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  • Retrieve Performance Data from SOA Infrastructure Database

    - by fip
    My earlier blog posting shows how to enable, retrieve and interpret BPEL engine performance statistics to aid performance troubleshooting. The strength of BPEL engine statistics at EM is its break down per request. But there are some limitations with the BPEL performance statistics mentioned in that blog posting: The statistics were stored in memory instead of being persisted. To avoid memory overflow, the data are stored to a buffer with limited size. When the statistic entries exceed the limitation, old data will be flushed out to give ways to new statistics. Therefore it can only keep the last X number of entries of data. The statistics 5 hour ago may not be there anymore. The BPEL engine performance statistics only includes latencies. It does not provide throughputs. Fortunately, Oracle SOA Suite runs with the SOA Infrastructure database and a lot of performance data are naturally persisted there. It is at a more coarse grain than the in-memory BPEL Statistics, but it does have its own strengths as it is persisted. Here I would like offer examples of some basic SQL queries you can run against the infrastructure database of Oracle SOA Suite 11G to acquire the performance statistics for a given period of time. You can run it immediately after you modify the date range to match your actual system. 1. Asynchronous/one-way messages incoming rates The following query will show number of messages sent to one-way/async BPEL processes during a given time period, organized by process names and states select composite_name composite, state, count(*) Count from dlv_message where receive_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; 2. Throughput of BPEL process instances The following query shows the number of synchronous and asynchronous process instances created during a given time period. It list instances of all states, including the unfinished and faulted ones. The results will include all composites cross all SOA partitions select state, count(*) Count, composite_name composite, component_name,componenttype from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype order by count(*) desc; 3. Throughput and latencies of BPEL process instances This query is augmented on the previous one, providing more comprehensive information. It gives not only throughput but also the maximum, minimum and average elapse time BPEL process instances. select composite_name Composite, component_name Process, componenttype, state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime from cube_instance where creation_date >= to_timestamp('2012-10-24 21:00:00','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('2012-10-24 21:59:59','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;   4. Combine all together Now let's combine all of these 3 queries together, and parameterize the start and end time stamps to make the script a bit more robust. The following script will prompt for the start and end time before querying against the database: accept startTime prompt 'Enter start time (YYYY-MM-DD HH24:MI:SS)' accept endTime prompt 'Enter end time (YYYY-MM-DD HH24:MI:SS)' Prompt "==== Rejected Messages ===="; REM 2012-10-24 21:00:00 REM 2012-10-24 21:59:59 select count(*), composite_dn from rejected_message where created_time >= to_timestamp('&&StartTime','YYYY-MM-DD HH24:MI:SS') and created_time <= to_timestamp('&&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_dn; Prompt " "; Prompt "==== Throughput of one-way/asynchronous messages ===="; select state, count(*) Count, composite_name composite from dlv_message where receive_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and receive_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, state order by Count; Prompt " "; Prompt "==== Throughput and latency of BPEL process instances ====" select state, count(*) Count, trunc(Max(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MaxTime, trunc(Min(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) MinTime, trunc(AVG(extract(day from (modify_date-creation_date))*24*60*60 + extract(hour from (modify_date-creation_date))*60*60 + extract(minute from (modify_date-creation_date))*60 + extract(second from (modify_date-creation_date))),4) AvgTime, composite_name Composite, component_name Process, componenttype from cube_instance where creation_date >= to_timestamp('&StartTime','YYYY-MM-DD HH24:MI:SS') and creation_date <= to_timestamp('&EndTime','YYYY-MM-DD HH24:MI:SS') group by composite_name, component_name, componenttype, state order by count(*) desc;  

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  • Fastest pathfinding for static node matrix

    - by Sean Martin
    I'm programming a route finding routine in VB.NET for an online game I play, and I'm searching for the fastest route finding algorithm for my map type. The game takes place in space, with thousands of solar systems connected by jump gates. The game devs have provided a DB dump containing a list of every system and the systems it can jump to. The map isn't quite a node tree, since some branches can jump to other branches - more of a matrix. What I need is a fast pathfinding algorithm. I have already implemented an A* routine and a Dijkstra's, both find the best path but are too slow for my purposes - a search that considers about 5000 nodes takes over 20 seconds to compute. A similar program on a website can do the same search in less than a second. This website claims to use D*, which I have looked into. That algorithm seems more appropriate for dynamic maps rather than one that does not change - unless I misunderstand it's premise. So is there something faster I can use for a map that is not your typical tile/polygon base? GBFS? Perhaps a DFS? Or have I likely got some problem with my A* - maybe poorly chosen heuristics or movement cost? Currently my movement cost is the length of the jump (the DB dump has solar system coordinates as well), and the heuristic is a quick euclidean calculation from the node to the goal. In case anyone has some optimizations for my A*, here is the routine that consumes about 60% of my processing time, according to my profiler. The coordinateData table contains a list of every system's coordinates, and neighborNode.distance is the distance of the jump. Private Function findDistance(ByVal startSystem As Integer, ByVal endSystem As Integer) As Integer 'hCount += 1 'If hCount Mod 0 = 0 Then 'Return hCache 'End If 'Initialize variables to be filled Dim x1, x2, y1, y2, z1, z2 As Integer 'LINQ queries for solar system data Dim systemFromData = From result In jumpDataDB.coordinateDatas Where result.systemId = startSystem Select result.x, result.y, result.z Dim systemToData = From result In jumpDataDB.coordinateDatas Where result.systemId = endSystem Select result.x, result.y, result.z 'LINQ execute 'Fill variables with solar system data for from and to system For Each solarSystem In systemFromData x1 = (solarSystem.x) y1 = (solarSystem.y) z1 = (solarSystem.z) Next For Each solarSystem In systemToData x2 = (solarSystem.x) y2 = (solarSystem.y) z2 = (solarSystem.z) Next Dim x3 = Math.Abs(x1 - x2) Dim y3 = Math.Abs(y1 - y2) Dim z3 = Math.Abs(z1 - z2) 'Calculate distance and round 'Dim distance = Math.Round(Math.Sqrt(Math.Abs((x1 - x2) ^ 2) + Math.Abs((y1 - y2) ^ 2) + Math.Abs((z1 - z2) ^ 2))) Dim distance = firstConstant * Math.Min(secondConstant * (x3 + y3 + z3), Math.Max(x3, Math.Max(y3, z3))) 'Dim distance = Math.Abs(x1 - x2) + Math.Abs(z1 - z2) + Math.Abs(y1 - y2) 'hCache = distance Return distance End Function And the main loop, the other 30% 'Begin search While openList.Count() != 0 'Set current system and move node to closed currentNode = lowestF() move(currentNode.id) For Each neighborNode In neighborNodes If Not onList(neighborNode.toSystem, 0) Then If Not onList(neighborNode.toSystem, 1) Then Dim newNode As New nodeData() newNode.id = neighborNode.toSystem newNode.parent = currentNode.id newNode.g = currentNode.g + neighborNode.distance newNode.h = findDistance(newNode.id, endSystem) newNode.f = newNode.g + newNode.h newNode.security = neighborNode.security openList.Add(newNode) shortOpenList(OLindex) = newNode.id OLindex += 1 Else Dim proposedG As Integer = currentNode.g + neighborNode.distance If proposedG < gValue(neighborNode.toSystem) Then changeParent(neighborNode.toSystem, currentNode.id, proposedG) End If End If End If Next 'Check to see if done If currentNode.id = endSystem Then Exit While End If End While If clarification is needed on my spaghetti code, I'll try to explain.

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  • PASS Summit 2011 &ndash; Part III

    - by Tara Kizer
    Well we’re about a month past PASS Summit 2011, and yet I haven’t finished blogging my notes! Between work and home life, I haven’t been able to come up for air in a bit.  Now on to my notes… On Thursday of the PASS Summit 2011, I attended Klaus Aschenbrenner’s (blog|twitter) “Advanced SQL Server 2008 Troubleshooting”, Joe Webb’s (blog|twitter) “SQL Server Locking & Blocking Made Simple”, Kalen Delaney’s (blog|twitter) “What Happened? Exploring the Plan Cache”, and Paul Randal’s (blog|twitter) “More DBA Mythbusters”.  I think my head grew two times in size from the Thursday sessions.  Just WOW! I took a ton of notes in Klaus' session.  He took a deep dive into how to troubleshoot performance problems.  Here is how he goes about solving a performance problem: Start by checking the wait stats DMV System health Memory issues I/O issues I normally start with blocking and then hit the wait stats.  Here’s the wait stat query (Paul Randal’s) that I use when working on a performance problem.  He highlighted a few waits to be aware of such as WRITELOG (indicates IO subsystem problem), SOS_SCHEDULER_YIELD (indicates CPU problem), and PAGEIOLATCH_XX (indicates an IO subsystem problem or a buffer pool problem).  Regarding memory issues, Klaus recommended that as a bare minimum, one should set the “max server memory (MB)” in sp_configure to 2GB or 10% reserved for the OS (whichever comes first).  This is just a starting point though! Regarding I/O issues, Klaus talked about disk partition alignment, which can improve SQL I/O performance by up to 100%.  You should use 64kb for NTFS cluster, and it’s automatic in Windows 2008 R2. Joe’s locking and blocking presentation was a good session to really clear up the fog in my mind about locking.  One takeaway that I had no idea could be done was that you can set a timeout in T-SQL code view LOCK_TIMEOUT.  If you do this via the application, you should trap error 1222. Kalen’s session went into execution plans.  The minimum size of a plan is 24k.  This adds up fast especially if you have a lot of plans that don’t get reused much.  You can use sys.dm_exec_cached_plans to check how often a plan is being reused by checking the usecounts column.  She said that we can use DBCC FLUSHPROCINDB to clear out the stored procedure cache for a specific database.  I didn’t know we had this available, so this was great to hear.  This will be less intrusive when an emergency comes up where I’ve needed to run DBCC FREEPROCCACHE. Kalen said one should enable “optimize for ad hoc workloads” if you have an adhoc loc.  This stores only a 300-byte stub of the first plan, and if it gets run again, it’ll store the whole thing.  This helps with plan cache bloat.  I have a lot of systems that use prepared statements, and Kalen says we simulate those calls by using sp_executesql.  Cool! Paul did a series of posts last year to debunk various myths and misconceptions around SQL Server.  He continues to debunk things via “DBA Mythbusters”.  You can get a PDF of a bunch of these here.  One of the myths he went over is the number of tempdb data files that you should have.  Back in 2000, the recommendation was to have as many tempdb data files as there are CPU cores on your server.  This no longer holds true due to the numerous cores we have on our servers.  Paul says you should start out with 1/4 to 1/2 the number of cores and work your way up from there.  BUT!  Paul likes what Bob Ward (twitter) says on this topic: 8 or less cores –> set number of files equal to the number of cores Greater than 8 cores –> start with 8 files and increase in blocks of 4 One common myth out there is to set your MAXDOP to 1 for an OLTP workload with high CXPACKET waits.  Instead of that, dig deeper first.  Look for missing indexes, out-of-date statistics, increase the “cost threshold for parallelism” setting, and perhaps set MAXDOP at the query level.  Paul stressed that you should not plan a backup strategy but instead plan a restore strategy.  What are your recoverability requirements?  Once you know that, now plan out your backups. As Paul always does, he talked about DBCC CHECKDB.  He said how fabulous it is.  I didn’t want to interrupt the presentation, so after his session had ended, I asked Paul about the need to run DBCC CHECKDB on your mirror systems.  You could have data corruption occur at the mirror and not at the principal server.  If you aren’t checking for data corruption on your mirror systems, you could be failing over to a corrupt database in the case of a disaster or even a planned failover.  You can’t run DBCC CHECKDB against the mirrored database, but you can run it against a snapshot off the mirrored database.

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  • Wireless not working on Dell XPS 17 after installing 12.04

    - by user60622
    I (linux newbie) have a Dell XPS 17 and tried to install Ubuntu 12.04. After installation all WLAN accesspoints near are detected. But I can not connect (but I am able to connect with other computers as well as with Dell XPS 17 under windows). Outputs: iwconfig lo no wireless extensions. wlan0 IEEE 802.11bg ESSID:"LerchenPoint" Mode:Managed Frequency:2.412 GHz Access Point: 58:6D:8F:A0:2D:58 Bit Rate=1 Mb/s Tx-Power=14 dBm Retry long limit:7 RTS thr:off Fragment thr:off Power Management:off Link Quality=70/70 Signal level=-37 dBm Rx invalid nwid:0 Rx invalid crypt:0 Rx invalid frag:0 Tx excessive retries:0 Invalid misc:19 Missed beacon:0 eth0 no wireless extensions. sudo lshw -class network *-network description: Wireless interface product: Centrino Wireless-N 1000 vendor: Intel Corporation physical id: 0 bus info: pci@0000:04:00.0 logical name: wlan0 version: 00 serial: 00:26:c7:99:98:28 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress bus_master cap_list ethernet physical wireless configuration: broadcast=yes driver=iwlwifi driverversion=3.2.0-24-generic firmware=39.31.5.1 build 35138 latency=0 link=no multicast=yes wireless=IEEE 802.11bg resources: irq:50 memory:f0400000-f0401fff *-network description: Ethernet interface product: RTL8111/8168B PCI Express Gigabit Ethernet controller vendor: Realtek Semiconductor Co., Ltd. physical id: 0 bus info: pci@0000:0a:00.0 logical name: eth0 version: 06 serial: f0:4d:a2:56:e3:94 size: 1Gbit/s capacity: 1Gbit/s width: 64 bits clock: 33MHz capabilities: pm msi pciexpress msix vpd bus_master cap_list ethernet physical tp mii 10bt 10bt-fd 100bt 100bt-fd 1000bt 1000bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=r8169 driverversion=2.3LK-NAPI duplex=full firmware=rtl_nic/rtl8168e-2.fw ip=192.168.0.123 latency=0 link=yes multicast=yes port=MII speed=1Gbit/s resources: irq:47 ioport:6000(size=256) memory:f0a04000-f0a04fff memory:f0a00000-f0a03fff dmesg | grep iwl [ 10.157531] iwlwifi 0000:04:00.0: PCI INT A -> GSI 17 (level, low) -> IRQ 17 [ 10.157561] iwlwifi 0000:04:00.0: setting latency timer to 64 [ 10.157598] iwlwifi 0000:04:00.0: pci_resource_len = 0x00002000 [ 10.157599] iwlwifi 0000:04:00.0: pci_resource_base = ffffc90011090000 [ 10.157601] iwlwifi 0000:04:00.0: HW Revision ID = 0x0 [ 10.157731] iwlwifi 0000:04:00.0: irq 50 for MSI/MSI-X [ 10.157834] iwlwifi 0000:04:00.0: Detected Intel(R) Centrino(R) Wireless-N 1000 BGN, REV=0x6C [ 10.157976] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S [ 10.179772] iwlwifi 0000:04:00.0: device EEPROM VER=0x15d, CALIB=0x6 [ 10.179775] iwlwifi 0000:04:00.0: Device SKU: 0X50 [ 10.179777] iwlwifi 0000:04:00.0: Valid Tx ant: 0X1, Valid Rx ant: 0X3 [ 10.179796] iwlwifi 0000:04:00.0: Tunable channels: 13 802.11bg, 0 802.11a channels [ 10.574728] iwlwifi 0000:04:00.0: loaded firmware version 39.31.5.1 build 35138 [ 10.726409] ieee80211 phy0: Selected rate control algorithm 'iwl-agn-rs' [ 19.714132] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S [ 19.777862] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S [ 2251.603089] iwlwifi 0000:04:00.0: PCI INT A disabled [ 2266.578350] iwlwifi 0000:04:00.0: PCI INT A -> GSI 17 (level, low) -> IRQ 17 [ 2266.578399] iwlwifi 0000:04:00.0: setting latency timer to 64 [ 2266.578435] iwlwifi 0000:04:00.0: pci_resource_len = 0x00002000 [ 2266.578437] iwlwifi 0000:04:00.0: pci_resource_base = ffffc90011090000 [ 2266.578439] iwlwifi 0000:04:00.0: HW Revision ID = 0x0 [ 2266.578704] iwlwifi 0000:04:00.0: irq 50 for MSI/MSI-X [ 2266.578808] iwlwifi 0000:04:00.0: Detected Intel(R) Centrino(R) Wireless-N 1000 BGN, REV=0x6C [ 2266.578916] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S [ 2266.600709] iwlwifi 0000:04:00.0: device EEPROM VER=0x15d, CALIB=0x6 [ 2266.600712] iwlwifi 0000:04:00.0: Device SKU: 0X50 [ 2266.600713] iwlwifi 0000:04:00.0: Valid Tx ant: 0X1, Valid Rx ant: 0X3 [ 2266.600727] iwlwifi 0000:04:00.0: Tunable channels: 13 802.11bg, 0 802.11a channels [ 2266.605978] iwlwifi 0000:04:00.0: loaded firmware version 39.31.5.1 build 35138 [ 2266.606331] ieee80211 phy0: Selected rate control algorithm 'iwl-agn-rs' [ 2266.614179] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S [ 2266.681541] iwlwifi 0000:04:00.0: L1 Enabled; Disabling L0S Solutions I tried: rfkill list all 0: dell-wifi: Wireless LAN Soft blocked: no Hard blocked: no 2: phy0: Wireless LAN Soft blocked: no Hard blocked: no echo "options iwlwifi 11n_disable=1" | sudo tee /etc/modprobe.d/iwlwifi.conf options iwlwifi 11n_disable=1 sudo modprobe -rfv iwlwifi WARNING: All config files need .conf: /etc/modprobe.d/blacklist, it will be ignored in a future release. rmmod /lib/modules/3.2.0-24-generic/kernel/drivers/net/wireless/iwlwifi/iwlwifi.ko rmmod /lib/modules/3.2.0-24-generic/kernel/net/mac80211/mac80211.ko rmmod /lib/modules/3.2.0-24-generic/kernel/net/wireless/cfg80211.ko sudo modprobe iwlwifi WARNING: All config files need .conf: /etc/modprobe.d/blacklist, it will be ignored in a future release. replacing iwlwifi-1000-5.ucode (current driver) against iwlwifi-1000-3.ucode sudo jockey-gtk: (jockey-gtk:2493): Gtk-CRITICAL **: gtk_icon_set_render_icon_pixbuf: assertion icon_set != NULL' failed (jockey-gtk:2493): Gtk-CRITICAL **: gtk_icon_set_render_icon_pixbuf: assertion icon_set != NULL' failed nothing is listet in "Additional drivers" (german: "Zusätzliche Treiber"). gksudo gedit /etc/modprobe.d/blacklist.conf add "blacklist acer_wmi" Any help would be appreciated very much. Thanks!!

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  • Detecting Duplicates Using Oracle Business Rules

    - by joeywong-Oracle
    Recently I was involved with a Business Process Management Proof of Concept (BPM PoC) where we wanted to show how customers could use Oracle Business Rules (OBR) to easily define some rules to detect certain conditions, such as duplicate account numbers, duplicate names, high transaction amounts, etc, in a set of transactions. Traditionally you would have to loop through the transactions and compare each transaction with each other to find matching conditions. This is not particularly nice as it relies on more traditional approaches (coding) and is not the most efficient way. OBR is a great place to house these types’ of rules as it allows users/developers to externalise the rules, in a simpler manner, externalising the rules from the message flows and allows users to change them when required. So I went ahead looking for some examples. After quite a bit of time spent Googling, I did not find much out in the blogosphere. In fact the best example was actually from...... wait for it...... Oracle Documentation! (http://docs.oracle.com/cd/E28271_01/user.1111/e10228/rules_start.htm#ASRUG228) However, if you followed the link there was not much explanation provided with the example. So the aim of this article is to provide a little more explanation to the example so that it can be better understood. Note: I won’t be covering the BPM parts in great detail. Use case: Payment instruction file is required to be processed. Before instruction file can be processed it needs to be approved by a business user. Before the approval process, it would be useful to run the payment instruction file through OBR to look for transactions of interest. The output of the OBR can then be used to flag the transactions for the approvers to investigate. Example BPM Process So let’s start defining the Business Rules Dictionary. For the input into our rules, we will be passing in an array of payments which contain some basic information for our demo purposes. Input to Business Rules And for our output we want to have an array of rule output messages. Note that the element I am using for the output is only for one rule message element and not an array. We will configure the Business Rules component later to return an array instead. Output from Business Rules Business Rule – Create Dictionary Fill in all the details and click OK. Open the Business Rules component and select Decision Functions from the side. Modify the Decision Function Configuration Select the decision function and click on the edit button (the pencil), don’t worry that JDeveloper indicates that there is an error with the decision function. Then click the Ouputs tab and make sure the checkbox under the List column is checked, this is to tell the Business Rules component that it should return an array of rule message elements. Updating the Decision Service Next we will define the actual rules. Click on Ruleset1 on the side and then the Create Rule in the IF/THEN Rule section. Creating new rule in ruleset Ok, this is where some detailed explanation is required. Remember that the input to this Business Rules dictionary is a list of payments, each of those payments were of the complex type PaymentType. Each of those payments in the Oracle Business Rules engine is treated as a fact in its working memory. Implemented rule So in the IF/THEN rule, the first task is to grab two PaymentType facts from the working memory and assign them to temporary variable names (payment1 and payment2 in our example). Matching facts Once we have them in the temporary variables, we can then start comparing them to each other. For our demonstration we want to find payments where the account numbers were the same but the account name was different. Suspicious payment instruction And to stop the rule from comparing the same facts to each other, over and over again, we have to include the last test. Stop rule from comparing endlessly And that’s it! No for loops, no need to keep track of what you have or have not compared, OBR handles all that for you because everything is done in its working memory. And once all the tests have been satisfied we need to assert a new fact for the output. Assert the output fact Save your Business Rules. Next step is to complete the data association in the BPM process. Pay extra care to use Copy List instead of the default Copy when doing data association at an array level. Input and output data association Deploy and test. Test data Rule matched Parting words: Ideally you would then use the output of the Business Rules component to then display/flag the transactions which triggered the rule so that the approver can investigate. Link: SOA Project Archive [Download]

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  • CD/DVD drive not mounted when inserted with Disc of any kind

    - by Cisco Sán
    I just noticed that if a insert a CD or a DVD of any kind, the Drive will start spinning but it will not show the mounted disc. Before it used to ask me what to do with the media inserted. Now it doesn't even do that. I ran in the terminal this code: eject -n and it displays this: " eject: device is `/dev/sr0'" what can I do to get the functionality back on my drive. also ran this command: sudo mount -o ro,unhide,uid=1000 /dev/cdrom /mnt/cdrom but in return i get this: " mount: mount point /mnt/cdrom does not exist" Running Ubuntu 11.10 HERE IS THE HISTORY UNTIL NOW thanks Waltinator: I ran the 'dmesg' but don't know what I'm looking for. Im a newbie on this. The same thing with the 'ls -rlt /var/log' command. Should I create the directory for the mount? at this point really don't know what to do. – Cisco Sán 7 hours ago Here are 3 lines from my dmesg after I successfully inserted a CD: [ 4804.416018] wlan0: no IPv6 routers present [ 8214.125450] ISdit ISO 9660 Extensions: Microsoft Joliet Level 3 [ 8214.136556] ISO 9660 Extensions: RRIP_1991A The first line is a previous event, my wireless going online. The next 2 lines are a good result. The number in square brackets is "seconds since boot", the rest of the line is usually helpful. And no, you should NOT create the mount point. Let's try to get the automatic mounting to work. – waltinator 7 hours ago ok this are my last 3 lines on the 'dmesg' [ 18.130819] init: plymouth-stop pre-start process (1396) terminated with status 1 [ 28.780011] wlan0: no IPv6 routers present [ 505.632119] CE: hpet increased min_delta_ns to 20113 nsec – Cisco Sán 6 hours ago It looks like your CD/DVD drive is not connected to the data bus, and not causing an interrupt when you insert a platter. – waltinator 6 hours ago Try dmesg | grep -A8 CD-ROM which should show you what the system thought was available when it came up. – waltinator 6 hours ago here is my printout [0.774351] scsi 0:0:0:0: CD-ROM HL-DT-ST DVD+-RW GSA-T40N A100 PQ: 0 ANSI: 5 [0.778117] sr0: scsi3-mmc drive: 24x/24x writer dvd-ram cd/rw xa/form2 cdda tray [0.778122] cdrom: Uniform CD-ROM driver Revision: 3.20 [0.778282] sr 0:0:0:0: Attached scsi CD-ROM sr0 [0.778340] sr 0:0:0:0: Attached scsi generic sg0 type 5 [0.780416] Freeing unused kernel memory: 984k freed [0.780732] Write protecting the kernel read-only data: 10240k [0.780986] Freeing unused kernel memory: 20k freed [0.786331] Freeing unused kernel memory: 1400k freed [0.804912] udevd[90]: starting version 173 [0.874178] r8169 Gigabit Ethernet driver 2.3LK-NAPI loaded [0.874208] r8169 0000:02:00.0: PCI INT A - GSI 16 (level, low) - IRQ 16 OK, your system sees the drive. Can you open and close the tray with eject and eject -t? Run udevadm monitor while you insert a CD (type ^C when done) and see if you get "change" and "add" messages. – waltinator 6 hours ago ok, "eject" works perfectly "eject -t" does nothing. this is the message for "udevadm monitor": KERNEL[13771.009267] change /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0:0/block/sr0 (block) UDEV [13773.878887] change /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0 /block/sr0 (block) – Cisco Sán 6 hours ago sudo hwinfo --cdrom (the hwinfo package is installable through Software Center) describes my CD-ROM, try it. – waltinator 4 hours ago My read out from the "sudo hwinfo --cdrom" are the following: hal.1: read hal dataprocess 2753: arguments to dbus_move_error() were incorrect, assertion "(dest) == NULL || !dbus_error_is_set ((dest))" failed in file ../../dbus/dbus-errors.c line 280. This is normally a bug in some application using the D-Bus library. libhal.c 3483 : Error unsubscribing to signals, error=The name org.freedesktop.Hal was not provided by any .service files 22: SCSI 00.0: 10602 CD-ROM (DVD) [Created at block.247] Unique ID: KD9E.JgkxTS4hgl2 Parent ID: 3p2J.gdUMCD83e+E SysFS ID: /class/block/sr0 SysFS BusID: 0:0:0:0 SysFS Device Link: /devices/pci0000:00/0000:00:1f.1/host0/target0:0:0/0:0:0:0 Hardware Class: cdrom Model: "HL-DT-ST DVD+-RW GSA-T40N" Vendor: "HL-DT-ST" Device: "DVD+-RW GSA-T40N" Revision: "A100" Driver: "ata_piix", "sr" Driver Modules: "ata_piix" Device File: /dev/sr0 (/dev/sg0) Device Files: /dev/sr0, /dev/scd0, /dev/disk/by-id/ata-HL-DT-ST_DVD+_-RW_GSA-T40N_K048BJ74257, /dev/disk/by-path/pci-0000:00:1f.1-scsi-0:0:0:0, /dev/cdrom, /dev/cdrw, /dev/dvd, /dev/dvdrw Device Number: block 11:0 (char 21:0) Features: DVD Config Status: cfg=new, avail=yes, need=no, active=unknown Attached to: #17 (IDE interface) Drive Speed: 31 Volume ID: "Movie" Publisher: "INTERVIDEO" Creation date: "20050424162207000" Thanks for the help. To Castro, hope this is what you meant and sorry for the comments..

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  • How would you gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    I'm relatively new to StackExchange and not sure if it's appropriate place to ask design question. Site gives me a hint "The question you're asking appears subjective and is likely to be closed". Please let me know. Anyway.. One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting? Thank you very much in advance for your thoughts.

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  • Intel Centrino Wireless-N 1000 Again ! Ubuntu 13.04 x64

    - by vafa
    First I have to say that I tried everything written about this concept. The problem is that it stops working randomly in 3 main forms : 1 - sometimes it disconnect from wireless network and reconnect automatically 2 - sometimes it disconnect and wont connect no matter what (needs reboot) 3 - some times it's still connected but cannot ping or surf or whatever. I already tried disabling N mod using these commands : sudo modprobe -r iwlwifi modprobe iwlwifi 11n_disable=1 (or 0, whatever) it didn't help . these are the results of lspci, sudo lshw -C network, ifconfig, iwconfig, rfkill list when it disconnected and didn't connect till reboot : ifconfig : eth0 Link encap:Ethernet HWaddr c8:0a:a9:34:65:77 UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:1563213476557380 errors:9379306629148050 dropped:3126435543049350 overruns:1563217771524675 frame:7816088857623375 TX packets:1563217771524675 errors:6252871086098700 dropped:0 overruns:1563217771524675 carrier:3126435543049350 collisions:7816088857623375 txqueuelen:1000 RX bytes:1563217771524675 (1.5 PB) TX bytes:1563217771524675 (1.5 PB) ham0 Link encap:Ethernet HWaddr 7a:79:19:a5:e4:93 inet addr:25.165.228.147 Bcast:25.255.255.255 Mask:255.0.0.0 inet6 addr: fe80::7879:19ff:fea5:e493/64 Scope:Link inet6 addr: 2620:9b::19a5:e493/96 Scope:Global UP BROADCAST RUNNING MULTICAST MTU:1404 Metric:1 RX packets:7743 errors:0 dropped:0 overruns:0 frame:0 TX packets:1250 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:500 RX bytes:665642 (665.6 KB) TX bytes:204056 (204.0 KB) lo Link encap:Local Loopback inet addr:127.0.0.1 Mask:255.0.0.0 inet6 addr: ::1/128 Scope:Host UP LOOPBACK RUNNING MTU:65536 Metric:1 RX packets:41138 errors:0 dropped:0 overruns:0 frame:0 TX packets:41138 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:6420962 (6.4 MB) TX bytes:6420962 (6.4 MB) wlan0 Link encap:Ethernet HWaddr 00:1e:64:45:fb:70 inet6 addr: fe80::21e:64ff:fe45:fb70/64 Scope:Link UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:286999 errors:0 dropped:0 overruns:0 frame:0 TX packets:226966 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:324386887 (324.3 MB) TX bytes:30674804 (30.6 MB) iwconfig : ham0 no wireless extensions. eth0 no wireless extensions. lo no wireless extensions. wlan0 IEEE 802.11bg ESSID:off/any Mode:Managed Access Point: Not-Associated Tx-Power=14 dBm Retry long limit:7 RTS thr:off Fragment thr:off Power Management:off sudo lshw -C network: *-network description: Wireless interface product: Centrino Wireless-N 1000 [Condor Peak] vendor: Intel Corporation physical id: 0 bus info: pci@0000:07:00.0 logical name: wlan0 version: 00 serial: 00:1e:64:45:fb:70 width: 64 bits clock: 33MHz capabilities: pm msi pciexpress bus_master cap_list ethernet physical wireless configuration: broadcast=yes driver=iwlwifi driverversion=3.8.0-30-generic firmware=39.31.5.1 build 35138 latency=0 link=no multicast=yes wireless=IEEE 802.11bg resources: irq:46 memory:c0400000-c0401fff *-network description: Ethernet interface product: AR8131 Gigabit Ethernet vendor: Qualcomm Atheros physical id: 0 bus info: pci@0000:09:00.0 logical name: eth0 version: c0 serial: c8:0a:a9:34:65:77 capacity: 1Gbit/s width: 64 bits clock: 33MHz capabilities: pm msi pciexpress vpd cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd 1000bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=atl1c driverversion=1.0.1.1-NAPI latency=0 link=no multicast=yes port=twisted pair resources: irq:47 memory:c0900000-c093ffff ioport:5000(size=128) *-network description: Ethernet interface physical id: 2 logical name: ham0 serial: 7a:79:19:a5:e4:93 size: 10Mbit/s capabilities: ethernet physical configuration: autonegotiation=off broadcast=yes driver=tun driverversion=1.6 duplex=full ip=25.165.228.147 link=yes multicast=yes port=twisted pair speed=10Mbit/s lspci: 00:00.0 Host bridge: Intel Corporation Mobile 4 Series Chipset Memory Controller Hub (rev 07) 00:01.0 PCI bridge: Intel Corporation Mobile 4 Series Chipset PCI Express Graphics Port (rev 07) 00:1a.0 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #4 (rev 03) 00:1a.1 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #5 (rev 03) 00:1a.7 USB controller: Intel Corporation 82801I (ICH9 Family) USB2 EHCI Controller #2 (rev 03) 00:1b.0 Audio device: Intel Corporation 82801I (ICH9 Family) HD Audio Controller (rev 03) 00:1c.0 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 1 (rev 03) 00:1c.3 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 4 (rev 03) 00:1c.5 PCI bridge: Intel Corporation 82801I (ICH9 Family) PCI Express Port 6 (rev 03) 00:1d.0 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #1 (rev 03) 00:1d.1 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #2 (rev 03) 00:1d.2 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #3 (rev 03) 00:1d.3 USB controller: Intel Corporation 82801I (ICH9 Family) USB UHCI Controller #6 (rev 03) 00:1d.7 USB controller: Intel Corporation 82801I (ICH9 Family) USB2 EHCI Controller #1 (rev 03) 00:1e.0 PCI bridge: Intel Corporation 82801 Mobile PCI Bridge (rev 93) 00:1f.0 ISA bridge: Intel Corporation ICH9M LPC Interface Controller (rev 03) 00:1f.2 SATA controller: Intel Corporation 82801IBM/IEM (ICH9M/ICH9M-E) 4 port SATA Controller [AHCI mode] (rev 03) 00:1f.3 SMBus: Intel Corporation 82801I (ICH9 Family) SMBus Controller (rev 03) 01:00.0 VGA compatible controller: NVIDIA Corporation G98M [GeForce G 105M] (rev a1) 07:00.0 Network controller: Intel Corporation Centrino Wireless-N 1000 [Condor Peak] 09:00.0 Ethernet controller: Qualcomm Atheros AR8131 Gigabit Ethernet (rev c0) rfkill list : 1: acer-wireless: Wireless LAN Soft blocked: no Hard blocked: no 2: acer-bluetooth: Bluetooth Soft blocked: yes Hard blocked: no 9: phy0: Wireless LAN Soft blocked: no Hard blocked: no any help will be REALLLYYYY appreciated

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  • How can I gather client's data on Google App Engine without using Datastore/Backend Instances too much?

    - by ruslan
    One of the projects I'm working on is online survey engine. It's my first big commercial project on Google App Engine. I need your advice on how to collect stats and efficiently record them in DataStore without bankrupting me. Initial requirements are: After user finishes survey client sends list of pairs [ID (int) + PercentHit (double)]. This list shows how close answers of this user match predefined answers of reference answerers (which identified by IDs). I call them "target IDs". Creator of the survey wants to see aggregated % for given IDs for last hour, particular timeframe or from the beginning of the survey. Some surveys may have thousands of target/reference answerers. So I created entity public class HitsStatsDO implements Serializable { @Id transient private Long id; transient private Long version = (long) 0; transient private Long startDate; @Parent transient private Key parent; // fake parent which contains target id @Transient int targetId; private double avgPercent; private long hitCount; } But writing HitsStatsDO for each target from each user would give a lot of data. For instance I had a survey with 3000 targets which was answered by ~4 million people within one week with 300K people taking survey in first day. Even if we assume they were answering it evenly for 24 hours it would give us ~1040 writes/second. Obviously it hits concurrent writes limit of Datastore. I decided I'll collect data for one hour and save that, that's why there are avgPercent and hitCount in HitsStatsDO. GAE instances are stateless so I had to use dynamic backend instance. There I have something like this: // Contains stats for one hour private class Shard { ReadWriteLock lock = new ReentrantReadWriteLock(); Map<Integer, HitsStatsDO> map = new HashMap<Integer, HitsStatsDO>(); // Key is target ID public void saveToDatastore(); public void updateStats(Long startDate, Map<Integer, Double> hits); } and map with shard for current hour and previous hour (which doesn't stay here for long) private HashMap<Long, Shard> shards = new HashMap<Long, Shard>(); // Key is HitsStatsDO.startDate So once per hour I dump Shard for previous hour to Datastore. Plus I have class LifetimeStats which keeps Map<Integer, HitsStatsDO> in memcached where map-key is target ID. Also in my backend shutdown hook method I dump stats for unfinished hour to Datastore. There is only one major issue here - I have only ONE backend instance :) It raises following questions on which I'd like to hear your opinion: Can I do this without using backend instance ? What if one instance is not enough ? How can I split data between multiple dynamic backend instances? It hard because I don't know how many I have because Google creates new one as load increases. I know I can launch exact number of resident backend instances. But how many ? 2, 5, 10 ? What if I have no load at all for a week. Constantly running 10 backend instances is too expensive. What do I do with data from clients while backend instance is dead/restarting?

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  • Atheros AR2413 wireless not working after shutdown

    - by Chandrasekhar
    I am using a Ubuntu 11.04 on an Acer aspire 3680 laptop and my wifi is not working. I followed the below commands to install the madwifi driver: sudo su apt-get install subversion cd /usr/src svn checkout http://madwifi-project.org/svn/madwifi/trunk madwifi tar cfvz madwifi.tgz cd madwifi make && make install echo "blacklist ath5k" /etc/modprobe.d/blacklist.conf echo "ath_pci" /etc/modules modprobe ath_pci sudo reboot After installation I am facing the same problem. My wifi wont work after I shutdown. Infact it didn't work after suspend but I rectified that problem by the following commands: Command 1: sudo rmmod -f ath_pci sudo rfkill unblock all sudo modprobe ath_pci along with the command SUSPEND_MODULES=ath_pci added to the /etc/pm/config.d/madwifi directory. So if I suspend and then on my laptop the wifi loads well and doesn't create a problem. But if I shutdown my laptop the wifi never loads again and eachtime I have to run a Ubuntu 9.04 live CD to load it. I did try adding the Command 1 to the /etc/rc.local directory but still it doesn't work. So my question is: What should I do in order to make my wireless work without having to run a live CD of ubuntu 9.04 everytime after shutdown? Thanks. Here are the outputs which one might need: Output 1 chandru@chandru-acer:~$ lspci 00:00.0 Host bridge: Intel Corporation Mobile 945GM/PM/GMS, 943/940GML and 945GT Express Memory Controller Hub (rev 03) 00:02.0 VGA compatible controller: Intel Corporation Mobile 945GM/GMS, 943/940GML Express Integrated Graphics Controller (rev 03) 00:02.1 Display controller: Intel Corporation Mobile 945GM/GMS/GME, 943/940GML Express Integrated Graphics Controller (rev 03) 00:1b.0 Audio device: Intel Corporation N10/ICH 7 Family High Definition Audio Controller (rev 02) 00:1c.0 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 1 (rev 02) 00:1c.1 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 2 (rev 02) 00:1c.2 PCI bridge: Intel Corporation N10/ICH 7 Family PCI Express Port 3 (rev 02) 00:1d.0 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #1 (rev 02) 00:1d.1 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #2 (rev 02) 00:1d.2 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #3 (rev 02) 00:1d.3 USB Controller: Intel Corporation N10/ICH 7 Family USB UHCI Controller #4 (rev 02) 00:1d.7 USB Controller: Intel Corporation N10/ICH 7 Family USB2 EHCI Controller (rev 02) 00:1e.0 PCI bridge: Intel Corporation 82801 Mobile PCI Bridge (rev e2) 00:1f.0 ISA bridge: Intel Corporation 82801GBM (ICH7-M) LPC Interface Bridge (rev 02) 00:1f.2 IDE interface: Intel Corporation 82801GBM/GHM (ICH7 Family) SATA IDE Controller (rev 02) 00:1f.3 SMBus: Intel Corporation N10/ICH 7 Family SMBus Controller (rev 02) 02:00.0 Ethernet controller: Marvell Technology Group Ltd. 88E8038 PCI-E Fast Ethernet Controller (rev 14) 0a:03.0 Ethernet controller: Atheros Communications Inc. AR2413 802.11bg NIC (rev 01) 0a:09.0 CardBus bridge: Texas Instruments PCIxx12 Cardbus Controller 0a:09.2 Mass storage controller: Texas Instruments 5-in-1 Multimedia Card Reader (SD/MMC/MS/MS PRO/xD) Output 2: lsmod Module Size Used by wlan_tkip 17074 2 binfmt_misc 13213 1 parport_pc 32111 0 ppdev 12849 0 snd_hda_codec_si3054 12924 1 snd_hda_codec_realtek 255882 1 joydev 17322 0 snd_atiixp_modem 18624 0 snd_via82xx_modem 18305 0 snd_intel8x0m 18493 0 snd_ac97_codec 105614 3 snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m snd_hda_intel 24113 2 ac97_bus 12642 1 snd_ac97_codec snd_hda_codec 90901 3 snd_hda_codec_si3054,snd_hda_codec_realtek,snd_hda_intel i915 451053 3 snd_hwdep 13274 1 snd_hda_codec snd_pcm 80042 7 snd_hda_codec_si3054,snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_ac97_codec,snd_hda_intel,snd_hda_codec snd_seq_midi 13132 0 snd_rawmidi 25269 1 snd_seq_midi drm_kms_helper 40971 1 i915 snd_seq_midi_event 14475 1 snd_seq_midi snd_seq 51291 2 snd_seq_midi,snd_seq_midi_event pcmcia 39671 0 snd_timer 28659 2 snd_pcm,snd_seq snd_seq_device 14110 3 snd_seq_midi,snd_rawmidi,snd_seq drm 184164 4 i915,drm_kms_helper yenta_socket 27230 0 tifm_7xx1 12898 0 wlan_scan_sta 21945 1 ath_rate_sample 17279 1 pcmcia_rsrc 18292 1 yenta_socket psmouse 73312 0 tifm_core 15040 1 tifm_7xx1 snd 55295 18 snd_hda_codec_si3054,snd_hda_codec_realtek,snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_ac97_codec,snd_hda_intel,snd_hda_codec,snd_hwdep,snd_pcm,snd_rawmidi,snd_seq,snd_timer,snd_seq_device serio_raw 12990 0 i2c_algo_bit 13184 1 i915 soundcore 12600 1 snd pcmcia_core 21505 3 pcmcia,yenta_socket,pcmcia_rsrc video 19112 1 i915 ath_pci 183044 0 snd_page_alloc 14073 5 snd_atiixp_modem,snd_via82xx_modem,snd_intel8x0m,snd_hda_intel,snd_pcm wlan 224640 5 wlan_tkip,wlan_scan_sta,ath_rate_sample,ath_pci ath_hal 398701 3 ath_rate_sample,ath_pci lp 13349 0 parport 36746 3 parport_pc,ppdev,lp usbhid 41704 0 hid 77084 1 usbhid sky2 49172 0 Output 3 root@chandru-acer:~# lshw -C network PCI (sysfs) *-network description: Ethernet interface product: 88E8038 PCI-E Fast Ethernet Controller vendor: Marvell Technology Group Ltd. physical id: 0 bus info: pci@0000:02:00.0 logical name: eth0 version: 14 serial: 00:16:36:fb:aa:64 capacity: 100Mbit/s width: 64 bits clock: 33MHz capabilities: pm vpd msi pciexpress bus_master cap_list ethernet physical tp 10bt 10bt-fd 100bt 100bt-fd autonegotiation configuration: autonegotiation=on broadcast=yes driver=sky2 driverversion=1.28 firmware=N/A latency=0 link=no multicast=yes port=twisted pair resources: irq:43 memory:44000000-44003fff ioport:2000(size=256) *-network description: Wireless interface product: AR2413 802.11bg NIC vendor: Atheros Communications Inc. physical id: 3 bus info: pci@0000:0a:03.0 logical name: wifi0 version: 01 serial: 00:19:7d:d3:0c:fd width: 32 bits clock: 33MHz capabilities: pm bus_master cap_list logical ethernet physical wireless configuration: broadcast=yes driver=ath_pci ip=192.168.1.6 latency=96 maxlatency=28 mingnt=10 multicast=yes wireless=IEEE 802.11g resources: irq:18 memory:d0000000-d000ffff Output 4 root@chandru-acer:~# lsmod | grep ath_pci ath_pci 183044 0 wlan 224640 5 wlan_tkip,wlan_scan_sta,ath_rate_sample,ath_pci ath_hal 398701 3 ath_rate_sample,ath_pci

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  • Oracle NoSQL Database Exceeds 1 Million Mixed YCSB Ops/Sec

    - by Charles Lamb
    We ran a set of YCSB performance tests on Oracle NoSQL Database using SSD cards and Intel Xeon E5-2690 CPUs with the goal of achieving 1M mixed ops/sec on a 95% read / 5% update workload. We used the standard YCSB parameters: 13 byte keys and 1KB data size (1,102 bytes after serialization). The maximum database size was 2 billion records, or approximately 2 TB of data. We sized the shards to ensure that this was not an "in-memory" test (i.e. the data portion of the B-Trees did not fit into memory). All updates were durable and used the "simple majority" replica ack policy, effectively 'committing to the network'. All read operations used the Consistency.NONE_REQUIRED parameter allowing reads to be performed on any replica. In the past we have achieved 100K ops/sec using SSD cards on a single shard cluster (replication factor 3) so for this test we used 10 shards on 15 Storage Nodes with each SN carrying 2 Rep Nodes and each RN assigned to its own SSD card. After correcting a scaling problem in YCSB, we blew past the 1M ops/sec mark with 8 shards and proceeded to hit 1.2M ops/sec with 10 shards.  Hardware Configuration We used 15 servers, each configured with two 335 GB SSD cards. We did not have homogeneous CPUs across all 15 servers available to us so 12 of the 15 were Xeon E5-2690, 2.9 GHz, 2 sockets, 32 threads, 193 GB RAM, and the other 3 were Xeon E5-2680, 2.7 GHz, 2 sockets, 32 threads, 193 GB RAM.  There might have been some upside in having all 15 machines configured with the faster CPU, but since CPU was not the limiting factor we don't believe the improvement would be significant. The client machines were Xeon X5670, 2.93 GHz, 2 sockets, 24 threads, 96 GB RAM. Although the clients had 96 GB of RAM, neither the NoSQL Database or YCSB clients require anywhere near that amount of memory and the test could have just easily been run with much less. Networking was all 10GigE. YCSB Scaling Problem We made three modifications to the YCSB benchmark. The first was to allow the test to accommodate more than 2 billion records (effectively int's vs long's). To keep the key size constant, we changed the code to use base 32 for the user ids. The second change involved to the way we run the YCSB client in order to make the test itself horizontally scalable.The basic problem has to do with the way the YCSB test creates its Zipfian distribution of keys which is intended to model "real" loads by generating clusters of key collisions. Unfortunately, the percentage of collisions on the most contentious keys remains the same even as the number of keys in the database increases. As we scale up the load, the number of collisions on those keys increases as well, eventually exceeding the capacity of the single server used for a given key.This is not a workload that is realistic or amenable to horizontal scaling. YCSB does provide alternate key distribution algorithms so this is not a shortcoming of YCSB in general. We decided that a better model would be for the key collisions to be limited to a given YCSB client process. That way, as additional YCSB client processes (i.e. additional load) are added, they each maintain the same number of collisions they encounter themselves, but do not increase the number of collisions on a single key in the entire store. We added client processes proportionally to the number of records in the database (and therefore the number of shards). This change to the use of YCSB better models a use case where new groups of users are likely to access either just their own entries, or entries within their own subgroups, rather than all users showing the same interest in a single global collection of keys. If an application finds every user having the same likelihood of wanting to modify a single global key, that application has no real hope of getting horizontal scaling. Finally, we used read/modify/write (also known as "Compare And Set") style updates during the mixed phase. This uses versioned operations to make sure that no updates are lost. This mode of operation provides better application behavior than the way we have typically run YCSB in the past, and is only practical at scale because we eliminated the shared key collision hotspots.It is also a more realistic testing scenario. To reiterate, all updates used a simple majority replica ack policy making them durable. Scalability Results In the table below, the "KVS Size" column is the number of records with the number of shards and the replication factor. Hence, the first row indicates 400m total records in the NoSQL Database (KV Store), 2 shards, and a replication factor of 3. The "Clients" column indicates the number of YCSB client processes. "Threads" is the number of threads per process with the total number of threads. Hence, 90 threads per YCSB process for a total of 360 threads. The client processes were distributed across 10 client machines. Shards KVS Size Clients Mixed (records) Threads OverallThroughput(ops/sec) Read Latencyav/95%/99%(ms) Write Latencyav/95%/99%(ms) 2 400m(2x3) 4 90(360) 302,152 0.76/1/3 3.08/8/35 4 800m(4x3) 8 90(720) 558,569 0.79/1/4 3.82/16/45 8 1600m(8x3) 16 90(1440) 1,028,868 0.85/2/5 4.29/21/51 10 2000m(10x3) 20 90(1800) 1,244,550 0.88/2/6 4.47/23/53

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  • CPU Usage in Very Large Coherence Clusters

    - by jpurdy
    When sizing Coherence installations, one of the complicating factors is that these installations (by their very nature) tend to be application-specific, with some being large, memory-intensive caches, with others acting as I/O-intensive transaction-processing platforms, and still others performing CPU-intensive calculations across the data grid. Regardless of the primary resource requirements, Coherence sizing calculations are inherently empirical, in that there are so many permutations that a simple spreadsheet approach to sizing is rarely optimal (though it can provide a good starting estimate). So we typically recommend measuring actual resource usage (primarily CPU cycles, network bandwidth and memory) at a given load, and then extrapolating from those measurements. Of course there may be multiple types of load, and these may have varying degrees of correlation -- for example, an increased request rate may drive up the number of objects "pinned" in memory at any point, but the increase may be less than linear if those objects are naturally shared by concurrent requests. But for most reasonably-designed applications, a linear resource model will be reasonably accurate for most levels of scale. However, at extreme scale, sizing becomes a bit more complicated as certain cluster management operations -- while very infrequent -- become increasingly critical. This is because certain operations do not naturally tend to scale out. In a small cluster, sizing is primarily driven by the request rate, required cache size, or other application-driven metrics. In larger clusters (e.g. those with hundreds of cluster members), certain infrastructure tasks become intensive, in particular those related to members joining and leaving the cluster, such as introducing new cluster members to the rest of the cluster, or publishing the location of partitions during rebalancing. These tasks have a strong tendency to require all updates to be routed via a single member for the sake of cluster stability and data integrity. Fortunately that member is dynamically assigned in Coherence, so it is not a single point of failure, but it may still become a single point of bottleneck (until the cluster finishes its reconfiguration, at which point this member will have a similar load to the rest of the members). The most common cause of scaling issues in large clusters is disabling multicast (by configuring well-known addresses, aka WKA). This obviously impacts network usage, but it also has a large impact on CPU usage, primarily since the senior member must directly communicate certain messages with every other cluster member, and this communication requires significant CPU time. In particular, the need to notify the rest of the cluster about membership changes and corresponding partition reassignments adds stress to the senior member. Given that portions of the network stack may tend to be single-threaded (both in Coherence and the underlying OS), this may be even more problematic on servers with poor single-threaded performance. As a result of this, some extremely large clusters may be configured with a smaller number of partitions than ideal. This results in the size of each partition being increased. When a cache server fails, the other servers will use their fractional backups to recover the state of that server (and take over responsibility for their backed-up portion of that state). The finest granularity of this recovery is a single partition, and the single service thread can not accept new requests during this recovery. Ordinarily, recovery is practically instantaneous (it is roughly equivalent to the time required to iterate over a set of backup backing map entries and move them to the primary backing map in the same JVM). But certain factors can increase this duration drastically (to several seconds): large partitions, sufficiently slow single-threaded CPU performance, many or expensive indexes to rebuild, etc. The solution of course is to mitigate each of those factors but in many cases this may be challenging. Larger clusters also lead to the temptation to place more load on the available hardware resources, spreading CPU resources thin. As an example, while we've long been aware of how garbage collection can cause significant pauses, it usually isn't viewed as a major consumer of CPU (in terms of overall system throughput). Typically, the use of a concurrent collector allows greater responsiveness by minimizing pause times, at the cost of reducing system throughput. However, at a recent engagement, we were forced to turn off the concurrent collector and use a traditional parallel "stop the world" collector to reduce CPU usage to an acceptable level. In summary, there are some less obvious factors that may result in excessive CPU consumption in a larger cluster, so it is even more critical to test at full scale, even though allocating sufficient hardware may often be much more difficult for these large clusters.

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  • Developing Schema Compare for Oracle (Part 6): 9i Query Performance

    - by Simon Cooper
    All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

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  • Why do I get an exception when playing multiple sound instances?

    - by Boreal
    Right now, I'm adding a rudimentary sound engine to my game. So far, I am able to load in a WAV file and play it once, then free up the memory when I close the game. However, the game crashes with a nice ArgumentOutOfBoundsException when I try to play another sound instance. Specified argument was out of the range of valid values. Parameter name: readLength I'm following this tutorial pretty much exactly, but I still keep getting the aforementioned error. Here's my sound-related code. /// <summary> /// Manages all sound instances. /// </summary> public static class Audio { static XAudio2 device; static MasteringVoice master; static List<SoundInstance> instances; /// <summary> /// The XAudio2 device. /// </summary> internal static XAudio2 Device { get { return device; } } /// <summary> /// Initializes the audio device and master track. /// </summary> internal static void Initialize() { device = new XAudio2(); master = new MasteringVoice(device); instances = new List<SoundInstance>(); } /// <summary> /// Releases all XA2 resources. /// </summary> internal static void Shutdown() { foreach(SoundInstance i in instances) i.Dispose(); master.Dispose(); device.Dispose(); } /// <summary> /// Registers a sound instance with the system. /// </summary> /// <param name="instance">Sound instance</param> internal static void AddInstance(SoundInstance instance) { instances.Add(instance); } /// <summary> /// Disposes any sound instance that has stopped playing. /// </summary> internal static void Update() { List<SoundInstance> temp = new List<SoundInstance>(instances); foreach(SoundInstance i in temp) if(!i.Playing) { i.Dispose(); instances.Remove(i); } } } /// <summary> /// Loads sounds from various files. /// </summary> internal class SoundLoader { /// <summary> /// Loads a .wav sound file. /// </summary> /// <param name="format">The decoded format will be sent here</param> /// <param name="buffer">The data will be sent here</param> /// <param name="soundName">The path to the WAV file</param> internal static void LoadWAV(out WaveFormat format, out AudioBuffer buffer, string soundName) { WaveStream wave = new WaveStream(soundName); format = wave.Format; buffer = new AudioBuffer(); buffer.AudioData = wave; buffer.AudioBytes = (int)wave.Length; buffer.Flags = BufferFlags.EndOfStream; } } /// <summary> /// Manages the data for a single sound. /// </summary> public class Sound : IAsset { WaveFormat format; AudioBuffer buffer; /// <summary> /// Loads a sound from a file. /// </summary> /// <param name="soundName">The path to the sound file</param> /// <returns>Whether the sound loaded successfully</returns> public bool Load(string soundName) { if(soundName.EndsWith(".wav")) SoundLoader.LoadWAV(out format, out buffer, soundName); else return false; return true; } /// <summary> /// Plays the sound. /// </summary> public void Play() { Audio.AddInstance(new SoundInstance(format, buffer)); } /// <summary> /// Unloads the sound from memory. /// </summary> public void Unload() { buffer.Dispose(); } } /// <summary> /// Manages a single sound instance. /// </summary> public class SoundInstance { SourceVoice source; bool playing; /// <summary> /// Whether the sound is currently playing. /// </summary> public bool Playing { get { return playing; } } /// <summary> /// Starts a new instance of a sound. /// </summary> /// <param name="format">Format of the sound</param> /// <param name="buffer">Buffer holding sound data</param> internal SoundInstance(WaveFormat format, AudioBuffer buffer) { source = new SourceVoice(Audio.Device, format); source.BufferEnd += (s, e) => playing = false; source.Start(); source.SubmitSourceBuffer(buffer); // THIS IS WHERE THE EXCEPTION IS THROWN playing = true; } /// <summary> /// Releases memory used by the instance. /// </summary> internal void Dispose() { source.Dispose(); } } The exception occurs on line 156 when I am playing the sound: source.SubmitSourceBuffer(buffer);

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  • Exiting a reboot loop

    - by user12617035
    If you're in a situation where the system is panic'ing during boot, you can use # boot net -s to regain control of your system. In my case, I'd added some diagnostic code to a (PCI) driver (that is used to boot the root filesystem). There was a bug in the driver, and each time during boot, the bug occurred, and so caused the system to panic: ... 000000000180b950 genunix:vfs_mountroot+60 (800, 200, 0, 185d400, 1883000, 18aec00) %l0-3: 0000000000001770 0000000000000640 0000000001814000 00000000000008fc %l4-7: 0000000001833c00 00000000018b1000 0000000000000600 0000000000000200 000000000180ba10 genunix:main+98 (18141a0, 1013800, 18362c0, 18ab800, 180e000, 1814000) %l0-3: 0000000070002000 0000000000000001 000000000180c000 000000000180e000 %l4-7: 0000000000000001 0000000001074800 0000000000000060 0000000000000000 skipping system dump - no dump device configured rebooting... If you're logged in via the console, you can send a BREAK sequence in order to gain control of the firmware's (OBP's) prompt. Enter Ctrl-Shift-[ in order to get the TELNET prompt. Once telnet has control, enter this: telnet> send brk You'll be presented with OBP's prompt: ok You then enter the following in order to boot into single-user mode via the network: ok boot net -s Note that booting from the network under Solaris will implicitly cause the system to be INSTALLED with whatever software had last been configured to be installed. However, we are using boot net -s as a "handle" with which to get at the Solaris prompt. Once at that prompt, we can perform actions as root that will let us back out our buggy driver (ok... MY buggy driver :-)) ...and replace it with the original, non-buggy driver. Entering the boot command caused the following output, as well as left us at the Solaris prompt (in single-user-mode): Sun Blade 1500, No Keyboard Copyright 1998-2004 Sun Microsystems, Inc. All rights reserved. OpenBoot 4.16.4, 1024 MB memory installed, Serial #53463393. Ethernet address 0:3:ba:2f:c9:61, Host ID: 832fc961. Rebooting with command: boot net -s Boot device: /pci@1f,700000/network@2 File and args: -s 1000 Mbps FDX Link up Timeout waiting for ARP/RARP packet Timeout waiting for ARP/RARP packet 4000 1000 Mbps FDX Link up Requesting Internet address for 0:3:ba:2f:c9:61 SunOS Release 5.10 Version Generic_118833-17 64-bit Copyright 1983-2005 Sun Microsystems, Inc. All rights reserved. Use is subject to license terms. Booting to milestone "milestone/single-user:default". Configuring devices. Using RPC Bootparams for network configuration information. Attempting to configure interface bge0... Configured interface bge0 Requesting System Maintenance Mode SINGLE USER MODE # Our goal is to now move to the directory containing the buggy driver and replace it with the original driver (that we had saved away before ever loading our buggy driver! :-) However, since we booted from the network, the root filesystem ("/") is NOT mounted on one of our local disks. It is mounted on an NFS filesystem exported by our install server. To verify this, enter the following command: # mount | head -1 / on my-server:/export/install/media/s10u2/solarisdvd.s10s_u2dvd/latest/Solaris_10/Tools/Boot remote/read/write/setuid/devices/dev=4ac0001 on Wed Dec 31 16:00:00 1969 As a result, we have to create a temporary mount point and then mount the local disk onto that mount point: # mkdir /tmp/mnt # mount /dev/dsk/c0t0d0s0 /tmp/mnt Note that your system will not necessarily have had its root filesystem on "c0t0d0s0". This is something that you should also have recorded before you ever loaded your.. er... "my" buggy driver! :-) One can find the local disk mounted under the root filesystem by entering: # df -k / Filesystem kbytes used avail capacity Mounted on /dev/dsk/c0t0d0s0 76703839 4035535 71901266 6% / To continue with our example, we can now move to the directory of buggy-driver in order to replace it with the original driver. Note that /tmp/mnt is prefixed to the path of where we'd "normally" find the driver: # cd /tmp/mnt/platform/sun4u/kernel/drv/sparcv9 # ls -l pci\* -rw-r--r-- 1 root root 288504 Dec 6 15:38 pcisch -rw-r--r-- 1 root root 288504 Dec 6 15:38 pcisch.aar -rwxr-xr-x 1 root sys 211616 Jun 8 2006 pcisch.orig # cp -p pcisch.orig pcisch We can now synchronize any in-memory filesystem data structures with those on disk... and then reboot. The system will then boot correctly... as expected: # sync;sync # reboot syncing file systems... done Sun Blade 1500, No Keyboard Copyright 1998-2004 Sun Microsystems, Inc. All rights reserved. OpenBoot 4.16.4, 1024 MB memory installed, Serial #xxxxxxxx. Ethernet address 0:3:ba:2f:c9:61, Host ID: yyyyyyyy. Rebooting with command: boot Boot device: /pci@1e,600000/ide@d/disk@0,0:a File and args: SunOS Release 5.10 Version Generic_118833-17 64-bit Copyright 1983-2005 Sun Microsystems, Inc. All rights reserved. Use is subject to license terms. Hostname: my-host NIS domain name is my-campus.Central.Sun.COM my-host console login: ...so that's how it's done! Of course, the easier way is to never write a buggy-driver... but.. then.. we all "have an eraser on the end of each of our pencils"... don't we ? :-) "...thank you... and good night..."

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  • How do I install LFE on Ubuntu Karmic?

    - by karlthorwald
    Erlang was already installed: $dpkg -l|grep erlang ii erlang 1:13.b.3-dfsg-2ubuntu2 Concurrent, real-time, distributed function ii erlang-appmon 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP application monitor ii erlang-asn1 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP modules for ASN.1 support ii erlang-base 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP virtual machine and base applica ii erlang-common-test 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP application for automated testin ii erlang-debugger 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP application for debugging and te ii erlang-dev 1:13.b.3-dfsg-2ubuntu2 Erlang/OTP development libraries and header [... many more] Erlang seems to work: $ erl Erlang R13B03 (erts-5.7.4) [source] [64-bit] [smp:2:2] [rq:2] [async-threads:0] [hipe] [kernel-poll:false] Eshell V5.7.4 (abort with ^G) 1> I downloaded lfe from github and checked out 0.5.2: git clone http://github.com/rvirding/lfe.git cd lfe git checkout -b local0.5.2 e207eb2cad $ configure configure: command not found $ make mkdir -p ebin erlc -I include -o ebin -W0 -Ddebug +debug_info src/*.erl #erl -I -pa ebin -noshell -eval -noshell -run edoc file src/leex.erl -run init stop #erl -I -pa ebin -noshell -eval -noshell -run edoc_run application "'Leex'" '"."' '[no_packages]' #mv src/*.html doc/ Must be something stupid i missed :o $ sudo make install make: *** No rule to make target `install'. Stop. $ erl -noshell -noinput -s lfe_boot start {"init terminating in do_boot",{undef,[{lfe_boot,start,[]},{init,start_it,1},{init,start_em,1}]}} Crash dump was written to: erl_crash.dump init terminating in do_boot () Is there an example how I would create a hello world source file and compile and run it?

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  • What are good design practices when working with Entity Framework

    - by AD
    This will apply mostly for an asp.net application where the data is not accessed via soa. Meaning that you get access to the objects loaded from the framework, not Transfer Objects, although some recommendation still apply. This is a community post, so please add to it as you see fit. Applies to: Entity Framework 1.0 shipped with Visual Studio 2008 sp1. Why pick EF in the first place? Considering it is a young technology with plenty of problems (see below), it may be a hard sell to get on the EF bandwagon for your project. However, it is the technology Microsoft is pushing (at the expense of Linq2Sql, which is a subset of EF). In addition, you may not be satisfied with NHibernate or other solutions out there. Whatever the reasons, there are people out there (including me) working with EF and life is not bad.make you think. EF and inheritance The first big subject is inheritance. EF does support mapping for inherited classes that are persisted in 2 ways: table per class and table the hierarchy. The modeling is easy and there are no programming issues with that part. (The following applies to table per class model as I don't have experience with table per hierarchy, which is, anyway, limited.) The real problem comes when you are trying to run queries that include one or many objects that are part of an inheritance tree: the generated sql is incredibly awful, takes a long time to get parsed by the EF and takes a long time to execute as well. This is a real show stopper. Enough that EF should probably not be used with inheritance or as little as possible. Here is an example of how bad it was. My EF model had ~30 classes, ~10 of which were part of an inheritance tree. On running a query to get one item from the Base class, something as simple as Base.Get(id), the generated SQL was over 50,000 characters. Then when you are trying to return some Associations, it degenerates even more, going as far as throwing SQL exceptions about not being able to query more than 256 tables at once. Ok, this is bad, EF concept is to allow you to create your object structure without (or with as little as possible) consideration on the actual database implementation of your table. It completely fails at this. So, recommendations? Avoid inheritance if you can, the performance will be so much better. Use it sparingly where you have to. In my opinion, this makes EF a glorified sql-generation tool for querying, but there are still advantages to using it. And ways to implement mechanism that are similar to inheritance. Bypassing inheritance with Interfaces First thing to know with trying to get some kind of inheritance going with EF is that you cannot assign a non-EF-modeled class a base class. Don't even try it, it will get overwritten by the modeler. So what to do? You can use interfaces to enforce that classes implement some functionality. For example here is a IEntity interface that allow you to define Associations between EF entities where you don't know at design time what the type of the entity would be. public enum EntityTypes{ Unknown = -1, Dog = 0, Cat } public interface IEntity { int EntityID { get; } string Name { get; } Type EntityType { get; } } public partial class Dog : IEntity { // implement EntityID and Name which could actually be fields // from your EF model Type EntityType{ get{ return EntityTypes.Dog; } } } Using this IEntity, you can then work with undefined associations in other classes // lets take a class that you defined in your model. // that class has a mapping to the columns: PetID, PetType public partial class Person { public IEntity GetPet() { return IEntityController.Get(PetID,PetType); } } which makes use of some extension functions: public class IEntityController { static public IEntity Get(int id, EntityTypes type) { switch (type) { case EntityTypes.Dog: return Dog.Get(id); case EntityTypes.Cat: return Cat.Get(id); default: throw new Exception("Invalid EntityType"); } } } Not as neat as having plain inheritance, particularly considering you have to store the PetType in an extra database field, but considering the performance gains, I would not look back. It also cannot model one-to-many, many-to-many relationship, but with creative uses of 'Union' it could be made to work. Finally, it creates the side effet of loading data in a property/function of the object, which you need to be careful about. Using a clear naming convention like GetXYZ() helps in that regards. Compiled Queries Entity Framework performance is not as good as direct database access with ADO (obviously) or Linq2SQL. There are ways to improve it however, one of which is compiling your queries. The performance of a compiled query is similar to Linq2Sql. What is a compiled query? It is simply a query for which you tell the framework to keep the parsed tree in memory so it doesn't need to be regenerated the next time you run it. So the next run, you will save the time it takes to parse the tree. Do not discount that as it is a very costly operation that gets even worse with more complex queries. There are 2 ways to compile a query: creating an ObjectQuery with EntitySQL and using CompiledQuery.Compile() function. (Note that by using an EntityDataSource in your page, you will in fact be using ObjectQuery with EntitySQL, so that gets compiled and cached). An aside here in case you don't know what EntitySQL is. It is a string-based way of writing queries against the EF. Here is an example: "select value dog from Entities.DogSet as dog where dog.ID = @ID". The syntax is pretty similar to SQL syntax. You can also do pretty complex object manipulation, which is well explained [here][1]. Ok, so here is how to do it using ObjectQuery< string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); The first time you run this query, the framework will generate the expression tree and keep it in memory. So the next time it gets executed, you will save on that costly step. In that example EnablePlanCaching = true, which is unnecessary since that is the default option. The other way to compile a query for later use is the CompiledQuery.Compile method. This uses a delegate: static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => ctx.DogSet.FirstOrDefault(it => it.ID == id)); or using linq static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet where dog.ID == id select dog).FirstOrDefault()); to call the query: query_GetDog.Invoke( YourContext, id ); The advantage of CompiledQuery is that the syntax of your query is checked at compile time, where as EntitySQL is not. However, there are other consideration... Includes Lets say you want to have the data for the dog owner to be returned by the query to avoid making 2 calls to the database. Easy to do, right? EntitySQL string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)).Include("Owner"); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); CompiledQuery static readonly Func<Entities, int, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, Dog>((ctx, id) => (from dog in ctx.DogSet.Include("Owner") where dog.ID == id select dog).FirstOrDefault()); Now, what if you want to have the Include parametrized? What I mean is that you want to have a single Get() function that is called from different pages that care about different relationships for the dog. One cares about the Owner, another about his FavoriteFood, another about his FavotireToy and so on. Basicly, you want to tell the query which associations to load. It is easy to do with EntitySQL public Dog Get(int id, string include) { string query = "select value dog " + "from Entities.DogSet as dog " + "where dog.ID = @ID"; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>(query, EntityContext.Instance)) .IncludeMany(include); oQuery.Parameters.Add(new ObjectParameter("ID", id)); oQuery.EnablePlanCaching = true; return oQuery.FirstOrDefault(); } The include simply uses the passed string. Easy enough. Note that it is possible to improve on the Include(string) function (that accepts only a single path) with an IncludeMany(string) that will let you pass a string of comma-separated associations to load. Look further in the extension section for this function. If we try to do it with CompiledQuery however, we run into numerous problems: The obvious static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.Include(include) where dog.ID == id select dog).FirstOrDefault()); will choke when called with: query_GetDog.Invoke( YourContext, id, "Owner,FavoriteFood" ); Because, as mentionned above, Include() only wants to see a single path in the string and here we are giving it 2: "Owner" and "FavoriteFood" (which is not to be confused with "Owner.FavoriteFood"!). Then, let's use IncludeMany(), which is an extension function static readonly Func<Entities, int, string, Dog> query_GetDog = CompiledQuery.Compile<Entities, int, string, Dog>((ctx, id, include) => (from dog in ctx.DogSet.IncludeMany(include) where dog.ID == id select dog).FirstOrDefault()); Wrong again, this time it is because the EF cannot parse IncludeMany because it is not part of the functions that is recognizes: it is an extension. Ok, so you want to pass an arbitrary number of paths to your function and Includes() only takes a single one. What to do? You could decide that you will never ever need more than, say 20 Includes, and pass each separated strings in a struct to CompiledQuery. But now the query looks like this: from dog in ctx.DogSet.Include(include1).Include(include2).Include(include3) .Include(include4).Include(include5).Include(include6) .[...].Include(include19).Include(include20) where dog.ID == id select dog which is awful as well. Ok, then, but wait a minute. Can't we return an ObjectQuery< with CompiledQuery? Then set the includes on that? Well, that what I would have thought so as well: static readonly Func<Entities, int, ObjectQuery<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, ObjectQuery<Dog>>((ctx, id) => (ObjectQuery<Dog>)(from dog in ctx.DogSet where dog.ID == id select dog)); public Dog GetDog( int id, string include ) { ObjectQuery<Dog> oQuery = query_GetDog(id); oQuery = oQuery.IncludeMany(include); return oQuery.FirstOrDefault; } That should have worked, except that when you call IncludeMany (or Include, Where, OrderBy...) you invalidate the cached compiled query because it is an entirely new one now! So, the expression tree needs to be reparsed and you get that performance hit again. So what is the solution? You simply cannot use CompiledQueries with parametrized Includes. Use EntitySQL instead. This doesn't mean that there aren't uses for CompiledQueries. It is great for localized queries that will always be called in the same context. Ideally CompiledQuery should always be used because the syntax is checked at compile time, but due to limitation, that's not possible. An example of use would be: you may want to have a page that queries which two dogs have the same favorite food, which is a bit narrow for a BusinessLayer function, so you put it in your page and know exactly what type of includes are required. Passing more than 3 parameters to a CompiledQuery Func is limited to 5 parameters, of which the last one is the return type and the first one is your Entities object from the model. So that leaves you with 3 parameters. A pitance, but it can be improved on very easily. public struct MyParams { public string param1; public int param2; public DateTime param3; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where dog.Age == myParams.param2 && dog.Name == myParams.param1 and dog.BirthDate > myParams.param3 select dog); public List<Dog> GetSomeDogs( int age, string Name, DateTime birthDate ) { MyParams myParams = new MyParams(); myParams.param1 = name; myParams.param2 = age; myParams.param3 = birthDate; return query_GetDog(YourContext,myParams).ToList(); } Return Types (this does not apply to EntitySQL queries as they aren't compiled at the same time during execution as the CompiledQuery method) Working with Linq, you usually don't force the execution of the query until the very last moment, in case some other functions downstream wants to change the query in some way: static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public IEnumerable<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name); } public void DataBindStuff() { IEnumerable<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } What is going to happen here? By still playing with the original ObjectQuery (that is the actual return type of the Linq statement, which implements IEnumerable), it will invalidate the compiled query and be force to re-parse. So, the rule of thumb is to return a List< of objects instead. static readonly Func<Entities, int, string, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, int, string, IEnumerable<Dog>>((ctx, age, name) => from dog in ctx.DogSet where dog.Age == age && dog.Name == name select dog); public List<Dog> GetSomeDogs( int age, string name ) { return query_GetDog(YourContext,age,name).ToList(); //<== change here } public void DataBindStuff() { List<Dog> dogs = GetSomeDogs(4,"Bud"); // but I want the dogs ordered by BirthDate gridView.DataSource = dogs.OrderBy( it => it.BirthDate ); } When you call ToList(), the query gets executed as per the compiled query and then, later, the OrderBy is executed against the objects in memory. It may be a little bit slower, but I'm not even sure. One sure thing is that you have no worries about mis-handling the ObjectQuery and invalidating the compiled query plan. Once again, that is not a blanket statement. ToList() is a defensive programming trick, but if you have a valid reason not to use ToList(), go ahead. There are many cases in which you would want to refine the query before executing it. Performance What is the performance impact of compiling a query? It can actually be fairly large. A rule of thumb is that compiling and caching the query for reuse takes at least double the time of simply executing it without caching. For complex queries (read inherirante), I have seen upwards to 10 seconds. So, the first time a pre-compiled query gets called, you get a performance hit. After that first hit, performance is noticeably better than the same non-pre-compiled query. Practically the same as Linq2Sql When you load a page with pre-compiled queries the first time you will get a hit. It will load in maybe 5-15 seconds (obviously more than one pre-compiled queries will end up being called), while subsequent loads will take less than 300ms. Dramatic difference, and it is up to you to decide if it is ok for your first user to take a hit or you want a script to call your pages to force a compilation of the queries. Can this query be cached? { Dog dog = from dog in YourContext.DogSet where dog.ID == id select dog; } No, ad-hoc Linq queries are not cached and you will incur the cost of generating the tree every single time you call it. Parametrized Queries Most search capabilities involve heavily parametrized queries. There are even libraries available that will let you build a parametrized query out of lamba expressions. The problem is that you cannot use pre-compiled queries with those. One way around that is to map out all the possible criteria in the query and flag which one you want to use: public struct MyParams { public string name; public bool checkName; public int age; public bool checkAge; } static readonly Func<Entities, MyParams, IEnumerable<Dog>> query_GetDog = CompiledQuery.Compile<Entities, MyParams, IEnumerable<Dog>>((ctx, myParams) => from dog in ctx.DogSet where (myParams.checkAge == true && dog.Age == myParams.age) && (myParams.checkName == true && dog.Name == myParams.name ) select dog); protected List<Dog> GetSomeDogs() { MyParams myParams = new MyParams(); myParams.name = "Bud"; myParams.checkName = true; myParams.age = 0; myParams.checkAge = false; return query_GetDog(YourContext,myParams).ToList(); } The advantage here is that you get all the benifits of a pre-compiled quert. The disadvantages are that you most likely will end up with a where clause that is pretty difficult to maintain, that you will incur a bigger penalty for pre-compiling the query and that each query you run is not as efficient as it could be (particularly with joins thrown in). Another way is to build an EntitySQL query piece by piece, like we all did with SQL. protected List<Dod> GetSomeDogs( string name, int age) { string query = "select value dog from Entities.DogSet where 1 = 1 "; if( !String.IsNullOrEmpty(name) ) query = query + " and dog.Name == @Name "; if( age > 0 ) query = query + " and dog.Age == @Age "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); if( !String.IsNullOrEmpty(name) ) oQuery.Parameters.Add( new ObjectParameter( "Name", name ) ); if( age > 0 ) oQuery.Parameters.Add( new ObjectParameter( "Age", age ) ); return oQuery.ToList(); } Here the problems are: - there is no syntax checking during compilation - each different combination of parameters generate a different query which will need to be pre-compiled when it is first run. In this case, there are only 4 different possible queries (no params, age-only, name-only and both params), but you can see that there can be way more with a normal world search. - Noone likes to concatenate strings! Another option is to query a large subset of the data and then narrow it down in memory. This is particularly useful if you are working with a definite subset of the data, like all the dogs in a city. You know there are a lot but you also know there aren't that many... so your CityDog search page can load all the dogs for the city in memory, which is a single pre-compiled query and then refine the results protected List<Dod> GetSomeDogs( string name, int age, string city) { string query = "select value dog from Entities.DogSet where dog.Owner.Address.City == @City "; ObjectQuery<Dog> oQuery = new ObjectQuery<Dog>( query, YourContext ); oQuery.Parameters.Add( new ObjectParameter( "City", city ) ); List<Dog> dogs = oQuery.ToList(); if( !String.IsNullOrEmpty(name) ) dogs = dogs.Where( it => it.Name == name ); if( age > 0 ) dogs = dogs.Where( it => it.Age == age ); return dogs; } It is particularly useful when you start displaying all the data then allow for filtering. Problems: - Could lead to serious data transfer if you are not careful about your subset. - You can only filter on the data that you returned. It means that if you don't return the Dog.Owner association, you will not be able to filter on the Dog.Owner.Name So what is the best solution? There isn't any. You need to pick the solution that works best for you and your problem: - Use lambda-based query building when you don't care about pre-compiling your queries. - Use fully-defined pre-compiled Linq query when your object structure is not too complex. - Use EntitySQL/string concatenation when the structure could be complex and when the possible number of different resulting queries are small (which means fewer pre-compilation hits). - Use in-memory filtering when you are working with a smallish subset of the data or when you had to fetch all of the data on the data at first anyway (if the performance is fine with all the data, then filtering in memory will not cause any time to be spent in the db). Singleton access The best way to deal with your context and entities accross all your pages is to use the singleton pattern: public sealed class YourContext { private const string instanceKey = "On3GoModelKey"; YourContext(){} public static YourEntities Instance { get { HttpContext context = HttpContext.Current; if( context == null ) return Nested.instance; if (context.Items[instanceKey] == null) { On3GoEntities entity = new On3GoEntities(); context.Items[instanceKey] = entity; } return (YourEntities)context.Items[instanceKey]; } } class Nested { // Explicit static constructor to tell C# compiler // not to mark type as beforefieldinit static Nested() { } internal static readonly YourEntities instance = new YourEntities(); } } NoTracking, is it worth it? When executing a query, you can tell the framework to track the objects it will return or not. What does it mean? With tracking enabled (the default option), the framework will track what is going on with the object (has it been modified? Created? Deleted?) and will also link objects together, when further queries are made from the database, which is what is of interest here. For example, lets assume that Dog with ID == 2 has an owner which ID == 10. Dog dog = (from dog in YourContext.DogSet where dog.ID == 2 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Person owner = (from o in YourContext.PersonSet where o.ID == 10 select dog).FirstOrDefault(); //dog.OwnerReference.IsLoaded == true; If we were to do the same with no tracking, the result would be different. ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog = oDogQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>) (from o in YourContext.PersonSet where o.ID == 10 select o); oPersonQuery.MergeOption = MergeOption.NoTracking; Owner owner = oPersonQuery.FirstOrDefault(); //dog.OwnerReference.IsLoaded == false; Tracking is very useful and in a perfect world without performance issue, it would always be on. But in this world, there is a price for it, in terms of performance. So, should you use NoTracking to speed things up? It depends on what you are planning to use the data for. Is there any chance that the data your query with NoTracking can be used to make update/insert/delete in the database? If so, don't use NoTracking because associations are not tracked and will causes exceptions to be thrown. In a page where there are absolutly no updates to the database, you can use NoTracking. Mixing tracking and NoTracking is possible, but it requires you to be extra careful with updates/inserts/deletes. The problem is that if you mix then you risk having the framework trying to Attach() a NoTracking object to the context where another copy of the same object exist with tracking on. Basicly, what I am saying is that Dog dog1 = (from dog in YourContext.DogSet where dog.ID == 2).FirstOrDefault(); ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>) (from dog in YourContext.DogSet where dog.ID == 2 select dog); oDogQuery.MergeOption = MergeOption.NoTracking; Dog dog2 = oDogQuery.FirstOrDefault(); dog1 and dog2 are 2 different objects, one tracked and one not. Using the detached object in an update/insert will force an Attach() that will say "Wait a minute, I do already have an object here with the same database key. Fail". And when you Attach() one object, all of its hierarchy gets attached as well, causing problems everywhere. Be extra careful. How much faster is it with NoTracking It depends on the queries. Some are much more succeptible to tracking than other. I don't have a fast an easy rule for it, but it helps. So I should use NoTracking everywhere then? Not exactly. There are some advantages to tracking object. The first one is that the object is cached, so subsequent call for that object will not hit the database. That cache is only valid for the lifetime of the YourEntities object, which, if you use the singleton code above, is the same as the page lifetime. One page request == one YourEntity object. So for multiple calls for the same object, it will load only once per page request. (Other caching mechanism could extend that). What happens when you are using NoTracking and try to load the same object multiple times? The database will be queried each time, so there is an impact there. How often do/should you call for the same object during a single page request? As little as possible of course, but it does happens. Also remember the piece above about having the associations connected automatically for your? You don't have that with NoTracking, so if you load your data in multiple batches, you will not have a link to between them: ObjectQuery<Dog> oDogQuery = (ObjectQuery<Dog>)(from dog in YourContext.DogSet select dog); oDogQuery.MergeOption = MergeOption.NoTracking; List<Dog> dogs = oDogQuery.ToList(); ObjectQuery<Person> oPersonQuery = (ObjectQuery<Person>)(from o in YourContext.PersonSet select o); oPersonQuery.MergeOption = MergeOption.NoTracking; List<Person> owners = oPersonQuery.ToList(); In this case, no dog will have its .Owner property set. Some things to keep in mind when you are trying to optimize the performance. No lazy loading, what am I to do? This can be seen as a blessing in disguise. Of course it is annoying to load everything manually. However, it decreases the number of calls to the db and forces you to think about when you should load data. The more you can load in one database call the better. That was always true, but it is enforced now with this 'feature' of EF. Of course, you can call if( !ObjectReference.IsLoaded ) ObjectReference.Load(); if you want to, but a better practice is to force the framework to load the objects you know you will need in one shot. This is where the discussion about parametrized Includes begins to make sense. Lets say you have you Dog object public class Dog { public Dog Get(int id) { return YourContext.DogSet.FirstOrDefault(it => it.ID == id ); } } This is the type of function you work with all the time. It gets called from all over the place and once you have that Dog object, you will do very different things to it in different functions. First, it should be pre-compiled, because you will call that very often. Second, each different pages will want to have access to a different subset of the Dog data. Some will want the Owner, some the FavoriteToy, etc. Of course, you could call Load() for each reference you need anytime you need one. But that will generate a call to the database each time. Bad idea. So instead, each page will ask for the data it wants to see when it first request for the Dog object: static public Dog Get(int id) { return GetDog(entity,"");} static public Dog Get(int id, string includePath) { string query = "select value o " + " from YourEntities.DogSet as o " +

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  • How to change TestNG dataProvider order

    - by momad
    Hi, I am running hundreds of tests against a large publishing system and would like to paralellize the tests using TestNG. However, I cannot find any easy way of doing this. Each test case instanciates an instance of this publisher, send some messages, wait for those messages to be published, then dump out the contents of the publish queues and compare against expected outcome. Doing this with so many tests (even if I paralellize using threads, still takes a very long time to complete (1 day or more)). We've found that in testing this sort of system, it's best to start up system once, run all tests to send their messages, wait for publish to do its thing, dump all outputs, and match outputs with tests and verify. For example, instead of the following: @Test public void testRule1() { Publisher pub = new Publisher(); pub.sendRule(new Rule("test1-a")); sleep(10); // wait 10 seconds pub.dumpRules(); verifyRule("test1-a"); } We wanted to do something like the following: @Test public void testRule1(bool sendMode) { if(sendMode) { this.pub.sendRule(new Rule("test1-a")); } else { verifyRule("test1-a"); } } Where you have a dataProvider run through all the tests with sendMode = true and then perform dumpAllRules() followed by running through all of the tests again with sendMode = false. The problem is, TestNG calls the same method twice, once with sendMode = true followed by sendMode = false. Is there anyway to accomplish this in TestNG? Thanks!

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  • How to keep character encoding with database queries.

    - by JasonS
    Hi, I am doing the following. 1) I am exporting a database and saving it to a file called dump.sql. 2) The file is then transferred to a different server via PHP ftp. 3) When the file has been successfully transferred the administrator has an option to run a 'dbtransfer' script on the new host. 4) This script blows up the script and runs the queries line by line. This works great - however there is a problem with foreign language encoding. We are using UTF-8. Step 1 : This works fine, file is in UTF-8 Format. Step 3 : When I test the contents of the dump.sql file using mb_check_encoding(). The string comes back as UTF-8. Step 4 : This creates tables with utf8_general_ci encoding. The information is dumped in. When I check the table after the transfer I get records like this: 'ç,Ç,ö,Ö,ü,Ü,ı,İ,ş,Ş,ğ,Ğ'. I don't understand how a UTF-8 string can lose its encoding when it goes into the database. Am I missing a step? Do I need to run some sort of function to ensure the string is parsed as UTF-8? Once the system is installed I can save foreign language queries. It is just the transfer that is messing up. Any ideas?

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  • Firefox extension is freezing Firefox until request is completed

    - by Michael
    For some reason the function is freezing along with firefox until it fully retrieve the stream from requested site. Is there any mechanism to prevent freezing, so it works as expected? in XUL <statusbarpanel id="eee_label" tooltip="eee_tooltip" onclick="eee.retrieve_rate(event);"/> Javascript retrieve_rate: function(e) { var ajax = null; ajax = new XMLHttpRequest(); ajax.open('GET', 'http://site.com', false); ajax.onload = function() { if (ajax.status == 200) { var regexp = /blabla/g; var match = regexp.exec(ajax.responseText); while (match != null) { window.dump('Currency: ' + match[1] + ', Rate: ' + match[2] + ', Change: ' + match[3] + "\n"); if(match[1] == "USD") rate_USD = sprintf("%s:%s", match[1], match[2]); if(match[1] == "EUR") rate_EUR = sprintf("%s:%s", match[1], match[2]); if(match[1] == "RUB") rate_RUB = sprintf("%s/%s", match[1], match[2]); match = regexp.exec(ajax.responseText); } var rate = document.getElementById('eee_label'); rate.label = rate_USD + " " + rate_EUR + " " + rate_RUB; } else { } }; ajax.send(); I tried to put window.dump() right after ajax.send() and it dumped in the console also after the request is completed.

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  • x86 CMP Instruction Difference

    - by Pindatjuh
    Question What is the (non-trivial) difference between the following two x86 instructions? 39 /r CMP r/m32,r32 Compare r32 with r/m32 3B /r CMP r32,r/m32 Compare r/m32 with r32 Background I'm building a Java assembler, which will be used by my compiler's intermediate language to produce Windows-32 executables. Currently I have following code: final ModelBase mb = new ModelBase(); // create new memory model mb.addCode(new Compare(Register.ECX, Register.EAX)); // add code mb.addCode(new Compare(Register.EAX, Register.ECX)); // add code final FileOutputStream fos = new FileOutputStream(new File("test.exe")); mb.writeToFile(fos); fos.close(); To output a valid executable file, which contains two CMP instruction in a TEXT-section. The executable outputted to "text.exe" will do nothing interesting, but that's not the point. The class Compare is a wrapper around the CMP instruction. The above code produces (inspecting with OllyDbg): Address Hex dump Command 0040101F |. 3BC8 CMP ECX,EAX 00401021 |. 3BC1 CMP EAX,ECX The difference is subtle: if I use the 39 byte-opcode: Address Hex dump Command 0040101F |. 39C1 CMP ECX,EAX 00401021 |. 39C8 CMP EAX,ECX Which makes me wonder about their synonymity and why this even exists.

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  • What is the suggested approach to Syncing/Backing up/Restoring from SQL Server 2008 to SQL Server 20

    - by Eoin Campbell
    I only have SQL Server 2008 (Dev Edition) on my development machine I only have SQL Server 2005 available with my hosting company (and I don't have direct connection access to this database) I'm just wondering what the best approach is for: Getting the initlal DB Structure & Data into production. And keeping any structural changes/data changes in sync in future. As far as I can see... Replication - not an option cos I can't connect to the production DB. Restoring a backup - not an option because as far as I can see, you cannot export a DB from 2008 that is restorable in 2005 (even with the 2008 DB set in 2005 compatibility mode) and it wouldn't make sense to be restoring production over the top of my dev version anyway. Dump all the scripts from my 2008 Database, Revert my Dev to machine from 2008 - 2005, and recreate the database from the scripts, then just use backup & restore to get the initial DB into production, then run scripts through the web panel from that point onwards Dump all the scripts from my 2008 Database and generate the entire 2005 db from scripts in production. then run scripts through the web panel from that point onwards With the last 2 options, I'd probably need to script all the data inserts as well using some tool (which I presume exists on the web) Are there any other possibile solutions that I'm not considering.

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  • Munging non-printable characters to dots using string.translate()

    - by Jim Dennis
    So I've done this before and it's a surprising ugly bit of code for such a seemingly simple task. The goal is to translate any non-printable character into a . (dot). For my purposes "printable" does exclude the last few characters from string.printable (new-lines, tabs, and so on). This is for printing things like the old MS-DOS debug "hex dump" format ... or anything similar to that (where additional whitespace will mangle the intended dump layout). I know I can use string.translate() and, to use that, I need a translation table. So I use string.maketrans() for that. Here's the best I could come up with: filter = string.maketrans( string.translate(string.maketrans('',''), string.maketrans('',''),string.printable[:-5]), '.'*len(string.translate(string.maketrans('',''), string.maketrans('',''),string.printable[:-5]))) ... which is an unreadable mess (though it does work). From there you can call use something like: for each_line in sometext: print string.translate(each_line, filter) ... and be happy. (So long as you don't look under the hood). Now it is more readable if I break that horrid expression into separate statements: ascii = string.maketrans('','') # The whole ASCII character set nonprintable = string.translate(ascii, ascii, string.printable[:-5]) # Optional delchars argument filter = string.maketrans(nonprintable, '.' * len(nonprintable)) And it's tempting to do that just for legibility. However, I keep thinking there has to be a more elegant way to express this!

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  • help with Firefox extension

    - by Johnny Grass
    I'm writing a Firefox extension that creates a socket server which will output the active tab's URL when a client makes a connection to it. I have the following code in my javascript file: var serverSocket; function startServer() { var listener = { onSocketAccepted : function(socket, transport) { try { var outputString = gBrowser.currentURI.spec + "\n"; var stream = transport.openOutputStream(0,0,0); stream.write(outputString,outputString.length); stream.close(); } catch(ex2){ dump("::"+ex2); } }, onStopListening : function(socket, status){} }; try { serverSocket = Components.classes["@mozilla.org/network/server-socket;1"] .createInstance(Components.interfaces.nsIServerSocket); serverSocket.init(7055,true,-1); serverSocket.asyncListen(listener); } catch(ex){ dump(ex); } document.getElementById("status").value = "Started"; } startServer(); As it is, it works for multiple tabs in a single window. If I open multiple windows, it ignores the additional windows. I think it is creating a server socket for each window, but since they are using the same port, the additional sockets fail to initialize. I need it to create a server socket when the browser launches and continue running when I close the windows (Mac OS X). As it is, when I close a window but Firefox remains running, the socket closes and I have to restart firefox to get it up an running. How do I go about that?

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  • Raycasting with tags problems in unity3d

    - by user1855858
    i need some help here. i have a part of code to search unblocked neighbour with raycast. i need to get raycast that just collide with "WP" tag. both of the iteration shown a right results, so do the dump and the raycast, the raycast does success to collide something, but when i check what the raycast collided with, there is no result shown.... anyone knows whats wrong with this code..?? int flag = 0, flahNeigh = 0; for(flag = 0; flag< wayPoints.WPList.Length; flag++) // iteration to seek neighbour nodes { for (flagNeigh = 0; flagNeigh < wayPoints.WPList.Length; flagNeigh++) { if (wayPoints.WPList[flag].loc != wayPoints.WPList[flagNeigh].loc) // dump its own node location { if (Physics.Raycast(wayPoints.WPList[flag].loc.position, wayPoints.WPList[flagNeigh].loc.position, out hitted)) // raycasting to each node else its self { if (hitted.collider.gameObject.CompareTag("WP")) // check if the ray only collide the node { print(flag + " : " + flagNeigh + " : " + wayPoints.WPList[flagNeigh].loc.position); // debugging to see whether the code works or not (the error comes) } } } } } thanks for the appreciation and answers... sorry if i have a bad english...^^

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