adds UEFI support and also support for disks over 2TB. XIV: Improved viewing of per-CPU statistics of mpstat. This one might seem of less importance at first, but nowadays having better sorting/filtering possibilities on a periodically updated mpstat output of 256+ vCPUs can be a blessing. XV: Support for Solaris Cluster 4.1: The What's New document doesn't actually mention this one, since OSC 4.1 has not been released at the time 11.1 was. But since then it is available, and it requires Solaris 11.1. And it's only a "pkg update" away. ...aand I seriously need to stop here. There's a lot I missed, Edge Virtual Bridging, lofi tuning, ZFS sharing and crypto enhancements, USB3.0, pulseaudio, trusted extensions updates, etc - but if I mention all those then I effectively copy the What's New document. Which I recommend reading now anyway, it is a great extract of the 300+ new projects and RFE-followups in S11.1. And this blogpost is a summary of that extract.  For closing words, allow me to come back to Request For Enhancements, RFEs. Any customer can request features. Open up a Support Request, explain that this is an RFE, describe the feature you/your company desires to have in S11 implemented. The more SRs are collected for an RFE, the more chance it's got to get implemented. Feel free to provide feedback about the product, as well as about the Solaris 11.1 Documentation using the "Feedback" button there. Both the Solaris engineers and the documentation writers are eager to hear your input.Feel free to comment about this post too. Except that it's too long ;)  wbr,charlie

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  • 10 tape technology features that make you go hmm.

    - by Karoly Vegh
    A week ago an Oracle/StorageTek Tape Specialist, Christian Vanden Balck, visited Vienna, and agreed to visit customers to do techtalks and update them about the technology boom going around tape. I had the privilege to attend some of his sessions and noted the information and features that took the customers by surprise and made them think. Allow me to share the top 10: I. StorageTek as a brand: StorageTek is one of he strongest names in the Tape field. The brand itself was valued so much by customers that even after Sun Microsystems acquiring StorageTek and the Oracle acquiring Sun the brand lives on with all the Oracle tapelibraries are officially branded StorageTek.See http://www.oracle.com/us/products/servers-storage/storage/tape-storage/overview/index.html II. Disk information density limitations: Disk technology struggles with information density. You haven't seen the disk sizes exploding lately, have you? That's partly because there are physical limits on a disk platter. The size is given, the number of platters is limited, they just can't grow, and are running out of physical area to write to. Now, in a T10000C tape cartridge we have over 1000m long tape. There you go, you have got your physical space and don't need to stuff all that data crammed together. You can write in a reliable pattern, and have space to grow too. III. Oracle has a market share of 62% worldwide in recording head manufacturing. That's right. If you are running LTO drives, with a good chance you rely on StorageTek production. That's two out of three LTO recording heads produced worldwide.  IV. You can store 1 Exabyte data in a single tape library. Yes, an Exabyte. That is 1000 Petabytes. Or, a million Terabytes. A thousand million GigaBytes. You can store that in a stacked StorageTek SL8500 tapelibrary. In one SL8500 you can put 10.000 T10000C cartridges, that store 10TB data (compressed). You can stack 10 of these SL8500s together. Boom. 1000.000 TB.(n.b.: stacking means interconnecting the libraries. Yes, cartridges are moved between the stacked libraries automatically.)  V. EMC: 'Tape doesn't suck after all. We moved on.': Do you remember the infamous 'Tape sucks, move on' Datadomain slogan? Of course they had to put it that way, having only had disk products. But here's a fun fact: on the EMCWorld 2012 there was a major presence of a Tape-tech company - EMC, in a sudden burst of sanity is embracing tape again. VI. The miraculous T10000C: Oracle StorageTek has developed an enterprise-grade tapedrive and cartridge, the T10000C. With awesome numbers: The Cartridge: Native 5TB capacity, 10TB with compression Over a kilometer long tape within the cartridge. And it's locked when unmounted, no rattling of your data.  Replaced the metalparticles datalayer with BaFe (bariumferrite) - metalparticles lose around 7% of magnetism within 30 days. BaFe does not. Yes we employ solid-state physicists doing R&D on demagnetisation in our labs. Can be partitioned, storage tiering within the cartridge!  The Drive: 2GB Cache Encryption implemented in HW - no performance hit 252 MB/s native sustained data rate, beats disk technology by far. Not to mention peak throughput.  Leading the tape while never touching the data side of it, protecting your data physically too Data integritiy checking (CRC recalculation) on tape within the drive without having to read it back to the server reordering data from tape-order, delivering it back in application-order  writing 32 tracks at once, reading them back for CRC check at once VII. You only use 20% of your data on a regular basis. The rest 80% is just lying around for years. On continuously spinning disks. Doubly consuming energy (power+cooling), blocking diskstorage capacity. There is a solution called SAM (Storage Archive Manager) that provides you a filesystem unifying disk and tape, moving data on-demand and for clients transparently between the different storage tiers. You can share these filesystems with NFS or CIFS for clients, and enjoy the low TCO of tape. Tapes don't spin. They sit quietly in their slots, storing 10TB data, using no energy, producing no heat, automounted when a client accesses their data.See: http://www.oracle.com/us/products/servers-storage/storage/storage-software/storage-archive-manager/overview/index.html VIII. HW supported for three decades: Did you know that the original PowderHorn library was released in '87 and has been only discontinued in 2010? That is over two decades of supported operation. Tape libraries are - just like the data carrying on tapecartridges - built for longevity. Oh, and the T10000C cartridge has 30-year archival life for long-term retention.  IX. Tape is easy to manage: Have you heard of Tape Storage Analytics? It is a central graphical tool to summarize, monitor, analyze dataflow, health and performance of drives and libraries, see: http://www.oracle.com/us/products/servers-storage/storage/tape-storage/tape-analytics/overview/index.html X. The next generation: The T10000B drives were able to reuse the T10000A cartridges and write on them even more data. On the same cartridges. We call this investment protection, and this is very important for Oracle for the future too. We usually support two generations of cartridges together. The current drive is a T10000C. (...I know I promised to enlist 10, but I got still two more I really want to mention. Allow me to work around the problem: ) X++. The TallBots, the robots moving around the cartridges in the StorageTek library from tapeslots to the drives are cableless. Cables, belts, chains running to moving parts in a library cause maintenance downtimes. So StorageTek eliminated them. The TallBots get power, commands, even firmwareupgrades through the rails they are running on. Also, the TallBots don't just hook'n'pull the tapes out of their slots, they actually grip'n'lift them out. No friction, no scratches, no zillion little plastic particles floating around in the library, in the drives, on your data. (X++)++: Tape beats SSDs and Disks. In terms of throughput (252 MB/s), in terms of TCO: disks cause around 290x more power and cooling, in terms of capacity: 10TB on a single media and soon more.  So... do you need to store large amounts of data? Are you legally bound to archive it for dozens of years? Would you benefit from automatic storage tiering? Have you got large mediachunks to be streamed at times? Have you got power and cooling issues in the growing datacenters? Do you find EMC's 180° turn of tape attitude interesting, but appreciate it at the same time? With all that, you aren't alone. The most data on this planet is stored on tape. Tape is coming. Big time.

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  • NUMA-aware placement of communication variables

    - by Dave
    For classic NUMA-aware programming I'm typically most concerned about simple cold, capacity and compulsory misses and whether we can satisfy the miss by locally connected memory or whether we have to pull the line from its home node over the coherent interconnect -- we'd like to minimize channel contention and conserve interconnect bandwidth. That is, for this style of programming we're quite aware of where memory is homed relative to the threads that will be accessing it. Ideally, a page is collocated on the node with the thread that's expected to most frequently access the page, as simple misses on the page can be satisfied without resorting to transferring the line over the interconnect. The default "first touch" NUMA page placement policy tends to work reasonable well in this regard. When a virtual page is first accessed, the operating system will attempt to provision and map that virtual page to a physical page allocated from the node where the accessing thread is running. It's worth noting that the node-level memory interleaving granularity is usually a multiple of the page size, so we can say that a given page P resides on some node N. That is, the memory underlying a page resides on just one node. But when thinking about accesses to heavily-written communication variables we normally consider what caches the lines underlying such variables might be resident in, and in what states. We want to minimize coherence misses and cache probe activity and interconnect traffic in general. I don't usually give much thought to the location of the home NUMA node underlying such highly shared variables. On a SPARC T5440, for instance, which consists of 4 T2+ processors connected by a central coherence hub, the home node and placement of heavily accessed communication variables has very little impact on performance. The variables are frequently accessed so likely in M-state in some cache, and the location of the home node is of little consequence because a requester can use cache-to-cache transfers to get the line. Or at least that's what I thought. Recently, though, I was exploring a simple shared memory point-to-point communication model where a client writes a request into a request mailbox and then busy-waits on a response variable. It's a simple example of delegation based on message passing. The server polls the request mailbox, and having fetched a new request value, performs some operation and then writes a reply value into the response variable. As noted above, on a T5440 performance is insensitive to the placement of the communication variables -- the request and response mailbox words. But on a Sun/Oracle X4800 I noticed that was not the case and that NUMA placement of the communication variables was actually quite important. For background an X4800 system consists of 8 Intel X7560 Xeons . Each package (socket) has 8 cores with 2 contexts per core, so the system is 8x8x2. Each package is also a NUMA node and has locally attached memory. Every package has 3 point-to-point QPI links for cache coherence, and the system is configured with a twisted ladder "mobius" topology. The cache coherence fabric is glueless -- there's not central arbiter or coherence hub. The maximum distance between any two nodes is just 2 hops over the QPI links. For any given node, 3 other nodes are 1 hop distant and the remaining 4 nodes are 2 hops distant. Using a single request (client) thread and a single response (server) thread, a benchmark harness explored all permutations of NUMA placement for the two threads and the two communication variables, measuring the average round-trip-time and throughput rate between the client and server. In this benchmark the server simply acts as a simple transponder, writing the request value plus 1 back into the reply field, so there's no particular computation phase and we're only measuring communication overheads. In addition to varying the placement of communication variables over pairs of nodes, we also explored variations where both variables were placed on one page (and thus on one node) -- either on the same cache line or different cache lines -- while varying the node where the variables reside along with the placement of the threads. The key observation was that if the client and server threads were on different nodes, then the best placement of variables was to have the request variable (written by the client and read by the server) reside on the same node as the client thread, and to place the response variable (written by the server and read by the client) on the same node as the server. That is, if you have a variable that's to be written by one thread and read by another, it should be homed with the writer thread. For our simple client-server model that means using split request and response communication variables with unidirectional message flow on a given page. This can yield up to twice the throughput of less favorable placement strategies. Our X4800 uses the QPI 1.0 protocol with source-based snooping. Briefly, when node A needs to probe a cache line it fires off snoop requests to all the nodes in the system. Those recipients then forward their response not to the original requester, but to the home node H of the cache line. H waits for and collects the responses, adjudicates and resolves conflicts and ensures memory-model ordering, and then sends a definitive reply back to the original requester A. If some node B needed to transfer the line to A, it will do so by cache-to-cache transfer and let H know about the disposition of the cache line. A needs to wait for the authoritative response from H. So if a thread on node A wants to write a value to be read by a thread on node B, the latency is dependent on the distances between A, B, and H. We observe the best performance when the written-to variable is co-homed with the writer A. That is, we want H and A to be the same node, as the writer doesn't need the home to respond over the QPI link, as the writer and the home reside on the very same node. With architecturally informed placement of communication variables we eliminate at least one QPI hop from the critical path. Newer Intel processors use the QPI 1.1 coherence protocol with home-based snooping. As noted above, under source-snooping a requester broadcasts snoop requests to all nodes. Those nodes send their response to the home node of the location, which provides memory ordering, reconciles conflicts, etc., and then posts a definitive reply to the requester. In home-based snooping the snoop probe goes directly to the home node and are not broadcast. The home node can consult snoop filters -- if present -- and send out requests to retrieve the line if necessary. The 3rd party owner of the line, if any, can respond either to the home or the original requester (or even to both) according to the protocol policies. There are myriad variations that have been implemented, and unfortunately vendor terminology doesn't always agree between vendors or with the academic taxonomy papers. The key is that home-snooping enables the use of a snoop filter to reduce interconnect traffic. And while home-snooping might have a longer critical path (latency) than source-based snooping, it also may require fewer messages and less overall bandwidth. It'll be interesting to reprise these experiments on a platform with home-based snooping. While collecting data I also noticed that there are placement concerns even in the seemingly trivial case when both threads and both variables reside on a single node. Internally, the cores on each X7560 package are connected by an internal ring. (Actually there are multiple contra-rotating rings). And the last-level on-chip cache (LLC) is partitioned in banks or slices, which with each slice being associated with a core on the ring topology. A hardware hash function associates each physical address with a specific home bank. Thus we face distance and topology concerns even for intra-package communications, although the latencies are not nearly the magnitude we see inter-package. I've not seen such communication distance artifacts on the T2+, where the cache banks are connected to the cores via a high-speed crossbar instead of a ring -- communication latencies seem more regular.

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  • MySQL at Mobile World Congress (on Valentine's Day...)

    - by mat.keep(at)oracle.com
    It is that time of year again when the mobile communications industry converges on Barcelona for what many regard as the premier telecommunications show of the year.Starting on February 14th, what better way for a Brit like me to spend Valentines Day with 50,000 mobile industry leaders (my wife doesn't tend to read this blog, so I'm reasonably safe with that statement).As ever, Oracle has an extensive presence at the show, and part of that presence this year includes MySQL.We will be running a live demonstration of the MySQL Cluster database on Booth 7C18 in the App Planet.The demonstration will show how the MySQL Cluster Connector for Java is implemented to provide native connectivity to the carrier grade MySQL Cluster database from Java ME clients via Java SE virtual machines and Java EE servers.  The demonstration will show how end-to-end Java services remain continuously available during both catastrophic failures and scheduled maintenance activities.The MySQL Cluster Connector for Java provides both a native Java API and JPA plug-in that directly maps Java objects to relational tables stored in the MySQL Cluster database, without the overhead and complexity of having to transform objects to JDBC, and then SQL  The result is 10x higher throughput, and a simpler development model for Java engineers.Stop by the stand for a demonstration, and an opportunity to speak with the MySQL telecoms team who will share experiences on how MySQL is being used to bring the innovation of the web to the carrier network.Of course, if you can't make it to Barcelona, you can still learn more about the MySQL Cluster Connector for Java from this whitepaper and are free to download it as part of MySQL Cluster Community Edition  Let us know via the comments if you have Java applications that you think will benefit from the MySQL Cluster Connector for JavaI can't promise that Valentines Day at MWC will be the time you fall in love with MySQL Cluster...but I'm confident you will at least develop a healthy respect for it  

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  • Managed hosting firewall vs managing own firewall

    - by ddawber
    I posted on stackoverflow as to the overall benefits of managed hosting vs non-managed hosting. The more I think about it, it seems to boil down to one question: should I use a managed host because they take care of the firewall, or would I be okay managing my own, software firewall? The sites on the box do get quite a lot of traffic but as for throughput and what-not, it's not something I know much about. Ideally, i'd take my sites over to a Linode stack and manage incoming connections using iptables or an alternative. Here are some example hardware solutions a managed host would provide: Cisco Pix 501, Pix 506, Pix 515 and ASA 5505 and ASA 5510 Firewalls, configurable in a control panel the likes of an enterprise firewall such as FortiGate 110C Aside from this, I do not need managed hosting, so I appreciate your suggestions.

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  • JMeter Stress testing

    - by mcondiff
    MAMP server hosting a Joomla instance. I'd like to hear the community's thoughts on the best way to stress test the server and find it's breaking point on concurrent users etc. Currently I have setup a test plan which I have going to the home page, grabbing the index.php, css, js and all images and have run tests on 1 to 100 users and a varying number of loops. What I'd like to know is how do I determine at what number of concurrent requests or looping requests is a good way to gauge if my server can handle the proposed increase in traffic? What is a good KB/sec, Throughput, Average, Max, Min via the Aggregate Report and at what number of threads/loops etc? I have googled and have not found immediate answers to these questions and thought to come here. More or less I have just used this http://jakarta.apache.org/jmeter/usermanual/jmeter_proxy_step_by_step.pdf to guide me and then I have been winging it in terms of Thread and Loop numbers. Any light shed on these subject would be much appreciated.

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  • CORAID using only 1 of the 2 available NICs for AoE traffic

    - by Peter Carrero
    We got 6 CORAID shelves in my workplace. On 2 of them I see AoE traffic on only 1 of the 2 NICs that are attached to the SAN switch. We got jumbo frames enabled on all devices. Both NICs show up when I issue the aoe-interfaces command. This wouldn't bother me too much if the throughput performance observed on the "bad" shelves using bonnie++ wasn't half of the result of the "good" shelves. The "good" shelves are older SR1521 model and they have ReiserFS on their LUNS - not that I think it makes a difference - and the "bad" shelves are newer SR2421 model and have JFS. Any help as to what is going on and how to rectify this would be greatly appreciated. BTW: even the lower performing shelves outperform another iSCSI device we got, but that is another story... Thanks.

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  • Commit in SQL

    - by PRajkumar
    SQL Transaction Control Language Commands (TCL)                                           (COMMIT) Commit Transaction As a SQL language we use transaction control language very frequently. Committing a transaction means making permanent the changes performed by the SQL statements within the transaction. A transaction is a sequence of SQL statements that Oracle Database treats as a single unit. This statement also erases all save points in the transaction and releases transaction locks. Oracle Database issues an implicit COMMIT before and after any data definition language (DDL) statement. Oracle recommends that you explicitly end every transaction in your application programs with a COMMIT or ROLLBACK statement, including the last transaction, before disconnecting from Oracle Database. If you do not explicitly commit the transaction and the program terminates abnormally, then the last uncommitted transaction is automatically rolled back.   Until you commit a transaction: ·         You can see any changes you have made during the transaction by querying the modified tables, but other users cannot see the changes. After you commit the transaction, the changes are visible to other users' statements that execute after the commit ·         You can roll back (undo) any changes made during the transaction with the ROLLBACK statement   Note: Most of the people think that when we type commit data or changes of what you have made has been written to data files, but this is wrong when you type commit it means that you are saying that your job has been completed and respective verification will be done by oracle engine that means it checks whether your transaction achieved consistency when it finds ok it sends a commit message to the user from log buffer but not from data buffer, so after writing data in log buffer it insists data buffer to write data in to data files, this is how it works.   Before a transaction that modifies data is committed, the following has occurred: ·         Oracle has generated undo information. The undo information contains the old data values changed by the SQL statements of the transaction ·         Oracle has generated redo log entries in the redo log buffer of the System Global Area (SGA). The redo log record contains the change to the data block and the change to the rollback block. These changes may go to disk before a transaction is committed ·         The changes have been made to the database buffers of the SGA. These changes may go to disk before a transaction is committed   Note:   The data changes for a committed transaction, stored in the database buffers of the SGA, are not necessarily written immediately to the data files by the database writer (DBWn) background process. This writing takes place when it is most efficient for the database to do so. It can happen before the transaction commits or, alternatively, it can happen some times after the transaction commits.   When a transaction is committed, the following occurs: 1.      The internal transaction table for the associated undo table space records that the transaction has committed, and the corresponding unique system change number (SCN) of the transaction is assigned and recorded in the table 2.      The log writer process (LGWR) writes redo log entries in the SGA's redo log buffers to the redo log file. It also writes the transaction's SCN to the redo log file. This atomic event constitutes the commit of the transaction 3.      Oracle releases locks held on rows and tables 4.      Oracle marks the transaction complete   Note:   The default behavior is for LGWR to write redo to the online redo log files synchronously and for transactions to wait for the redo to go to disk before returning a commit to the user. However, for lower transaction commit latency application developers can specify that redo be written asynchronously and that transaction do not need to wait for the redo to be on disk.   The syntax of Commit Statement is   COMMIT [WORK] [COMMENT ‘your comment’]; ·         WORK is optional. The WORK keyword is supported for compliance with standard SQL. The statements COMMIT and COMMIT WORK are equivalent. Examples Committing an Insert INSERT INTO table_name VALUES (val1, val2); COMMIT WORK; ·         COMMENT Comment is also optional. This clause is supported for backward compatibility. Oracle recommends that you used named transactions instead of commit comments. Specify a comment to be associated with the current transaction. The 'text' is a quoted literal of up to 255 bytes that Oracle Database stores in the data dictionary view DBA_2PC_PENDING along with the transaction ID if a distributed transaction becomes in doubt. This comment can help you diagnose the failure of a distributed transaction. Examples The following statement commits the current transaction and associates a comment with it: COMMIT     COMMENT 'In-doubt transaction Code 36, Call (415) 555-2637'; ·         WRITE Clause Use this clause to specify the priority with which the redo information generated by the commit operation is written to the redo log. This clause can improve performance by reducing latency, thus eliminating the wait for an I/O to the redo log. Use this clause to improve response time in environments with stringent response time requirements where the following conditions apply: The volume of update transactions is large, requiring that the redo log be written to disk frequently. The application can tolerate the loss of an asynchronously committed transaction. The latency contributed by waiting for the redo log write to occur contributes significantly to overall response time. You can specify the WAIT | NOWAIT and IMMEDIATE | BATCH clauses in any order. Examples To commit the same insert operation and instruct the database to buffer the change to the redo log, without initiating disk I/O, use the following COMMIT statement: COMMIT WRITE BATCH; Note: If you omit this clause, then the behavior of the commit operation is controlled by the COMMIT_WRITE initialization parameter, if it has been set. The default value of the parameter is the same as the default for this clause. Therefore, if the parameter has not been set and you omit this clause, then commit records are written to disk before control is returned to the user. WAIT | NOWAIT Use these clauses to specify when control returns to the user. The WAIT parameter ensures that the commit will return only after the corresponding redo is persistent in the online redo log. Whether in BATCH or IMMEDIATE mode, when the client receives a successful return from this COMMIT statement, the transaction has been committed to durable media. A crash occurring after a successful write to the log can prevent the success message from returning to the client. In this case the client cannot tell whether or not the transaction committed. The NOWAIT parameter causes the commit to return to the client whether or not the write to the redo log has completed. This behavior can increase transaction throughput. With the WAIT parameter, if the commit message is received, then you can be sure that no data has been lost. Caution: With NOWAIT, a crash occurring after the commit message is received, but before the redo log record(s) are written, can falsely indicate to a transaction that its changes are persistent. If you omit this clause, then the transaction commits with the WAIT behavior. IMMEDIATE | BATCH Use these clauses to specify when the redo is written to the log. The IMMEDIATE parameter causes the log writer process (LGWR) to write the transaction's redo information to the log. This operation option forces a disk I/O, so it can reduce transaction throughput. The BATCH parameter causes the redo to be buffered to the redo log, along with other concurrently executing transactions. When sufficient redo information is collected, a disk write of the redo log is initiated. This behavior is called "group commit", as redo for multiple transactions is written to the log in a single I/O operation. If you omit this clause, then the transaction commits with the IMMEDIATE behavior. ·         FORCE Clause Use this clause to manually commit an in-doubt distributed transaction or a corrupt transaction. ·         In a distributed database system, the FORCE string [, integer] clause lets you manually commit an in-doubt distributed transaction. The transaction is identified by the 'string' containing its local or global transaction ID. To find the IDs of such transactions, query the data dictionary view DBA_2PC_PENDING. You can use integer to specifically assign the transaction a system change number (SCN). If you omit integer, then the transaction is committed using the current SCN. ·         The FORCE CORRUPT_XID 'string' clause lets you manually commit a single corrupt transaction, where string is the ID of the corrupt transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to specify this clause. ·         Specify FORCE CORRUPT_XID_ALL to manually commit all corrupt transactions. You must have DBA privileges to specify this clause. Examples Forcing an in doubt transaction. Example The following statement manually commits a hypothetical in-doubt distributed transaction. Query the V$CORRUPT_XID_LIST data dictionary view to find the transaction IDs of corrupt transactions. You must have DBA privileges to view the V$CORRUPT_XID_LIST and to issue this statement. COMMIT FORCE '22.57.53';

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  • pfsense multi-site VPN VOIP deployment

    - by sysconfig
    have main office pfsense firewall configured like this: local networks WAN - internet LAN - local network VOIP - IP phones need to connect remote offices (multi-users) and single remote users (from home) use IPSEC or OpenVPN to build "permanent" automatically connecting tunnels from remote location to main location. in remote locations, network will look like this: WAN - internet LAN - local network multiple users VOIP - multiple IP phones in order for the IP phones to work they have to be able to "see" the VOIP network and the VOIP server back at the main office for single remote users ( like from home ) the setup will be similar but only one phone and one computer so questions: best way to tie networks together? IPSEC or OpenVPN can this be setup to automatically connect ? any issues/suggestions with that design/topology ? QoS or issues with running the VOIP traffic over a VPN throughput, quality etc.. obviously depends on remote locations connection to some degree

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  • Wireshark (WinPCap) does not see Intel X520-DA2 10 GbE NIC teaming intermittently

    - by GregC
    I am running a team of two 10 GigE ports on Intel X520-DA2 network card. They work well in tandem and achieve the desired throughput. However, I see an intermittent issue whereby WireShark and my own application (using WinPCap) only show the underlying ports, failing to recognize the team adapter. Details: Intel 17.4 NIC drivers on Windows Server 2008 R2 with all patches. HP DL370 G6 server. RSS enabled on Intel both underlying Intel NICs. The exact error: Unable to open the adapter (rpcap://\Device\NPF_{401D5903-16E7-41DC-8484-5D96765B9692}). failed to set hardware filter to promiscuous mode

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  • pfsense multi-site VPN VOIP deployment

    - by sysconfig
    have main office pfsense firewall configured like this: local networks WAN - internet LAN - local network VOIP - IP phones need to connect remote offices (multi-users) and single remote users (from home) use IPSEC or OpenVPN to build "permanent" automatically connecting tunnels from remote location to main location. in remote locations, network will look like this: WAN - internet LAN - local network multiple users VOIP - multiple IP phones in order for the IP phones to work they have to be able to "see" the VOIP network and the VOIP server back at the main office for single remote users ( like from home ) the setup will be similar but only one phone and one computer so questions: best way to tie networks together? IPSEC or OpenVPN can this be setup to automatically connect ? any issues/suggestions with that design/topology ? QoS or issues with running the VOIP traffic over a VPN throughput, quality etc.. obviously depends on remote locations connection to some degree

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  • Cisco VPN Solution [on hold]

    - by Joey Harris
    Not sure if I can ask this type of question here so please delete if it should not be here. Im building a small server environment for a company and they are going to require a VPN gateway to connect to a main office from potentially anywhere in the world. I was hoping somebody could give me a recommendation on a Cisco product that can offer VPN connectivity for up to 100 clients and supports split tunneling. All products I've looked at are a few thousand dollars. I'm hoping someone can find me something that's only a few hundred dollars. I've seen the VPN Concentrator series but the modals that aren't thousands of dollars only support 4Mbps throughput. There will be file transfers going on so I'm hoping for something more then 500KBps.

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  • Unhappy with performance of GBit Ethernet to Fiber converter

    - by Aaron Digulla
    I just bought a TP-Link MC200CM GBit Ethernet (1000-T) to Fiber (1000-SX) media converter. The device works but I'm unhappy with the performance: When connecting my computer over 1000-T (twisted pair, Cat 6, 18meters) with my server, I get a throughput of about 610MBit/s. If I replace the cable with two media converters, I'm left with about 310-315MBit/s (i.e. half the performance). My setup is like this: Computer <- GBit switch <- long cable <- GBit switch <- server Computer <- GBit switch <- MC200CM <- 30m fiber <- MC200CM <- GBit switch <- server Is there a way to improve the performance? Will another MC be faster? Or is that about as much as I can expect with the additional 2 converters?

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  • Hardware Raid Card Reviews with SSDs

    - by Nalandial
    Yes I realize there are several questions about this but none of them seem to have the answer I'm looking for. I have two SSDs and am looking to buy a purely hardware raid card for them; however, I can't seem to find any reviews that have specifically tested hardware raid cards with SSDs rather than testing the SSDs themselves. I'm looking for a review because I'm assuming that for example: 100% gain with two 7200rpm drives doesn't necessarily mean 100% gain with a pair of SSDs, since there would be higher speeds, meaning more throughput, meaning more processor/memory usage for the card. If this assumption is wrong then that's fantastic; however if it's true, I am quite sad and would really appreciate any advice or reviews you can find. Thanks in advance!

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