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  • Avoiding QoS degradation for video streaming clients

    - by aarege31
    Suppose I have two routers connected via a 1Gbit connection. A client behind router 1 streams to a client behind router 2 while other clients behind router 1 transmit data to other clients behind router 2. Are there any best practice policing, scheduling or queue management algorithms available that help a beginner understand what is necessary to prevent QoS degration in simple cases as above as well as in real world environments?

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  • Synergy 1.5 crash (OSX 10.6.8)

    - by Oliver
    THANKS FOR TAKING THE TIME TO READ THIS I recently installed Synergy 1.5 r2278 (for Mac OSX 10.6.8) and was using it fine for most of the day, then it decided to stop working (the only thing I changed systemwise was the screensaver - and then after it started crashing disabled it - to see if it would resolve). When I start Synergy (on the Mac - Client) it says: after about 5 seconds (and successfully connecting to the Server) "synergyc quit unexpectedly" Here is the crash log (w/ binery info removed - too long for post requirements) Process: synergyc [1026] Path: /Applications/Synergy.app/Contents/MacOS/synergyc Identifier: synergy Version: ??? (???) Code Type: X86 (Native) Parent Process: Synergy [1023] Date/Time: 2014-05-28 15:36:17.746 +0930 OS Version: Mac OS X 10.6.8 (10K549) Report Version: 6 Interval Since Last Report: 2144189 sec Crashes Since Last Report: 23 Per-App Interval Since Last Report: 10242 sec Per-App Crashes Since Last Report: 9 Anonymous UUID: 86D5A57C-13D4-470E-AC72-48ACDDDE5EB0 Exception Type: EXC_CRASH (SIGABRT) Exception Codes: 0x0000000000000000, 0x0000000000000000 Crashed Thread: 5 Application Specific Information: abort() called Thread 0: Dispatch queue: com.apple.main-thread 0 libSystem.B.dylib 0x95cf3afa mach_msg_trap + 10 1 libSystem.B.dylib 0x95cf4267 mach_msg + 68 2 com.apple.CoreFoundation 0x95af02df __CFRunLoopRun + 2079 3 com.apple.CoreFoundation 0x95aef3c4 CFRunLoopRunSpecific + 452 4 com.apple.CoreFoundation 0x95aef1f1 CFRunLoopRunInMode + 97 5 com.apple.HIToolbox 0x93654e04 RunCurrentEventLoopInMode + 392 6 com.apple.HIToolbox 0x93654bb9 ReceiveNextEventCommon + 354 7 com.apple.HIToolbox 0x937dd137 ReceiveNextEvent + 83 8 synergyc 0x000356d0 COSXEventQueueBuffer::waitForEvent(double) + 48 9 synergyc 0x00010dd5 CEventQueue::getEvent(CEvent&, double) + 325 10 synergyc 0x00011fb0 CEventQueue::loop() + 272 11 synergyc 0x00044eb6 CClientApp::mainLoop() + 134 12 synergyc 0x0005c509 standardStartupStatic(int, char**) + 41 13 synergyc 0x000448a9 CClientApp::runInner(int, char**, ILogOutputter*, int (*)(int, char**)) + 137 14 synergyc 0x0005c4b0 CAppUtilUnix::run(int, char**) + 64 15 synergyc 0x000427df CApp::run(int, char**) + 63 16 synergyc 0x00006e65 main + 117 17 synergyc 0x00006dd9 start + 53 Thread 1: 0 libSystem.B.dylib 0x95d607da __sigwait + 10 1 libSystem.B.dylib 0x95d607b6 sigwait$UNIX2003 + 71 2 synergyc 0x00009583 CArchMultithreadPosix::threadSignalHandler(void*) + 67 3 libSystem.B.dylib 0x95d21259 _pthread_start + 345 4 libSystem.B.dylib 0x95d210de thread_start + 34 Thread 2: 0 libSystem.B.dylib 0x95d21aa2 __semwait_signal + 10 1 libSystem.B.dylib 0x95d2175e _pthread_cond_wait + 1191 2 libSystem.B.dylib 0x95d212b1 pthread_cond_timedwait$UNIX2003 + 72 3 synergyc 0x00009476 CArchMultithreadPosix::waitCondVar(CArchCondImpl*, CArchMutexImpl*, double) + 150 4 synergyc 0x0002b18f CCondVarBase::wait(double) const + 63 5 synergyc 0x0002ce68 CSocketMultiplexer::serviceThread(void*) + 136 6 synergyc 0x0002d698 TMethodJob<CSocketMultiplexer>::run() + 40 7 synergyc 0x0002b8f4 CThread::threadFunc(void*) + 132 8 synergyc 0x00008f30 CArchMultithreadPosix::doThreadFunc(CArchThreadImpl*) + 80 9 synergyc 0x0000902a CArchMultithreadPosix::threadFunc(void*) + 74 10 libSystem.B.dylib 0x95d21259 _pthread_start + 345 11 libSystem.B.dylib 0x95d210de thread_start + 34 Thread 3: Dispatch queue: com.apple.libdispatch-manager 0 libSystem.B.dylib 0x95d1a382 kevent + 10 1 libSystem.B.dylib 0x95d1aa9c _dispatch_mgr_invoke + 215 2 libSystem.B.dylib 0x95d19f59 _dispatch_queue_invoke + 163 3 libSystem.B.dylib 0x95d19cfe _dispatch_worker_thread2 + 240 4 libSystem.B.dylib 0x95d19781 _pthread_wqthread + 390 5 libSystem.B.dylib 0x95d195c6 start_wqthread + 30 Thread 4: 0 libSystem.B.dylib 0x95d19412 __workq_kernreturn + 10 1 libSystem.B.dylib 0x95d199a8 _pthread_wqthread + 941 2 libSystem.B.dylib 0x95d195c6 start_wqthread + 30 Thread 5 Crashed: 0 libSystem.B.dylib 0x95d610ee __semwait_signal_nocancel + 10 1 libSystem.B.dylib 0x95d60fd2 nanosleep$NOCANCEL$UNIX2003 + 166 2 libSystem.B.dylib 0x95ddbfb2 usleep$NOCANCEL$UNIX2003 + 61 3 libSystem.B.dylib 0x95dfd6f0 abort + 105 4 libSystem.B.dylib 0x95d79b1b _Unwind_Resume + 59 5 synergyc 0x00008fd1 CArchMultithreadPosix::doThreadFunc(CArchThreadImpl*) + 241 6 synergyc 0x0000902a CArchMultithreadPosix::threadFunc(void*) + 74 7 libSystem.B.dylib 0x95d21259 _pthread_start + 345 8 libSystem.B.dylib 0x95d210de thread_start + 34 Thread 5 crashed with X86 Thread State (32-bit): eax: 0x0000003c ebx: 0x95d60f39 ecx: 0xb0288a7c edx: 0x95d610ee edi: 0x00521950 esi: 0xb0288ad8 ebp: 0xb0288ab8 esp: 0xb0288a7c ss: 0x0000001f efl: 0x00000247 eip: 0x95d610ee cs: 0x00000007 ds: 0x0000001f es: 0x0000001f fs: 0x0000001f gs: 0x00000037 cr2: 0x002fe000 Model: MacBook2,1, BootROM MB21.00A5.B07, 2 processors, Intel Core 2 Duo, 2.16 GHz, 2 GB

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  • How do I password protect my printer in Windows 7?

    - by Dillie-O
    I have two young kids who have gotten rather computer saavy. They love playing their games, especially when it allows them to print out awards or coloring pages. Unfortunately this means that in the time it takes to refresh my cup of coffee, they can easily drop a 10 page document into the printer queue, and my printer ink runs out rather fast. How would I setup some kind of password protection on the printing, so that I would have to do some kind of final approval before they get their printouts?

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  • Server is sending SPAM but it's not an open relay

    - by alexandernst
    I have a problem with Dovecot + Postfix. My server is sending SPAM from the local user "dovecot", but my server is not configured as an open relay (mails can be sent without auth-ing only from localhost). Also, nobody except me, has SSH access to the server. How can I find what exactly is triggering all those SPAM mails? How can I get something like a backtrace that shows what exactly happened the moments before a SPAM email got in the queue of postfix? Regards

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  • Postfix sendmail bypass restrictions [on hold]

    - by EnEli
    I have setup a postfix/dovecot mail server and all thing work fine! BUT: I use virtual mailboxes and when you try to send a mail to a non existent mailbox via telnet postfix will punch you... But if you use sendmail, all restricitons are bypassed... This is bad becuase dovecot does not know what to do with this mail! It will stay in the queue for ever... How can I force sendmail to use normal smtp?

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  • Email a very large list of WordPress subscribers = fail (every single time)

    - by Greg-J
    I have tried using a number of plugins to email my 40,000 registered users on my WordPress-powered site, to no avail. I have tried Subscribe2 (seems to send some, but I have no idea how many) as well as a few Newsletter plugins. I either run out of memory trying to add 40K entries to the mail queue, or I error out trying to add 40K emails in the BCC of the email being sent. Is there anyone out there with a large subscriber-base that has found a successful solution? If so, please share.

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  • SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

    - by pinaldave
    Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Troubleshooting High-CPU Utilization for SQL Server

    - by Susantha Bathige
    The objective of this FAQ is to outline the basic steps in troubleshooting high CPU utilization on  a server hosting a SQL Server instance. The first and the most common step if you suspect high CPU utilization (or are alerted for it) is to login to the physical server and check the Windows Task Manager. The Performance tab will show the high utilization as shown below: Next, we need to determine which process is responsible for the high CPU consumption. The Processes tab of the Task Manager will show this information: Note that to see all processes you should select Show processes from all user. In this case, SQL Server (sqlserver.exe) is consuming 99% of the CPU (a normal benchmark for max CPU utilization is about 50-60%). Next we examine the scheduler data. Scheduler is a component of SQLOS which evenly distributes load amongst CPUs. The query below returns the important columns for CPU troubleshooting. Note – if your server is under severe stress and you are unable to login to SSMS, you can use another machine’s SSMS to login to the server through DAC – Dedicated Administrator Connection (see http://msdn.microsoft.com/en-us/library/ms189595.aspx for details on using DAC) SELECT scheduler_id ,cpu_id ,status ,runnable_tasks_count ,active_workers_count ,load_factor ,yield_count FROM sys.dm_os_schedulers WHERE scheduler_id See below for the BOL definitions for the above columns. scheduler_id – ID of the scheduler. All schedulers that are used to run regular queries have ID numbers less than 1048576. Those schedulers that have IDs greater than or equal to 1048576 are used internally by SQL Server, such as the dedicated administrator connection scheduler. cpu_id – ID of the CPU with which this scheduler is associated. status – Indicates the status of the scheduler. runnable_tasks_count – Number of workers, with tasks assigned to them that are waiting to be scheduled on the runnable queue. active_workers_count – Number of workers that are active. An active worker is never preemptive, must have an associated task, and is either running, runnable, or suspended. current_tasks_count - Number of current tasks that are associated with this scheduler. load_factor – Internal value that indicates the perceived load on this scheduler. yield_count – Internal value that is used to indicate progress on this scheduler.                                                                 Now to interpret the above data. There are four schedulers and each assigned to a different CPU. All the CPUs are ready to accept user queries as they all are ONLINE. There are 294 active tasks in the output as per the current_tasks_count column. This count indicates how many activities currently associated with the schedulers. When a  task is complete, this number is decremented. The 294 is quite a high figure and indicates all four schedulers are extremely busy. When a task is enqueued, the load_factor  value is incremented. This value is used to determine whether a new task should be put on this scheduler or another scheduler. The new task will be allocated to less loaded scheduler by SQLOS. The very high value of this column indicates all the schedulers have a high load. There are 268 runnable tasks which mean all these tasks are assigned a worker and waiting to be scheduled on the runnable queue.   The next step is  to identify which queries are demanding a lot of CPU time. The below query is useful for this purpose (note, in its current form,  it only shows the top 10 records). SELECT TOP 10 st.text  ,st.dbid  ,st.objectid  ,qs.total_worker_time  ,qs.last_worker_time  ,qp.query_plan FROM sys.dm_exec_query_stats qs CROSS APPLY sys.dm_exec_sql_text(qs.sql_handle) st CROSS APPLY sys.dm_exec_query_plan(qs.plan_handle) qp ORDER BY qs.total_worker_time DESC This query as total_worker_time as the measure of CPU load and is in descending order of the  total_worker_time to show the most expensive queries and their plans at the top:      Note the BOL definitions for the important columns: total_worker_time - Total amount of CPU time, in microseconds, that was consumed by executions of this plan since it was compiled. last_worker_time - CPU time, in microseconds, that was consumed the last time the plan was executed.   I re-ran the same query again after few seconds and was returned the below output. After few seconds the SP dbo.TestProc1 is shown in fourth place and once again the last_worker_time is the highest. This means the procedure TestProc1 consumes a CPU time continuously each time it executes.      In this case, the primary cause for high CPU utilization was a stored procedure. You can view the execution plan by clicking on query_plan column to investigate why this is causing a high CPU load. I have used SQL Server 2008 (SP1) to test all the queries used in this article.

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  • Global Cache CR Requested But Current Block Received

    - by Liu Maclean(???)
    ????????«MINSCN?Cache Fusion Read Consistent» ????,???????????? ??????????????????: SQL> select * from V$version; BANNER -------------------------------------------------------------------------------- Oracle Database 11g Enterprise Edition Release 11.2.0.3.0 - 64bit Production PL/SQL Release 11.2.0.3.0 - Production CORE 11.2.0.3.0 Production TNS for Linux: Version 11.2.0.3.0 - Production NLSRTL Version 11.2.0.3.0 - Production SQL> select count(*) from gv$instance; COUNT(*) ---------- 2 SQL> select * from global_name; GLOBAL_NAME -------------------------------------------------------------------------------- www.oracledatabase12g.com ?11gR2 2??RAC??????????status???XG,????Xcurrent block???INSTANCE 2?hold?,?????INSTANCE 1?????????,?????: SQL> select * from test; ID ---------- 1 2 SQL> select dbms_rowid.rowid_block_number(rowid),dbms_rowid.rowid_relative_fno(rowid) from test; DBMS_ROWID.ROWID_BLOCK_NUMBER(ROWID) DBMS_ROWID.ROWID_RELATIVE_FNO(ROWID) ------------------------------------ ------------------------------------ 89233 1 89233 1 SQL> alter system flush buffer_cache; System altered. INSTANCE 1 Session A: SQL> update test set id=id+1 where id=1; 1 row updated. INSTANCE 1 Session B: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1755287 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD1/trace/VPROD1_ora_19111.trc GLOBAL CACHE ELEMENT DUMP (address: 0xa4ff3080): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: X rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kdswh11: kdst_fetch' bscn: 0x0.146e20 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0xa9f6a6f8,0xa9f6a6f8] seq: 32 hist: 58 145:0 118 66 144:0 192 352 197 48 121 113 424 180 58 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x02000001 lflg: 0x1 state: XCURRENT tsn: 0 tsh: 2 addr: 0xa9f6a5c8 obj: 76896 cls: DATA bscn: 0x0.1ac898 BH (0xa9f6a5c8) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0xa9e56000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 3 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x91f4e970,0xbae9d5b8] lru: [0x91f58848,0xa9f6a828] lru-flags: debug_dump obj-flags: object_ckpt_list ckptq: [0x9df6d1d8,0xa9f6a740] fileq: [0xa2ece670,0xbdf4ed68] objq: [0xb4964e00,0xb4964e00] objaq: [0xb4964de0,0xb4964de0] st: XCURRENT md: NULL fpin: 'kdswh11: kdst_fetch' tch: 2 le: 0xa4ff3080 flags: buffer_dirty redo_since_read LRBA: [0x19.5671.0] LSCN: [0x0.1ac898] HSCN: [0x0.1ac898] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001ac898 seq: 0x01 flg: 0x00 tail: 0xc8980601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data ??????block: (1/89233)?GLOBAL CACHE ELEMENT DUMP?LOCK????X ??XG , ??????Current Block????Instance??modify???,????????????? ????Instance 2 ????: Instance 2 Session C: SQL> update test set id=id+1 where id=2; 1 row updated. Instance 2 Session D: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1756658 SQL> oradebug setmypid; Statement processed. SQL> oradebug dump gc_elements 255; Statement processed. SQL> oradebug tracefile_name; /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_ora_13038.trc GLOBAL CACHE ELEMENT DUMP (address: 0x89fb25a0): id1: 0x15c91 id2: 0x1 pkey: OBJ#76896 block: (1/89233) lock: XG rls: 0x0 acq: 0x0 latch: 3 flags: 0x20 fair: 0 recovery: 0 fpin: 'kduwh01: kdusru' bscn: 0x0.1acdf3 bctx: (nil) write: 0 scan: 0x0 lcp: (nil) lnk: [NULL] lch: [0x96f4cf80,0x96f4cf80] seq: 61 hist: 324 21 143:0 19 16 352 329 144:6 14 7 352 197 LIST OF BUFFERS LINKED TO THIS GLOBAL CACHE ELEMENT: flg: 0x0a000001 state: XCURRENT tsn: 0 tsh: 1 addr: 0x96f4ce50 obj: 76896 cls: DATA bscn: 0x0.1acdf6 BH (0x96f4ce50) file#: 1 rdba: 0x00415c91 (1/89233) class: 1 ba: 0x96bd4000 set: 5 pool: 3 bsz: 8192 bsi: 0 sflg: 2 pwc: 0,15 dbwrid: 0 obj: 76896 objn: 76896 tsn: 0 afn: 1 hint: f hash: [0x96ee1fe8,0xbae9d5b8] lru: [0x96f4d0b0,0x96f4cdc0] obj-flags: object_ckpt_list ckptq: [0xbdf519b8,0x96f4d5a8] fileq: [0xbdf519d8,0xbdf519d8] objq: [0xb4a47b90,0xb4a47b90] objaq: [0x96f4d0e8,0xb4a47b70] st: XCURRENT md: NULL fpin: 'kduwh01: kdusru' tch: 1 le: 0x89fb25a0 flags: buffer_dirty redo_since_read remote_transfered LRBA: [0x11.9e18.0] LSCN: [0x0.1acdf6] HSCN: [0x0.1acdf6] HSUB: [1] buffer tsn: 0 rdba: 0x00415c91 (1/89233) scn: 0x0000.001acdf6 seq: 0x01 flg: 0x00 tail: 0xcdf60601 frmt: 0x02 chkval: 0x0000 type: 0x06=trans data GCS CLIENT 0x89fb2618,6 resp[(nil),0x15c91.1] pkey 76896.0 grant 2 cvt 0 mdrole 0x42 st 0x100 lst 0x20 GRANTQ rl G0 master 1 owner 2 sid 0 remote[(nil),0] hist 0x94121c601163423c history 0x3c.0x4.0xd.0xb.0x1.0xc.0x7.0x9.0x14.0x1. cflag 0x0 sender 1 flags 0x0 replay# 0 abast (nil).x0.1 dbmap (nil) disk: 0x0000.00000000 write request: 0x0000.00000000 pi scn: 0x0000.00000000 sq[(nil),(nil)] msgseq 0x1 updseq 0x0 reqids[6,0,0] infop (nil) lockseq x2b8 pkey 76896.0 hv 93 [stat 0x0, 1->1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 ?Instance 2??????block: (1/89233)? GLOBAL CACHE ELEMENT Lock Convert?lock: XG ????GC_ELEMENTS DUMP???XCUR Cache Fusion?,???????X$ VIEW,??? X$LE X$KJBR X$KJBL, ???X$ VIEW???????????????????: INSTANCE 2 Session D: SELECT * FROM x$le WHERE le_addr IN (SELECT le_addr FROM x$bh WHERE obj IN (SELECT data_object_id FROM dba_objects WHERE owner = 'SYS' AND object_name = 'TEST') AND class = 1 AND state != 3); ADDR INDX INST_ID LE_ADDR LE_ID1 LE_ID2 ---------------- ---------- ---------- ---------------- ---------- ---------- LE_RLS LE_ACQ LE_FLAGS LE_MODE LE_WRITE LE_LOCAL LE_RECOVERY ---------- ---------- ---------- ---------- ---------- ---------- ----------- LE_BLKS LE_TIME LE_KJBL ---------- ---------- ---------------- 00007F94CA14CF60 7003 2 0000000089FB25A0 89233 1 0 0 32 2 0 1 0 1 0 0000000089FB2618 PCM Resource NAME?[ID1][ID2],[BL]???, ID1?ID2 ??blockno? fileno????, ??????????GC_elements dump?? id1: 0x15c91 id2: 0×1 pkey: OBJ#76896 block: (1/89233)?? ,?  kjblname ? kjbrname ??”[0x15c91][0x1],[BL]” ??: INSTANCE 2 Session D: SQL> set linesize 80 pagesize 1400 SQL> SELECT * 2 FROM x$kjbl l 3 WHERE l.kjblname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBLLOCKP KJBLGRANT KJBLREQUE ---------------- ---------- ---------- ---------------- --------- --------- KJBLROLE KJBLRESP KJBLNAME ---------- ---------------- ------------------------------ KJBLNAME2 KJBLQUEUE ------------------------------ ---------- KJBLLOCKST KJBLWRITING ---------------------------------------------------------------- ----------- KJBLREQWRITE KJBLOWNER KJBLMASTER KJBLBLOCKED KJBLBLOCKER KJBLSID KJBLRDOMID ------------ ---------- ---------- ----------- ----------- ---------- ---------- KJBLPKEY ---------- 00007F94CA22A288 451 2 0000000089FB2618 KJUSEREX KJUSERNL 0 00 [0x15c91][0x1],[BL][ext 0x0,0x 89233,1,BL 0 GRANTED 0 0 1 0 0 0 0 0 76896 SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; no rows selected Instance 1 session B: SQL> SELECT r.* FROM x$kjbr r WHERE r.kjbrname LIKE '%[0x15c91][0x1],[BL]%'; ADDR INDX INST_ID KJBRRESP KJBRGRANT KJBRNCVL ---------------- ---------- ---------- ---------------- --------- --------- KJBRROLE KJBRNAME KJBRMASTER KJBRGRANTQ ---------- ------------------------------ ---------- ---------------- KJBRCVTQ KJBRWRITER KJBRSID KJBRRDOMID KJBRPKEY ---------------- ---------------- ---------- ---------- ---------- 00007F801ACA68F8 1355 1 00000000B5A62AE0 KJUSEREX KJUSERNL 0 [0x15c91][0x1],[BL][ext 0x0,0x 0 00000000B48BB330 00 00 0 0 76896 ??????Instance 1???block: (1/89233),??????Instance 2 build cr block ????Instance 1, ?????????? ????? Instance 1? Foreground Process ? Instance 2?LMS??????RAC  TRACE: Instance 2: [oracle@vrh2 ~]$ ps -ef|grep ora_lms|grep -v grep oracle 23364 1 0 Apr29 ? 00:33:15 ora_lms0_VPROD2 SQL> oradebug setospid 23364 Oracle pid: 13, Unix process pid: 23364, image: [email protected] (LMS0) SQL> oradebug event 10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high; Statement processed. SQL> oradebug tracefile_name /s01/orabase/diag/rdbms/vprod/VPROD2/trace/VPROD2_lms0_23364.trc Instance 1 session B : SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1756658 3 1756661 3 1755287 Instance 1 session A : SQL> alter session set events '10046 trace name context forever,level 8:10708 trace name context forever,level 103: trace[rac.*] disk high'; Session altered. SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761520 ?x$BH?????,???????Instance 1???build??CR block,????? TRACE ??: Instance 1 foreground Process: PARSING IN CURSOR #140336527348792 len=18 dep=0 uid=0 oct=3 lid=0 tim=1335939136125254 hv=1689401402 ad='b1a4c828' sqlid='c99yw1xkb4f1u' select * from test END OF STMT PARSE #140336527348792:c=2999,e=2860,p=0,cr=0,cu=0,mis=1,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125253 EXEC #140336527348792:c=0,e=40,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939136125373 WAIT #140336527348792: nam='SQL*Net message to client' ela= 6 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939136125420 *** 2012-05-02 02:12:16.125 kclscrs: req=0 block=1/89233 2012-05-02 02:12:16.125574 : kjbcro[0x15c91.1 76896.0][4] *** 2012-05-02 02:12:16.125 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:12:16.125 kclscrs: bid=1:3:1:0:f:1e:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1c:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:14:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:12:16.125718 : kjbcro[0x15c91.1 76896.0][4] 2012-05-02 02:12:16.125751 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:12:16.125780 : kjbsentscn[0x0.1ae0f0][to 2] 2012-05-02 02:12:16.125806 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177740 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:12:16.125918 : kjbmscr(0x15c91.1)reqid=0x8(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:12:16.126959 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:12:16.127 kclwcrs: wait=0 tm=1233 *** 2012-05-02 02:12:16.127 kclwcrs: got 1 blocks from ksxprcv WAIT #140336527348792: nam='gc cr block 2-way' ela= 1233 p1=1 p2=89233 p3=1 obj#=76896 tim=1335939136127199 2012-05-02 02:12:16.127272 : kjbcrcomplete[0x15c91.1 76896.0][0] 2012-05-02 02:12:16.127309 : kjbrcvdscn[0x0.1ae0f0][from 2][idx 2012-05-02 02:12:16.127329 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f0][from 2] ???? kjbcro[0x15c91.1 76896.0][4] kjbsentscn[0x0.1ae0f0][to 2] ?Instance 2??SCN=1ae0f0=1761520? block: (1/89233),???’gc cr block 2-way’ ??,?????????CR block? Instance 2 LMS TRACE 2012-05-02 02:12:15.634057 : GSIPC:RCVD: ksxp msg 0x7f16e1598588 sndr 1 seq 0.177740 type 36 tkts 0 2012-05-02 02:12:15.634094 : GSIPC:RCVD: watq msg 0x7f16e1598588 sndr 1, seq 177740, type 36, tkts 0 2012-05-02 02:12:15.634108 : GSIPC:TKT: collect msg 0x7f16e1598588 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.634162 : kjbrcvdscn[0x0.1ae0f0][from 1][idx 2012-05-02 02:12:15.634186 : kjbrcvdscn[no bscn1, wm 32768, RMno 0, reminc 18, dom 0] kjga st 0x4, step 0.0.0, cinc 20, rmno 6, flags 0x0 lb 0, hb 0, myb 15250, drmb 15250, apifrz 0 GCS CLIENT END 2012-05-02 02:12:15.635211 : kjbdowncvt[0x15c91.1 76896.0][1][options x0] 2012-05-02 02:12:15.635230 : GSIPC:AMBUF: rcv buff 0x7f16e1c56420, pool rcvbuf, rqlen 1103 2012-05-02 02:12:15.635308 : GSIPC:GPBMSG: new bmsg 0x7f16e1c56490 mb 0x7f16e1c56420 msg 0x7f16e1c564b0 mlen 152 dest x101 flushsz -1 2012-05-02 02:12:15.635334 : kjbmslset(0x15c91.1)) seq 0x4 reqid=0x6 (shadow 0xb48bb330.xb)(rsn 2)(mas@1) 2012-05-02 02:12:15.635355 : GSIPC:SPBMSG: send bmsg 0x7f16e1c56490 blen 184 msg 0x7f16e1c564b0 mtype 33 attr|dest x30101 bsz|fsz x1ffff 2012-05-02 02:12:15.635377 : GSIPC:SNDQ: enq msg 0x7f16e1c56490, type 65521 seq 118669, inst 1, receiver 1, queued 1 *** 2012-05-02 02:12:15.635 kclccctx: cleanup copy 0x7f16e1d94798 2012-05-02 02:12:15.635479 : [kjmpmsgi:compl][type 36][msg 0x7f16e1598588][seq 177740.0][qtime 0][ptime 1257] 2012-05-02 02:12:15.635511 : GSIPC:BSEND: flushing sndq 0xb491dd28, id 1, dcx 0xbc516778, inst 1, rcvr 1 qlen 0 1 2012-05-02 02:12:15.635536 : GSIPC:BSEND: no batch1 msg 0x7f16e1c56490 type 65521 len 184 dest (1:1) 2012-05-02 02:12:15.635557 : kjbsentscn[0x0.1ae0f1][to 1] 2012-05-02 02:12:15.635578 : GSIPC:SENDM: send msg 0x7f16e1c56490 dest x10001 seq 118669 type 65521 tkts x10002 mlen xb800e8 WAIT #0: nam='gcs remote message' ela= 180 waittime=1 poll=0 event=0 obj#=0 tim=1335939135635819 2012-05-02 02:12:15.635853 : GSIPC:RCVD: ksxp msg 0x7f16e167e0b0 sndr 1 seq 0.177741 type 32 tkts 0 2012-05-02 02:12:15.635875 : GSIPC:RCVD: watq msg 0x7f16e167e0b0 sndr 1, seq 177741, type 32, tkts 0 2012-05-02 02:12:15.636012 : GSIPC:TKT: collect msg 0x7f16e167e0b0 from 1 for rcvr -1, tickets 0 2012-05-02 02:12:15.636040 : kjbrcvdscn[0x0.1ae0f1][from 1][idx 2012-05-02 02:12:15.636060 : kjbrcvdscn[no bscn <= rscn 0x0.1ae0f1][from 1] 2012-05-02 02:12:15.636082 : GSIPC:TKT: dest (1:1) rtkt not acked 1  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:12:15.636102 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:12:15.636125 : [kjmxmpm][type 32][seq 0.177741][msg 0x7f16e167e0b0][from 1] 2012-05-02 02:12:15.636146 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23a,(client 0x9fff7b58,0x1)(from 1)(lseq xdf0) 2????LMS????????? ??gcs remote message GSIPC ????SCN=[0x0.1ae0f0] block=1/89233???,??BAST kjbmpbast(0x15c91.1),?? block=1/89233??????? ??fairness??(?11.2.0.3???_fairness_threshold=2),?current block?KCL: F156: fairness downconvert,?Xcurrent DownConvert? Scurrent: Instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 2 0 3 1756658 ??Instance 2 LMS ?cr block??? kjbmslset(0x15c91.1)) ????SEND QUEUE GSIPC:SNDQ: enq msg 0x7f16e1c56490? ???????Instance 1???? block: (1/89233)??? ??????: Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29273 437 Instance 1 session A: SQL> SQL> select * from test; ID ---------- 2 2 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 3 1761942 3 1761932 1 0 3 1761520 Instance 2: SQL> select CURRENT_RESULTS,LIGHT_WORKS from v$cr_block_server; CURRENT_RESULTS LIGHT_WORKS --------------- ----------- 29274 437 select * from test END OF STMT PARSE #140336529675592:c=0,e=337,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940051 EXEC #140336529675592:c=0,e=96,p=0,cr=0,cu=0,mis=0,r=0,dep=0,og=1,plh=1357081020,tim=1335939668940204 WAIT #140336529675592: nam='SQL*Net message to client' ela= 5 driver id=1650815232 #bytes=1 p3=0 obj#=0 tim=1335939668940348 *** 2012-05-02 02:21:08.940 kclscrs: req=0 block=1/89233 2012-05-02 02:21:08.940676 : kjbcro[0x15c91.1 76896.0][5] *** 2012-05-02 02:21:08.940 kclscrs: req=0 typ=nowait-abort *** 2012-05-02 02:21:08.940 kclscrs: bid=1:3:1:0:f:21:0:0:10:0:0:0:1:2:4:1:20:0:0:0:c3:49:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:0:4:3:2:1:2:0:1f:0:4d:26:a3:52:0:0:0:0:c7:c:ca:62:c3:49:0:0:0:0:1:0:17:8e:47:76:1:2:dc:5:a9:fe:17:75:0:0:0:0:0:0:0:0:0:0:0:0:99:ed:0:0:0:0:0:0:10:0:0:0 2012-05-02 02:21:08.940799 : kjbcro[0x15c91.1 76896.0][5] 2012-05-02 02:21:08.940833 : GSIPC:GMBQ: buff 0xba0ee018, queue 0xbb79a7b8, pool 0x60013fa0, freeq 0, nxt 0xbb79a7b8, prv 0xbb79a7b8 2012-05-02 02:21:08.940859 : kjbsentscn[0x0.1ae28c][to 2] 2012-05-02 02:21:08.940870 : GSIPC:SENDM: send msg 0xba0ee088 dest x20001 seq 177810 type 36 tkts xff0000 mlen x1680198 2012-05-02 02:21:08.940976 : kjbmscr(0x15c91.1)reqid=0xa(req 0xa4ff30f8)(rinst 1)hldr 2(infosz 200)(lseq x2b8) 2012-05-02 02:21:08.941314 : GSIPC:KSXPCB: msg 0xba0ee088 status 30, type 36, dest 2, rcvr 1 *** 2012-05-02 02:21:08.941 kclwcrs: wait=0 tm=707 *** 2012-05-02 02:21:08.941 kclwcrs: got 1 blocks from ksxprcv 2012-05-02 02:21:08.941818 : kjbassume[0x15c91.1][sender 2][mymode x1][myrole x0][srole x0][flgs x0][spiscn 0x0.0][swscn 0x0.0] 2012-05-02 02:21:08.941852 : kjbrcvdscn[0x0.1ae28d][from 2][idx 2012-05-02 02:21:08.941871 : kjbrcvdscn[no bscn ??????????????SCN=[0x0.1ae28c]=1761932 Version?CR block, ????receive????Xcurrent Block??SCN=1ae28d=1761933,Instance 1???Xcurrent Block???build????????SCN=1761932?CR BLOCK, ????????Current block,?????????'gc current block 2-way'? ?????????????request current block,?????kjbcro;?????Instance 2?LMS???????Current Block: Instance 2 LMS trace: 2012-05-02 02:21:08.448743 : GSIPC:RCVD: ksxp msg 0x7f16e14a4398 sndr 1 seq 0.177810 type 36 tkts 0 2012-05-02 02:21:08.448778 : GSIPC:RCVD: watq msg 0x7f16e14a4398 sndr 1, seq 177810, type 36, tkts 0 2012-05-02 02:21:08.448798 : GSIPC:TKT: collect msg 0x7f16e14a4398 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.448816 : kjbrcvdscn[0x0.1ae28c][from 1][idx 2012-05-02 02:21:08.448834 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28c][from 1] 2012-05-02 02:21:08.448857 : GSIPC:TKT: dest (1:1) rtkt not acked 2  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.448875 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.448970 : [kjmxmpm][type 36][seq 0.177810][msg 0x7f16e14a4398][from 1] 2012-05-02 02:21:08.448993 : kjbmpbast(0x15c91.1) reqid=0x6 (req 0xa4ff30f8)(reqinst 1)(reqid 10)(flags x0) *** 2012-05-02 02:21:08.449 kclcrrf: req=48054 block=1/89233 *** 2012-05-02 02:21:08.449 kcl_compress_block: compressed: 6 free space: 7680 2012-05-02 02:21:08.449085 : kjbsentscn[0x0.1ae28d][to 1] 2012-05-02 02:21:08.449142 : kjbdeliver[to 1][0xa4ff30f8][10][current 1] 2012-05-02 02:21:08.449164 : kjbmssch(reqlock 0xa4ff30f8,10)(to 1)(bsz 344) 2012-05-02 02:21:08.449183 : GSIPC:AMBUF: rcv buff 0x7f16e18bcec8, pool rcvbuf, rqlen 1102 *** 2012-05-02 02:21:08.449 kclccctx: cleanup copy 0x7f16e1d94838 *** 2012-05-02 02:21:08.449 kcltouched: touch seconds 3271 *** 2012-05-02 02:21:08.449 kclgrantlk: req=48054 2012-05-02 02:21:08.449347 : [kjmpmsgi:compl][type 36][msg 0x7f16e14a4398][seq 177810.0][qtime 0][ptime 1119] WAIT #0: nam='gcs remote message' ela= 568 waittime=1 poll=0 event=0 obj#=0 tim=1335939668449962 2012-05-02 02:21:08.450001 : GSIPC:RCVD: ksxp msg 0x7f16e1bb22a0 sndr 1 seq 0.177811 type 32 tkts 0 2012-05-02 02:21:08.450024 : GSIPC:RCVD: watq msg 0x7f16e1bb22a0 sndr 1, seq 177811, type 32, tkts 0 2012-05-02 02:21:08.450043 : GSIPC:TKT: collect msg 0x7f16e1bb22a0 from 1 for rcvr -1, tickets 0 2012-05-02 02:21:08.450060 : kjbrcvdscn[0x0.1ae28e][from 1][idx 2012-05-02 02:21:08.450078 : kjbrcvdscn[no bscn <= rscn 0x0.1ae28e][from 1] 2012-05-02 02:21:08.450097 : GSIPC:TKT: dest (1:1) rtkt not acked 3  unassigned bufs 0  tkts 0  newbufs 0 2012-05-02 02:21:08.450116 : GSIPC:TKT: remove ctx dest (1:1) 2012-05-02 02:21:08.450136 : [kjmxmpm][type 32][seq 0.177811][msg 0x7f16e1bb22a0][from 1] 2012-05-02 02:21:08.450155 : kjbmpocr(0xb0.6)seq 0x1,reqid=0x23e,(client 0x9fff7b58,0x1)(from 1)(lseq xdf4) ???Instance 2??LMS???,???build cr block,??????Instance 1?????Current Block??????Instance 2??v$cr_block_server??????LIGHT_WORKS?????current block transfer??????,??????? CR server? Light Work Rule(Light Work Rule?8i Cr Server?????????,?Remote LMS?? build CR????????,resource holder?LMS???????block,????CR build If creating the consistent read version block involves too much work (such as reading blocks from disk), then the holder sends the block to the requestor, and the requestor completes the CR fabrication. The holder maintains a fairness counter of CR requests. After the fairness threshold is reached, the holder downgrades it to lock mode.)? ??????? CR Request ????Current Block?? ???:??????class?block,CR server??????? ??undo block?? undo header block?CR quest, LMS????Current Block, ????? ???? ??????? block cleanout? CR  Version??????? ???????? data blocks, ??????? CR quest  & CR received?(???????Light Work Rule,LMS"??"), ??Current Block??DownConvert???S lock,??LMS???????ship??current version?block? ??????? , ?????? ,???????DownConvert?????”_fairness_threshold“???200,????Xcurrent Block?????Scurrent, ????LMS?????Current Version?Data Block: SQL> show parameter fair NAME TYPE VALUE ------------------------------------ ----------- ------------------------------ _fairness_threshold integer 200 Instance 1: SQL> update test set id=id+1 where id=4; 1 row updated. Instance 2: SQL> update test set id=id+1 where id=2; 1 row updated. SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1838166 ?Instance 1? ????,? ??instance 2? v$cr_block_server?? instance 1 SQL> select * from test; ID ---------- 10 3 instance 2: SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 SQL> select * from test; ID ---------- 10 3 SQL> select state,cr_scn_bas from x$bh where file#=1 and dbablk=89233 and state!=0; STATE CR_SCN_BAS ---------- ---------- 1 0 3 1883707 8 0 ................... SQL> / STATE CR_SCN_BAS ---------- ---------- 2 0 3 1883707 3 1883695 repeat cr request on Instance 1 SQL> / STATE CR_SCN_BAS ---------- ---------- 8 0 3 1883707 3 1883695 ??????_fairness_threshold????????,?????200 ????????CR serve??Downgrade?lock, ????data block? CR Request????Receive? Current Block?

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  • Cheatsheet: 2010 04.01 ~ 04.07

    - by gOODiDEA
    Web Web Performance Best Practices: How masters.com re-designed their site to boost performance – and what that re-design missed What’s wrong with extending the DOM John Resig on Advanced Javascript to Improve your Web App .NET Hammock for REST - a REST library for .NET Programming Windows Phone 7 Series by Charlez Petzold – Free EBook Testing the Lock-Free Queue Some Last-Minute New C# 4.0 Features - while (x --> 0) { Console.WriteLine("x = {0}", x); } Better Coding with Visual Studio 2010 Revisiting Asynchronous ASP.NET Pages Database Understanding RAID for SQL Server – Part 2 Cassandra Jump Start For The Windows Developer Cassandra Internals – Writing - Cassandra Write Operation Performance Explained Cassandra Internals – Reading - Cassandra Reads Performance Explained MongoDB Growing Up: Release 1.4 and Commercial Support by 10gen Why NoSQL Will Not Die How Many Hard Drives Do I Need to Support SQL Server? Other Presentation: CouchDB and Lucene MongoDB Cacti Graphs HBase vs Cassandra: why we moved How to use the DedicatedDumpFile registry value to overcome space limitations on the system drive when capturing a system memory dump

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  • World Record Batch Rate on Oracle JD Edwards Consolidated Workload with SPARC T4-2

    - by Brian
    Oracle produced a World Record batch throughput for single system results on Oracle's JD Edwards EnterpriseOne Day-in-the-Life benchmark using Oracle's SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2. The workload includes both online and batch workload. The SPARC T4-2 server delivered a result of 8,000 online users while concurrently executing a mix of JD Edwards EnterpriseOne Long and Short batch processes at 95.5 UBEs/min (Universal Batch Engines per minute). In order to obtain this record benchmark result, the JD Edwards EnterpriseOne, Oracle WebLogic and Oracle Database 11g Release 2 servers were executed each in separate Oracle Solaris Containers which enabled optimal system resources distribution and performance together with scalable and manageable virtualization. One SPARC T4-2 server running Oracle Solaris Containers and consolidating JD Edwards EnterpriseOne, Oracle WebLogic servers and the Oracle Database 11g Release 2 utilized only 55% of the available CPU power. The Oracle DB server in a Shared Server configuration allows for optimized CPU resource utilization and significant memory savings on the SPARC T4-2 server without sacrificing performance. This configuration with SPARC T4-2 server has achieved 33% more Users/core, 47% more UBEs/min and 78% more Users/rack unit than the IBM Power 770 server. The SPARC T4-2 server with 2 processors ran the JD Edwards "Day-in-the-Life" benchmark and supported 8,000 concurrent online users while concurrently executing mixed batch workloads at 95.5 UBEs per minute. The IBM Power 770 server with twice as many processors supported only 12,000 concurrent online users while concurrently executing mixed batch workloads at only 65 UBEs per minute. This benchmark demonstrates more than 2x cost savings by consolidating the complete solution in a single SPARC T4-2 server compared to earlier published results of 10,000 users and 67 UBEs per minute on two SPARC T4-2 and SPARC T4-1. The Oracle DB server used mirrored (RAID 1) volumes for the database providing high availability for the data without impacting performance. Performance Landscape JD Edwards EnterpriseOne Day in the Life (DIL) Benchmark Consolidated Online with Batch Workload System Rack Units BatchRate(UBEs/m) Online Users Users /Units Users /Core Version SPARC T4-2 (2 x SPARC T4, 2.85 GHz) 3 95.5 8,000 2,667 500 9.0.2 IBM Power 770 (4 x POWER7, 3.3 GHz, 32 cores) 8 65 12,000 1,500 375 9.0.2 Batch Rate (UBEs/m) — Batch transaction rate in UBEs per minute Configuration Summary Hardware Configuration: 1 x SPARC T4-2 server with 2 x SPARC T4 processors, 2.85 GHz 256 GB memory 4 x 300 GB 10K RPM SAS internal disk 2 x 300 GB internal SSD 2 x Sun Storage F5100 Flash Arrays Software Configuration: Oracle Solaris 10 Oracle Solaris Containers JD Edwards EnterpriseOne 9.0.2 JD Edwards EnterpriseOne Tools (8.98.4.2) Oracle WebLogic Server 11g (10.3.4) Oracle HTTP Server 11g Oracle Database 11g Release 2 (11.2.0.1) Benchmark Description JD Edwards EnterpriseOne is an integrated applications suite of Enterprise Resource Planning (ERP) software. Oracle offers 70 JD Edwards EnterpriseOne application modules to support a diverse set of business operations. Oracle's Day in the Life (DIL) kit is a suite of scripts that exercises most common transactions of JD Edwards EnterpriseOne applications, including business processes such as payroll, sales order, purchase order, work order, and manufacturing processes, such as ship confirmation. These are labeled by industry acronyms such as SCM, CRM, HCM, SRM and FMS. The kit's scripts execute transactions typical of a mid-sized manufacturing company. The workload consists of online transactions and the UBE – Universal Business Engine workload of 61 short and 4 long UBEs. LoadRunner runs the DIL workload, collects the user’s transactions response times and reports the key metric of Combined Weighted Average Transaction Response time. The UBE processes workload runs from the JD Enterprise Application server. Oracle's UBE processes come as three flavors: Short UBEs < 1 minute engage in Business Report and Summary Analysis, Mid UBEs > 1 minute create a large report of Account, Balance, and Full Address, Long UBEs > 2 minutes simulate Payroll, Sales Order, night only jobs. The UBE workload generates large numbers of PDF files reports and log files. The UBE Queues are categorized as the QBATCHD, a single threaded queue for large and medium UBEs, and the QPROCESS queue for short UBEs run concurrently. Oracle's UBE process performance metric is Number of Maximum Concurrent UBE processes at transaction rate, UBEs/minute. Key Points and Best Practices Two JD Edwards EnterpriseOne Application Servers, two Oracle WebLogic Servers 11g Release 1 coupled with two Oracle Web Tier HTTP server instances and one Oracle Database 11g Release 2 database on a single SPARC T4-2 server were hosted in separate Oracle Solaris Containers bound to four processor sets to demonstrate consolidation of multiple applications, web servers and the database with best resource utilizations. Interrupt fencing was configured on all Oracle Solaris Containers to channel the interrupts to processors other than the processor sets used for the JD Edwards Application server, Oracle WebLogic servers and the database server. A Oracle WebLogic vertical cluster was configured on each WebServer Container with twelve managed instances each to load balance users' requests and to provide the infrastructure that enables scaling to high number of users with ease of deployment and high availability. The database log writer was run in the real time RT class and bound to a processor set. The database redo logs were configured on the raw disk partitions. The Oracle Solaris Container running the Enterprise Application server completed 61 Short UBEs, 4 Long UBEs concurrently as the mixed size batch workload. The mixed size UBEs ran concurrently from the Enterprise Application server with the 8,000 online users driven by the LoadRunner. See Also SPARC T4-2 Server oracle.com OTN JD Edwards EnterpriseOne oracle.com OTN Oracle Solaris oracle.com OTN Oracle Database 11g Release 2 Enterprise Edition oracle.com OTN Oracle Fusion Middleware oracle.com OTN Disclosure Statement Copyright 2012, Oracle and/or its affiliates. All rights reserved. Oracle and Java are registered trademarks of Oracle and/or its affiliates. Other names may be trademarks of their respective owners. Results as of 09/30/2012.

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  • Scaling-out Your Services by Message Bus based WCF Transport Extension &ndash; Part 1 &ndash; Background

    - by Shaun
    Cloud computing gives us more flexibility on the computing resource, we can provision and deploy an application or service with multiple instances over multiple machines. With the increment of the service instances, how to balance the incoming message and workload would become a new challenge. Currently there are two approaches we can use to pass the incoming messages to the service instances, I would like call them dispatcher mode and pulling mode.   Dispatcher Mode The dispatcher mode introduces a role which takes the responsible to find the best service instance to process the request. The image below describes the sharp of this mode. There are four clients communicate with the service through the underlying transportation. For example, if we are using HTTP the clients might be connecting to the same service URL. On the server side there’s a dispatcher listening on this URL and try to retrieve all messages. When a message came in, the dispatcher will find a proper service instance to process it. There are three mechanism to find the instance: Round-robin: Dispatcher will always send the message to the next instance. For example, if the dispatcher sent the message to instance 2, then the next message will be sent to instance 3, regardless if instance 3 is busy or not at that moment. Random: Dispatcher will find a service instance randomly, and same as the round-robin mode it regardless if the instance is busy or not. Sticky: Dispatcher will send all related messages to the same service instance. This approach always being used if the service methods are state-ful or session-ful. But as you can see, all of these approaches are not really load balanced. The clients will send messages at any time, and each message might take different process duration on the server side. This means in some cases, some of the service instances are very busy while others are almost idle. For example, if we were using round-robin mode, it could be happened that most of the simple task messages were passed to instance 1 while the complex ones were sent to instance 3, even though instance 1 should be idle. This brings some problem in our architecture. The first one is that, the response to the clients might be longer than it should be. As it’s shown in the figure above, message 6 and 9 can be processed by instance 1 or instance 2, but in reality they were dispatched to the busy instance 3 since the dispatcher and round-robin mode. Secondly, if there are many requests came from the clients in a very short period, service instances might be filled by tons of pending tasks and some instances might be crashed. Third, if we are using some cloud platform to host our service instances, for example the Windows Azure, the computing resource is billed by service deployment period instead of the actual CPU usage. This means if any service instance is idle it is wasting our money! Last one, the dispatcher would be the bottleneck of our system since all incoming messages must be routed by the dispatcher. If we are using HTTP or TCP as the transport, the dispatcher would be a network load balance. If we wants more capacity, we have to scale-up, or buy a hardware load balance which is very expensive, as well as scaling-out the service instances. Pulling Mode Pulling mode doesn’t need a dispatcher to route the messages. All service instances are listening to the same transport and try to retrieve the next proper message to process if they are idle. Since there is no dispatcher in pulling mode, it requires some features on the transportation. The transportation must support multiple client connection and server listening. HTTP and TCP doesn’t allow multiple clients are listening on the same address and port, so it cannot be used in pulling mode directly. All messages in the transportation must be FIFO, which means the old message must be received before the new one. Message selection would be a plus on the transportation. This means both service and client can specify some selection criteria and just receive some specified kinds of messages. This feature is not mandatory but would be very useful when implementing the request reply and duplex WCF channel modes. Otherwise we must have a memory dictionary to store the reply messages. I will explain more about this in the following articles. Message bus, or the message queue would be best candidate as the transportation when using the pulling mode. First, it allows multiple application to listen on the same queue, and it’s FIFO. Some of the message bus also support the message selection, such as TIBCO EMS, RabbitMQ. Some others provide in memory dictionary which can store the reply messages, for example the Redis. The principle of pulling mode is to let the service instances self-managed. This means each instance will try to retrieve the next pending incoming message if they finished the current task. This gives us more benefit and can solve the problems we met with in the dispatcher mode. The incoming message will be received to the best instance to process, which means this will be very balanced. And it will not happen that some instances are busy while other are idle, since the idle one will retrieve more tasks to make them busy. Since all instances are try their best to be busy we can use less instances than dispatcher mode, which more cost effective. Since there’s no dispatcher in the system, there is no bottleneck. When we introduced more service instances, in dispatcher mode we have to change something to let the dispatcher know the new instances. But in pulling mode since all service instance are self-managed, there no extra change at all. If there are many incoming messages, since the message bus can queue them in the transportation, service instances would not be crashed. All above are the benefits using the pulling mode, but it will introduce some problem as well. The process tracking and debugging become more difficult. Since the service instances are self-managed, we cannot know which instance will process the message. So we need more information to support debug and track. Real-time response may not be supported. All service instances will process the next message after the current one has done, if we have some real-time request this may not be a good solution. Compare with the Pros and Cons above, the pulling mode would a better solution for the distributed system architecture. Because what we need more is the scalability, cost-effect and the self-management.   WCF and WCF Transport Extensibility Windows Communication Foundation (WCF) is a framework for building service-oriented applications. In the .NET world WCF is the best way to implement the service. In this series I’m going to demonstrate how to implement the pulling mode on top of a message bus by extending the WCF. I don’t want to deep into every related field in WCF but will highlight its transport extensibility. When we implemented an RPC foundation there are many aspects we need to deal with, for example the message encoding, encryption, authentication and message sending and receiving. In WCF, each aspect is represented by a channel. A message will be passed through all necessary channels and finally send to the underlying transportation. And on the other side the message will be received from the transport and though the same channels until the business logic. This mode is called “Channel Stack” in WCF, and the last channel in the channel stack must always be a transport channel, which takes the responsible for sending and receiving the messages. As we are going to implement the WCF over message bus and implement the pulling mode scaling-out solution, we need to create our own transport channel so that the client and service can exchange messages over our bus. Before we deep into the transport channel, let’s have a look on the message exchange patterns that WCF defines. Message exchange pattern (MEP) defines how client and service exchange the messages over the transportation. WCF defines 3 basic MEPs which are datagram, Request-Reply and Duplex. Datagram: Also known as one-way, or fire-forgot mode. The message sent from the client to the service, and no need any reply from the service. The client doesn’t care about the message result at all. Request-Reply: Very common used pattern. The client send the request message to the service and wait until the reply message comes from the service. Duplex: The client sent message to the service, when the service processing the message it can callback to the client. When callback the service would be like a client while the client would be like a service. In WCF, each MEP represent some channels associated. MEP Channels Datagram IInputChannel, IOutputChannel Request-Reply IRequestChannel, IReplyChannel Duplex IDuplexChannel And the channels are created by ChannelListener on the server side, and ChannelFactory on the client side. The ChannelListener and ChannelFactory are created by the TransportBindingElement. The TransportBindingElement is created by the Binding, which can be defined as a new binding or from a custom binding. For more information about the transport channel mode, please refer to the MSDN document. The figure below shows the transport channel objects when using the request-reply MEP. And this is the datagram MEP. And this is the duplex MEP. After investigated the WCF transport architecture, channel mode and MEP, we finally identified what we should do to extend our message bus based transport layer. They are: Binding: (Optional) Defines the channel elements in the channel stack and added our transport binding element at the bottom of the stack. But we can use the build-in CustomBinding as well. TransportBindingElement: Defines which MEP is supported in our transport and create the related ChannelListener and ChannelFactory. This also defines the scheme of the endpoint if using this transport. ChannelListener: Create the server side channel based on the MEP it’s. We can have one ChannelListener to create channels for all supported MEPs, or we can have ChannelListener for each MEP. In this series I will use the second approach. ChannelFactory: Create the client side channel based on the MEP it’s. We can have one ChannelFactory to create channels for all supported MEPs, or we can have ChannelFactory for each MEP. In this series I will use the second approach. Channels: Based on the MEPs we want to support, we need to implement the channels accordingly. For example, if we want our transport support Request-Reply mode we should implement IRequestChannel and IReplyChannel. In this series I will implement all 3 MEPs listed above one by one. Scaffold: In order to make our transport extension works we also need to implement some scaffold stuff. For example we need some classes to send and receive message though out message bus. We also need some codes to read and write the WCF message, etc.. These are not necessary but would be very useful in our example.   Message Bus There is only one thing remained before we can begin to implement our scaling-out support WCF transport, which is the message bus. As I mentioned above, the message bus must have some features to fulfill all the WCF MEPs. In my company we will be using TIBCO EMS, which is an enterprise message bus product. And I have said before we can use any message bus production if it’s satisfied with our requests. Here I would like to introduce an interface to separate the message bus from the WCF. This allows us to implement the bus operations by any kinds bus we are going to use. The interface would be like this. 1: public interface IBus : IDisposable 2: { 3: string SendRequest(string message, bool fromClient, string from, string to = null); 4:  5: void SendReply(string message, bool fromClient, string replyTo); 6:  7: BusMessage Receive(bool fromClient, string replyTo); 8: } There are only three methods for the bus interface. Let me explain one by one. The SendRequest method takes the responsible for sending the request message into the bus. The parameters description are: message: The WCF message content. fromClient: Indicates if this message was came from the client. from: The channel ID that this message was sent from. The channel ID will be generated when any kinds of channel was created, which will be explained in the following articles. to: The channel ID that this message should be received. In Request-Reply and Duplex MEP this is necessary since the reply message must be received by the channel which sent the related request message. The SendReply method takes the responsible for sending the reply message. It’s very similar as the previous one but no “from” parameter. This is because it’s no need to reply a reply message again in any MEPs. The Receive method takes the responsible for waiting for a incoming message, includes the request message and specified reply message. It returned a BusMessage object, which contains some information about the channel information. The code of the BusMessage class is 1: public class BusMessage 2: { 3: public string MessageID { get; private set; } 4: public string From { get; private set; } 5: public string ReplyTo { get; private set; } 6: public string Content { get; private set; } 7:  8: public BusMessage(string messageId, string fromChannelId, string replyToChannelId, string content) 9: { 10: MessageID = messageId; 11: From = fromChannelId; 12: ReplyTo = replyToChannelId; 13: Content = content; 14: } 15: } Now let’s implement a message bus based on the IBus interface. Since I don’t want you to buy and install the TIBCO EMS or any other message bus products, I will implement an in process memory bus. This bus is only for test and sample purpose. It can only be used if the service and client are in the same process. Very straightforward. 1: public class InProcMessageBus : IBus 2: { 3: private readonly ConcurrentDictionary<Guid, InProcMessageEntity> _queue; 4: private readonly object _lock; 5:  6: public InProcMessageBus() 7: { 8: _queue = new ConcurrentDictionary<Guid, InProcMessageEntity>(); 9: _lock = new object(); 10: } 11:  12: public string SendRequest(string message, bool fromClient, string from, string to = null) 13: { 14: var entity = new InProcMessageEntity(message, fromClient, from, to); 15: _queue.TryAdd(entity.ID, entity); 16: return entity.ID.ToString(); 17: } 18:  19: public void SendReply(string message, bool fromClient, string replyTo) 20: { 21: var entity = new InProcMessageEntity(message, fromClient, null, replyTo); 22: _queue.TryAdd(entity.ID, entity); 23: } 24:  25: public BusMessage Receive(bool fromClient, string replyTo) 26: { 27: InProcMessageEntity e = null; 28: while (true) 29: { 30: lock (_lock) 31: { 32: var entity = _queue 33: .Where(kvp => kvp.Value.FromClient == fromClient && (kvp.Value.To == replyTo || string.IsNullOrWhiteSpace(kvp.Value.To))) 34: .FirstOrDefault(); 35: if (entity.Key != Guid.Empty && entity.Value != null) 36: { 37: _queue.TryRemove(entity.Key, out e); 38: } 39: } 40: if (e == null) 41: { 42: Thread.Sleep(100); 43: } 44: else 45: { 46: return new BusMessage(e.ID.ToString(), e.From, e.To, e.Content); 47: } 48: } 49: } 50:  51: public void Dispose() 52: { 53: } 54: } The InProcMessageBus stores the messages in the objects of InProcMessageEntity, which can take some extra information beside the WCF message itself. 1: public class InProcMessageEntity 2: { 3: public Guid ID { get; set; } 4: public string Content { get; set; } 5: public bool FromClient { get; set; } 6: public string From { get; set; } 7: public string To { get; set; } 8:  9: public InProcMessageEntity() 10: : this(string.Empty, false, string.Empty, string.Empty) 11: { 12: } 13:  14: public InProcMessageEntity(string content, bool fromClient, string from, string to) 15: { 16: ID = Guid.NewGuid(); 17: Content = content; 18: FromClient = fromClient; 19: From = from; 20: To = to; 21: } 22: }   Summary OK, now I have all necessary stuff ready. The next step would be implementing our WCF message bus transport extension. In this post I described two scaling-out approaches on the service side especially if we are using the cloud platform: dispatcher mode and pulling mode. And I compared the Pros and Cons of them. Then I introduced the WCF channel stack, channel mode and the transport extension part, and identified what we should do to create our own WCF transport extension, to let our WCF services using pulling mode based on a message bus. And finally I provided some classes that need to be used in the future posts that working against an in process memory message bus, for the demonstration purpose only. In the next post I will begin to implement the transport extension step by step.   Hope this helps, Shaun All documents and related graphics, codes are provided "AS IS" without warranty of any kind. Copyright © Shaun Ziyan Xu. This work is licensed under the Creative Commons License.

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  • Defining the Features we would like to see

    - by Patrick Liekhus
    OK, now that we have a very rough idea of what we are building, let’s get a list of the top features that this application needs to allow us to do.  In this next list we are not prioritizing them yet, just getting on paper the high level backlog of items that this system must do. Add a new task to my work queue Change the status of the task Print a hard copy of the task list by day for my records Log a phone conversation A manager should be able to assign tasks to another user How do we login? Change the Covey roles per user Manage the statuses used Manage the Covey quadrants Can we make this available on the following user interfaces? Windows Desktop Web Browser Sliverlight (WPF) Excel Add-in Outlook Add-in Android Devices iPhone Devices Windows Mobile Devices Blackberry Devices While this looks like a simple spread sheet, it can get pretty complex and busy quickly.  Next time we will work on making this into a Product Backlog and prioritizing the features we would like to see.

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  • Azure Storage Explorer

    - by kaleidoscope
    Azure Storage Explorer –  an another way to Deploy the services on Cloud Azure Storage Explorer is a useful GUI tool for inspecting and altering the data in your Azure cloud storage projects including the logs of your cloud-hosted applications. All three types of cloud storage can be viewed: blobs, queues, and tables. You can also create or delete blob/queue/table containers and items. Text blobs can be edited and all data types can be imported/exported between the cloud and local files. Table records can be imported/exported between the cloud and spreadsheet CSV files. Why Azure Storage Explorer Azure Storage Explorer is a licensed CodePlex project provided by Neudesic – a Microsoft partner.  It is a simple UI that requires you to input your blob storage name, access key and endpoints in the Storage Settings dialog. For more details please refer to the link: http://azurestorageexplorer.codeplex.com/Release/ProjectReleases.aspx?ReleaseId=35189   Anish, S

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  • FairScheduling Conventions in Hadoop

    - by dan.mcclary
    While scheduling and resource allocation control has been present in Hadoop since 0.20, a lot of people haven't discovered or utilized it in their initial investigations of the Hadoop ecosystem. We could chalk this up to many things: Organizations are still determining what their dataflow and analysis workloads will comprise Small deployments under tests aren't likely to show the signs of strains that would send someone looking for resource allocation options The default scheduling options -- the FairScheduler and the CapacityScheduler -- are not placed in the most prominent position within the Hadoop documentation. However, for production deployments, it's wise to start with at least the foundations of scheduling in place so that you can tune the cluster as workloads emerge. To do that, we have to ask ourselves something about what the off-the-rack scheduling options are. We have some choices: The FairScheduler, which will work to ensure resource allocations are enforced on a per-job basis. The CapacityScheduler, which will ensure resource allocations are enforced on a per-queue basis. Writing your own implementation of the abstract class org.apache.hadoop.mapred.job.TaskScheduler is an option, but usually overkill. If you're going to have several concurrent users and leverage the more interactive aspects of the Hadoop environment (e.g. Pig and Hive scripting), the FairScheduler is definitely the way to go. In particular, we can do user-specific pools so that default users get their fair share, and specific users are given the resources their workloads require. To enable fair scheduling, we're going to need to do a couple of things. First, we need to tell the JobTracker that we want to use scheduling and where we're going to be defining our allocations. We do this by adding the following to the mapred-site.xml file in HADOOP_HOME/conf: <property> <name>mapred.jobtracker.taskScheduler</name> <value>org.apache.hadoop.mapred.FairScheduler</value> </property> <property> <name>mapred.fairscheduler.allocation.file</name> <value>/path/to/allocations.xml</value> </property> <property> <name>mapred.fairscheduler.poolnameproperty</name> <value>pool.name</value> </property> <property> <name>pool.name</name> <value>${user.name}</name> </property> What we've done here is simply tell the JobTracker that we'd like to task scheduling to use the FairScheduler class rather than a single FIFO queue. Moreover, we're going to be defining our resource pools and allocations in a file called allocations.xml For reference, the allocation file is read every 15s or so, which allows for tuning allocations without having to take down the JobTracker. Our allocation file is now going to look a little like this <?xml version="1.0"?> <allocations> <pool name="dan"> <minMaps>5</minMaps> <minReduces>5</minReduces> <maxMaps>25</maxMaps> <maxReduces>25</maxReduces> <minSharePreemptionTimeout>300</minSharePreemptionTimeout> </pool> <mapreduce.job.user.name="dan"> <maxRunningJobs>6</maxRunningJobs> </user> <userMaxJobsDefault>3</userMaxJobsDefault> <fairSharePreemptionTimeout>600</fairSharePreemptionTimeout> </allocations> In this case, I've explicitly set my username to have upper and lower bounds on the maps and reduces, and allotted myself double the number of running jobs. Now, if I run hive or pig jobs from either the console or via the Hue web interface, I'll be treated "fairly" by the JobTracker. There's a lot more tweaking that can be done to the allocations file, so it's best to dig down into the description and start trying out allocations that might fit your workload.

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  • New Year's resolution 2012

    Same procedure as every year... Hundreds of thousands of people have their annual new year's resolution to begin the new year. And so am I. My resolution for 2012: Writing more blog articles (again). Actually, it's quite difficult to find to proper time and space to write up an article for any kind of blog, newspaper or magazine. Especially, when you are very busy with daily work and fulfilling customers demands with very tight schedules. But seriously, I'll try to keep it up with at least one or two articles per month during 2012. There are quite some good topics to write about in the queue. Cheers, JoKi

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  • Messaging technologies between applications ?

    - by Samuel
    Recently, I had to create a program to send messages between two winforms executable. I used a tool with simple built-in functionalities to prevent having to figure out all the ins and outs of this vast quantity of protocols that exist. But now, I'm ready to learn more about the internals difference between each of theses protocols. I googled a couple of them but it would be greatly appreciate to have a good reference book that gives me a clean idea of how each protocol works and what are the pros and cons in a couple of context. Here is a list of nice protocols that I found: Shared memory TCP List item Named Pipe File Mapping Mailslots MSMQ (Microsoft Queue Solution) WCF I know that all of these protocols are not specific to a language, it would be nice if example could be in .net. Thank you very much.

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  • Drawing graphics in Java game

    - by wolf
    I am quite new to game development, so here is a question (maybe a stupid one): In my sidescroller i have a bunch of different graphics objects that i need to draw (player, background tiles, creatures, projectiles etc). Most tutorials i've read so far show that each object has its own draw method, which is then called from some other method. What if I had one method that does all the drawing? Lets say i keep all my objects in an array or queue (or multiple arrays) and then go through each of them, get an image and draw it. So basically would it be better (and why) to have each object have its own draw method or one method that does all the drawing? Or does it matter at all? I feel like the second option is more comfortable, because then all the stuff to do with drawing would be in one place...

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  • Developing an analytics's system processing large amounts of data - where to start

    - by Ryan
    Imagine you're writing some sort of Web Analytics system - you're recording raw page hits along with some extra things like tagging cookies etc and then producing stats such as Which pages got most traffic over a time period Which referers sent most traffic Goals completed (goal being a view of a particular page) And more advanced things like which referers sent the most number of vistors who later hit a goal. The naieve way of approaching this would be to throw it in a relational database and run queries over it - but that won't scale. You could pre-calculate everything (have a queue of incoming 'hits' and use to update report tables) - but what if you later change a goal - how could you efficiently re-calculate just the data that would be effected. Obviously this has been done before ;) so any tips on where to start, methods & examples, architecture, technologies etc.

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  • T-SQL Tuesday - IO capacity planning

    - by Michael Zilberstein
    This post is my contribution to Adam Machanic's T-SQL Tuesday #004 , hosted this time by Mike Walsh . Being applicative DBA, I usually don't take part in discussions which storage to buy or how to configure it. My interaction with IO is usually via PerfMon. When somebody calls me asking why everything is suddenly so slow on database server, "disk queue length" or "average seconds per transfer" counters provide an overwhelming answer in 60-70% of such cases. Sometimes it can be...(read more)

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  • lubuntu notify-send remove limit of 21?

    - by giuspen
    sending notifications with notify-send in lubuntu notify-send -i error -t 1000 "Error" "error notification" I can send only 21 of them, after that no more notifications sent, the only way to receive more notifications is to click on the panel where there's a letter with the number 21 and then click on the button "clear all notifications". Is there a way to avoid the need to go clicking the button, also is there a way to remove at all that letter with number of notifications received? UPDATE: I realize that notification-daemon (0.7.3) is used. I downloaded the sources and edited the source code (nd-queue.c - on_bubble_destroyed) to do not buffer but always destroy the bubbles but I would prefer another way...

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  • Problems with brother printer drivers on 64bit 12.04

    - by Jeff Klein
    I'm running 12.04 64bit on a toshiba satellite laptop. I have a Brotrher MFC-J825dw printer. I've installed brothers driver for it and the cupswrapper but it won't print. I says it is receiving data but it never shows up in the queue. I've also tried the text only generic driver and the same thing happens. I think some dependencies are missing for the cups wrapper and when I try to find it it says it can't be installed. Nopt sure if that's the problem because it doesn't explain the generic driver failure. In any case, any ideas?

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  • What datastructure would you use for a collision-detection in a tilemap?

    - by Solom
    Currently I save those blocks in my map that could be colliding with the player in a HashMap (Vector2, Block). So the Vector2 represents the coordinates of the blog. Whenever the player moves I then iterate over all these Blocks (that are in a specific range around the player) and check if a collision happened. This was my first rough idea on how to implement the collision-detection. Currently if the player moves I put more and more blocks in the HashMap until a specific "upper bound", then I clear it and start over. I was fully aware that it was not the brightest solution for the problem, but as said, it was a rough first implementation (I'm still learning a lot about game-design and the data-structure). What data-structure would you use to save the Blocks? I thought about a Queue or even a Stack, but I'm not sure, hence I ask.

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