Search Results

Search found 11834 results on 474 pages for 'radio group'.

Page 366/474 | < Previous Page | 362 363 364 365 366 367 368 369 370 371 372 373  | Next Page >

• making mysql query using splite string?

  - by Marco

  lets say i have a group of number like (3,2,5) the normal way i use to split them and searching mysql to get value is to split them using explode in PHP EXAMPLE $string = '3,4,5'; $array = explode(',',$string); foreach($array as $value){ $query = 'SELECT ID FROM TABLE WHERE ID = "'.$value.'"'; } it work like this but it make the script extremely slow i need now if there is away to split this string into the query it self and return the result without looping with PHP ?

  Read the article

• mySQL : using BETWEEN in table ?

  - by Meko

  I have a table that includes somestudent group name ,lesson time,day names like Schedule. I am using C# whit MYSql and I want to find which lesson is when user press button from table. I can find it like entering exact value like in table 08:30 or 10:25 , it finds. But I want to make that getting system time and checking that is it between 08:30 and 10:25 or 10:25 and 12:30 . Then I can sythat it is first lesson or it is second lesson . I have also table includes Table_Time column has 5 record like 08:20 , 10:25 , 12:20 so on. Could I use like : select Lesson_Time from mydb.clock where Lesson_Time between (current time)-30 AND (current time)+30 Or can I use between operator between two columns ? Like creating Lesson_Time_Start and Lesson_Time_End and compairing current time like Lesson_Start_Time

  Read the article

• mysql query for change in values in a logging table

  - by kiasectomondo

  I have a table like this: Index , PersonID , ItemCount , UnixTimeStamp 1 , 1 , 1 , 1296000000 2 , 1 , 2 , 1296000100 3 , 2 , 4 , 1296003230 4 , 2 , 6 , 1296093949 5 , 1 , 0 , 1296093295 Time and index always go up. Its basically a logging table to log the itemcount each time it changes. I get the most recent ItemCount for each Person like this: SELECT * FROM table a INNER JOIN ( SELECT MAX(index) as i FROM table GROUP BY PersonID) b ON a.index = b.i; What I want to do is get get the most recent record for each PersonID that is at least 24 hours older than the most recent record for each Person ID. Then I want to take the difference in ItemCount between these two to get a change in itemcount for each person over the last 24 hours: personID ChangeInItemCountOverAtLeast24Hours 1 3 2 -11 3 6 Im sort of stuck with what to do next. How can I join another itemcount based on latest adjusted timestamp of individual rows?

  Read the article

• Put empty spaces in an SQL select

  - by David Undy

  I'm having difficulty creating a month-count select query in SQL. Basically, I have a list of entries, all of which have a date associated with them. What I want the end result to be, is a list containing 12 rows (one for each month), and each row would contain the month number (1 for January, 2 for February, etc), and a count of how many entries had that month set as it's date. Something like this: Month - Count 1 - 12 2 - 0 3 - 7 4 - 0 5 - 9 6 - 0 I can get an result containing months that have a count of higher than 0, but if the month contains no entries, the row isn't created. I get this result just by doing SELECT Month(goalDate) as monthNumber, count(*) as monthCount FROM goalsList WHERE Year(goalDate) = 2012 GROUP BY Month(goalDate) ORDER BY monthNumber Thanks in advance for the help!

  Read the article

• MySQL query to find the most popular value in a column joined by another value in a second table

  - by Budove

  I have two tables: users: user_id, user_zip settings: user_id, pref_ex_loc I need to find the single most popular 'pref_ex_loc' from the settings table based on a particular user_zip, which will be specified as the variable $userzip. Here is the query that I have now and obviously it doesn't work. $popularexloc = "SELECT pref_ex_loc, user_id COUNT(pref_ex_loc) AS countloc FROM settings FULL OUTER JOIN users ON settings.user_id = users.user_id WHERE users.user_zip='$userzip' GROUP BY settings.pref_ex_loc ORDER BY countloc LIMIT 1"; $popexloc = mysql_query($popularexloc) or die('SQL Error :: '.mysql_error()); $exlocrow = mysql_fetch_array($popexloc); $mostpopexloc=$exlocrow[0]; echo '<option value="'.$mostpopexloc.'">'.$mostpopexloc.'</option>'; What am I doing wrong here? I'm not getting any kind of error from this either.

  Read the article

• complex data requirement.

  - by Abulalia

  Here is my query: select Table1.a, Table1.b, Table1.c, Table1.d, Table2.e, Table3.f, Table4.g, Table5.h from Table1 left join Table6 on Table1.b=Table6.b left join Table3 on Table6.j=Table3.j left join Table7 on Table1.b=Table7.b left join Table5 on Table7.h=Table5.h inner join Table4 on Table1.k=Table4.k inner join Table2 on Table1.m=Table2.m where Table2.e <= x and Table2.n = y and Table3.f in (‘r’, ‘s’) and Table1.d = z group by Table1.a, Table1.b, Table1.c, Table1.d, Table2.e, Table3.f, Table4.g, Table5.h order by Table1.a, Table1.b, Table1.c I am looking for records (a,b,c,d,e,f,g,h) for every a when the very first record b (there are multiple records b for each a) is either 'r' or 's'. Can someone help?

  Read the article

• match word '90%' using regular expression

  - by amadhu

  Hi All, I want word '90%' to be matched with my String "I have 90% shares of this company". how can I write regular expression for same? I tried something like this: Pattern p = Pattern.compile("\\b90\\%\\b", Pattern.CASE_INSENSITIVE | Pattern.MULTILINE); Matcher m = p.matcher("I have 90% shares of this company"); while (m.find()){ System.out.println(m.group()); } but no luck. Can any one thow some lights on this? Many thanks, Archi

  Read the article

• Scan a Windows PC for Viruses from a Ubuntu Live CD

  - by Trevor Bekolay

  Getting a virus is bad. Getting a virus that causes your computer to crash when you reboot is even worse. We’ll show you how to clean viruses from your computer even if you can’t boot into Windows by using a virus scanner in a Ubuntu Live CD. There are a number of virus scanners available for Ubuntu, but we’ve found that avast! is the best choice, with great detection rates and usability. Unfortunately, avast! does not have a proper 64-bit version, and forcing the install does not work properly. If you want to use avast! to scan for viruses, then ensure that you have a 32-bit Ubuntu Live CD. If you currently have a 64-bit Ubuntu Live CD on a bootable flash drive, it does not take long to wipe your flash drive and go through our guide again and select normal (32-bit) Ubuntu 9.10 instead of the x64 edition. For the purposes of fixing your Windows installation, the 64-bit Live CD will not provide any benefits. Once Ubuntu 9.10 boots up, open up Firefox by clicking on its icon in the top panel. Navigate to http://www.avast.com/linux-home-edition. Click on the Download tab, and then click on the link to download the DEB package. Save it to the default location. While avast! is downloading, click on the link to the registration form on the download page. Fill in the registration form if you do not already have a trial license for avast!. By the time you’ve filled out the registration form, avast! will hopefully be finished downloading. Open a terminal window by clicking on Applications in the top-left corner of the screen, then expanding the Accessories menu and clicking on Terminal. In the terminal window, type in the following commands, pressing enter after each line. cd Downloadssudo dpkg –i avast* This will install avast! on the live Ubuntu environment. To ensure that you can use the latest virus database, while still in the terminal window, type in the following command: sudo sysctl –w kernel.shmmax=128000000 Now we’re ready to open avast!. Click on Applications on the top-left corner of the screen, expand the Accessories folder, and click on the new avast! Antivirus item. You will first be greeted with a window that asks for your license key. Hopefully you’ve received it in your email by now; open the email that avast! sends you, copy the license key, and paste it in the Registration window. avast! Antivirus will open. You’ll notice that the virus database is outdated. Click on the Update database button and avast! will start downloading the latest virus database. To scan your Windows hard drive, you will need to “mount” it. While the virus database is downloading, click on Places on the top-left of your screen, and click on your Windows hard drive, if you can tell which one it is by its size. If you can’t tell which is the correct hard drive, then click on Computer and check out each hard drive until you find the right one. When you find it, make a note of the drive’s label, which appears in the menu bar of the file browser. Also note that your hard drive will now appear on your desktop. By now, your virus database should be updated. At the time this article was written, the most recent version was 100404-0. In the main avast! window, click on the radio button next to Selected folders and then click on the “+” button to the right of the list box. It will open up a dialog box to browse to a location. To find your Windows hard drive, click on the “>” next to the computer icon. In the expanded list, find the folder labelled “media” and click on the “>” next to it to expand it. In this list, you should be able to find the label that corresponds to your Windows hard drive. If you want to scan a certain folder, then you can go further into this hierarchy and select that folder. However, we will scan the entire hard drive, so we’ll just press OK. Click on Start scan and avast! will start scanning your hard drive. If a virus is found, you’ll be prompted to select an action. If you know that the file is a virus, then you can Delete it, but there is the possibility of false positives, so you can also choose Move to chest to quarantine it. When avast! is done scanning, it will summarize what it found on your hard drive. You can take different actions on those files at this time by right-clicking on them and selecting the appropriate action. When you’re done, click Close. Your Windows PC is now free of viruses, in the eyes of avast!. Reboot your computer and with any luck it will now boot up! Alternatives to avast! If avast! and a liberal amount of Googling doesn’t fix your problem, it’s possible that a different virus scanner will fix your obscure issue. Here are a list of other virus scanners available for Ubuntu that are either free or offer free trials. See their support forums for help on installing these virus scanners. Avira AntiVir Personal for Linux / Solaris Panda Antivirus for Linux Installation and usage guide from Ubuntu F-PROT Antivirus for Linux ClamAV installation and usage guide from Ubuntu NOD32 Antivirus for Linux Kaspersky Anti-Virus 2010 Bitdefender Antivirus for Unices Conclusion Running avast! from a Ubuntu Live CD can clean the vast majority of viruses from your Windows PC. This is another reason to always have a Ubuntu Live CD ready just in case something happens to your Windows installation! Similar Articles Productive Geek Tips Secure Computing: Windows Live OneCareHow To Remove Antivirus Live and Other Rogue/Fake Antivirus MalwareUse the Windows Key for the "Start" Menu in Ubuntu LinuxScan Files for Viruses Before You Download With Dr.WebAsk the Readers: Share Your Tips for Defeating Viruses and Malware TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 The Ultimate Guide For YouTube Lovers Will it Blend? iPad Edition Penolo Lets You Share Sketches On Twitter Visit Woolyss.com for Old School Games, Music and Videos Add a Custom Title in IE using Spybot or Spyware Blaster When You Need to Hail a Taxi in NYC

  Read the article

• Windows Azure Learning Plan - Security

  - by BuckWoody

  This is one in a series of posts on a Windows Azure Learning Plan. You can find the main post here. This one deals with Security for  Windows Azure.   General Security Information Overview and general  information about Windows Azure Security - what it is, how it works, and where you can learn more. General Security Whitepaper – answers most questions http://blogs.msdn.com/b/usisvde/archive/2010/08/10/security-white-paper-on-windows-azure-answers-many-faq.aspx Windows Azure Security Notes from the Patterns and Practices site http://blogs.msdn.com/b/jmeier/archive/2010/08/03/now-available-azure-security-notes-pdf.aspx Overview of Azure Security http://www.windowsecurity.com/articles/Microsoft-Azure-Security-Cloud.html Azure Security Resources http://reddevnews.com/articles/2010/08/19/microsoft-releases-windows-azure-security-resources.aspx Cloud Computing Security Considerations http://www.microsoft.com/downloads/en/details.aspx?FamilyID=68fedf9c-1c27-4642-aa5b-0a34472303ea&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+MicrosoftDownloadCenter+%28Microsoft+Download+Center Security in Cloud Computing – a Microsoft Perspective http://www.microsoft.com/downloads/en/details.aspx?FamilyID=7c8507e8-50ca-4693-aa5a-34b7c24f4579&utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+MicrosoftDownloadCenter+%28Microsoft+Download+Center Physical Security for Microsoft’s Online Computing Information on the Infrastructure and Locations for Azure Physical Security. The Global Foundation Services Group at Microsoft handles physical security http://www.globalfoundationservices.com/security/index.html Microsoft’s Security Response Center http://www.microsoft.com/security/msrc/ Software Security for Microsoft’s Online Computing Steps we take as a company to develop secure software Windows Azure is developed using the Trustworthy Computing Initiative http://www.microsoft.com/about/twc/en/us/default.aspx and  http://msdn.microsoft.com/en-us/library/ms995349.aspx Identity and Access in the Cloud http://blogs.msdn.com/b/technology_titbits_by_rajesh_makhija/archive/2010/10/29/identity-and-access-in-the-cloud.aspx Security Steps you should take While Microsoft takes great pains to secure the infrastructure, platform and code for Windows Azure, you have a responsibility to write secure code. These pointers can help you do that. Securing your cloud architecture, step-by-step http://technet.microsoft.com/en-us/magazine/gg296364.aspx Security Guidelines for Windows Azure http://redmondmag.com/articles/2010/06/15/microsoft-issues-security-guidelines-for-windows-azure.aspx  Best Practices for Windows Azure Security http://blogs.msdn.com/b/vbertocci/archive/2010/06/14/security-best-practices-for-developing-windows-azure-applications.aspx Active Directory and Windows Azure http://blogs.msdn.com/b/plankytronixx/archive/2010/10/22/projecting-your-active-directory-identity-to-the-azure-cloud.aspx Understanding Encryption (great overview and tutorial) http://blogs.msdn.com/b/plankytronixx/archive/2010/10/23/crypto-primer-understanding-encryption-public-private-key-signatures-and-certificates.aspx Securing your Connection Strings (SQL Azure) http://blogs.msdn.com/b/sqlazure/archive/2010/09/07/10058942.aspx Getting started with Windows Identity Foundation (WIF) quickly http://blogs.msdn.com/b/alikl/archive/2010/10/26/windows-identity-foundation-wif-fast-track.aspx

  Read the article

• Oracle Coherence, Split-Brain and Recovery Protocols In Detail

  - by Ricardo Ferreira

  This article provides a high level conceptual overview of Split-Brain scenarios in distributed systems. It will focus on a specific example of cluster communication failure and recovery in Oracle Coherence. This includes a discussion on the witness protocol (used to remove failed cluster members) and the panic protocol (used to resolve Split-Brain scenarios). Note that the removal of cluster members does not necessarily indicate a Split-Brain condition. Oracle Coherence does not (and cannot) detect a Split-Brain as it occurs, the condition is only detected when cluster members that previously lost contact with each other regain contact. Cluster Topology and Configuration In order to create an good didactic for the article, let's assume a cluster topology and configuration. In this example we have a six member cluster, consisting of one JVM on each physical machine. The member IDs are as follows: Member ID  IP Address  1  10.149.155.76  2  10.149.155.77  3  10.149.155.236  4  10.149.155.75  5  10.149.155.79  6  10.149.155.78 Members 1, 2, and 3 are connected to a switch, and members 4, 5, and 6 are connected to a second switch. There is a link between the two switches, which provides network connectivity between all of the machines. Member 1 is the first member to join this cluster, thus making it the senior member. Member 6 is the last member to join this cluster. Here is a log snippet from Member 6 showing the complete member set: 2010-02-26 15:27:57.390/3.062 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=main, member=6): Started DefaultCacheServer... SafeCluster: Name=cluster:0xDDEB Group{Address=224.3.5.3, Port=35465, TTL=4} MasterMemberSet ( ThisMember=Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) OldestMember=Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) ActualMemberSet=MemberSet(Size=6, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) Member(Id=2, Timestamp=2010-02-26 15:27:17.847, Address=10.149.155.77:8088, MachineId=1101, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:296, Role=CoherenceServer) Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer) Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) Member(Id=5, Timestamp=2010-02-26 15:27:49.095, Address=10.149.155.79:8088, MachineId=1103, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:3229, Role=CoherenceServer) Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) ) RecycleMillis=120000 RecycleSet=MemberSet(Size=0, BitSetCount=0 ) ) At approximately 15:30, the connection between the two switches is severed: Thirty seconds later (the default packet timeout in development mode) the logs indicate communication failures across the cluster. In this example, the communication failure was caused by a network failure. In a production setting, this type of communication failure can have many root causes, including (but not limited to) network failures, excessive GC, high CPU utilization, swapping/virtual memory, and exceeding maximum network bandwidth. In addition, this type of failure is not necessarily indicative of a split brain. Any communication failure will be logged in this fashion. Member 2 logs a communication failure with Member 5: 2010-02-26 15:30:32.638/196.928 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=PacketPublisher, member=2): Timeout while delivering a packet; requesting the departure confirmation for Member(Id=5, Timestamp=2010-02-26 15:27:49.095, Address=10.149.155.79:8088, MachineId=1103, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:3229, Role=CoherenceServer) by MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) ) The Coherence clustering protocol (TCMP) is a reliable transport mechanism built on UDP. In order for the protocol to be reliable, it requires an acknowledgement (ACK) for each packet delivered. If a packet fails to be acknowledged within the configured timeout period, the Coherence cluster member will log a packet timeout (as seen in the log message above). When this occurs, the cluster member will consult with other members to determine who is at fault for the communication failure. If the witness members agree that the suspect member is at fault, the suspect is removed from the cluster. If the witnesses unanimously disagree, the accuser is removed. This process is known as the witness protocol. Since Member 2 cannot communicate with Member 5, it selects two witnesses (Members 1 and 4) to determine if the communication issue is with Member 5 or with itself (Member 2). However, Member 4 is on the switch that is no longer accessible by Members 1, 2 and 3; thus a packet timeout for member 4 is recorded as well: 2010-02-26 15:30:35.648/199.938 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=PacketPublisher, member=2): Timeout while delivering a packet; requesting the departure confirmation for Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) by MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) ) Member 1 has the ability to confirm the departure of member 4, however Member 6 cannot as it is also inaccessible. At the same time, Member 3 sends a request to remove Member 6, which is followed by a report from Member 3 indicating that Member 6 has departed the cluster: 2010-02-26 15:30:35.706/199.996 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=2): MemberLeft request for Member 6 received from Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer) 2010-02-26 15:30:35.709/199.999 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=2): MemberLeft notification for Member 6 received from Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer) The log for Member 3 determines how Member 6 departed the cluster: 2010-02-26 15:30:35.161/191.694 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=PacketPublisher, member=3): Timeout while delivering a packet; requesting the departure confirmation for Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) by MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) Member(Id=2, Timestamp=2010-02-26 15:27:17.847, Address=10.149.155.77:8088, MachineId=1101, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:296, Role=CoherenceServer) ) 2010-02-26 15:30:35.165/191.698 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=Cluster, member=3): Member departure confirmed by MemberSet(Size=2, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) Member(Id=2, Timestamp=2010-02-26 15:27:17.847, Address=10.149.155.77:8088, MachineId=1101, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:296, Role=CoherenceServer) ); removing Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) In this case, Member 3 happened to select two witnesses that it still had connectivity with (Members 1 and 2) thus resulting in a simple decision to remove Member 6. Given the departure of Member 6, Member 2 is left with a single witness to confirm the departure of Member 4: 2010-02-26 15:30:35.713/200.003 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=Cluster, member=2): Member departure confirmed by MemberSet(Size=1, BitSetCount=2 Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) ); removing Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) In the meantime, Member 4 logs a missing heartbeat from the senior member. This message is also logged on Members 5 and 6. 2010-02-26 15:30:07.906/150.453 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=PacketListenerN, member=4): Scheduled senior member heartbeat is overdue; rejoining multicast group. Next, Member 4 logs a TcpRing failure with Member 2, thus resulting in the termination of Member 2: 2010-02-26 15:30:21.421/163.968 Oracle Coherence GE 3.5.3/465p2 <D4> (thread=Cluster, member=4): TcpRing: Number of socket exceptions exceeded maximum; last was "java.net.SocketTimeoutException: connect timed out"; removing the member: 2 For quick process termination detection, Oracle Coherence utilizes a feature called TcpRing which is a sparse collection of TCP/IP-based connections between different members in the cluster. Each member in the cluster is connected to at least one other member, which (if at all possible) is running on a different physical box. This connection is not used for any data transfer, only heartbeat communications are sent once a second per each link. If a certain number of exceptions are thrown while trying to re-establish a connection, the member throwing the exceptions is removed from the cluster. Member 5 logs a packet timeout with Member 3 and cites witnesses Members 4 and 6: 2010-02-26 15:30:29.791/165.037 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=PacketPublisher, member=5): Timeout while delivering a packet; requesting the departure confirmation for Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer) by MemberSet(Size=2, BitSetCount=2 Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) ) 2010-02-26 15:30:29.798/165.044 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=Cluster, member=5): Member departure confirmed by MemberSet(Size=2, BitSetCount=2 Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) Member(Id=6, Timestamp=2010-02-26 15:27:58.635, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) ); removing Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer) Eventually we are left with two distinct clusters consisting of Members 1, 2, 3 and Members 4, 5, 6, respectively. In the latter cluster, Member 4 is promoted to senior member. The connection between the two switches is restored at 15:33. Upon the restoration of the connection, the cluster members immediately receive cluster heartbeats from the two senior members. In the case of Members 1, 2, and 3, the following is logged: 2010-02-26 15:33:14.970/369.066 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=Cluster, member=1): The member formerly known as Member(Id=4, Timestamp=2010-02-26 15:30:35.341, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) has been forcefully evicted from the cluster, but continues to emit a cluster heartbeat; henceforth, the member will be shunned and its messages will be ignored. Likewise for Members 4, 5, and 6: 2010-02-26 15:33:14.343/336.890 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=Cluster, member=4): The member formerly known as Member(Id=1, Timestamp=2010-02-26 15:30:31.64, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) has been forcefully evicted from the cluster, but continues to emit a cluster heartbeat; henceforth, the member will be shunned and its messages will be ignored. This message indicates that a senior heartbeat is being received from members that were previously removed from the cluster, in other words, something that should not be possible. For this reason, the recipients of these messages will initially ignore them. After several iterations of these messages, the existence of multiple clusters is acknowledged, thus triggering the panic protocol to reconcile this situation. When the presence of more than one cluster (i.e. Split-Brain) is detected by a Coherence member, the panic protocol is invoked in order to resolve the conflicting clusters and consolidate into a single cluster. The protocol consists of the removal of smaller clusters until there is one cluster remaining. In the case of equal size clusters, the one with the older Senior Member will survive. Member 1, being the oldest member, initiates the protocol: 2010-02-26 15:33:45.970/400.066 Oracle Coherence GE 3.5.3/465p2 <Warning> (thread=Cluster, member=1): An existence of a cluster island with senior Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) containing 3 nodes have been detected. Since this Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) is the senior of an older cluster island, the panic protocol is being activated to stop the other island's senior and all junior nodes that belong to it. Member 3 receives the panic: 2010-02-26 15:33:45.803/382.336 Oracle Coherence GE 3.5.3/465p2 <Error> (thread=Cluster, member=3): Received panic from senior Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer) caused by Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer) Member 4, the senior member of the younger cluster, receives the kill message from Member 3: 2010-02-26 15:33:44.921/367.468 Oracle Coherence GE 3.5.3/465p2 <Error> (thread=Cluster, member=4): Received a Kill message from a valid Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer); stopping cluster service. In turn, Member 4 requests the departure of its junior members 5 and 6: 2010-02-26 15:33:44.921/367.468 Oracle Coherence GE 3.5.3/465p2 <Error> (thread=Cluster, member=4): Received a Kill message from a valid Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer); stopping cluster service. 2010-02-26 15:33:43.343/349.015 Oracle Coherence GE 3.5.3/465p2 <Error> (thread=Cluster, member=6): Received a Kill message from a valid Member(Id=4, Timestamp=2010-02-26 15:27:39.574, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer); stopping cluster service. Once Members 4, 5, and 6 restart, they rejoin the original cluster with senior member 1. The log below is from Member 4. Note that it receives a different member id when it rejoins the cluster. 2010-02-26 15:33:44.921/367.468 Oracle Coherence GE 3.5.3/465p2 <Error> (thread=Cluster, member=4): Received a Kill message from a valid Member(Id=3, Timestamp=2010-02-26 15:27:24.892, Address=10.149.155.236:8088, MachineId=1260, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:32459, Role=CoherenceServer); stopping cluster service. 2010-02-26 15:33:46.921/369.468 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Service Cluster left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Invocation:InvocationService, member=4): Service InvocationService left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=OptimisticCache, member=4): Service OptimisticCache left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=ReplicatedCache, member=4): Service ReplicatedCache left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=DistributedCache, member=4): Service DistributedCache left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Invocation:Management, member=4): Service Management left the cluster 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member 6 left service Management with senior member 5 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member 6 left service DistributedCache with senior member 5 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member 6 left service ReplicatedCache with senior member 5 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member 6 left service OptimisticCache with senior member 5 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member 6 left service InvocationService with senior member 5 2010-02-26 15:33:47.046/369.593 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=4): Member(Id=6, Timestamp=2010-02-26 15:33:47.046, Address=10.149.155.78:8088, MachineId=1102, Location=process:228, Role=CoherenceServer) left Cluster with senior member 4 2010-02-26 15:33:49.218/371.765 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=main, member=n/a): Restarting cluster 2010-02-26 15:33:49.421/371.968 Oracle Coherence GE 3.5.3/465p2 <D5> (thread=Cluster, member=n/a): Service Cluster joined the cluster with senior service member n/a 2010-02-26 15:33:49.625/372.172 Oracle Coherence GE 3.5.3/465p2 <Info> (thread=Cluster, member=n/a): This Member(Id=5, Timestamp=2010-02-26 15:33:50.499, Address=10.149.155.75:8088, MachineId=1099, Location=process:800, Role=CoherenceServer, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=1) joined cluster "cluster:0xDDEB" with senior Member(Id=1, Timestamp=2010-02-26 15:27:06.931, Address=10.149.155.76:8088, MachineId=1100, Location=site:usdhcp.oraclecorp.com,machine:dhcp-burlington6-4fl-east-10-149,process:511, Role=CoherenceServer, Edition=Grid Edition, Mode=Development, CpuCount=2, SocketCount=2) Cool isn't it?

  Read the article

• Configuring Cisco 877W router from scratch for DHCP, WiFi, ADSL2+, NAT

  - by David M Williams

  Hi all, I apologise if this is a BIG question but I am quite lost with the Cisco IOS. I know what I want to achieve just not how to do it :( I have a Cisco 877W router with 4 FastEthernet interfaces, 1 ATM interface and 1 802.11 Radio. I want to set it up for a small network and am trying to construct a configuration below. I was using Google to try and flesh it out but I think I need help and guidance from actual experts! If it helps, output from show ver says Cisco IOS software, C870 software (C870-ADVSECURITYK9-M), version 12.4(4)T7, release software (fc1) ROM: System bootstrap, version 12.3(8r)YI4, release software Here's what I have so far, which hopefully outlines clearly enough what I am wanting to do. The bits in angle brackets are placeholders (eg the secret password). ! ! Set router hostname ! hostname Shazam ! ! Set usernames and passwords ! username david privilege 15 secret 0 <PASSWORD> enable secret <SECRETPASSWORD> ! ! Configure SSH and telnet access ! line vty 0 4 privilege level 15 login local transport input telnet ssh ! ! Local logging ! logging buffered 51200 warning ! ! Set date and time for NSW, Australia (GMT +10h) ! ! ! Set router IP address to 192.168.1.1 on FastEthernet0 port ! interface FastEthernet0 ip address 192.168.1.1 255.255.255.0 no shut ip nat inside ! ! Forward any unknown DNS requests to Google ! ip dns server ip name-server 8.8.8.8 ip name-server 8.8.4.4 ! ! Set up DHCP ! DHCP pool covers 192.168.1.100 - .199 ! Set gateway and DNS server to be the router, ie 192.168.1.1 ! service dhcp ip routing ip dhcp excluded-address 192.168.1.1 192.168.1.99 ip dhcp excluded-address 192.168.1.200 192.168.1.255 ip dhcp pool <DHCPPOOLNAME> network 192.168.1.0 255.255.255.0 default-router 192.168.1.1 dns-server 192.168.1.1 lease 7 ! ! DHCP reservations ! ! Assign IP address 192.168.1.105 to MAC address 00-21-5D-2F-58-04 ! ! Configure ADSL2 connection details ! interface atm dsl operating-mode adsl2+ ! ! Set up NAT rules ! ! Forward port 35394 to 192.168.1.105 ! ! Set up WiFi ! ! SSID visible, WPA2 security, Pre-shared key I'm hoping most of this is boiler-plate stuff to you guys. I'm keen to not just get a working script but to actually understand it also. Unfortunately, I'm finding the Cisco reference material online very complex. Thank you!

  Read the article

• Improving Partitioned Table Join Performance

  - by Paul White

  The query optimizer does not always choose an optimal strategy when joining partitioned tables. This post looks at an example, showing how a manual rewrite of the query can almost double performance, while reducing the memory grant to almost nothing. Test Data The two tables in this example use a common partitioning partition scheme. The partition function uses 41 equal-size partitions: CREATE PARTITION FUNCTION PFT (integer) AS RANGE RIGHT FOR VALUES ( 125000, 250000, 375000, 500000, 625000, 750000, 875000, 1000000, 1125000, 1250000, 1375000, 1500000, 1625000, 1750000, 1875000, 2000000, 2125000, 2250000, 2375000, 2500000, 2625000, 2750000, 2875000, 3000000, 3125000, 3250000, 3375000, 3500000, 3625000, 3750000, 3875000, 4000000, 4125000, 4250000, 4375000, 4500000, 4625000, 4750000, 4875000, 5000000 ); GO CREATE PARTITION SCHEME PST AS PARTITION PFT ALL TO ([PRIMARY]); There two tables are: CREATE TABLE dbo.T1 ( TID integer NOT NULL IDENTITY(0,1), Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T1 PRIMARY KEY CLUSTERED (TID) ON PST (TID) );   CREATE TABLE dbo.T2 ( TID integer NOT NULL, Column1 integer NOT NULL, Padding binary(100) NOT NULL DEFAULT 0x,   CONSTRAINT PK_T2 PRIMARY KEY CLUSTERED (TID, Column1) ON PST (TID) ); The next script loads 5 million rows into T1 with a pseudo-random value between 1 and 5 for Column1. The table is partitioned on the IDENTITY column TID: INSERT dbo.T1 WITH (TABLOCKX) (Column1) SELECT (ABS(CHECKSUM(NEWID())) % 5) + 1 FROM dbo.Numbers AS N WHERE n BETWEEN 1 AND 5000000; In case you don’t already have an auxiliary table of numbers lying around, here’s a script to create one with 10 million rows: CREATE TABLE dbo.Numbers (n bigint PRIMARY KEY);   WITH L0 AS(SELECT 1 AS c UNION ALL SELECT 1), L1 AS(SELECT 1 AS c FROM L0 AS A CROSS JOIN L0 AS B), L2 AS(SELECT 1 AS c FROM L1 AS A CROSS JOIN L1 AS B), L3 AS(SELECT 1 AS c FROM L2 AS A CROSS JOIN L2 AS B), L4 AS(SELECT 1 AS c FROM L3 AS A CROSS JOIN L3 AS B), L5 AS(SELECT 1 AS c FROM L4 AS A CROSS JOIN L4 AS B), Nums AS(SELECT ROW_NUMBER() OVER (ORDER BY (SELECT NULL)) AS n FROM L5) INSERT dbo.Numbers WITH (TABLOCKX) SELECT TOP (10000000) n FROM Nums ORDER BY n OPTION (MAXDOP 1); Table T1 contains data like this: Next we load data into table T2. The relationship between the two tables is that table 2 contains ‘n’ rows for each row in table 1, where ‘n’ is determined by the value in Column1 of table T1. There is nothing particularly special about the data or distribution, by the way. INSERT dbo.T2 WITH (TABLOCKX) (TID, Column1) SELECT T.TID, N.n FROM dbo.T1 AS T JOIN dbo.Numbers AS N ON N.n >= 1 AND N.n <= T.Column1; Table T2 ends up containing about 15 million rows: The primary key for table T2 is a combination of TID and Column1. The data is partitioned according to the value in column TID alone. Partition Distribution The following query shows the number of rows in each partition of table T1: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T1 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are 40 partitions containing 125,000 rows (40 * 125k = 5m rows). The rightmost partition remains empty. The next query shows the distribution for table 2: SELECT PartitionID = CA1.P, NumRows = COUNT_BIG(*) FROM dbo.T2 AS T CROSS APPLY (VALUES ($PARTITION.PFT(TID))) AS CA1 (P) GROUP BY CA1.P ORDER BY CA1.P; There are roughly 375,000 rows in each partition (the rightmost partition is also empty): Ok, that’s the test data done. Test Query and Execution Plan The task is to count the rows resulting from joining tables 1 and 2 on the TID column: SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; The optimizer chooses a plan using parallel hash join, and partial aggregation: The Plan Explorer plan tree view shows accurate cardinality estimates and an even distribution of rows across threads (click to enlarge the image): With a warm data cache, the STATISTICS IO output shows that no physical I/O was needed, and all 41 partitions were touched: Running the query without actual execution plan or STATISTICS IO information for maximum performance, the query returns in around 2600ms. Execution Plan Analysis The first step toward improving on the execution plan produced by the query optimizer is to understand how it works, at least in outline. The two parallel Clustered Index Scans use multiple threads to read rows from tables T1 and T2. Parallel scan uses a demand-based scheme where threads are given page(s) to scan from the table as needed. This arrangement has certain important advantages, but does result in an unpredictable distribution of rows amongst threads. The point is that multiple threads cooperate to scan the whole table, but it is impossible to predict which rows end up on which threads. For correct results from the parallel hash join, the execution plan has to ensure that rows from T1 and T2 that might join are processed on the same thread. For example, if a row from T1 with join key value ‘1234’ is placed in thread 5’s hash table, the execution plan must guarantee that any rows from T2 that also have join key value ‘1234’ probe thread 5’s hash table for matches. The way this guarantee is enforced in this parallel hash join plan is by repartitioning rows to threads after each parallel scan. The two repartitioning exchanges route rows to threads using a hash function over the hash join keys. The two repartitioning exchanges use the same hash function so rows from T1 and T2 with the same join key must end up on the same hash join thread. Expensive Exchanges This business of repartitioning rows between threads can be very expensive, especially if a large number of rows is involved. The execution plan selected by the optimizer moves 5 million rows through one repartitioning exchange and around 15 million across the other. As a first step toward removing these exchanges, consider the execution plan selected by the optimizer if we join just one partition from each table, disallowing parallelism: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = 1 AND $PARTITION.PFT(T2.TID) = 1 OPTION (MAXDOP 1); The optimizer has chosen a (one-to-many) merge join instead of a hash join. The single-partition query completes in around 100ms. If everything scaled linearly, we would expect that extending this strategy to all 40 populated partitions would result in an execution time around 4000ms. Using parallelism could reduce that further, perhaps to be competitive with the parallel hash join chosen by the optimizer. This raises a question. If the most efficient way to join one partition from each of the tables is to use a merge join, why does the optimizer not choose a merge join for the full query? Forcing a Merge Join Let’s force the optimizer to use a merge join on the test query using a hint: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN); This is the execution plan selected by the optimizer: This plan results in the same number of logical reads reported previously, but instead of 2600ms the query takes 5000ms. The natural explanation for this drop in performance is that the merge join plan is only using a single thread, whereas the parallel hash join plan could use multiple threads. Parallel Merge Join We can get a parallel merge join plan using the same query hint as before, and adding trace flag 8649: SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (MERGE JOIN, QUERYTRACEON 8649); The execution plan is: This looks promising. It uses a similar strategy to distribute work across threads as seen for the parallel hash join. In practice though, performance is disappointing. On a typical run, the parallel merge plan runs for around 8400ms; slower than the single-threaded merge join plan (5000ms) and much worse than the 2600ms for the parallel hash join. We seem to be going backwards! The logical reads for the parallel merge are still exactly the same as before, with no physical IOs. The cardinality estimates and thread distribution are also still very good (click to enlarge): A big clue to the reason for the poor performance is shown in the wait statistics (captured by Plan Explorer Pro): CXPACKET waits require careful interpretation, and are most often benign, but in this case excessive waiting occurs at the repartitioning exchanges. Unlike the parallel hash join, the repartitioning exchanges in this plan are order-preserving ‘merging’ exchanges (because merge join requires ordered inputs): Parallelism works best when threads can just grab any available unit of work and get on with processing it. Preserving order introduces inter-thread dependencies that can easily lead to significant waits occurring. In extreme cases, these dependencies can result in an intra-query deadlock, though the details of that will have to wait for another time to explore in detail. The potential for waits and deadlocks leads the query optimizer to cost parallel merge join relatively highly, especially as the degree of parallelism (DOP) increases. This high costing resulted in the optimizer choosing a serial merge join rather than parallel in this case. The test results certainly confirm its reasoning. Collocated Joins In SQL Server 2008 and later, the optimizer has another available strategy when joining tables that share a common partition scheme. This strategy is a collocated join, also known as as a per-partition join. It can be applied in both serial and parallel execution plans, though it is limited to 2-way joins in the current optimizer. Whether the optimizer chooses a collocated join or not depends on cost estimation. The primary benefits of a collocated join are that it eliminates an exchange and requires less memory, as we will see next. Costing and Plan Selection The query optimizer did consider a collocated join for our original query, but it was rejected on cost grounds. The parallel hash join with repartitioning exchanges appeared to be a cheaper option. There is no query hint to force a collocated join, so we have to mess with the costing framework to produce one for our test query. Pretending that IOs cost 50 times more than usual is enough to convince the optimizer to use collocated join with our test query: -- Pretend IOs are 50x cost temporarily DBCC SETIOWEIGHT(50);   -- Co-located hash join SELECT COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID OPTION (RECOMPILE);   -- Reset IO costing DBCC SETIOWEIGHT(1); Collocated Join Plan The estimated execution plan for the collocated join is: The Constant Scan contains one row for each partition of the shared partitioning scheme, from 1 to 41. The hash repartitioning exchanges seen previously are replaced by a single Distribute Streams exchange using Demand partitioning. Demand partitioning means that the next partition id is given to the next parallel thread that asks for one. My test machine has eight logical processors, and all are available for SQL Server to use. As a result, there are eight threads in the single parallel branch in this plan, each processing one partition from each table at a time. Once a thread finishes processing a partition, it grabs a new partition number from the Distribute Streams exchange…and so on until all partitions have been processed. It is important to understand that the parallel scans in this plan are different from the parallel hash join plan. Although the scans have the same parallelism icon, tables T1 and T2 are not being co-operatively scanned by multiple threads in the same way. Each thread reads a single partition of T1 and performs a hash match join with the same partition from table T2. The properties of the two Clustered Index Scans show a Seek Predicate (unusual for a scan!) limiting the rows to a single partition: The crucial point is that the join between T1 and T2 is on TID, and TID is the partitioning column for both tables. A thread that processes partition ‘n’ is guaranteed to see all rows that can possibly join on TID for that partition. In addition, no other thread will see rows from that partition, so this removes the need for repartitioning exchanges. CPU and Memory Efficiency Improvements The collocated join has removed two expensive repartitioning exchanges and added a single exchange processing 41 rows (one for each partition id). Remember, the parallel hash join plan exchanges had to process 5 million and 15 million rows. The amount of processor time spent on exchanges will be much lower in the collocated join plan. In addition, the collocated join plan has a maximum of 8 threads processing single partitions at any one time. The 41 partitions will all be processed eventually, but a new partition is not started until a thread asks for it. Threads can reuse hash table memory for the new partition. The parallel hash join plan also had 8 hash tables, but with all 5,000,000 build rows loaded at the same time. The collocated plan needs memory for only 8 * 125,000 = 1,000,000 rows at any one time. Collocated Hash Join Performance The collated join plan has disappointing performance in this case. The query runs for around 25,300ms despite the same IO statistics as usual. This is much the worst result so far, so what went wrong? It turns out that cardinality estimation for the single partition scans of table T1 is slightly low. The properties of the Clustered Index Scan of T1 (graphic immediately above) show the estimation was for 121,951 rows. This is a small shortfall compared with the 125,000 rows actually encountered, but it was enough to cause the hash join to spill to physical tempdb: A level 1 spill doesn’t sound too bad, until you realize that the spill to tempdb probably occurs for each of the 41 partitions. As a side note, the cardinality estimation error is a little surprising because the system tables accurately show there are 125,000 rows in every partition of T1. Unfortunately, the optimizer uses regular column and index statistics to derive cardinality estimates here rather than system table information (e.g. sys.partitions). Collocated Merge Join We will never know how well the collocated parallel hash join plan might have worked without the cardinality estimation error (and the resulting 41 spills to tempdb) but we do know: Merge join does not require a memory grant; and Merge join was the optimizer’s preferred join option for a single partition join Putting this all together, what we would really like to see is the same collocated join strategy, but using merge join instead of hash join. Unfortunately, the current query optimizer cannot produce a collocated merge join; it only knows how to do collocated hash join. So where does this leave us? CROSS APPLY sys.partitions We can try to write our own collocated join query. We can use sys.partitions to find the partition numbers, and CROSS APPLY to get a count per partition, with a final step to sum the partial counts. The following query implements this idea: SELECT row_count = SUM(Subtotals.cnt) FROM ( -- Partition numbers SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1 ) AS P CROSS APPLY ( -- Count per collocated join SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals; The estimated plan is: The cardinality estimates aren’t all that good here, especially the estimate for the scan of the system table underlying the sys.partitions view. Nevertheless, the plan shape is heading toward where we would like to be. Each partition number from the system table results in a per-partition scan of T1 and T2, a one-to-many Merge Join, and a Stream Aggregate to compute the partial counts. The final Stream Aggregate just sums the partial counts. Execution time for this query is around 3,500ms, with the same IO statistics as always. This compares favourably with 5,000ms for the serial plan produced by the optimizer with the OPTION (MERGE JOIN) hint. This is another case of the sum of the parts being less than the whole – summing 41 partial counts from 41 single-partition merge joins is faster than a single merge join and count over all partitions. Even so, this single-threaded collocated merge join is not as quick as the original parallel hash join plan, which executed in 2,600ms. On the positive side, our collocated merge join uses only one logical processor and requires no memory grant. The parallel hash join plan used 16 threads and reserved 569 MB of memory:   Using a Temporary Table Our collocated merge join plan should benefit from parallelism. The reason parallelism is not being used is that the query references a system table. We can work around that by writing the partition numbers to a temporary table (or table variable): SET STATISTICS IO ON; DECLARE @s datetime2 = SYSUTCDATETIME();   CREATE TABLE #P ( partition_number integer PRIMARY KEY);   INSERT #P (partition_number) SELECT p.partition_number FROM sys.partitions AS p WHERE p.[object_id] = OBJECT_ID(N'T1', N'U') AND p.index_id = 1;   SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals;   DROP TABLE #P;   SELECT DATEDIFF(Millisecond, @s, SYSUTCDATETIME()); SET STATISTICS IO OFF; Using the temporary table adds a few logical reads, but the overall execution time is still around 3500ms, indistinguishable from the same query without the temporary table. The problem is that the query optimizer still doesn’t choose a parallel plan for this query, though the removal of the system table reference means that it could if it chose to: In fact the optimizer did enter the parallel plan phase of query optimization (running search 1 for a second time): Unfortunately, the parallel plan found seemed to be more expensive than the serial plan. This is a crazy result, caused by the optimizer’s cost model not reducing operator CPU costs on the inner side of a nested loops join. Don’t get me started on that, we’ll be here all night. In this plan, everything expensive happens on the inner side of a nested loops join. Without a CPU cost reduction to compensate for the added cost of exchange operators, candidate parallel plans always look more expensive to the optimizer than the equivalent serial plan. Parallel Collocated Merge Join We can produce the desired parallel plan using trace flag 8649 again: SELECT row_count = SUM(Subtotals.cnt) FROM #P AS p CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: One difference between this plan and the collocated hash join plan is that a Repartition Streams exchange operator is used instead of Distribute Streams. The effect is similar, though not quite identical. The Repartition uses round-robin partitioning, meaning the next partition id is pushed to the next thread in sequence. The Distribute Streams exchange seen earlier used Demand partitioning, meaning the next partition id is pulled across the exchange by the next thread that is ready for more work. There are subtle performance implications for each partitioning option, but going into that would again take us too far off the main point of this post. Performance The important thing is the performance of this parallel collocated merge join – just 1350ms on a typical run. The list below shows all the alternatives from this post (all timings include creation, population, and deletion of the temporary table where appropriate) from quickest to slowest: Collocated parallel merge join: 1350ms Parallel hash join: 2600ms Collocated serial merge join: 3500ms Serial merge join: 5000ms Parallel merge join: 8400ms Collated parallel hash join: 25,300ms (hash spill per partition) The parallel collocated merge join requires no memory grant (aside from a paltry 1.2MB used for exchange buffers). This plan uses 16 threads at DOP 8; but 8 of those are (rather pointlessly) allocated to the parallel scan of the temporary table. These are minor concerns, but it turns out there is a way to address them if it bothers you. Parallel Collocated Merge Join with Demand Partitioning This final tweak replaces the temporary table with a hard-coded list of partition ids (dynamic SQL could be used to generate this query from sys.partitions): SELECT row_count = SUM(Subtotals.cnt) FROM ( VALUES (1),(2),(3),(4),(5),(6),(7),(8),(9),(10), (11),(12),(13),(14),(15),(16),(17),(18),(19),(20), (21),(22),(23),(24),(25),(26),(27),(28),(29),(30), (31),(32),(33),(34),(35),(36),(37),(38),(39),(40),(41) ) AS P (partition_number) CROSS APPLY ( SELECT cnt = COUNT_BIG(*) FROM dbo.T1 AS T1 JOIN dbo.T2 AS T2 ON T2.TID = T1.TID WHERE $PARTITION.PFT(T1.TID) = p.partition_number AND $PARTITION.PFT(T2.TID) = p.partition_number ) AS SubTotals OPTION (QUERYTRACEON 8649); The actual execution plan is: The parallel collocated hash join plan is reproduced below for comparison: The manual rewrite has another advantage that has not been mentioned so far: the partial counts (per partition) can be computed earlier than the partial counts (per thread) in the optimizer’s collocated join plan. The earlier aggregation is performed by the extra Stream Aggregate under the nested loops join. The performance of the parallel collocated merge join is unchanged at around 1350ms. Final Words It is a shame that the current query optimizer does not consider a collocated merge join (Connect item closed as Won’t Fix). The example used in this post showed an improvement in execution time from 2600ms to 1350ms using a modestly-sized data set and limited parallelism. In addition, the memory requirement for the query was almost completely eliminated  – down from 569MB to 1.2MB. The problem with the parallel hash join selected by the optimizer is that it attempts to process the full data set all at once (albeit using eight threads). It requires a large memory grant to hold all 5 million rows from table T1 across the eight hash tables, and does not take advantage of the divide-and-conquer opportunity offered by the common partitioning. The great thing about the collocated join strategies is that each parallel thread works on a single partition from both tables, reading rows, performing the join, and computing a per-partition subtotal, before moving on to a new partition. From a thread’s point of view… If you have trouble visualizing what is happening from just looking at the parallel collocated merge join execution plan, let’s look at it again, but from the point of view of just one thread operating between the two Parallelism (exchange) operators. Our thread picks up a single partition id from the Distribute Streams exchange, and starts a merge join using ordered rows from partition 1 of table T1 and partition 1 of table T2. By definition, this is all happening on a single thread. As rows join, they are added to a (per-partition) count in the Stream Aggregate immediately above the Merge Join. Eventually, either T1 (partition 1) or T2 (partition 1) runs out of rows and the merge join stops. The per-partition count from the aggregate passes on through the Nested Loops join to another Stream Aggregate, which is maintaining a per-thread subtotal. Our same thread now picks up a new partition id from the exchange (say it gets id 9 this time). The count in the per-partition aggregate is reset to zero, and the processing of partition 9 of both tables proceeds just as it did for partition 1, and on the same thread. Each thread picks up a single partition id and processes all the data for that partition, completely independently from other threads working on other partitions. One thread might eventually process partitions (1, 9, 17, 25, 33, 41) while another is concurrently processing partitions (2, 10, 18, 26, 34) and so on for the other six threads at DOP 8. The point is that all 8 threads can execute independently and concurrently, continuing to process new partitions until the wider job (of which the thread has no knowledge!) is done. This divide-and-conquer technique can be much more efficient than simply splitting the entire workload across eight threads all at once. Related Reading Understanding and Using Parallelism in SQL Server Parallel Execution Plans Suck © 2013 Paul White – All Rights Reserved Twitter: @SQL_Kiwi

  Read the article

• Find More Streaming TV Online with Clicker.tv

  - by DigitalGeekery

  Looking for a way to access more of your favorite TV Shows and other online entertainment? Today we’ll take a look at Clicker.tv which offers an awesome way to find tons of TV programs and movies. Clicker.tv Clicker.tv is an HTML5 web application that indexes both free and premium content from sources like Hulu, Netflix, Amazon, iTunes, and more. Some movies or episodes, such as those from Netflix and Amazon.com’s Video on Demand, will require viewers to have a membership, or pay a fee to access content. There is also a Clicker.tv app for Boxee.   Navigation Navigating in Clicker.tv is rather easy with your keyboard. Directional Keys: navigate up, down, left, and right. Enter: make a selection Backspace: return to previous screen Escape: return to the Clicker.tv home screen. Note: You can also navigate through Clicker.tv with your PC remote. Recommended Browsers Firefox 3.6 + Safari 4.0 + Internet Explorer 8 + Google Chrome Note: You’ll need the latest version of Flash installed to play the majority of content. Earlier versions of the above browsers may work, but for full keyboard functionality, stick with the recommendations. Using Clicker.tv The first time you go to Clicker.tv, (link below) you’ll be met with a welcome screen and some helpful hints. Click Enter when finished.   The Home screen feature Headliners, Trending Shows, and Trending Episodes. You can scroll through the different options and category links along the left side.   The Search link pulls up an onscreen keyboard so you can enter search terms with a remote as well as a keyboard. Type in your search terms and matching items are displayed on the screen.   You can also browse by a wide variety of categories. Select TV to browse only available TV programs. Or, browse only Movies in the movie category. There are also links for Web content and Music.   Creating an Account You can access all Clicker.tv content without an account, but a Clicker account allows users to create playlists and subscribe to shows and have them automatically added to their playlist. You’ll need to go to Clicker.com and create an account. You’ll find the link at the upper right of the page. Enter a username, password and email address. There also an option to link with Facebook, or you can simply Skip this step.   Go to Clicker.tv and sign in. You can manually type in your credentials or use the onscreen keyboard with your remote.   Settings If you’d prefer not to display content from premium sites or Netflix, you can remove them through the Settings. Toggle Amazon, iTunes and Netflix on or off.   Watching Episodes To watch an episode, select the image to begin playing from the default source, or select one of the other options. You can see in the example below that you can choose to watch the episode from Fox, Hulu, or Amazon Video on Demand.   Your episode will then launch and begin playing from your chosen source. If you choose a premium content source such as iTunes or Amazon’s VOD, you’ll be taken to the Amazon’s website or iTunes and prompted to purchase the content.   Playlists Once you’ve created an account and signed in, you can begin adding Shows to your playlist. Choose a series and select Add to Playlist.   You’ll see in the example below that Family Guy has been Added and the number 142 is shown next to the playlist icon to indicate that 142 episodes has been added to your playlist. Underneath the listings for each episode in your playlist you can mark as Watched, or Remove individual episodes.   You can also view the playlist or make any changes from the Clicker.com website. Click on “Playlist” on the top right of the Clicker.com site to access your playlists. You can select individual episodes from your playlists, remove them, or mark them as watched or unwatched. Clicker.TV and Boxee Boxee offers a Clicker.TV app that features a limited amount of the Clicker.TV content. You’ll find Clicker.TV located in the Boxee Apps Library. Select the Clicker App and then choose Start. From the Clicker App interface you can search or browse for available content. Select an episode you’d like to view… Then select play in the pop up window. You can also add it to your Boxee queue, share it, or add a shortcut, just as you can from other Boxee apps. When you click play your episode will launch and begin playing in Boxee. Conclusion Clicker.TV is currently still in Beta and has some limitations. Typical remotes won’t work completely in all external websites. So, you’ll still need a keyboard to be able to perform some operations such as switching to full screen mode. The Boxee app offers a more fully remote friendly environment, but unfortunately lacks a good portion of the Clicker.tv content. As with many content sites, availability of certain programming may be limited by your geographic location. Want to add Clicker.TV functionality to Windows Media Center? You can do so through the Boxee Integration for Windows 7 Media Center plug-in. Clicker.tv Clicker.com Similar Articles Productive Geek Tips Share Digital Media With Other Computers on a Home Network with Windows 7Stream Music and Video Over the Internet with Windows Media Player 12Listen to Online Radio with AntennaEnable Media Streaming in Windows Home Server to Windows Media PlayerNorton Internet Security 2010 [Review] TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips HippoRemote Pro 2.2 Xobni Plus for Outlook All My Movies 5.9 CloudBerry Online Backup 1.5 for Windows Home Server Nice Websites To Watch TV Shows Online 24 Million Sites Windows Media Player Glass Icons (icons we like) How to Forecast Weather, without Gadgets Outlook Tools, one stop tweaking for any Outlook version Zoofs, find the most popular tweeted YouTube videos

  Read the article

• [MINI HOW-TO] Change the Default Color Scheme in Office 2010

  - by Mysticgeek

  Like in Office 2007 the default color scheme for 2010 is blue. If you are not a fan of it, here we show you how to change it to silver or black. In this example we are using Microsoft Word, but it works the same way in Excel, Outlook, and PowerPoint as well. Once you change the color scheme in one Office application, it will change it for all of the other apps in the suite. Change Color Scheme To change the color scheme click on the File tab to access Backstage View and click on Options. In Word Options the General section should open by default…use the dropdown menu next to Color Scheme to change it to Silver, Blue, or Black then click OK. Here is what Black looks like…who knows why Microsoft decided to leave the blue around the edges. This is the default Blue color scheme… And finally we take a look at the Silver color scheme in Excel… That is all there is to it! It would be nice if they would incorporate other color schemes to Office 2010, as some of you may not be happy with only three choices. If you’re using Office 2007 check out our article on how to change the color scheme in it. Also, The Geek has a cool article on how to set the Color Scheme of Office 2007 with a quick registry hack. Similar Articles Productive Geek Tips Set the Office 2007 Color Scheme With a Quick Registry HackChange The Default Color Scheme In Office 2007Maximize Space by "Auto-Hiding" the Ribbon in Office 2007How To Personalize the Windows Command PromptOrganize & Group Your Tabs in Firefox the Easy Way TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips Xobni Plus for Outlook All My Movies 5.9 CloudBerry Online Backup 1.5 for Windows Home Server Snagit 10 2010 World Cup Schedule Boot Snooze – Reboot and then Standby or Hibernate Customize Everything Related to Dates, Times, Currency and Measurement in Windows 7 Google Earth replacement Icon (Icons we like) Build Great Charts in Excel with Chart Advisor tinysong gives a shortened URL for you to post on Twitter (or anywhere)

  Read the article

• Toorcon 15 (2013)

  - by danx

  The Toorcon gang (senior staff): h1kari (founder), nfiltr8, and Geo Introduction to Toorcon 15 (2013) A Tale of One Software Bypass of MS Windows 8 Secure Boot Breaching SSL, One Byte at a Time Running at 99%: Surviving an Application DoS Security Response in the Age of Mass Customized Attacks x86 Rewriting: Defeating RoP and other Shinanighans Clowntown Express: interesting bugs and running a bug bounty program Active Fingerprinting of Encrypted VPNs Making Attacks Go Backwards Mask Your Checksums—The Gorry Details Adventures with weird machines thirty years after "Reflections on Trusting Trust" Introduction to Toorcon 15 (2013) Toorcon 15 is the 15th annual security conference held in San Diego. I've attended about a third of them and blogged about previous conferences I attended here starting in 2003. As always, I've only summarized the talks I attended and interested me enough to write about them. Be aware that I may have misrepresented the speaker's remarks and that they are not my remarks or opinion, or those of my employer, so don't quote me or them. Those seeking further details may contact the speakers directly or use The Google. For some talks, I have a URL for further information. A Tale of One Software Bypass of MS Windows 8 Secure Boot Andrew Furtak and Oleksandr Bazhaniuk Yuri Bulygin, Oleksandr ("Alex") Bazhaniuk, and (not present) Andrew Furtak Yuri and Alex talked about UEFI and Bootkits and bypassing MS Windows 8 Secure Boot, with vendor recommendations. They previously gave this talk at the BlackHat 2013 conference. MS Windows 8 Secure Boot Overview UEFI (Unified Extensible Firmware Interface) is interface between hardware and OS. UEFI is processor and architecture independent. Malware can replace bootloader (bootx64.efi, bootmgfw.efi). Once replaced can modify kernel. Trivial to replace bootloader. Today many legacy bootkits—UEFI replaces them most of them. MS Windows 8 Secure Boot verifies everything you load, either through signatures or hashes. UEFI firmware relies on secure update (with signed update). You would think Secure Boot would rely on ROM (such as used for phones0, but you can't do that for PCs—PCs use writable memory with signatures DXE core verifies the UEFI boat loader(s) OS Loader (winload.efi, winresume.efi) verifies the OS kernel A chain of trust is established with a root key (Platform Key, PK), which is a cert belonging to the platform vendor. Key Exchange Keys (KEKs) verify an "authorized" database (db), and "forbidden" database (dbx). X.509 certs with SHA-1/SHA-256 hashes. Keys are stored in non-volatile (NV) flash-based NVRAM. Boot Services (BS) allow adding/deleting keys (can't be accessed once OS starts—which uses Run-Time (RT)). Root cert uses RSA-2048 public keys and PKCS#7 format signatures. SecureBoot — enable disable image signature checks SetupMode — update keys, self-signed keys, and secure boot variables CustomMode — allows updating keys Secure Boot policy settings are: always execute, never execute, allow execute on security violation, defer execute on security violation, deny execute on security violation, query user on security violation Attacking MS Windows 8 Secure Boot Secure Boot does NOT protect from physical access. Can disable from console. Each BIOS vendor implements Secure Boot differently. There are several platform and BIOS vendors. It becomes a "zoo" of implementations—which can be taken advantage of. Secure Boot is secure only when all vendors implement it correctly. Allow only UEFI firmware signed updates protect UEFI firmware from direct modification in flash memory protect FW update components program SPI controller securely protect secure boot policy settings in nvram protect runtime api disable compatibility support module which allows unsigned legacy Can corrupt the Platform Key (PK) EFI root certificate variable in SPI flash. If PK is not found, FW enters setup mode wich secure boot turned off. Can also exploit TPM in a similar manner. One is not supposed to be able to directly modify the PK in SPI flash from the OS though. But they found a bug that they can exploit from User Mode (undisclosed) and demoed the exploit. It loaded and ran their own bootkit. The exploit requires a reboot. Multiple vendors are vulnerable. They will disclose this exploit to vendors in the future. Recommendations: allow only signed updates protect UEFI fw in ROM protect EFI variable store in ROM Breaching SSL, One Byte at a Time Yoel Gluck and Angelo Prado Angelo Prado and Yoel Gluck, Salesforce.com CRIME is software that performs a "compression oracle attack." This is possible because the SSL protocol doesn't hide length, and because SSL compresses the header. CRIME requests with every possible character and measures the ciphertext length. Look for the plaintext which compresses the most and looks for the cookie one byte-at-a-time. SSL Compression uses LZ77 to reduce redundancy. Huffman coding replaces common byte sequences with shorter codes. US CERT thinks the SSL compression problem is fixed, but it isn't. They convinced CERT that it wasn't fixed and they issued a CVE. BREACH, breachattrack.com BREACH exploits the SSL response body (Accept-Encoding response, Content-Encoding). It takes advantage of the fact that the response is not compressed. BREACH uses gzip and needs fairly "stable" pages that are static for ~30 seconds. It needs attacker-supplied content (say from a web form or added to a URL parameter). BREACH listens to a session's requests and responses, then inserts extra requests and responses. Eventually, BREACH guesses a session's secret key. Can use compression to guess contents one byte at-a-time. For example, "Supersecret SupersecreX" (a wrong guess) compresses 10 bytes, and "Supersecret Supersecret" (a correct guess) compresses 11 bytes, so it can find each character by guessing every character. To start the guess, BREACH needs at least three known initial characters in the response sequence. Compression length then "leaks" information. Some roadblocks include no winners (all guesses wrong) or too many winners (multiple possibilities that compress the same). The solutions include: lookahead (guess 2 or 3 characters at-a-time instead of 1 character). Expensive rollback to last known conflict check compression ratio can brute-force first 3 "bootstrap" characters, if needed (expensive) block ciphers hide exact plain text length. Solution is to align response in advance to block size Mitigations length: use variable padding secrets: dynamic CSRF tokens per request secret: change over time separate secret to input-less servlets Future work eiter understand DEFLATE/GZIP HTTPS extensions Running at 99%: Surviving an Application DoS Ryan Huber Ryan Huber, Risk I/O Ryan first discussed various ways to do a denial of service (DoS) attack against web services. One usual method is to find a slow web page and do several wgets. Or download large files. Apache is not well suited at handling a large number of connections, but one can put something in front of it Can use Apache alternatives, such as nginx How to identify malicious hosts short, sudden web requests user-agent is obvious (curl, python) same url requested repeatedly no web page referer (not normal) hidden links. hide a link and see if a bot gets it restricted access if not your geo IP (unless the website is global) missing common headers in request regular timing first seen IP at beginning of attack count requests per hosts (usually a very large number) Use of captcha can mitigate attacks, but you'll lose a lot of genuine users. Bouncer, goo.gl/c2vyEc and www.github.com/rawdigits/Bouncer Bouncer is software written by Ryan in netflow. Bouncer has a small, unobtrusive footprint and detects DoS attempts. It closes blacklisted sockets immediately (not nice about it, no proper close connection). Aggregator collects requests and controls your web proxies. Need NTP on the front end web servers for clean data for use by bouncer. Bouncer is also useful for a popularity storm ("Slashdotting") and scraper storms. Future features: gzip collection data, documentation, consumer library, multitask, logging destroyed connections. Takeaways: DoS mitigation is easier with a complete picture Bouncer designed to make it easier to detect and defend DoS—not a complete cure Security Response in the Age of Mass Customized Attacks Peleus Uhley and Karthik Raman Peleus Uhley and Karthik Raman, Adobe ASSET, blogs.adobe.com/asset/ Peleus and Karthik talked about response to mass-customized exploits. Attackers behave much like a business. "Mass customization" refers to concept discussed in the book Future Perfect by Stan Davis of Harvard Business School. Mass customization is differentiating a product for an individual customer, but at a mass production price. For example, the same individual with a debit card receives basically the same customized ATM experience around the world. Or designing your own PC from commodity parts. Exploit kits are another example of mass customization. The kits support multiple browsers and plugins, allows new modules. Exploit kits are cheap and customizable. Organized gangs use exploit kits. A group at Berkeley looked at 77,000 malicious websites (Grier et al., "Manufacturing Compromise: The Emergence of Exploit-as-a-Service", 2012). They found 10,000 distinct binaries among them, but derived from only a dozen or so exploit kits. Characteristics of Mass Malware: potent, resilient, relatively low cost Technical characteristics: multiple OS, multipe payloads, multiple scenarios, multiple languages, obfuscation Response time for 0-day exploits has gone down from ~40 days 5 years ago to about ~10 days now. So the drive with malware is towards mass customized exploits, to avoid detection There's plenty of evicence that exploit development has Project Manager bureaucracy. They infer from the malware edicts to: support all versions of reader support all versions of windows support all versions of flash support all browsers write large complex, difficult to main code (8750 lines of JavaScript for example Exploits have "loose coupling" of multipe versions of software (adobe), OS, and browser. This allows specific attacks against specific versions of multiple pieces of software. Also allows exploits of more obscure software/OS/browsers and obscure versions. Gave examples of exploits that exploited 2, 3, 6, or 14 separate bugs. However, these complete exploits are more likely to be buggy or fragile in themselves and easier to defeat. Future research includes normalizing malware and Javascript. Conclusion: The coming trend is that mass-malware with mass zero-day attacks will result in mass customization of attacks. x86 Rewriting: Defeating RoP and other Shinanighans Richard Wartell Richard Wartell The attack vector we are addressing here is: First some malware causes a buffer overflow. The malware has no program access, but input access and buffer overflow code onto stack Later the stack became non-executable. The workaround malware used was to write a bogus return address to the stack jumping to malware Later came ASLR (Address Space Layout Randomization) to randomize memory layout and make addresses non-deterministic. The workaround malware used was to jump t existing code segments in the program that can be used in bad ways "RoP" is Return-oriented Programming attacks. RoP attacks use your own code and write return address on stack to (existing) expoitable code found in program ("gadgets"). Pinkie Pie was paid $60K last year for a RoP attack. One solution is using anti-RoP compilers that compile source code with NO return instructions. ASLR does not randomize address space, just "gadgets". IPR/ILR ("Instruction Location Randomization") randomizes each instruction with a virtual machine. Richard's goal was to randomize a binary with no source code access. He created "STIR" (Self-Transofrming Instruction Relocation). STIR disassembles binary and operates on "basic blocks" of code. The STIR disassembler is conservative in what to disassemble. Each basic block is moved to a random location in memory. Next, STIR writes new code sections with copies of "basic blocks" of code in randomized locations. The old code is copied and rewritten with jumps to new code. the original code sections in the file is marked non-executible. STIR has better entropy than ASLR in location of code. Makes brute force attacks much harder. STIR runs on MS Windows (PEM) and Linux (ELF). It eliminated 99.96% or more "gadgets" (i.e., moved the address). Overhead usually 5-10% on MS Windows, about 1.5-4% on Linux (but some code actually runs faster!). The unique thing about STIR is it requires no source access and the modified binary fully works! Current work is to rewrite code to enforce security policies. For example, don't create a *.{exe,msi,bat} file. Or don't connect to the network after reading from the disk. Clowntown Express: interesting bugs and running a bug bounty program Collin Greene Collin Greene, Facebook Collin talked about Facebook's bug bounty program. Background at FB: FB has good security frameworks, such as security teams, external audits, and cc'ing on diffs. But there's lots of "deep, dark, forgotten" parts of legacy FB code. Collin gave several examples of bountied bugs. Some bounty submissions were on software purchased from a third-party (but bounty claimers don't know and don't care). We use security questions, as does everyone else, but they are basically insecure (often easily discoverable). Collin didn't expect many bugs from the bounty program, but they ended getting 20+ good bugs in first 24 hours and good submissions continue to come in. Bug bounties bring people in with different perspectives, and are paid only for success. Bug bounty is a better use of a fixed amount of time and money versus just code review or static code analysis. The Bounty program started July 2011 and paid out $1.5 million to date. 14% of the submissions have been high priority problems that needed to be fixed immediately. The best bugs come from a small % of submitters (as with everything else)—the top paid submitters are paid 6 figures a year. Spammers like to backstab competitors. The youngest sumitter was 13. Some submitters have been hired. Bug bounties also allows to see bugs that were missed by tools or reviews, allowing improvement in the process. Bug bounties might not work for traditional software companies where the product has release cycle or is not on Internet. Active Fingerprinting of Encrypted VPNs Anna Shubina Anna Shubina, Dartmouth Institute for Security, Technology, and Society (I missed the start of her talk because another track went overtime. But I have the DVD of the talk, so I'll expand later) IPsec leaves fingerprints. Using netcat, one can easily visually distinguish various crypto chaining modes just from packet timing on a chart (example, DES-CBC versus AES-CBC) One can tell a lot about VPNs just from ping roundtrips (such as what router is used) Delayed packets are not informative about a network, especially if far away from the network More needed to explore about how TCP works in real life with respect to timing Making Attacks Go Backwards Fuzzynop FuzzyNop, Mandiant This talk is not about threat attribution (finding who), product solutions, politics, or sales pitches. But who are making these malware threats? It's not a single person or group—they have diverse skill levels. There's a lot of fat-fingered fumblers out there. Always look for low-hanging fruit first: "hiding" malware in the temp, recycle, or root directories creation of unnamed scheduled tasks obvious names of files and syscalls ("ClearEventLog") uncleared event logs. Clearing event log in itself, and time of clearing, is a red flag and good first clue to look for on a suspect system Reverse engineering is hard. Disassembler use takes practice and skill. A popular tool is IDA Pro, but it takes multiple interactive iterations to get a clean disassembly. Key loggers are used a lot in targeted attacks. They are typically custom code or built in a backdoor. A big tip-off is that non-printable characters need to be printed out (such as "[Ctrl]" "[RightShift]") or time stamp printf strings. Look for these in files. Presence is not proof they are used. Absence is not proof they are not used. Java exploits. Can parse jar file with idxparser.py and decomile Java file. Java typially used to target tech companies. Backdoors are the main persistence mechanism (provided externally) for malware. Also malware typically needs command and control. Application of Artificial Intelligence in Ad-Hoc Static Code Analysis John Ashaman John Ashaman, Security Innovation Initially John tried to analyze open source files with open source static analysis tools, but these showed thousands of false positives. Also tried using grep, but tis fails to find anything even mildly complex. So next John decided to write his own tool. His approach was to first generate a call graph then analyze the graph. However, the problem is that making a call graph is really hard. For example, one problem is "evil" coding techniques, such as passing function pointer. First the tool generated an Abstract Syntax Tree (AST) with the nodes created from method declarations and edges created from method use. Then the tool generated a control flow graph with the goal to find a path through the AST (a maze) from source to sink. The algorithm is to look at adjacent nodes to see if any are "scary" (a vulnerability), using heuristics for search order. The tool, called "Scat" (Static Code Analysis Tool), currently looks for C# vulnerabilities and some simple PHP. Later, he plans to add more PHP, then JSP and Java. For more information see his posts in Security Innovation blog and NRefactory on GitHub. Mask Your Checksums—The Gorry Details Eric (XlogicX) Davisson Eric (XlogicX) Davisson Sometimes in emailing or posting TCP/IP packets to analyze problems, you may want to mask the IP address. But to do this correctly, you need to mask the checksum too, or you'll leak information about the IP. Problem reports found in stackoverflow.com, sans.org, and pastebin.org are usually not masked, but a few companies do care. If only the IP is masked, the IP may be guessed from checksum (that is, it leaks data). Other parts of packet may leak more data about the IP. TCP and IP checksums both refer to the same data, so can get more bits of information out of using both checksums than just using one checksum. Also, one can usually determine the OS from the TTL field and ports in a packet header. If we get hundreds of possible results (16x each masked nibble that is unknown), one can do other things to narrow the results, such as look at packet contents for domain or geo information. With hundreds of results, can import as CSV format into a spreadsheet. Can corelate with geo data and see where each possibility is located. Eric then demoed a real email report with a masked IP packet attached. Was able to find the exact IP address, given the geo and university of the sender. Point is if you're going to mask a packet, do it right. Eric wouldn't usually bother, but do it correctly if at all, to not create a false impression of security. Adventures with weird machines thirty years after "Reflections on Trusting Trust" Sergey Bratus Sergey Bratus, Dartmouth College (and Julian Bangert and Rebecca Shapiro, not present) "Reflections on Trusting Trust" refers to Ken Thompson's classic 1984 paper. "You can't trust code that you did not totally create yourself." There's invisible links in the chain-of-trust, such as "well-installed microcode bugs" or in the compiler, and other planted bugs. Thompson showed how a compiler can introduce and propagate bugs in unmodified source. But suppose if there's no bugs and you trust the author, can you trust the code? Hell No! There's too many factors—it's Babylonian in nature. Why not? Well, Input is not well-defined/recognized (code's assumptions about "checked" input will be violated (bug/vunerabiliy). For example, HTML is recursive, but Regex checking is not recursive. Input well-formed but so complex there's no telling what it does For example, ELF file parsing is complex and has multiple ways of parsing. Input is seen differently by different pieces of program or toolchain Any Input is a program input executes on input handlers (drives state changes & transitions) only a well-defined execution model can be trusted (regex/DFA, PDA, CFG) Input handler either is a "recognizer" for the inputs as a well-defined language (see langsec.org) or it's a "virtual machine" for inputs to drive into pwn-age ELF ABI (UNIX/Linux executible file format) case study. Problems can arise from these steps (without planting bugs): compiler linker loader ld.so/rtld relocator DWARF (debugger info) exceptions The problem is you can't really automatically analyze code (it's the "halting problem" and undecidable). Only solution is to freeze code and sign it. But you can't freeze everything! Can't freeze ASLR or loading—must have tables and metadata. Any sufficiently complex input data is the same as VM byte code Example, ELF relocation entries + dynamic symbols == a Turing Complete Machine (TM). @bxsays created a Turing machine in Linux from relocation data (not code) in an ELF file. For more information, see Rebecca "bx" Shapiro's presentation from last year's Toorcon, "Programming Weird Machines with ELF Metadata" @bxsays did same thing with Mach-O bytecode Or a DWARF exception handling data .eh_frame + glibc == Turning Machine X86 MMU (IDT, GDT, TSS): used address translation to create a Turning Machine. Page handler reads and writes (on page fault) memory. Uses a page table, which can be used as Turning Machine byte code. Example on Github using this TM that will fly a glider across the screen Next Sergey talked about "Parser Differentials". That having one input format, but two parsers, will create confusion and opportunity for exploitation. For example, CSRs are parsed during creation by cert requestor and again by another parser at the CA. Another example is ELF—several parsers in OS tool chain, which are all different. Can have two different Program Headers (PHDRs) because ld.so parses multiple PHDRs. The second PHDR can completely transform the executable. This is described in paper in the first issue of International Journal of PoC. Conclusions trusting computers not only about bugs! Bugs are part of a problem, but no by far all of it complex data formats means bugs no "chain of trust" in Babylon! (that is, with parser differentials) we need to squeeze complexity out of data until data stops being "code equivalent" Further information See and langsec.org. USENIX WOOT 2013 (Workshop on Offensive Technologies) for "weird machines" papers and videos.

  Read the article

• Chicago SQL Saturday

  - by Johnm

  This past Saturday, April 17, 2010, I journeyed North to the great city of Chicago for some SQL Server fun, learning and fellowship. The Chicago edition of this grassroots phenomenon was the 31st scheduled SQL Saturday since the program's birth in late 2007. The Chicago SQL Saturday consisted of four tracks with eight sessions each and was a very energetic and fast paced day for the 300+/- SQL Server enthusiasts in attendance. The speaker line up included national notables such as Kevin Kline, Brent Ozar, and Brad McGehee. My hometown of Indianapolis was well represented in the speaker line up with Arie Jones, Aaron King and Derek Comingore. The day began with a very humorous keynote by Kevin Kline and Brent Ozar who emphasized the importance of community events such as SQL Saturday and the monthly user group meetings. They also brilliantly included the impact that getting involved in the SQL community through social media can have on your professional career. My approach to the day was to try to experience as much of the event as I could, so there were very few sessions that I attended for their full duration. I leaped from session to session like a bumble bee, gleaning bits of nectar from each session. Amid these leaps I took the opportunity to briefly chat with some of the in-the-queue speakers as well as other attendees that wondered the hallways. I especially enjoyed a great discussion with Devin Knight about his plans regarding the upcoming Jacksonville SQL Saturday as well as an interesting SQL interpretation of the Iron Chef, which I think would catch on like wild-fire. There were two sessions that stood out as exceptional. So much so that I could not pull myself away: Kevin Kline presented on "SQL Server Internals and Architecture". This session could have been classified as one that is intended for the beginner. Kevin even personally warned me of such as I entered the room. I am a believer in revisiting the basics regardless of the level of your mastery, so I entered into this session in that spirit. It was a very clear and precise presentation. Masterfully illustrated and demonstrated. Brad McGehee presented on "How and When to Use Indexed Views". This was a topic that I was recently exploring and was considering to for use in an integration project. Brad effectively communicated the complexity of this feature and what is involved to gain their full benefit. It was clear at the conclusion of this session that it was not the right feature for my specific needs. Overall, the event was a great success. The use of volunteers, from an attendee's perspective was masterful. The only recommendation that I would have for the next Chicago SQL Saturday would be to include more time in between sessions to permit some level of networking among the attendees, one-on-one questions for speakers and visits to the sponsor booths. Congratulations to Wendy Pastrick, Ted Krueger, and Aaron Lowe for their efforts and a very successful SQL Saturday!

  Read the article

• Need help fixing a strange path error in bash

  - by Evan

  UPDATE Ok, I found some errors in the path which I think I fixed, but now it's not running in any case - which for some reason I think is a step forward. Thanks for suggesting the following steps, here is their output: user@computer:~$ echo $PATH /usr/share/fsl/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/bin:/usr/bin:/bin:/usr/bin/X11:/usr/games:/usr/local/matlab/bin:/usr/local/VoxBo/bin:/usr/local/itt/idl64/bin:/usr/local/afni/bin/:/usr/local/mricron:/usr/lib/voxbo/bin:/home/user/folder:/usr/local/bin:/usr/bin:/bin:/usr/bin/X11/:/usr/games/:/usr/local/matlab/bin:/usr/local/VoxBo/bin/:/usr/local/itt/idl64/bin:/usr/local/afni/bin/:/usr/local/mricron/ user@computer:~$ typeset -p PATH declare -x PATH="/usr/share/fsl/bin:/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/usr/games:/usr/local/bin:/usr/bin:/bin:/usr/bin/X11:/usr/games:/usr/local/matlab/bin:/usr/local/VoxBo/bin:/usr/local/itt/idl64/bin:/usr/local/afni/bin/:/usr/local/mricron:/usr/lib/voxbo/bin:/home/user/folder:/usr/local/bin:/usr/bin:/bin:/usr/bin/X11/:/usr/games/:/usr/local/matlab/bin:/usr/local/VoxBo/bin/:/usr/local/itt/idl64/bin:/usr/local/afni/bin/:/usr/local/mricron/" user@computer:~$ type app1 app1 is /home/user/folder/app1 user@computer:~$ type app2 app2 is /home/user/folder/app2 user@computer:~$ app1 bash: /home/user/folder/app1: No such file or directory user@computer:~$ app2 bash: /home/user/folder/app2: No such file or directory user@computer:~$ /home/user/folder/app1 bash: /home/user/folder/app1: No such file or directory user@computer:~$ /home/user/folder/app2 bash: /home/user/folder/app2: No such file or directory user@computer:~$ cd /home/user/folder user@computer:~/folder$ app1 bash: /home/user/folder/app1: No such file or directory user@computer:~/folder$ ./app1 bash: ./app1: No such file or directory user@computer:~/folder$ ./app2 bash: ./app2: No such file or directory user@computer:~/folder$ ls -l total 29384 -rwxr-xr-x 1 user user 14949776 2011-02-03 11:09 app1 -rwxr-xr-x 1 user user 15137300 2011-02-03 11:10 app2 user@computer:~/folder$ Thanks for everyone's input! ORIGINAL QUESTION I have two executable files I downloaded and am trying to add to the path. They are located in /home/user/folder and the specific files are /home/user/folder/app1 /home/user/folder/app2 Both app1 and app2 have the executable flag set to all (user, group, other). I can execute the files if I am in /home/user/folder and I execute these commands ./app1 ./app2 However I can't run them from elsewhere. I added this line to my .profile PATH="$PATH:/home/user/folder" and then sourced the path with . /home/user/.profile and I can see app1 and app2 when I use command completion (pressing tab). However here is what happens when I try to run app1 or app2 with the following commands (the following only shows 'app1' but the same is true of 'app2') user@comp:~$ app1 -bash: app1: command not found user@comp:~$ /home/user/folder/app1 -bash: app1: command not found user@comp:~/folder$ ./app1 (program runs) I'm stumped :), I must have missed something simple. Thanks for your help!!

  Read the article

• Evolution Of High Definition TV Viewing

  - by Gopinath

  The following guest post is written by Rob, who is also blogging on entertainment technology topics on iwantsky.com Gone are the days when you need to squint to be able to see the emotions on the faces of Humphrey Bogart and Ingrid Bergman as the lovers bid each other adieu in the classic film Casablanca. These days, watching an ordinary ant painstakingly carry a leaf in Animal Planet can be an exhilarating experience as you get to see not only the slightest movement but also the demarcation line between the insect’s head, thorax and abdomen. The crystal clear imagery was made possible by the sharp minds and the tinkering hands of the scientists that have designed the modern world’s HDTV. What is HDTV and what makes people so agog to have this new innovation in TV watching? HDTV stands for High Definition TV. Television viewing has indeed made a big leap. From the grainy black and whites, TV viewing had moved to colored TVs, progressed to SD TVs and now to HDTV. HDTV is the emerging trend in TV viewing as it delivers bigger and clearer pictures and better audio. Viewers can have a cinema-like TV viewing experience right in the comforts of their own home. With HDTV the viewer is allowed to have a better viewing range. With Standard (SD) TV, the viewer has to be at a distance that is from 3 to 6 times the size of the screen. HDTV allows the viewer to enjoy sharper and clearer images as it is possible to sit at a distance that is 1.5 or 3 times the size of the screen without noticing any image pixilation. Although HDTV appears to be a fairly new innovation, this system has actually existed in various forms years ago. Development of the HDTV was started in Europe as early as 1940s. However, the NTSC and the PAL/SECAM, the two analog TV standards became dominant and became popular worldwide. The analog TV was replaced by the digital TV platform in the 1990s. Even during the analog era, attempts have been made to develop HDTV. Japan has come out with MUSE system. However, due to channel bandwidth requirement concerns, the program was shelved. The entry of four organizations into the HDTV market spurred the development of a beneficial coalition. The AT&T, ATRC, MIT and Zenith HDTV combined forces. In 1993, a Grand Alliance was formed. This group is composed of researchers and HDTV manufacturers. A common standard for the broadcast system of HDTV was developed. In 1995, the system was tested and found successful. With the higher screen resolution of HDTV, viewing has never been more enjoyable. [Image courtesy: samsung] This article titled,Evolution Of High Definition TV Viewing, was originally published at Tech Dreams. Grab our rss feed or fan us on Facebook to get updates from us.

  Read the article

• Remote Desktop to Your Azure Virtual Machine

  - by Shaun

  The Windows Azure Team had just published their new development portal this week and the SDK 1.3. Within this new release there are a lot of cool feature available. The one I’m looking forward to is Remote Desktop Access to your running Windows Azure Virtual Machine.   Configuration Remote Desktop Access It would be very simple to make the azure service enable the remote desktop access. First of all let’s create a new windows azure project from the Visual Studio. In this example I just created a normal MVC 2 web role without any modifications. Then we right-click the azure project node in the solution explorer window and select “Publish”. Then let’s select the “Deploy your Windows Azure project to Windows Azure” on the top radio button. And then select the credential, deployment service/slot, storage and label as susal. You must have the Management API Certificates uploaded to your Windows Azure account, and install the certification on you machine before in order to use this one-click deployment feature. If you are familiar with this dialog you will notice that there’s a linkage named “Configure Remote Desktop connections”. Here is where you need to make this service enable the remote desktop feature. After clicked this link we will set the configuration of the remote desktop access authorization information. There are 4 steps we need to do to configure our access. Certificates: We need either create or select a certificate file in order to encypt the access cerdenticals. In this example I will use the certificate file for my Management API. Username: The remote desktop user name to access the virtual machine. Password: The password for the access. Expiration: The access cerdentals would be expired after 1 month by default but we can amend here. After that we clicked the OK button to back to the publish dialog.   The next step is to back to the new windows azure portal and navigate to the hosted services list. I created a new hosted service and upload the certificate file onto this service. The user name and password access to the azure machine must be encrypted from the local machine, and then send to the windows azure platform, then decrypted on the azure side by the same file. This is why we need to upload the certificate file onto azure. We navigated to the “Hosted Services, Storage Accounts & CDN"” from the left panel and created a new hosted service named “SDK13” and selected the “Certificates” node. Then we clicked the “Add Certificates” button. Then we select the local certificate file and the password to install it into this azure service.   The final step would be back to our Visual Studio and in the pulish dialog just click the OK button. The Visual Studio will upload our package and the configuration into our service with the remote desktop settings.   Remote Desktop Access to Azure Virtual Machine All things had been done, let’s have a look back on the Windows Azure Development Portal. If I selected the web role that I had just published we can see on the toolbar there’s a section named “Remote Access”. In this section the Enable checkbox had been checked which means this role has the Remote Desktop Access feature enabled. If we want to modify the access cerdentals we can simply click the Configure button. Then we can update the user name, password, certificates and the expiration date.   Let’s select the instance node under the web role. In this case I just created one instance for demo. We can see that when we selected the instance node, the Connect button turned enabled. After clicked this button there will be a RDP file downloaded. This is a Remote Desctop configuration file that we can use to access to our azure virtual machine. Let’s download it to our local machine and execute. We input the user name and password we specified when we published our application to azure and then click OK. There might be some certificates warning dislog appeared. This is because the certificates we use to encryption is not signed by a trusted provider. Just select OK in these cases as we know the certificate is safty to us. Finally, the virtual machine of Windows Azure appeared.   A Quick Look into the Azure Virtual Machine Let’s just have a very quick look into our virtual machine. There are 3 disks available for us: C, D and E. Disk C: Store the local resource, diagnosis information, etc. Disk D: System disk which contains the OS, IIS, .NET Frameworks, etc. Disk E: Sotre our application code. The IIS which hosting our webiste on Azure. The IP configuration of the azure virtual machine.   Summary In this post I covered one of the new feature of the Azure SDK 1.3 – Remote Desktop Access. We can set the access per service and all of the instances of this service could be accessed through the remote desktop tool. With this feature we can deep into the virtual machines of our instances to see the inner information such as the system event, IIS log, system information, etc. But we should pay attention to modify the system settings. 2 reasons from what I know for now: 1. If we have more than one instances against our service we should ensure that all system settings we modifed are applied to all instances/virtual machines. Otherwise, as the machines are under the azure load balance proxy our application process may doesn’t work due to the defferent settings between the instances. 2. When the virtual machine encounted some problem and need to be translated to another physical machine all settings we made would be disappeared.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

  Read the article

• Windows Phone 7 Design using Expression Blend - Resources

  - by Nikita Polyakov

  I’ve been doing a series of talks across Florida regarding Windows Phone 7 Design using Microsoft Expression Blend 4. I discuss the WP7 phone and application experience; show how to use Expression Blend toolset to effectively design such apps. Next presentation is on 5/4/2010 at 6:30PM EST will be a webcast format over LiveMeeting at Ft. Lauderdale Online group. Registration and the LiveMeeting link are both here: http://www.fladotnet.com/Reg.aspx?EventID=459 [I will post a link if it’s recorded]   Here are the resources from my presentations: The Biggest source is the Windows Phone UI and Design Language video from MIX10 Windows Phone 7 Design Guide as it’s found on the WP7 Dev Home Page Study The Silverlight Mobile Tutorials on official Silverlight website I will be blogging a separate entry for a new demo app that will showcase the elements I presented. I suggest you actually watch all of the MIX videos about SL and Design as great primer to get you thinking the WP7 way.   A lot happening with WP7Dev and it’s just the beginning! So watch these Twitter accounts and blogs: @Ckindel - Charlie Kindel - WP7 Dev Head http://blogs.msdn.com/ckindel @WP7Dev - Official Dev Twitter @WP7 - Official WP7 Twitter Peter Torr - http://blogs.msdn.com/ptorr Mike Harsh - http://blogs.msdn.com/mharsh Shawn Oster - http://www.shawnoster.com   Other worthwhile mention my local friends speaking and blogging about Windows Phone 7: Bill Reiss is doing great presentations on Building games with XNA for Windows Phone 7. Be on the lookout for those around Florida. Bill is a Silverlight MVP and has a legacy of XNA and Silverlight games, see his site. Kevin Wolf aka ByteMaster he is a Device Application Developer MVP with tremendous experience building mobile applications. He has developed WinMo-GF a multi-platform gaming framework. Get these tools and get creating! You will need the following components installed in this order: Expression Blend 4 Beta Windows Phone Developer Tools Microsoft Expression Blend Add-in Preview for Windows Phone Microsoft Expression Blend SDK Preview for Windows Phone Want more training? Don’t forget that Channel 9 has complete walkthroughs of their WP7 Training Kit posted online. PS: To continue with all this design talk check out Microsoft .toolbox “Learn to create Silverlight applications using Expression Studio and to apply fundamental design principles.” A great website with a lot of design tutorials set up as a wonderful full course on design all for free, including a great forum community and neat little avatars you can build yourself.

  Read the article

• It’s time that you ought to know what you don’t know

  - by fatherjack

  There is a famous quote about unknown unknowns and known knowns and so on but I’ll let you review that if you are interested. What I am worried about is that there are things going on in your environment that you ought to know about, indeed you have asked to be told about but you are not getting the information. When you schedule a SQL Agent job you can set it to send an email to an inbox monitored by someone who needs to know and indeed can do something about it. However, what happens if the email process isnt successful? Check your servers with this: USE [msdb] GO /* This code selects the top 10 most recent SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT TOP 10 [s].[name] , [sjh].[step_name] , [sjh].[sql_message_id] , [sjh].[sql_severity] , [sjh].[message] , [sjh].[run_date] , [sjh].[run_time] , [sjh].[run_duration] , [sjh].[operator_id_emailed] , [sjh].[operator_id_netsent] , [sjh].[operator_id_paged] , [sjh].[retries_attempted] FROM [dbo].[sysjobhistory] AS sjh INNER JOIN [dbo].[sysjobs] AS s ON [sjh].[job_id] = [s].[job_id] WHERE EXISTS ( SELECT * FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [sjh].[job_id] = [s2].[job_id] AND [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 ) AND sjh.[run_status] = 0 AND sjh.[step_id] != 0 AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [run_date])) >= @date ORDER BY [sjh].[run_date] DESC , [sjh].[run_time] DESC go USE [msdb] go /* This code summarises details of SQLAgent jobs that failed to complete successfully and where the email notification failed too. Jonathan Allen Jul 2012 */ DECLARE @Date DATETIME SELECT @Date = DATEADD(d, DATEDIFF(d, '19000101', GETDATE()) - 1, '19000101') SELECT [s].name , [s2].[step_id] , CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) AS [rundate] , COUNT(*) AS [execution count] FROM [dbo].[sysjobs] AS s INNER JOIN [dbo].[sysjobhistory] AS s2 ON [s].[job_id] = [s2].[job_id] WHERE [s2].[message] LIKE '%failed to notify%' AND CONVERT(DATETIME, CONVERT(VARCHAR(15), [s2].[run_date])) >= @date AND [s2].[run_status] = 0 GROUP BY name , [s2].[step_id] , [s2].[run_date] ORDER BY [s2].[run_dateDESC] These two result sets will show if there are any SQL Agent jobs that have run on your servers that failed and failed to successfully email about the failure. I hope it’s of use to you. Disclaimer – Jonathan is a Friend of Red Gate and as such, whenever they are discussed, will have a generally positive disposition towards Red Gate tools. Other tools are often available and you should always try others before you come back and buy the Red Gate ones. All code in this blog is provided “as is” and no guarantee, warranty or accuracy is applicable or inferred, run the code on a test server and be sure to understand it before you run it on a server that means a lot to you or your manager.

  Read the article

• Silverlight Cream for March 22, 2010 -- #817

  - by Dave Campbell

  In this Issue: Bart Czernicki, Tim Greenfield, Andrea Boschin(-2-), AfricanGeek, Fredrik Normén, Ian Griffiths, Christian Schormann, Pete Brown, Jeff Handley, Brad Abrams, and Tim Heuer. Shoutout: At the beginning of MIX10, Brad Abrams reported Silverlight 4 and RIA Services Release Candidate Available NOW From SilverlightCream.com: Using the Bing Maps Silverlight control on the Windows Phone 7 Bart Czernicki has a very cool BingMaps and WP7 tutorial up... you're going to want to bookmark this one for sure! Code included and external links... thanks Bart! Silverlight Rx DataClient within MVVM Tim Greenfield has a great post up about Rx and MVVM with Silverlight 3. Lots of good insight into Rx and interesting code bits. SilverVNC - a VNC Viewer with Silverlight 4.0 RC Andrea Boschin digs into Silverlight 4 RC and it's full-trust on sockets and builds an implementation of RFB protocol... give it a try and give Andrea some feedback. Chromeless Window for OOB applications in Silverlight 4.0 RC Andrea Boschin also has a post up on investigating the OOB no-chrome features in SL4RC. Windows Phone 7 and WCF AfricanGeek has his latest video tutorial up and it's on WCF and WP7... I've got a feeling we're all going to have to get our arms around this. Some steps for moving WCF RIA Services Preveiw to the RC version Fredrik Normén details his steps in transitioning to the RC version of RIA Services. Silverlight Business Apps: Module 8.5 - The Value of MEF with Silverlight Ian Griffiths has a video tutorial up at Channel 9 on MEF and Silverlight, posted by John Papa Introducing Blend 4 – For Silverlight, WPF and Windows Phone Christian Schormann has an early MIX10 post up about te new features in Expression Blend with regard to Silverlight, WPF, and WP7. Building your first Silverlight for Windows Phone Application Pete Brown has his first post up on building a WP7 app with the MIX10 bits. Lookups in DataGrid and DataForm with RIA Services Jeff Handley elaborates on a post by someone else about using lookup data in the DataGrid and DataForm with RIA Services Silverlight 4 + RIA Services - Ready for Business: Starting a New Project with the Business Application Template Brad Abrams is starting a series highlighting the key features of Silverlight 4 and RIA with the new releases. He has a post up Silverlight 4 + RIA Services - Ready for Business: Index, including links and source. Then in this first post of the series, he introduces the Business Application Template. Custom Window Chrome and Events Watch a tutorial video by Tim Heuer on creating custom chrome for OOB apps. Stay in the 'Light! Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCream Join me @ SilverlightCream | Phoenix Silverlight User Group Technorati Tags: Silverlight    Silverlight 3    Silverlight 4    Windows Phone MIX10

  Read the article

• Silverlight Cream for April 01, 2010 -- #827

  - by Dave Campbell

  In this Issue: Max Paulousky, Hassan, Viktor Larsson, Fons Sonnemans, Jim McCurdy, Scott Marlowe, Mike Taulty, Brad Abrams, Jesse Liberty, Scott Barnes, Christopher Bennage, and John Papa and Ward Bell. Shoutouts: Tim Heuer posted a survey: What tools are the minimum to get started in Silverlight?... have you responded yet? Don't want to miss this discussion: Channel 9 Live at MIX10: Bill Buxton & Erik Meijer - Perspectives on Design Bookmark this... Jesse Liberty has moved his site: Silverlight Geek I stand with Tim Heuer on this: Congratulations to latest 2nd quarter Silverlight MVPs From SilverlightCream.com: Wizards. Prototype of sketching Wizard for WPF - 1 Max Paulousky is creating a SketchFlow WPF wizard in Expression Blend... looks like good Expression Blend and SketchFlow no matter what the target is Windows Phone 7 Navigation Hassan has another WP7 Video up, and this one is on Navigation and passing data from page to page. Silverlight 4 PathListBox Viktor Larsson is blogging about the PathListBox, and definitely had a good time doing so.. lots of fun examples. CountDown Clock in Silverlight 4 Fons Sonnemans has reworked his Sivlerlight 3 FlipClock to be this Silverlight 4 CountDown Clock utilizing the Viewbox control to make it scalable. Generic class for deep clone of Silverlight and CLR objects Jim McCurdy has a Silverlight 3 and 4-tested CloneObject class that he's using for creating a deep copy of an object and all it's properties... think drag/drop or undo/redo. Animating the Fill Color of a Silverlight Ellipse Scott Marlowe has a tutorial up that animates a pass/fail indicator with a smooth transition from a red to a green state... all with code. Silverlight 4, Blend 4, MVVM, Binding, DependencyObject Mike Taulty has a great tutorial up on Blend4 and binding... he's got a somewhat contrived example going, but it certainly looks good to me :) Silverlight 4 + RIA Services - Ready for Business: Authentication and Personalization Next up in Brad Abrams' series is Authentication and Personalization. RIA Services makes this easy to do... let Brad show you! An Annotated Line of Business Application Jesse Liberty is walking through the design and delivery of his HyperVideo project with this mini tutorial. Want to understand the thought process behind the LOB app, check this out. How to hack Expression Blend Seems like there was just some discussion about some of this today and here Scott Barnes posts this hack job for Expression Blend... pretty cool actually :) d:DesignInstance in Blend 4 Christopher Bennage has a follow-on post about using d:DesignInstance in Blend 4, and this is a very nice tutorial on the subject Silverlight TV 19: Hidden Gems from MIX10, UFC's Multi-Touch App John Papa and Ward Bell front and center for Silverlight TV number 19... and check out those threads! Stay in the 'Light! Twitter SilverlightNews | Twitter WynApse | WynApse.com | Tagged Posts | SilverlightCream Join me @ SilverlightCream | Phoenix Silverlight User Group Technorati Tags: Silverlight    Silverlight 3    Silverlight 4    Windows Phone MIX10

  Read the article

• Podcast Show Notes: The Red Room Interview &ndash; Part 1

  - by Bob Rhubart

    The latest OTN Arch2Arch podcast is Part 1 of a three-part series featuring a discussion of a broad range of SOA  issues with three members of the small army of contributors to The Red Room Blog, now part of the OJam.biz site, the Australia-New Zealand outpost of the global Oracle community. The panelists for this program are: Sean Boiling - Sales Consulting Manager for Oracle Fusion Middleware LinkedIn | Twitter | Blog Richard Ward - SOA Channel Development Manager at Oracle LinkedIn | Blog Mervin Chiang - Consulting Principal at Leonardo Consulting LinkedIn | Twitter | Blog (You can also follow the Red Room itself on Twitter: @OracleRedRoom.) The genesis of this interview goes back to 2009, and the original Red Room blog, on which Sean, Richard, Mervin, and other Red Roomers published a 10-part series of posts that, taken together, form a kind of SOA best-practices guide, presented in an irreverent style that is rare in a lot of technical writing. It was on the basis of their expertise and irreverence that I wanted to get a few of the Red Room bloggers on an Arch2Arch podcast.  Easier said than done. Trying to schedule a group interview with very busy people on the other side of world (they’re actually 15 hours in the future, relative to my location) is not a simple process. The conversations about getting some of the Red Room people on the program began in the summer of 2009. The interview finally happened at 5:30 PM EDT on Tuesday March 30, 2010, which for the panelists, located in Australia, was 8:30 AM on Wednesday March 31, 2010. I was waiting for dinner, and Sean, Richard, and Mervin were waiting for breakfast. But the call went off without a hitch, and the panelists carried on a great discussion of SOA issues. Listen to Part 1 Many thanks to Gareth Llewellyn for his help in putting this together. SOA Best Practices Here’s a complete list of the posts in the original 10-part Red Room series: SOA is Dead. Long Live SOA by Sean Boiling Are you doing SOP’s instead of SOA? by Saul Cunningham All The President's SOA by Sean Boiling SOA – Pay Now or Pay Dearly by Richard Ward SOA where are the skills? by Richard Ward Project Management Pitfalls within SOA by Anton Gouws Viewing SOA as a project instead of an architecture by Saul Cunningham Kiss and Tell by Sean Boiling Failure to implement and adhere to SOA Governance by Mervin Chiang Ten Out Of Ten by Sean Boiling Parts 2 of the Red Room Interview will be available next week, followed by Part 3, so stay tuned: RSS Change in the Wind Beginning with next week’s program, the OTN Arch2Arch Podcast will be rechristened as the OTN ArchBeat Podcast, to better align with this blog. The transformation will be painless – you won’t feel a thing.   del.icio.us Tags: otn,oracle,Archbeat,Arch2Arch,soa,service oriented architecture,podcast Technorati Tags: otn,oracle,Archbeat,Arch2Arch,soa,service oriented architecture,podcast

  Read the article

• A couple of nice features when using OracleTextSearch

  - by kyle.hatlestad

  If you have your UCM/URM instance configured to use the Oracle 11g database as the search engine, you can be using OracleTextSearch as the search definition. OracleTextSearch uses the advanced features of Oracle Text for indexing and searching. This includes the ability to specify metadata fields to be optimized for the search index, fast rebuilding, and index optimization. If you are on 10g of UCM, then you'll need to load the OracleTextSearch component that is available in the CS10gR35UpdateBundle component on the support site (patch #6907073). If you are on 11g, no component is needed. Then you specify the search indexer name with the configuration flag of SearchIndexerEngineName=OracleTextSearch. Please see the docs for other configuration settings and setup instructions. So I thought I would highlight a couple of other unique features available with OracleTextSearch. The first is the Drill Down feature. This feature allows you to specify specific metadata fields that will break down the results of that field based on the total results. So in the above graphic, you can see how it broke down the extensions and gives a count for each. Then you just need to click on that link to then drill into that result. This setting is perfect for option list fields and ones with a distinct set of values possible. By default, it will use the fields Type, Security Group, and Account (if enabled). But you can also specify your own fields. In 10g, you can use the following configuration entry: DrillDownFields=xWebsiteObjectType,dExtension,dSecurityGroup,dDocType And in 11g, you can specify it through the Configuration Manager applet. Simply click on the Advanced Search Design, highlight the field to filter, click Edit, and check 'Is a filter category'. The other feature you get with OracleTextSearch are search snippets. These snippets show the occurrence of the search term in context of their usage. This is very similar to how Google displays its results. If you are on 10g, this is enabled by default. If you are on 11g, you need to turn on the feature. The following configuration entry will enable it: OracleTextDisableSearchSnippet=false Once enabled, you can add the snippets to your search results. Go to Change View -> Customize and add a new search result view. In the Available Fields in the Special section, select Snippet and move it to the Main or Additional Information. If you want to include the snippets with the Classic results, you can add the idoc variable of <$srfDocSnippet$> to display them. One caveat is that this can effect search performance on large collections. So plan the infrastructure accordingly.

  Read the article

< Previous Page | 362 363 364 365 366 367 368 369 370 371 372 373  | Next Page >