Search Results

Search found 1122 results on 45 pages for 'concurrent'.

Page 36/45 | < Previous Page | 32 33 34 35 36 37 38 39 40 41 42 43  | Next Page >

  • Many clients on a wireless AP for UDP broadcast packets

    - by distorteddisco
    I asked this question on StackOverflow and was directed over here, so I'd appreciate any advice. I'm deploying a smartphone application as part of a live music performance that depends on receiving UDP broadcast packets from a wireless access point. I'm guessing that between 20 and 50 clients will be connected at any one time. I'm aware that a maximum of 20 clients per access point is advised, but as the UDP broadcast packets are ground through the LAN, how would I be able to link multiple APs together? I'm looking for recommendations on a suitable AP for this. The actual data transmission rates are very low - only a few kB/s - as I'm just sending small messages to the smartphone apps, and there will be no WAN internet connection. I tried it with a few connected peers on an adhoc wireless connection without any problems, but ran into dropped packet issues on an old WRT54G running ddwrt, though it's in pretty rough shape. What's the best way to do this? I suppose I could limit concurrent wireless connections to 20 clients... but more would be nice. EDIT: I should also say that it's purely one-way communication; the smartphone application is only receiving broadcast packets, not sending anything.

    Read the article

  • Is NFS capable of preserving order of operations?

    - by JustJeff
    I have a diskless host 'A', that has a directory NFS mounted on server 'B'. A process on A writes to two files F1 and F2 in that directory, and a process on B monitors these files for changes. Assume that B polls for changes faster than A is expected to make them. Process A seeks the head of the files, writes data, and flushes. Process B seeks the head of the files and does reads. Are there any guarantees about how the order of the changes performed by A will be detected at B? Specifically, if A alternately writes to one file, and then the other, is it reasonable to expect that B will notice alternating changes to F1 and F2? Or could B conceivably detect a series of changes on F1 and then a series on F2? I know there are a lot of assumptions embedded in the question. For instance, I am virtually certain that, even operating on just one file, if A performs 100 operations on the file, B may see a smaller number of changes that give the same result, due to NFS caching some of the actions on A before they are communicated to B. And of course there would be issues with concurrent file access even if NFS weren't involved and both the reading and the writing process were running on the same real file system. The reason I'm even putting the question up here is that it seems like most of the time, the setup described above does detect the changes at B in the same order they are made at A, but that occasionally some events come through in transposed order. So, is it worth trying to make this work? Is there some way to tune NFS to make it work, perhaps cache settings or something? Or is fine-grained behavior like this just too much expect from NFS?

    Read the article

  • Is there such a thing as a file hosted container which deduplicates data held within?

    - by Mallow
    Background I have backups of a website which stores all of it's data into a single file. This file is several gigs large and I have many different backups of this file. Most of the data within is mostly the same plus whatever was added or changed to it. I want to keep all the concurrent backups I've made through the years in case I find a horrible surprise of data corruption along the line. However storing a 10gig file every month gets expensive. Seeking Solution I've often thought about different ways of alleviating this problem. One thought that comes up very often combines the idea of a duplicating file system which doesn't require it's own partitioned volume on a hard drive. Something like what truecrypt does, what it calls, "file hosted containers" which when using the truecrypt program allows you to mount and dismount that volume as a regular hard drive. Question Is there a virtual hard drive mounter which uses file-based container which uses data deduplicaiton file system? (This question is a little awkward to put into words, if you have a better idea on how to ask this question please feel free to help out.)

    Read the article

  • amazon ec2-medium apache requests per second terrible

    - by TheDayIsDone
    EDITED -- test running from localhost now to rule out network... i have a c1.medium using EBS. when i do an apache benchmark and i'm just printing a "hello" for the test from localhost - no database hits, it's very slow. i can repeat this test many times with the same results. any thoughts? thanks in advance. ab -n 1000 -c 100 http://localhost/home/test/ Benchmarking localhost (be patient) Completed 100 requests Completed 200 requests Completed 300 requests Completed 400 requests Completed 500 requests Completed 600 requests Completed 700 requests Completed 800 requests Completed 900 requests Completed 1000 requests Finished 1000 requests Server Software: Apache/2.2.23 Server Hostname: localhost Server Port: 80 Document Path: /home/test/ Document Length: 5 bytes Concurrency Level: 100 Time taken for tests: 25.300 seconds Complete requests: 1000 Failed requests: 0 Write errors: 0 Total transferred: 816000 bytes HTML transferred: 5000 bytes Requests per second: 39.53 [#/sec] (mean) Time per request: 2530.037 [ms] (mean) Time per request: 25.300 [ms] (mean, across all concurrent requests) Transfer rate: 31.50 [Kbytes/sec] received Connection Times (ms) min mean[+/-sd] median max Connect: 0 7 21.0 0 73 Processing: 81 2489 665.7 2500 4057 Waiting: 80 2443 654.0 2445 4057 Total: 85 2496 653.5 2500 4057 Percentage of the requests served within a certain time (ms) 50% 2500 66% 2651 75% 2842 80% 2932 90% 3301 95% 3506 98% 3762 99% 3838 100% 4057 (longest request)

    Read the article

  • Very high CPU and low RAM usage - is it possible to place some of swap some of the CPU usage to the RAM (with CloudLinux LVE Manager installed)?

    - by Chriswede
    I had to install CloudLinux so that I could somewhat controle the CPU ussage and more importantly the Concurrent-Connections the Websites use. But as you can see the Server load is way to high and thats why some sites take up to 10 sec. to load! Server load 22.46 (8 CPUs) (!) Memory Used 36.32% (2,959,188 of 8,146,632) (ok) Swap Used 0.01% (132 of 2,104,504) (ok) Server: 8 x Intel(R) Xeon(R) CPU E31230 @ 3.20GHz Memory: 8143680k/9437184k available (2621k kernel code, 234872k reserved, 1403k data, 244k init) Linux Yesterday: Total of 214,514 Page-views (Awstat) Now my question: Can I shift some of the CPU usage to the RAM? Or what else could I do to make the sites run faster (websites are dynamic - so SQL heavy) Thanks top - 06:10:14 up 29 days, 20:37, 1 user, load average: 11.16, 13.19, 12.81 Tasks: 526 total, 1 running, 524 sleeping, 0 stopped, 1 zombie Cpu(s): 42.9%us, 21.4%sy, 0.0%ni, 33.7%id, 1.9%wa, 0.0%hi, 0.0%si, 0.0%st Mem: 8146632k total, 7427632k used, 719000k free, 131020k buffers Swap: 2104504k total, 132k used, 2104372k free, 4506644k cached PID USER PR NI VIRT RES SHR S %CPU %MEM TIME+ COMMAND 318421 mysql 15 0 1315m 754m 4964 S 474.9 9.5 95300:17 mysqld 6928 root 10 -5 0 0 0 S 2.0 0.0 90:42.85 kondemand/3 476047 headus 17 0 172m 19m 10m S 1.7 0.2 0:00.05 php 476055 headus 18 0 172m 18m 9.9m S 1.7 0.2 0:00.05 php 476056 headus 15 0 172m 19m 10m S 1.7 0.2 0:00.05 php 476061 headus 18 0 172m 19m 10m S 1.7 0.2 0:00.05 php 6930 root 10 -5 0 0 0 S 1.3 0.0 161:48.12 kondemand/5 6931 root 10 -5 0 0 0 S 1.3 0.0 193:11.74 kondemand/6 476049 headus 17 0 172m 19m 10m S 1.3 0.2 0:00.04 php 476050 headus 15 0 172m 18m 9.9m S 1.3 0.2 0:00.04 php 476057 headus 17 0 172m 18m 9.9m S 1.3 0.2 0:00.04 php 6926 root 10 -5 0 0 0 S 1.0 0.0 90:13.88 kondemand/1 6932 root 10 -5 0 0 0 S 1.0 0.0 247:47.50 kondemand/7 476064 worldof 18 0 172m 19m 10m S 1.0 0.2 0:00.03 php 6927 root 10 -5 0 0 0 S 0.7 0.0 93:52.80 kondemand/2 6929 root 10 -5 0 0 0 S 0.3 0.0 161:54.38 kondemand/4 8459 root 15 0 103m 5576 1268 S 0.3 0.1 54:45.39 lvest

    Read the article

  • Is 40+ Logons on Exchange 2003 per user normal?

    - by cbsch
    Hello! We've had a problem at work where users sometimes randomly can't connect to exchange. I've found out that it's because they reached the limit of 32 concurrent logons. I increased the maximum allowed connections by adding the key "Maximum Allowed Sessions Per User" in HKLM\SYSTEM\CurrentControlSet\Services\MSExchangeIS\ParametersSystem. But I'm not sure if this is a real good fix. Looking at the logons some users has as many as 15 logons with the exact same logon time. I know for sure that Outlook 2007 does this, as I was watching them while a user connected with Outlook after a restart on the Exchange service. Every user also has an iPhone connected to exchange, I don't know if these cause the same thing. Is this normal? Could there be a bug in the software? (The Outlook 2007 has nothing configured, except added the user, pure vanilla installs). The users are mobile, and when Outlook generates up to 15 connection every time it connects, and I've read (no sources, sorry) that Outlook doesn't time out connections before 2 hours. I might have to set this number real high to prevent it from being a problem.

    Read the article

  • Very high Magento/Apache memory usage even without visitors (are we fooled by our hosting company?)

    - by MrDobalina
    I am no server guy and we have issues with our speed so I come here asking for advise. We have a VPS with 2 cores and 2gb of RAM at a Magento specialized hosting company. Over the course of the last weeks our site speed has gotten worse, even though our store is new, has less than 1000 SKUs and not even 100 visitos a day. At magespeedtest.com we only get 1.87 trans/sec @ 2.11 secs each with a mere 5 concurrent users. Our magento log files are clean, we have no huge database tables or anything like that. When we take a look at our server real time stats, we see that the memory usage jumped up from about 34% to 71% and now 82% in just a few days in idle, with no visitors on the site. Our hosting company said that we do not need to worry about that as it`s maybe related to mysql which creates buffers (which are maybe not even actually being used) and what is important is CPU and swap - stats are ok here. They also said that the low benchmark scores are caused by bad extensions or template modifications on our side. We are not sure if we can trust that statement as we only have 4 plugins installed (all from aheadworks and amasty which are known to be one of the best magento extension developers). Our template modifications are purely html and css, no modifications to the php code. Our pagespeed is ranked with 93/100 in firebug and Magento is properly configured, so the problem really just gets obvious when there are a handful of users on the site at the same time. Can anyone confirm our hosting`s statement about memory usage and where can I start looking for a solution?

    Read the article

  • Webcast Q&A: Los Angeles Department of Building & Safety Lowers Customer Service Costs with Oracle WebCenter

    - by Kellsey Ruppel
    This week we had the fifth webcast in our WebCenter in Action webcast series, "Los Angeles Department of Building & Safety Lowers Customer Service Costs with Oracle WebCenter", where customers Giovani Dacumos and Minh Ong from the Los Angeles Department of Building & Safety (LADBS), and Sheetal Paranjpye and Rajiv Desai from Oracle Partner 3Di, shared how Oracle WebCenter is powering LADBS' externally facing website and providing a superior self-service experience for their customers. We asked the speakers to provide some dialogue for Q&A.   Giovani Dacumos, Director of Systems and Minh Ong, LADBS Q: Did you run into any issues when integrating all of the different applications together?A: Yes. We did have issues integrating a secure sign on between the portal and other legacy applications. We used portlets and iframes to overcome those.  This is a new technology for us and we are also learning as we go so there were a lot of challenges in developing and implementing our vision. Q: What has been the biggest benefit your end users have seen?A: The biggest benefit for our ends users is ease-of-use. We've given them a system that provided a new and improved source of information, as well as a very organized flow of transaction processing. It has made our online service very user friendly. Q: Was there any resistance internally when implementing the solution? If so, how did you overcome that?A: There was no internal resistance during the implementation, only challenges. As mentioned earlier, this is a new technology for us. We've come across issues that needed assistance from Oracle. Working with 3Di and Oracle has helped us tremendously to find solutions to our implementation issues. Q: Given the performance, what do you estimate to be the top end capacity of the system? A: With the current performance and architecture we have, we are able to support approx 300-400 concurrent users.  We would need more hardware to support additional user load. Q: What's the overview or summary of feedback from the users interacting with the site?A: LADBS has a wide spectrum of customers, from simple users like homeowners to large construction firms. Anything new that we offer could be a little bit challenging for some, but overall, the customers liked it. They saw a huge improvement on the usability. Q: Can you describe the impressions about the site before and after the project within LADBS?A: The old site was using old technology and it was hard for us to keep on building into it as we got more business requirements. It made our application seem a bit complicated.  It was confusing for our new customers to use and we've improved on this with the new site. It's now easier for them to complete their transactions and, at the same time, allowed us to provide more useful information. Sheetal Paranjpye and Rajiv Desai, 3Di Q: Did you run into any obstacles when implementing the solution?A: Yes we did run into some obstacles. One of the key show stoppers was the issue with portlet to portal communication. The GIS viewer (portlet) needed information to be passed  to and from Permit LA (Portal), but we were able to get everything configured and up and working quickly! Q: Was there a lot of custom work that needed to be done for this particular solution?A: We have done some customizations where workflows/ Task flows are involved.  Q: What do you think were the keys to success for rolling out WebCenter?A: Having a service oriented architecture and using portlets have been the key areas for rolling out Oracle WebCenter at LADBS. The Oracle WebCenter Content integration allows the flexibility to business users to maintain the content, which has really cut down on the reliance of IT, and employee productivity has increased as a result. If you missed the webcast, be sure to catch the replay to see a live demonstration of WebCenter in action! Los Angeles Department of Building & Safety Lowers Customer Service Costs with Oracle WebCenter from Oracle WebCenter

    Read the article

  • Oracle Support Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1)

    - by faye.todd(at)oracle.com
    Master Note for Troubleshooting Advanced Queuing and Oracle Streams Propagation Issues (Doc ID 233099.1) Copyright (c) 2010, Oracle Corporation. All Rights Reserved. In this Document  Purpose  Last Review Date  Instructions for the Reader  Troubleshooting Details     1. Scope and Application      2. Definitions and Classifications     3. How to Use This Guide     4. Basic AQ Propagation Troubleshooting     5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages     6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment     7. Performance Issues  References Applies to: Oracle Server - Enterprise Edition - Version: 8.1.7.0 to 11.2.0.2 - Release: 8.1.7 to 11.2Information in this document applies to any platform. Purpose This document presents a step-by-step methodology for troubleshooting and resolving problems with Advanced Queuing Propagation in both Streams and basic Advanced Queuing environments. It also serves as a master reference for other more specific notes on Oracle Streams Propagation and Advanced Queuing Propagation issues. Last Review Date December 20, 2010 Instructions for the Reader A Troubleshooting Guide is provided to assist in debugging a specific issue. When possible, diagnostic tools are included in the document to assist in troubleshooting. Troubleshooting Details 1. Scope and Application This note is intended for Database Administrators of Oracle databases where issues are being encountered with propagating messages between advanced queues, whether the queues are used for user-created messaging systems or for Oracle Streams. It contains troubleshooting steps and links to notes for further problem resolution.It can also be used a template to document a problem when it is necessary to engage Oracle Support Services. Knowing what is NOT happening can frequently speed up the resolution process by focusing solely on the pertinent problem area. This guide is divided into five parts: Section 2: Definitions and Classifications (discusses the different types and features of propagations possible - helpful for understanding the rest of the guide) Section 3: How to Use this Guide (to be used as a start part for determining the scope of the problem and what sections to consult) Section 4. Basic AQ propagation troubleshooting (applies to both AQ propagation of user enqueued and dequeued messages as well as Oracle Streams propagations) Section 5. Additional troubleshooting steps for AQ propagation of user enqueued and dequeued messages Section 6. Additional troubleshooting steps for Oracle Streams propagation Section 7. Performance issues 2. Definitions and Classifications Given the potential scope of issues that can be encountered with AQ propagation, the first recommended step is to do some basic diagnosis to determine the type of problem that is being encountered. 2.1. What Type of Propagation is Being Used? 2.1.1. Buffered Messaging For an advanced queue, messages can be maintained on disk (persistent messaging) or in memory (buffered messaging). To determine if a queue is buffered or not, reference the GV_$BUFFERED_QUEUES view. If the queue does not appear in this view, it is persistent. 2.1.2. Propagation mode - queue-to-dblink vs queue-to-queue As of 10.2, an AQ propagation can also be defined as queue-to-dblink, or queue-to-queue: queue-to-dblink: The propagation delivers messages or events from the source queue to all subscribing queues at the destination database identified by the dblink. A single propagation schedule is used to propagate messages to all subscribing queues. Hence any changes made to this schedule will affect message delivery to all the subscribing queues. This mode does not support multiple propagations from the same source queue to the same target database. queue-to-queue: Added in 10.2, this propagation mode delivers messages or events from the source queue to a specific destination queue identified on the database link. This allows the user to have fine-grained control on the propagation schedule for message delivery. This new propagation mode also supports transparent failover when propagating to a destination Oracle RAC system. With queue-to-queue propagation, you are no longer required to re-point a database link if the owner instance of the queue fails on Oracle RAC. This mode supports multiple propagations to the same target database if the target queues are different. The default is queue-to-dblink. To verify if queue-to-queue propagation is being used, in non-Streams environments query DBA_QUEUE_SCHEDULES.DESTINATION - if a remote queue is listed along with the remote database link, then queue-to-queue propagation is being used. For Streams environments, the DBA_PROPAGATION.QUEUE_TO_QUEUE column can be checked.See the following note for a method to switch between the two modes:Document 827473.1 How to alter propagation from queue-to-queue to queue-to-dblink 2.1.3. Combined Capture and Apply (CCA) for Streams In 11g Oracle Streams environments, an optimization called Combined Capture and Apply (CCA) is implemented by default when possible. Although a propagation is configured in this case, Streams does not use it; instead it passes information directly from capture to an apply receiver. To see if CCA is in use: COLUMN CAPTURE_NAME HEADING 'Capture Name' FORMAT A30COLUMN OPTIMIZATION HEADING 'CCA Mode?' FORMAT A10SELECT CAPTURE_NAME, DECODE(OPTIMIZATION,0, 'No','Yes') OPTIMIZATIONFROM V$STREAMS_CAPTURE; Also, see the following note:Document 463820.1 Streams Combined Capture and Apply in 11g 2.2. Queue Table Compatibility There are three types of queue table compatibility. In more recent databases, queue tables may be present in all three modes of compatibility: 8.0 - earliest version, deprecated in 10.2 onwards 8.1 - support added for RAC, asynchronous notification, secure queues, queue level access control, rule-based subscribers, separate storage of history information 10.0 - if the database is in 10.1-compatible mode, then the default value for queue table compatibility is 10.0 2.3. Single vs Multiple Consumer Queue Tables If more than one recipient can dequeue a message from a queue, then its queue table is multiple consumer. You can propagate messages from a multiple-consumer queue to a single-consumer queue. Propagation from a single-consumer queue to a multiple-consumer queue is not possible. 3. How to Use This Guide 3.1. Are Messages Being Propagated at All, or is the Propagation Just Slow? Run the following query on the source database for the propagation (assuming that it is running): select TOTAL_NUMBER from DBA_QUEUE_SCHEDULES where QNAME='<source_queue_name>'; If TOTAL_NUMBER is increasing, then propagation is most likely functioning, although it may be slow. For performance issues, see Section 7. 3.2. Propagation Between Persistent User-Created Queues See Sections 4 and 5 (and optionally Section 6 if performance is an issue). 3.3. Propagation Between Buffered User-Created Queues See Sections 4, 5, and 6 (and optionally Section 7 if performance is an issue). 3.4. Propagation between Oracle Streams Queues (without Combined Capture and Apply (CCA) Optimization) See Sections 4 and 6 (and optionally Section 7 if performance is an issue). 3.5. Propagation between Oracle Streams Queues (with Combined Capture and Apply (CCA) Optimization) Although an AQ propagation is not used directly in this case, some characteristics of the message transfer are inferred from the propagation parameters used. Some parts of Sections 4 and 6 still apply. 3.6. Messaging Gateway Propagations This note does not apply to Messaging Gateway propagations. 4. Basic AQ Propagation Troubleshooting 4.1. Double-check Your Code Make sure that you are consistent in your usage of the database link(s) names, queue names, etc. It may be useful to plot a diagram of which queues are connected via which database links to make sure that the logical structure is correct. 4.2. Verify that Job Queue Processes are Running 4.2.1. Versions 10.2 and Lower - DBA_JOBS Package For versions 10.2 and lower, a scheduled propagation is managed by DBMS_JOB package. The propagation is performed by job queue process background processes. Therefore we need to verify that there are sufficient processes available for the propagation process. We should have at least 4 job queue processes running and preferably more depending on the number of other jobs running in the database. It should be noted that for AQ specific work, AQ will only ever use half of the job queue processes available.An issue caused by an inadequate job queue processes parameter setting is described in the following note:Document 298015.1 Kwqjswproc:Excep After Loop: Assigning To Self 4.2.1.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; 4.2.1.2. Job Queue Processes in Memory The following command will show how many job queue processes are currentlyin use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.1.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (spids) of job queue processes involved in propagation via select p.SPID, p.PROGRAM from V$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOBand j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%'; and these SPIDs can be used to check at the operating system level that they exist.In 8i a job queue process will have a name similar to: ora_snp1_<instance_name>.In 9i onwards you will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.2.2. Version 11.1 and Above - Oracle Scheduler In version 11.1 and above, Oracle Scheduler is used to perform AQ and Streams propagations. Oracle Scheduler automatically tunes the number of slave processes for these jobs based on the load on the computer system, and the JOB_QUEUE_PROCESSES initialization parameter is only used to specify the maximum number of slave processes. Therefore, the JOB_QUEUE_PROCESSES initialization parameter does not need to be set (it defaults to a very high number), unless you want to limit the number of slaves that can be created. If JOB_QUEUE_PROCESSES = 0, no propagation jobs will run.See the following note for a discussion of Oracle Streams 11g and Oracle Scheduler:Document 1083608.1 11g Streams and Oracle Scheduler 4.2.2.1. Job Queue Processes in Initalization Parameter File The parameter JOB_QUEUE_PROCESSES in the init.ora/spfile should be > 0, and preferably be left at its default value. The value can be changed dynamically via connect / as sysdbaalter system set JOB_QUEUE_PROCESSES=10; To set the JOB_QUEUE_PROCESSES parameter to its default value, run: connect / as sysdbaalter system reset JOB_QUEUE_PROCESSES; and then bounce the instance. 4.2.2.2. Job Queue Processes in Memory The following command will show how many job queue processes are currently in use by this instance (this may be different than what is in the init.ora/spfile): connect / as sysdbashow parameter job; 4.2.2.3. OS PIDs Corresponding to Job Queue Processes Identify the operating system process ids (SPIDs) of job queue processes involved in propagation via col PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_namefrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDRand jr.JOB_name=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%'; and these SPIDs can be used to check at the operating system level that they exist.You will see a coordinator process: ora_cjq0_ and multiple slave processes: ora_jnnn_<instance_name>, where nnn is an integer between 1 and 999. 4.3. Check the Alert Log and Any Associated Trace Files The first place to check for propagation failures is the alert logs at all sites (local and if relevant all remote sites). When a job queue process attempts to execute a schedule and fails it will always write an error stack to the alert log. This error stack will also be written in a job queue process trace file, which will be written to the BACKGROUND_DUMP_DEST location for 10.2 and below, and in the DIAGNOSTIC_DEST location for 11g. The fact that errors are written to the alert log demonstrates that the schedule is executing. This means that the problem could be with the set up of the schedule. In this example the ORA-02068 demonstrates that the failure was at the remote site. Further investigation revealed that the remote database was not open, hence the ORA-03114 error. Starting the database resolved the problem. Thu Feb 14 10:40:05 2002 Propagation Schedule for (AQADM.MULTIPLEQ, SHANE816.WORLD) encountered following error:ORA-04052: error occurred when looking up Remote object [email protected]: error occurred at recursive SQL level 4ORA-02068: following severe error from SHANE816ORA-03114: not connected to ORACLEORA-06512: at "SYS.DBMS_AQADM_SYS", line 4770ORA-06512: at "SYS.DBMS_AQADM", line 548ORA-06512: at line 1 Other potential errors that may be written to the alert log can be found in the following notes:Document 827184.1 AQ Propagation with CLOB data types Fails with ORA-22990 (11.1)Document 846297.1 AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn] (10.2, 11.1)Document 731292.1 ORA-25215 Reported on Local Propagation When Using Transformation with ANYDATA queue tables (10.2, 11.1, 11.2)Document 365093.1 ORA-07445 [kwqppay2aqe()+7360] Reported on Propagation of a Transformed Message (10.1, 10.2)Document 219416.1 Advanced Queuing Propagation Fails with ORA-22922 (9.0)Document 1203544.1 AQ Propagation Aborted with ORA-600 [ociksin: invalid status] on SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE After Upgrade (11.1, 11.2)Document 1087324.1 ORA-01405 ORA-01422 reported by Advanced Queuing Propagation schedules after RAC reconfiguration (10.2)Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370 incorrect usage of method" (9.2, 10.2, 11.1, 11.2)Document 332792.1 ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up Statspack (8.1, 9.0, 9.2, 10.1)Document 353325.1 ORA-24056: Internal inconsistency for QUEUE <queue_name> and destination <dblink> (8.1, 9.0, 9.2, 10.1, 10.2, 11.1, 11.2)Document 787367.1 ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2 (10.1, 10.2)Document 566622.1 ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1 (9.2, 10.1)Document 731539.1 ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTP (9.0, 9.2, 10.1, 10.2, 11.1)Document 253131.1 Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555) (9.2)Document 118884.1 How to unschedule a propagation schedule stuck in pending stateDocument 222992.1 DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 1204080.1 AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.Document 1233675.1 AQ Propagation stops after upgrade to 11.2.0.1 ORA-30757 4.3.1. Errors Related to Incorrect Network Configuration The most common propagation errors result from an incorrect network configuration. The list below contains common errors caused by tnsnames.ora file or database links being configured incorrectly: - ORA-12154: TNS:could not resolve service name- ORA-12505: TNS:listener does not currently know of SID given in connect descriptor- ORA-12514: TNS:listener could not resolve SERVICE_NAME - ORA-12541: TNS-12541 TNS:no listener 4.4. Check the Database Links Exist and are Functioning Correctly For schedules to remote databases confirm the database link exists via. SQL> col DBLINK for a45SQL> select QNAME, NVL(REGEXP_SUBSTR(DESTINATION, '[^@]+', 1, 2), DESTINATION) dblink2 from DBA_QUEUE_SCHEDULES3 where MESSAGE_DELIVERY_MODE = 'PERSISTENT';QNAME DBLINK------------------------------ ---------------------------------------------MY_QUEUE ORCL102B.WORLD Connect as the owner of the link and select across it to verify it works and connects to the database we expect. i.e. select * from ALL_QUEUES@ ORCL102B.WORLD; You need to ensure that the userid that scheduled the propagation (using DBMS_AQADM.SCHEDULE_PROPAGATION or DBMS_PROPAGATION_ADM.CREATE_PROPAGATION if using Streams) has access to the database link for the destination. 4.5. Has Propagation Been Correctly Scheduled? Check that the propagation schedule has been created and that a job queue process has been assigned. Look for the entry in DBA_QUEUE_SCHEDULES and SYS.AQ$_SCHEDULES for your schedule. For 10g and below, check that it has a JOBNO entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_JOBS with that JOBNO. For 11g and above, check that the schedule has a JOB_NAME entry in SYS.AQ$_SCHEDULES, and that there is an entry in DBA_SCHEDULER_JOBS with that JOB_NAME. Check the destination is as intended and spelled correctly. SQL> select SCHEMA, QNAME, DESTINATION, SCHEDULE_DISABLED, PROCESS_NAME from DBA_QUEUE_SCHEDULES;SCHEMA QNAME DESTINATION S PROCESS------- ---------- ------------------ - -----------AQADM MULTIPLEQ AQ$_LOCAL N J000 AQ$_LOCAL in the destination column shows that the queue to which we are propagating to is in the same database as the source queue. If the propagation was to a remote (different) database, a database link will be in the DESTINATION column. The entry in the SCHEDULE_DISABLED column, N, means that the schedule is NOT disabled. If Y (yes) appears in this column, propagation is disabled and the schedule will not be executed. If not using Oracle Streams, propagation should resume once you have enabled the schedule by invoking DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE (for 10.2 Oracle Streams and above, the DBMS_PROPAGATION_ADM.START_PROPAGATION procedure should be used). The PROCESS_NAME is the name of the job queue process currently allocated to execute the schedule. This process is allocated dynamically at execution time. If the PROCESS_NAME column is null (empty) the schedule is not currently executing. You may need to execute this statement a number of times to verify if a process is being allocated. If a process is at some time allocated to the schedule, it is attempting to execute. SQL> select SCHEMA, QNAME, LAST_RUN_DATE, NEXT_RUN_DATE from DBA_QUEUE_SCHEDULES;SCHEMA QNAME LAST_RUN_DATE NEXT_RUN_DATE------ ----- ----------------------- ----------------------- AQADM MULTIPLEQ 13-FEB-2002 13:18:57 13-FEB-2002 13:20:30 In 11g, these dates are expressed in TIMESTAMP WITH TIME ZONE datatypes. If the NEXT_RUN_DATE and NEXT_RUN_TIME columns are null when this statement is executed, the scheduled propagation is currently in progress. If they never change it would suggest that the schedule itself is never executing. If the next scheduled execution is too far away, change the NEXT_TIME parameter of the schedule so that schedules are executed more frequently (assuming that the window is not set to be infinite). Parameters of a schedule can be changed using the DBMS_AQADM.ALTER_PROPAGATION_SCHEDULE call. In 10g and below, scheduling propagation posts a job in the DBA_JOBS view. The columns are more or less the same as DBA_QUEUE_SCHEDULES so you just need to recognize the job and verify that it exists. SQL> select JOB, WHAT from DBA_JOBS where WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';JOB WHAT---- ----------------- 720 next_date := sys.dbms_aqadm.aq$_propaq(job); For 11g, scheduling propagation posts a job in DBA_SCHEDULER_JOBS instead: SQL> select JOB_NAME from DBA_SCHEDULER_JOBS where JOB_NAME like 'AQ_JOB$_%';JOB_NAME------------------------------AQ_JOB$_41 If no job exists, check DBA_QUEUE_SCHEDULES to make sure that the schedule has not been disabled. For 10g and below, the job number is dynamic for AQ propagation schedules. The procedure that is executed to expedite a propagation schedule runs, removes itself from DBA_JOBS, and then reposts a new job for the next scheduled propagation. The job number should therefore always increment unless the schedule has been set up to run indefinitely. 4.6. Is the Schedule Executing but Failing to Complete? Run the following query: SQL> select FAILURES, LAST_ERROR_MSG from DBA_QUEUE_SCHEDULES;FAILURES LAST_ERROR_MSG------------ -----------------------1 ORA-25207: enqueue failed, queue AQADM.INQ is disabled from enqueueingORA-02063: preceding line from SHANE816 The failures column shows how many times we have attempted to execute the schedule and failed. Oracle will attempt to execute the schedule 16 times after which it will be removed from the DBA_JOBS or DBA_SCHEDULER_JOBS view and the schedule will become disabled. The column DBA_QUEUE_SCHEDULES.SCHEDULE_DISABLED will show 'Y'. For 11g and above, the DBA_SCHEDULER_JOBS.STATE column will show 'BROKEN' for the job corresponding to DBA_QUEUE_SCHEDULES.JOB_NAME. Prior to 10g the back off algorithm for failures was exponential, whereas from 10g onwards it is linear. The propagation will become disabled on the 17th attempt. Only the last execution failure will be reflected in the LAST_ERROR_MSG column. That is, if the schedule fails 5 times for 5 different reasons, only the last set of errors will be recorded in DBA_QUEUE_SCHEDULES. Any errors need to be resolved to allow propagation to continue. If propagation has also become disabled due to 17 failures, first resolve the reason for the error and then re-enable the schedule using the DBMS_AQADM.ENABLE_PROPAGATION_SCHEDULE procedure, or DBMS_PROPAGATION_ADM.START_PROPAGATION if using 10.2 or above Oracle Streams. As soon as the schedule executes successfully the error message entries will be deleted. Oracle does not keep a history of past failures. However, when using Oracle Streams, the errors will be retained in the DBA_PROPAGATION view even after the schedule resumes successfully. See the following note for instructions on how to clear out the errors from the DBA_PROPAGATION view:Document 808136.1 How to clear the old errors from DBA_PROPAGATION view?If a schedule is active and no errors are being reported then the source queue may not have any messages to be propagated. 4.7. Do the Propagation Notification Queue Table and Queue Exist? Check to see that the propagation notification queue table and queue exist and are enabled for enqueue and dequeue. Propagation makes use of the propagation notification queue for handling propagation run-time events, and the messages in this queue are stored in a SYS-owned queue table. This queue should never be stopped or dropped and the corresponding queue table never be dropped. 10g and belowThe propagation notification queue table is of the format SYS.AQ$_PROP_TABLE_n, where 'n' is the RAC instance number, i.e. '1' for a non-RAC environment. This queue and queue table are created implicitly when propagation is first scheduled. If propagation has been scheduled and these objects do not exist, try unscheduling and rescheduling propagation. If they still do not exist contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ$_PROP_TABLE_1SQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ$_PROP_NOTIFY_1 YES YESAQ$_AQ$_PROP_TABLE_1_E NO NO If the AQ$_PROP_NOTIFY_1 queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_1_E should not be enabled for enqueue or dequeue.11g and aboveThe propagation notification queue table is of the format SYS.AQ_PROP_TABLE, and is created when the database is created. If they do not exist, contact Oracle Support. SQL> select QUEUE_TABLE from DBA_QUEUE_TABLES2 where QUEUE_TABLE like '%PROP_TABLE%' and OWNER = 'SYS';QUEUE_TABLE------------------------------AQ_PROP_TABLESQL> select NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED2 from DBA_QUEUES where owner='SYS'3 and QUEUE_TABLE like '%PROP_TABLE%';NAME ENQUEUE DEQUEUE------------------------------ ------- -------AQ_PROP_NOTIFY YES YESAQ$_AQ_PROP_TABLE_E NO NO If the AQ_PROP_NOTIFY queue is not enabled for enqueue or dequeue, it should be so enabled using DBMS_AQADM.START_QUEUE. However, the exception queue AQ$_AQ$_PROP_TABLE_E should not be enabled for enqueue or dequeue. 4.8. Does the Remote Queue Exist and is it Enabled for Enqueueing? Check that the remote queue the propagation is transferring messages to exists and is enabled for enqueue: SQL> select DESTINATION from USER_QUEUE_SCHEDULES where QNAME = 'OUTQ';DESTINATION-----------------------------------------------------------------------------"AQADM"."INQ"@M2V102.ESSQL> select OWNER, NAME, ENQUEUE_ENABLED, DEQUEUE_ENABLED from [email protected];OWNER NAME ENQUEUE DEQUEUE-------- ------ ----------- -----------AQADM INQ YES YES 4.9. Do the Target and Source Database Charactersets Differ? If a message fails to propagate, check the database charactersets of the source and target databases. Investigate whether the same message can propagate between the databases with the same characterset or it is only a particular combination of charactersets which causes a problem. 4.10. Check the Queue Table Type Agreement Propagation is not possible between queue tables which have types that differ in some respect. One way to determine if this is the case is to run the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure for the two queues that the propagation operates on. If the types do not agree, DBMS_AQADM.VERIFY_QUEUE_TYPES will return '0'.For AQ propagation between databases which have different NLS_LENGTH_SEMANTICS settings, propagation will not work, unless the queues are Oracle Streams ANYDATA queues.See the following notes for issues caused by lack of type agreement:Document 1079577.1 Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"Document 282987.1 Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueDocument 353754.1 Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT 4.11. Enable Propagation Tracing 4.11.1. System Level This is set it in the init.ora/spfile as follows: event="24040 trace name context forever, level 10" and restart the instanceThis event cannot be set dynamically with an alter system command until version 10.2: SQL> alter system set events '24040 trace name context forever, level 10'; To unset the event: SQL> alter system set events '24040 trace name context off'; Debugging information will be logged to job queue trace file(s) (jnnn) as propagation takes place. You can check the trace file for errors, and for statements indicating that messages have been sent. For the most part the trace information is understandable. This trace should also be uploaded to Oracle Support if a service request is created. 4.11.2. Attaching to a Specific Process We can also attach to an existing job queue processes that is running a propagation schedule and trace it individually using the oradebug utility, as follows:10.2 and below connect / as sysdbaselect p.SPID, p.PROGRAM from v$PROCESS p, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j where s.SID=jr.SID and s.PADDR=p.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 11g connect / as sysdbacol PROGRAM for a30select p.SPID, p.PROGRAM, j.JOB_NAMEfrom v$PROCESS p, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j where s.SID=jr.SESSION_ID and s.PADDR=p.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%';-- For the process id (SPID) attach to it via oradebug and generate the following traceoradebug setospid <SPID>oradebug unlimitoradebug Event 10046 trace name context forever, level 12oradebug Event 24040 trace name context forever, level 10-- Trace the process for 5 minutesoradebug Event 10046 trace name context offoradebug Event 24040 trace name context off-- The following command returns the pathname/filename to the file being written tooradebug tracefile_name 4.11.3. Further Tracing The previous tracing steps only trace the job queue process executing the propagation on the source. At times it is useful to trace the propagation receiver process (the session which is enqueueing the messages into the target queue) on the target database which is associated with the job queue process on the source database.These following queries provide ways of identifying the processes involved in propagation so that you can attach to them via oradebug to generate trace information.In order to identify the propagation receiver process you need to execute the query as a user with privileges to access the v$ views in both the local and remote databases so the database link must connect as a user with those privileges in the remote database. The <DBLINK> in the queries should be replaced by the appropriate database link.The queries have two forms due to the differences between operating systems. The value returned by 'Rem Process' is the operating system identifier of the propagation receiver on the remote database. Once identified, this process can be attached to and traced on the remote database using the commands given in Section 4.11.2.10.2 and below - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from v$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 10.2 and below - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_JOBS_RUNNING jr, V$SESSION s, DBA_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SID and s.PADDR=pl.ADDR and jr.JOB=j.JOB and j.WHAT like '%sys.dbms_aqadm.aq$_propaq(job)%' and pl.SPID=sr.PROCESS; 11g - Windows select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=substr(sr.PROCESS, instr(sr.PROCESS,':')+1); 11g - Unix select pl.SPID "JobQ Process", pl.PROGRAM, sr.PROCESS "Rem Process" from V$PROCESS pl, DBA_SCHEDULER_RUNNING_JOBS jr, V$SESSION s, DBA_SCHEDULER_JOBS j, V$SESSION@<DBLINK> sr where s.SID=jr.SESSION_ID and s.PADDR=pl.ADDR and jr.JOB_NAME=j.JOB_NAME and j.JOB_NAME like '%AQ_JOB$_%%' and pl.SPID=sr.PROCESS;   5. Additional Troubleshooting Steps for AQ Propagation of User-Enqueued and Dequeued Messages 5.1. Check the Privileges of All Users Involved Ensure that the owner of the database link has the necessary privileges on the aq packages. SQL> select TABLE_NAME, PRIVILEGE from USER_TAB_PRIVS;TABLE_NAME PRIVILEGE------------------------------ ----------------------------------------DBMS_LOCK EXECUTEDBMS_AQ EXECUTEDBMS_AQADM EXECUTEDBMS_AQ_BQVIEW EXECUTEQT52814_BUFFER SELECT Note that when queue table is created, a view called QT<nnn>_BUFFER is created in the SYS schema, and the queue table owner is given SELECT privileges on it. The <nnn> corresponds to the object_id of the associated queue table. SQL> select * from USER_ROLE_PRIVS;USERNAME GRANTED_ROLE ADM DEF OS_------------------------------ ------------------------------ ---- ---- ---AQ_USER1 AQ_ADMINISTRATOR_ROLE NO YES NOAQ_USER1 CONNECT NO YES NOAQ_USER1 RESOURCE NO YES NO It is good practice to configure central AQ administrative user. All admin and processing jobs are created, executed and administered as this user. This configuration is not mandatory however, and the database link can be owned by any existing queue user. If this latter configuration is used, ensure that the connecting user has the necessary privileges on the AQ packages and objects involved. Privileges for an AQ Administrative user Execute on DBMS_AQADM Execute on DBMS_AQ Granted the AQ_ADMINISTRATOR_ROLE Privileges for an AQ user Execute on DBMS_AQ Execute on the message payload Enqueue privileges on the remote queue Dequeue privileges on the originating queue Privileges need to be confirmed on both sites when propagation is scheduled to remote destinations. Verify that the user ID used to login to the destination through the database link has been granted privileges to use AQ. 5.2. Verify Queue Payload Types AQ will not propagate messages from one queue to another if the payload types of the two queues are not verified to be equivalent. An AQ administrator can verify if the source and destination's payload types match by executing the DBMS_AQADM.VERIFY_QUEUE_TYPES procedure. The results of the type checking will be stored in the SYS.AQ$_MESSAGE_TYPES table. This table can be accessed using the object identifier OID of the source queue and the address database link of the destination queue, i.e. [schema.]queue_name[@destination]. Prior to Oracle 9i the payload (message type) had to be the same for all the queue tables involved in propagation. From Oracle9i onwards a transformation can be used so that payloads can be converted from one type to another. The following procedural call made on the source database can verify whether we can propagate between the source and the destination queue tables. connect aq_user1/[email protected] serverout onDECLARErc_value number;BEGINDBMS_AQADM.VERIFY_QUEUE_TYPES(src_queue_name => 'AQ_USER1.Q_1', dest_queue_name => 'AQ_USER2.Q_2',destination => 'dbl_aq_user2.es',rc => rc_value);dbms_output.put_line('rc_value code is '||rc_value);END;/ If propagation is possible then the return code value will be 1. If it is 0 then propagation is not possible and further investigation of the types and transformations used by and in conjunction with the queue tables is required. With regard to comparison of the types the following sql can be used to extract the DDL for a specific type with' %' changed appropriately on the source and target. This can then be compared for the source and target. SET LONG 20000 set pagesize 50 EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'STORAGE',false); SELECT DBMS_METADATA.GET_DDL('TYPE',t.type_name) from user_types t WHERE t.type_name like '%'; EXECUTE DBMS_METADATA.SET_TRANSFORM_PARAM(DBMS_METADATA.SESSION_TRANSFORM, 'DEFAULT'); 5.3. Check Message State and Destination The first step in this process is to identify the queue table associated with the problem source queue. Although you schedule propagation for a specific queue, most of the meta-data associated with that queue is stored in the underlying queue table. The following statement finds the queue table for a given queue (note that this is a multiple-consumer queue table). SQL> select QUEUE_TABLE from DBA_QUEUES where NAME = 'MULTIPLEQ';QUEUE_TABLE --------------------MULTIPLEQTABLE For a small amount of messages in a multiple-consumer queue table, the following query can be run: SQL> select MSG_STATE, CONSUMER_NAME, ADDRESS from AQ$MULTIPLEQTABLE where QUEUE = 'MULTIPLEQ';MSG_STATE CONSUMER_NAME ADDRESS-------------- ----------------------- -------------READY AQUSER2 [email protected] AQUSER1READY AQUSER3 AQADM.INQ In this example we see 2 messages ready to be propagated to remote queues and 1 that is not. If the address column is blank, the message is not scheduled for propagation and can only be dequeued from the queue upon which it was enqueued. The MSG_STATE column values are discussed in Document 102330.1 Advanced Queueing MSG_STATE Values and their Interpretation. If the address column has a value, the message has been enqueued for propagation to another queue. The first row in the example includes a database link (@M2V102.ES). This demonstrates that the message should be propagated to a queue at a remote database. The third row does not include a database link so will be propagated to a queue that resides on the same database as the source queue. The consumer name is the intended recipient at the target queue. Note that we are not querying the base queue table directly; rather, we are querying a view that is available on top of every queue table, AQ$<queue_table_name>.A more realistic query in an environment where the queue table contains thousands of messages is8.0.3-compatible multiple-consumer queue table and all compatibility single-consumer queue tables select count(*), MSG_STATE, QUEUE from AQ$<queue_table_name>  group by MSG_STATE, QUEUE; 8.1.3 and 10.0-compatible queue tables select count(*), MSG_STATE, QUEUE, CONSUMER_NAME from AQ$<queue_table_name>group by MSG_STATE, QUEUE, CONSUMER_NAME; For multiple-consumer queue tables, if you did not see the expected CONSUMER_NAME , check the syntax of the enqueue code and verify the recipients are declared correctly. If a recipients list is not used on enqueue, check the subscriber list in the AQ$_<queue_table_name>_S view (note that a single-consumer queue table does not have a subscriber view. This view records all members of the default subscription list which were added using the DBMS_AQADM.ADD_SUBSCRIBER procedure and also those enqueued using a recipient list. SQL> select QUEUE, NAME, ADDRESS from AQ$MULTIPLEQTABLE_S;QUEUE NAME ADDRESS---------- ----------- -------------MULTIPLEQ AQUSER2 [email protected] AQUSER1 In this example we have 2 subscribers registered with the queue. We have a local subscriber AQUSER1, and a remote subscriber AQUSER2, on the queue INQ, owned by AQADM, at M2V102.ES. Unless overridden with a recipient list during enqueue every message enqueued to this queue will be propagated to INQ at M2V102.ES.For 8.1 style and above multiple consumer queue tables, you can also check the following information at the target: select CONSUMER_NAME, DEQ_TXN_ID, DEQ_TIME, DEQ_USER_ID, PROPAGATED_MSGID from AQ$<queue_table_name> where QUEUE = '<QUEUE_NAME>'; For 8.0 style queues, if the queue table supports multiple consumers you can obtain the same information from the history column of the queue table: select h.CONSUMER, h.TRANSACTION_ID, h.DEQ_TIME, h.DEQ_USER, h.PROPAGATED_MSGIDfrom AQ$<queue_table_name> t, table(t.history) h where t.Q_NAME = '<QUEUE_NAME>'; A non-NULL TRANSACTION_ID indicates that the message was successfully propagated. Further, the DEQ_TIME indicates the time of propagation, the DEQ_USER indicates the userid used for propagation, and the PROPAGATED_MSGID indicates the message ID of the message that was enqueued at the destination. 6. Additional Troubleshooting Steps for Propagation in an Oracle Streams Environment 6.1. Is the Propagation Enabled? For a propagation job to propagate messages, the propagation must be enabled. For Streams, a special view called DBA_PROPAGATION exists to convey information about Streams propagations. If messages are not being propagated by a propagation as expected, then the propagation might not be enabled. To query for this: SELECT p.PROPAGATION_NAME, DECODE(s.SCHEDULE_DISABLED, 'Y', 'Disabled','N', 'Enabled') SCHEDULE_DISABLED, s.PROCESS_NAME, s.FAILURES, s.LAST_ERROR_MSGFROM DBA_QUEUE_SCHEDULES s, DBA_PROPAGATION pWHERE p.DESTINATION_DBLINK = NVL(REGEXP_SUBSTR(s.DESTINATION, '[^@]+', 1, 2), s.DESTINATION) AND s.SCHEMA = p.SOURCE_QUEUE_OWNER AND s.QNAME = p.SOURCE_QUEUE_NAME AND MESSAGE_DELIVERY_MODE = 'PERSISTENT' order by PROPAGATION_NAME; At times, the propagation job may become "broken" or fail to start after an error has been encountered or after a database restart. If an error is indicated by the above query, an attempt to disable the propagation and then re-enable it can be made. In the examples below, for the propagation named STRMADMIN_PROPAGATE where the queue name is STREAMS_QUEUE owned by STRMADMIN and the destination database link is ORCL2.WORLD, the commands would be:10.2 and above exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE'); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); If the above does not fix the problem, stop the propagation specifying the force parameter (2nd parameter on stop_propagation) as TRUE: exec dbms_propagation_adm.stop_propagation('STRMADMIN_PROPAGATE',true); exec dbms_propagation_adm.start_propagation('STRMADMIN_PROPAGATE'); The statistics for the propagation as well as any old error messages are cleared when the force parameter is set to TRUE. Therefore if the propagation schedule is stopped with FORCE set to TRUE, and upon restart there is still an error message in DBA_PROPAGATION, then the error message is current.9.2 or 10.1 exec dbms_aqadm.disable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms.aqadm.enable_propagation_schedule('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); If the above does not fix the problem, perform an unschedule of propagation and then schedule_propagation: exec dbms_aqadm.unschedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); exec dbms_aqadm.schedule_propagation('STRMADMIN.STREAMS_QUEUE','ORCL2.WORLD'); Typically if the error from the first query in Section 6.1 recurs after restarting the propagation as shown above, further troubleshooting of the error is needed. 6.2. Check Propagation Rule Sets and Transformations Inspect the configuration of the rules in the rule set that is associated with the propagation process to make sure that they evaluate to TRUE as expected. If not, then the object or schema will not be propagated. Remember that when a negative rule evaluates to TRUE, the specified object or schema will not be propagated. Finally inspect any rule-based transformations that are implemented with propagation to make sure they are changing the data in the intended way.The following query shows what rule sets are assigned to a propagation: select PROPAGATION_NAME, RULE_SET_OWNER||'.'||RULE_SET_NAME "Positive Rule Set",NEGATIVE_RULE_SET_OWNER||'.'||NEGATIVE_RULE_SET_NAME "Negative Rule Set"from DBA_PROPAGATION; The next two queries list the propagation rules and their conditions. The first is for the positive rule set, the second is for the negative rule set: set long 4000select rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES rwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER and RULE_SET_NAME in(select RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME;   set long 4000select c.PROPAGATION_NAME, rsr.RULE_SET_OWNER||'.'||rsr.RULE_SET_NAME RULE_SET ,rsr.RULE_OWNER||'.'||rsr.RULE_NAME RULE_NAME,r.RULE_CONDITION CONDITION fromDBA_RULE_SET_RULES rsr, DBA_RULES r ,DBA_PROPAGATION cwhere rsr.RULE_NAME = r.RULE_NAME and rsr.RULE_OWNER = r.RULE_OWNER andrsr.RULE_SET_OWNER=c.NEGATIVE_RULE_SET_OWNER and rsr.RULE_SET_NAME=c.NEGATIVE_RULE_SET_NAMEand rsr.RULE_SET_NAME in(select NEGATIVE_RULE_SET_NAME from DBA_PROPAGATION) order by rsr.RULE_SET_OWNER, rsr.RULE_SET_NAME; 6.3. Determining the Total Number of Messages and Bytes Propagated As in Section 3.1, determining if messages are flowing can be instructive to see whether the propagation is entirely hung or just slow. If the propagation is not in flow control (see Section 6.5.2), but the statistics are incrementing slowly, there may be a performance issue. For Streams implementations two views are available that can assist with this that can show the number of messages sent by a propagation, as well as the number of acknowledgements being returned from the target site: the V$PROPAGATION_SENDER view at the Source site and the V$PROPAGATION_RECEIVER view at the destination site. It is helpful to query both to determine if messages are being delivered to the target. Look for the statistics to increase.Source: select QUEUE_SCHEMA, QUEUE_NAME, DBLINK,HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS, TOTAL_BYTESfrom V$PROPAGATION_SENDER; Target: select SRC_QUEUE_SCHEMA, SRC_QUEUE_NAME, SRC_DBNAME, DST_QUEUE_SCHEMA, DST_QUEUE_NAME, HIGH_WATER_MARK, ACKNOWLEDGEMENT, TOTAL_MSGS from V$PROPAGATION_RECEIVER; 6.4. Check Buffered Subscribers The V$BUFFERED_SUBSCRIBERS view displays information about subscribers for all buffered queues in the instance. This view can be queried to make sure that the site that the propagation is propagating to is listed as a subscriber address for the site being propagated from: select QUEUE_SCHEMA, QUEUE_NAME, SUBSCRIBER_ADDRESS from V$BUFFERED_SUBSCRIBERS; The SUBSCRIBER_ADDRESS column will not be populated when the propagation is local (between queues on the same database). 6.5. Common Streams Propagation Errors 6.5.1. ORA-02082: A loopback database link must have a connection qualifier. This error can occur if you use the Streams Setup Wizard in Oracle Enterprise Manager without first configuring the GLOBAL_NAME for your database. 6.5.2. ORA-25307: Enqueue rate too high. Enable flow control DBA_QUEUE_SCHEDULES will display this informational message for propagation when the automatic flow control (10g feature of Streams) has been invoked.Similar to Streams capture processes, a Streams propagation process can also go into a state of 'flow control. This is an informative message that indicates flow control has been automatically enabled to reduce the rate at which messages are being enqueued into at target queue.This typically occurs when the target site is unable to keep up with the rate of messages flowing from the source site. Other than checking that the apply process is running normally on the target site, usually no action is required by the DBA. Propagation and the capture process will be resumed automatically when the target site is able to accept more messages.The following document contains more information:Document 302109.1 Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlSee the following document for one potential cause of this situation:Document 1097115.1 Oracle Streams Apply Reader is in 'Paused' State 6.5.3. ORA-25315 unsupported configuration for propagation of buffered messages This error typically occurs when the target database is RAC and usually indicates that an attempt was made to propagate buffered messages with the database link pointing to an instance in the destination database which is not the owner instance of the destination queue. To resolve the problem, use queue-to-queue propagation for buffered messages. 6.5.4. ORA-600 [KWQBMCRCPTS101] after dropping / recreating propagation For cause/fixes refer to:Document 421237.1 ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams Propagation 6.5.5. Stopping or Dropping a Streams Propagation Hangs See the following note:Document 1159787.1 Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It Hang 6.6. Streams Propagation-Related Notes for Common Issues Document 437838.1 Streams Specific PatchesDocument 749181.1 How to Recover Streams After Dropping PropagationDocument 368912.1 Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentDocument 564649.1 ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveDocument 553017.1 Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201Document 944846.1 Streams Propagation Fails Ora-7445 [kohrsmc]Document 745601.1 ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'Document 333068.1 ORA-23603: Streams Enqueue Aborted Eue To Low SGADocument 363496.1 Ora-25315 Propagating on RAC StreamsDocument 368237.1 Unable to Unschedule Propagation. Streams Queue is InvalidDocument 436332.1 dbms_propagation_adm.stop_propagation hangsDocument 727389.1 Propagation Fails With ORA-12528Document 730911.1 ORA-4063 Is Reported After Dropping Negative Prop.RulesetDocument 460471.1 Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsDocument 1165583.1 ORA-600 [kwqpuspse0-ack] In Streams EnvironmentDocument 1059029.1 Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationDocument 556309.1 Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedDocument 839568.1 Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''Document 311021.1 Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredDocument 359971.1 STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068Document 1101616.1 DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747 7. Performance Issues A propagation may seem to be slow if the queries from Sections 3.1 and 6.3 show that the message statistics are not changing quickly. In Oracle Streams, this more usually is due to a slow apply process at the target rather than a slow propagation. Propagation could be inferred to be slow if the message statistics are changing, and the state of a capture process according to V$STREAMS_CAPTURE.STATE is PAUSED FOR FLOW CONTROL, but an ORA-25307 'Enqueue rate too high. Enable flow control' warning is NOT observed in DBA_QUEUE_SCHEDULES per Section 6.5.2. If this is the case, see the following notes / white papers for suggestions to increase performance:Document 335516.1 Master Note for Streams Performance RecommendationsDocument 730036.1 Overview for Troubleshooting Streams Performance IssuesDocument 780733.1 Streams Propagation Tuning with Network ParametersWhite Paper: http://www.oracle.com/technetwork/database/features/availability/maa-wp-10gr2-streams-performance-130059.pdfWhite Paper: Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2, http://www.oracle.com/technetwork/database/features/availability/maa-10gr2-streams-configuration-132039.pdf, See APPENDIX A: USING STREAMS CONFIGURATIONS OVER A NETWORKFor basic AQ propagation, the network tuning in the aforementioned Appendix A of the white paper 'Oracle Streams Configuration Best Practices: Oracle Database 10g Release 10.2' is applicable. References NOTE:102330.1 - Advanced Queueing MSG_STATE Values and their InterpretationNOTE:102771.1 - Advanced Queueing Propagation using PL/SQLNOTE:1059029.1 - Combined Capture and Apply (CCA) : Capture aborts : ORA-1422 after schedule_propagationNOTE:1079577.1 - Advanced Queuing Propagation Fails With "ORA-22370: incorrect usage of method"NOTE:1083608.1 - 11g Streams and Oracle SchedulerNOTE:1087324.1 - ORA-01405 ORA-01422 reported by Adavanced Queueing Propagation schedules after RAC reconfigurationNOTE:1097115.1 - Oracle Streams Apply Reader is in 'Paused' StateNOTE:1101616.1 - DBMS_PROPAGATION_ADM.DROP_PROPAGATION FAILS WITH ORA-1747NOTE:1159787.1 - Troubleshooting Streams Propagation When It is Not Functioning and Attempts to Stop It HangNOTE:1165583.1 - ORA-600 [kwqpuspse0-ack] In Streams EnvironmentNOTE:118884.1 - How to unschedule a propagation schedule stuck in pending stateNOTE:1203544.1 - AQ PROPAGATION ABORTED WITH ORA-600[OCIKSIN: INVALID STATUS] ON SYS.DBMS_AQADM_SYS.AQ$_PROPAGATION_PROCEDURE AFTER UPGRADENOTE:1204080.1 - AQ Propagation Failing With ORA-25329 After Upgraded From 8i or 9i to 10g or 11g.NOTE:219416.1 - Advanced Queuing Propagation fails with ORA-22922NOTE:222992.1 - DBMS_AQADM.DISABLE_PROPAGATION_SCHEDULE Returns ORA-24082NOTE:253131.1 - Concurrent Writes May Corrupt LOB Segment When Using Auto Segment Space Management (ORA-1555)NOTE:282987.1 - Propagated Messages marked UNDELIVERABLE after Drop and Recreate Of Remote QueueNOTE:298015.1 - Kwqjswproc:Excep After Loop: Assigning To SelfNOTE:302109.1 - Streams Propagation Error: ORA-25307 Enqueue rate too high. Enable flow controlNOTE:311021.1 - Streams Propagation Process : Ora 12154 After Reboot with Transparent Application Failover TAF configuredNOTE:332792.1 - ORA-04061 error relating to SYS.DBMS_PRVTAQIP reported when setting up StatspackNOTE:333068.1 - ORA-23603: Streams Enqueue Aborted Eue To Low SGANOTE:335516.1 - Master Note for Streams Performance RecommendationsNOTE:353325.1 - ORA-24056: Internal inconsistency for QUEUE and destination NOTE:353754.1 - Streams Messaging Propagation Fails between Single and Multi-byte Charactersets when using Chararacter Length Semantics in the ADT.NOTE:359971.1 - STREAMS propagation to Primary of physical Standby configuation errors with Ora-01033, Ora-02068NOTE:363496.1 - Ora-25315 Propagating on RAC StreamsNOTE:365093.1 - ORA-07445 [kwqppay2aqe()+7360] reported on Propagation of a Transformed MessageNOTE:368237.1 - Unable to Unschedule Propagation. Streams Queue is InvalidNOTE:368912.1 - Queue to Queue Propagation Schedule encountered ORA-12514 in a RAC environmentNOTE:421237.1 - ORA-600 [KWQBMCRCPTS101] reported by a Qmon slave process after dropping a Streams PropagationNOTE:436332.1 - dbms_propagation_adm.stop_propagation hangsNOTE:437838.1 - Streams Specific PatchesNOTE:460471.1 - Propagation Blocked by Qmon Process - Streams_queue_table / 'library cache lock' waitsNOTE:463820.1 - Streams Combined Capture and Apply in 11gNOTE:553017.1 - Stream Propagation Process Errors Ora-4052 Ora-6554 From 11g To 10201NOTE:556309.1 - Changing Propagation/ queue_to_queue : false -> true does does not work; no LCRs propagatedNOTE:564649.1 - ORA-02068/ORA-03114/ORA-03113 Errors From Streams Propagation Process - Remote Database is Available and Unschedule/Reschedule Does Not ResolveNOTE:566622.1 - ORA-22275 when propagating >4K AQ$_JMS_TEXT_MESSAGEs from 9.2.0.8 to 10.2.0.1NOTE:727389.1 - Propagation Fails With ORA-12528NOTE:730036.1 - Overview for Troubleshooting Streams Performance IssuesNOTE:730911.1 - ORA-4063 Is Reported After Dropping Negative Prop.RulesetNOTE:731292.1 - ORA-25215 Reported On Local Propagation When Using Transformation with ANYDATA queue tablesNOTE:731539.1 - ORA-29268: HTTP client error 401 Unauthorized Error when the AQ Servlet attempts to Propagate a message via HTTPNOTE:745601.1 - ORA-23603 'STREAMS enqueue aborted due to low SGA' Error from Streams Propagation, and V$STREAMS_CAPTURE.STATE Hanging on 'Enqueuing Message'NOTE:749181.1 - How to Recover Streams After Dropping PropagationNOTE:780733.1 - Streams Propagation Tuning with Network ParametersNOTE:787367.1 - ORA-22275 reported on Propagating Messages with LOB component when propagating between 10.1 and 10.2NOTE:808136.1 - How to clear the old errors from DBA_PROPAGATION view ?NOTE:827184.1 - AQ Propagation with CLOB data types Fails with ORA-22990NOTE:827473.1 - How to alter propagation from queue_to_queue to queue_to_dblinkNOTE:839568.1 - Propagation failing with error: ORA-01536: space quota exceeded for tablespace ''NOTE:846297.1 - AQ Propagation Fails : ORA-00600[kope2upic2954] or Ora-00600[Kghsstream_copyn]NOTE:944846.1 - Streams Propagation Fails Ora-7445 [kohrsmc]

    Read the article

  • Romanian parter Omnilogic Delivers “No Limits” Scalability, Performance, Security, and Affordability through Next-Generation, Enterprise-Grade Engineered Systems

    - by swalker
    Omnilogic SRL is a leading technology and information systems provider in Romania and central and Eastern Europe. An Oracle Value-Added Distributor Partner, Omnilogic resells Oracle software, hardware, and engineered systems to Oracle Partner Network members and provides specialized training, support, and testing facilities. Independent software vendors (ISVs) also use Omnilogic’s demonstration and testing facilities to upgrade the performance and efficiency of their solutions and those of their customers by migrating them from competitor technologies to Oracle platforms. Omnilogic also has a dedicated offering for ISV solutions, based on Oracle technology in a hosting service provider model. Omnilogic wanted to help Oracle Partners and ISVs migrate solutions to Oracle Exadata and sell Oracle Exadata to end-customers. It installed Oracle Exadata Database Machine X2-2 Quarter Rack at its data center to create a demonstration and testing environment. Demonstrations proved that Oracle Exadata achieved processing speeds up to 100 times faster than competitor systems, cut typical back-up times from 6 hours to 20 minutes, and stored 10 times more data. Oracle Partners and ISVs learned that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, without business disruption, and with reduced ongoing operating costs. Challenges A word from Omnilogic “Oracle Exadata is the new killer application—the smartest solution on the market. There is no competition.” – Sorin Dragomir, Chief Operating Officer, Omnilogic SRL Enable Oracle Partners in Romania and central and eastern Europe to achieve Oracle Exadata Ready status by providing facilities to test and optimize existing applications and build real-life proofs of concept (POCs) for new solutions on Oracle Exadata Database Machine Provide technical support and demonstration facilities for ISVs migrating their customers’ solutions from competitor technologies to Oracle Exadata to maximize performance, scalability, and security; optimize hardware and datacenter space; cut maintenance costs; and improve return on investment Demonstrate power of Oracle Exadata’s high-performance, high-capacity engineered systems for customer-facing businesses, such as government organizations, telecommunications, banking and insurance, and utility companies, which typically require continuous availability to support very large data volumes Showcase Oracle Exadata’s unchallenged online transaction processing (OLTP) capabilities that cut application run times to provide unrivalled query turnaround and user response speeds while significantly reducing back-up times and eliminating risk of unplanned outages Capitalize on providing a world-class training and demonstration environment for Oracle Exadata to accelerate sales with Oracle Partners Solutions Created a testing environment to enable Oracle Partners and ISVs to test their own solutions and those of their customers on Oracle Exadata running on Oracle Enterprise Linux or Oracle Solaris Express to benchmark performance prior to migration Leveraged expertise on Oracle Exadata to offer Oracle Exadata training, migration, support seminars and to showcase live demonstrations for Oracle Partners Proved how Oracle Exadata’s pre-engineered systems, that come assembled, configured, and ready to run, reduce deployment time and cost, minimize risk, and help customers achieve the full performance potential immediately after go live Increased processing speeds 10-fold and with zero data loss for a telecommunications provider’s client-facing customer relationship management solution Achieved performance improvements of between 6 and 100 times faster for financial and utility company applications currently running on IBM, Microsoft, or SAP HANA platforms Showed how daily closure procedures carried out overnight by banks, insurance companies, and other financial institutions to analyze each day’s business, can typically be cut from around six hours to 20 minutes, some 18 times faster, when running on Oracle Exadata Simulated concurrent back-ups while running applications under normal working conditions to prove that Oracle Exadata-based solutions can be backed up during business hours without causing bottlenecks or impacting the end-user experience Demonstrated that Oracle Exadata’s built-in analytics, data mining and OLTP capabilities make it the highest-performance, lowest-cost choice for large data warehousing operations Showed how Oracle Exadata’s columnar compression and intelligent storage architecture allows 10 times more data to be stored than on competitor platforms Demonstrated how Oracle Exadata cuts hardware requirements significantly by consolidating workloads on to fewer servers which delivers greater power efficiency and lower operating costs that competing systems from IBM and other manufacturers Proved to ISVs that migrating solutions to Oracle Exadata’s preconfigured, pre-integrated hardware and software can be completed rapidly, at low cost, and with minimal business disruption Demonstrated how storage servers, database servers, and network switches can be added incrementally and inexpensively to the Oracle Exadata platform to support business expansion On track to grow revenues by 10% in year one and by 15% annually thereafter through increased business generated from Oracle Partners and ISVs

    Read the article

  • Using NServiceBus behind a custom web service

    - by Michael Stephenson
    In this post I'd like to talk about an architecture scenario we had recently and how we were able to utilise NServiceBus to help us address this problem. Scenario Cognos is a reporting system used by one of my clients. A while back we developed a web service façade to allow line of business applications to be able to access reports from Cognos to support their various functions. The service was intended to provide access to reports which were quick running reports or pre-generated reports which could be accessed real-time on demand. One of the key aims of the web service was to provide a simple generic interface to allow applications to get any report without needing to worry about the complex .net SDK for Cognos. The web service also supported multi-hop kerberos delegation so that report data could be accesses under the context of the end user. This service was working well for a period of time. The Problem The problem we encountered was that reports were now also required to be available to batch processes. The original design was optimised for low latency so users would enjoy a positive experience, however when the batch processes started to request 250+ concurrent reports over an extended period of time you can begin to imagine the sorts of problems that come into play. The key problems this new scenario caused are: Users may be affected and the latency of on demand reports was significantly slower The Cognos infrastructure was not scaled sufficiently to be able to cope with these long peaks of load From a cost perspective it just isn't feasible to scale the Cognos infrastructure to be able to handle the load when it is only for a couple of hour window each night. We really needed to introduce a second pattern for accessing this service which would support high through-put scenarios. We also had little control over the batch process in terms of being able to throttle its load. We could however make some changes to the way it accessed the reports. The Approach My idea was to introduce a throttling mechanism between the Web Service Façade and Cognos. This would allow the batch processes to push reports requests hard at the web service which we were confident the web service can handle. The web service would then queue these requests and process them behind the scenes and make a call back to the batch application to provide the report once it had been accessed. In terms of technology we had some limitations because we were not able to use WCF or IIS7 where the MSMQ-Activated WCF services could have helped, but we did have MSMQ as an option and I thought NServiceBus could do just the job to help us here. The flow of how this would work was as follows: The batch applications would send a request for a report to the web service The web service uses NServiceBus to send the message to a Queue The NServiceBus Generic Host is running as a windows service with a message handler which subscribes to these messages The message handler gets the message, accesses the report from Cognos The message handler calls back to the original batch application, this is decoupled because the calling application provides a call back url The report gets into the batch application and is processed as normal This approach looks something like the below diagram: The key points are an application wanting to take advantage of the batch driven reports needs to do the following: Implement our call back contract Make a call to the service providing a call back url Provide a correlation ID so it knows how to tie each response back to its request What does NServiceBus offer in this solution So this scenario is not the typical messaging service bus type of solution people implement with NServiceBus, but it did offer the following: Simplified interaction with MSMQ Offered the ability to configure the number of processes working through the queue so we could find a balance between load on Cognos versus the applications end to end processing time NServiceBus offers retries and a way to manage failed messages NServiceBus offers a high availability setup The simple thing is that NServiceBus gave us the platform to build the solution on. We just implemented a message handler which functionally processed a message and we could rely on NServiceBus to do all of the hard work around managing the queues and all of the lower level things that would have took ages to write to any kind of robust level. Conclusion With this approach we were able to deal with a fairly significant performance issue with out too much rework. Hopefully this write up gives people some insight into ideas on how to leverage the excellent NServiceBus framework to help solve integration and high through-put scenarios.

    Read the article

  • The Evolution Of C#

    - by Paulo Morgado
    The first release of C# (C# 1.0) was all about building a new language for managed code that appealed, mostly, to C++ and Java programmers. The second release (C# 2.0) was mostly about adding what wasn’t time to built into the 1.0 release. The main feature for this release was Generics. The third release (C# 3.0) was all about reducing the impedance mismatch between general purpose programming languages and databases. To achieve this goal, several functional programming features were added to the language and LINQ was born. Going forward, new trends are showing up in the industry and modern programming languages need to be more: Declarative With imperative languages, although having the eye on the what, programs need to focus on the how. This leads to over specification of the solution to the problem in hand, making next to impossible to the execution engine to be smart about the execution of the program and optimize it to run it more efficiently (given the hardware available, for example). Declarative languages, on the other hand, focus only on the what and leave the how to the execution engine. LINQ made C# more declarative by using higher level constructs like orderby and group by that give the execution engine a much better chance of optimizing the execution (by parallelizing it, for example). Concurrent Concurrency is hard and needs to be thought about and it’s very hard to shoehorn it into a programming language. Parallel.For (from the parallel extensions) looks like a parallel for because enough expressiveness has been built into C# 3.0 to allow this without having to commit to specific language syntax. Dynamic There was been lots of debate on which ones are the better programming languages: static or dynamic. The fact is that both have good qualities and users of both types of languages want to have it all. All these trends require a paradigm switch. C# is, in many ways, already a multi-paradigm language. It’s still very object oriented (class oriented as some might say) but it can be argued that C# 3.0 has become a functional programming language because it has all the cornerstones of what a functional programming language needs. Moving forward, will have even more. Besides the influence of these trends, there was a decision of co-evolution of the C# and Visual Basic programming languages. Since its inception, there was been some effort to position C# and Visual Basic against each other and to try to explain what should be done with each language or what kind of programmers use one or the other. Each language should be chosen based on the past experience and familiarity of the developer/team/project/company and not by particular features. In the past, every time a feature was added to one language, the users of the other wanted that feature too. Going forward, when a feature is added to one language, the other will work hard to add the same feature. This doesn’t mean that XML literals will be added to C# (because almost the same can be achieved with LINQ To XML), but Visual Basic will have auto-implemented properties. Most of these features require or are built on top of features of the .NET Framework and, the focus for C# 4.0 was on dynamic programming. Not just dynamic types but being able to talk with anything that isn’t a .NET class. Also introduced in C# 4.0 is co-variance and contra-variance for generic interfaces and delegates. Stay tuned for more on the new C# 4.0 features.

    Read the article

  • Autoscaling in a modern world&hellip;. Part 4

    - by Steve Loethen
    Now that I have the rules and services XML files in the cloud, it is time to sever the bounds of earth and live totally in the cloud.  I have to host the Autoscaling object in Azure as well, point it to the rules, tell it the management certs and get out of the way. A couple of questions.  Where to host?  The most obvious place to me was a worker role.  A simple, single purpose worker role, doing nothing but watching my app.  Here are the steps I used. 1) Created a project.  Separate project from my web site.  I wanted to be able to run the web in the cloud and the autoscaler local for debugging purposes.  Seemed like the easiest way.  2) Add the Wasabi block to the project. 3) Configure the settings.  I used the same settings used for the console app.  It points to the same web role, uses the same rules file.  4) Make sure the certification needed to manage the role is added to the cert store in the sky (“LocalMachine” and “My” are default locations). I ran the worker role in the local fabric.  It worked.  I then published to the cloud, and verified it worked again.  Here is what my code looked like. public override bool OnStart() { Trace.WriteLine("Set Default Connection Limit", "Information"); // Set the maximum number of concurrent connections ServicePointManager.DefaultConnectionLimit = 12; Trace.WriteLine("Set up configuration change code", "Information"); // set up config CloudStorageAccount.SetConfigurationSettingPublisher((configName, configSetter) => configSetter(RoleEnvironment.GetConfigurationSettingValue(configName))); Trace.WriteLine("Get current diagnostic configuration", "Information"); // Get current diagnostic configuration DiagnosticMonitorConfiguration dmc = DiagnosticMonitor.GetDefaultInitialConfiguration(); Trace.WriteLine("Set Diagnostic Buffer Size", "Information"); // Set Diagnostic Buffer size dmc.Logs.BufferQuotaInMB = 4; Trace.WriteLine("Set log transfer period", "Information"); // Set log transfer period dmc.Logs.ScheduledTransferPeriod = TimeSpan.FromMinutes(1); Trace.WriteLine("Set log verbosity", "Information"); // Set log filter to verbose dmc.Logs.ScheduledTransferLogLevelFilter = LogLevel.Verbose; Trace.WriteLine("Start the diagnostic monitor", "Information"); // Start the diagnostic monitor DiagnosticMonitor.Start("Microsoft.WindowsAzure.Plugins.Diagnostics.ConnectionString", dmc); Trace.WriteLine("Get the current Autoscaler from the EntLib Container", "Information"); // Get the current Autoscaler from the EntLib Container scaler = EnterpriseLibraryContainer.Current.GetInstance<Autoscaler>(); Trace.WriteLine("Start the autoscaler", "Information"); // Start the autoscaler scaler.Start(); Trace.WriteLine("call the base class OnStart", "Information"); // call the base class OnStart return base.OnStart(); } public override void OnStop() { Trace.WriteLine("Stop the Autoscaler", "Information"); // Stop the Autoscaler scaler.Stop(); } I did have to turn on some basic logging for wasabi, which will cover in the next post.  This let me figure out that I hadn’t done the certificate step.

    Read the article

  • FairWarning Privacy Monitoring Solutions Rely on MySQL to Secure Patient Data

    - by Rebecca Hansen
    FairWarning® solutions have audited well over 120 billion events, each of which was processed and stored in a MySQL database. FairWarning is the world's leading supplier of privacy monitoring solutions for electronic health records, relied on by over 1,200 Hospitals and 5,000 Clinics to keep their patients' data safe. In January 2014, FairWarning was awarded the highest commendation in healthcare IT as the first ever Category Leader for Patient Privacy Monitoring in the "2013 Best in KLAS: Software & Services" report[1]. FairWarning has used MySQL as their solutions’ database from their start in 2005 to worldwide expansion and market leadership. FairWarning recently migrated their solutions from MyISAM to InnoDB and updated from MySQL 5.5 to 5.6. Following are some of benefits they’ve had as a result of those changes and reasons for their continued reliance on MySQL (from FairWarning MySQL Case Study). Scalability to Handle Terabytes of Data FairWarning's customers have a lot of data: On average, FairWarning customers receive over 700,000 events to be processed daily. Over 25% of their customers receive over 30 million events per day, which equates to over 1 billion events and nearly one terabyte (TB) of new data each month. Databases range in size from a few hundred GBs to 10+ TBs for enterprise deployments (data are rolled off after 13 months). Low or Zero Admin = Few DBAs "MySQL has not required a lot of administration. After it's been tuned, configured, and optimized for size on initial setup, we have very low administrative costs. I can scale and add more customers without adding DBAs. This has had a big, positive impact on our business.” - Chris Arnold, FairWarning Vice President of Product Management and Engineering. Performance Schema  As the size of FairWarning's customers has increased, so have their tables and data volumes. MySQL 5.6’ new maintenance and management features have helped FairWarning keep up. In particular, MySQL 5.6 performance schema’s low-level metrics have provided critical insight into how the system is performing and why. Support for Mutli-CPU Threads MySQL 5.6' support for multiple concurrent CPU threads, and FairWarning's custom data loader allow multiple files to load into a single table simultaneously vs. one at a time. As a result, their data load time has been reduced by 500%. MySQL Enterprise Hot Backup Because hospitals and clinics never stop, FairWarning solutions can’t either. FairWarning changed from using mysqldump to MySQL Enterprise Hot Backup, which has reduced downtime, restore time, and storage requirements. For many of their larger customers, restore time has decreased by 80%. MySQL Enterprise Edition and Product Roadmap Provide Complete Solution "MySQL's product roadmap fully addresses our needs. We like the fact that MySQL Enterprise Edition has everything included; there's no need to purchase separate modules."  - Chris Arnold Learn More>> FairWarning MySQL Case Study Why MySQL 5.6 is an Even Better Embedded Database for Your Products presentation Updating Your Products to MySQL 5.6, Best Practices for OEMs on-demand webinar (audio and / or slides + Q&A transcript) MyISAM to InnoDB – Why and How on-demand webinar (same stuff) Top 10 Reasons to Use MySQL as an Embedded Database white paper [1] 2013 Best in KLAS: Software & Services report, January, 2014. © 2014 KLAS Enterprises, LLC. All rights reserved.

    Read the article

  • Jersey non blocking client

    - by Pavel Bucek
    Although Jersey already have support for making asynchronous requests, it is implemented by standard blocking way - every asynchronous request is handled by one thread and that thread is released only after request is completely processed. That is OK for lots of cases, but imagine how that will work when you need to do lots of parallel requests. Of course you can limit (and its really wise thing to do, you do want control your resources) number of threads used for asynchronous requests, but you'll get another maybe not pleasant consequence - obviously processing time will incerase. There are few projects which are trying to deal with that problem, commonly named as async http clients. I didn't want to "re-implement a wheel" and I decided I'll use AHC - Async Http Client made by Jeanfrancois Arcand. There is also interesting implementation from Apache - HttpAsyncClient, but it is still in "very early stages of development" and others haven't been in similar or better shape as AHC. How this works? Non-blocking clients allow users to make same asynchronous requests as we can do with standard approach but implementation is different - threads are better utilized, they don't spend most of time in idle state. Simply described - when you make a request (send it over the network), you are waiting for reply from other side. And there comes main advantage of non-blocking approach - it uses these threads for further work, like making other requests or processing responses etc.. Idle time is minimized and your resources (threads) will be far better used. Who should consider using this? Everyone who is making lots of asynchronous requests. I haven't done proper benchmark yet, but some simple dumb tests are showing huge improvement in cases where lots of concurrent asynchronous requests are made in short period. Last but not least - this module is still experimental, so if you don't like something or if you have ideas for improvements/any feedback, feel free to comment this blog post, send mail to [email protected] or contact me personally. All feedback is greatly appreciated! maven dependency (will be present in java.net maven 2 repo by the end of the day): link: http://download.java.net/maven/2/com/sun/jersey/experimental/jersey-non-blocking-client <dependency> <groupId>com.sun.jersey.experimental</groupId> <artifactId>jersey-non-blocking-client</artifactId> <version>1.9-SNAPSHOT</version> </dependency> code snippet: ClientConfig cc = new DefaultNonBlockingClientConfig(); cc.getProperties().put(NonBlockingClientConfig.PROPERTY_THREADPOOL_SIZE, 10); // default value, feel free to change Client c = NonBlockingClient.create(cc); AsyncWebResource awr = c.asyncResource("http://oracle.com"); Future<ClientResponse> responseFuture = awr.get(ClientResponse.class); // or awr.get(new TypeListener<ClientResponse>(ClientResponse.class) { @Override public void onComplete(Future<ClientResponse> f) throws InterruptedException { ... } }); javadoc (temporary location, won't be updated): http://anise.cz/~paja/jersey-non-blocking-client/

    Read the article

  • Access Denied

    - by Tony Davis
    When Microsoft executives wake up in the night screaming, I suspect they are having a nightmare about their own version of Frankenstein's monster. Created with the best of intentions, without thinking too hard of the long-term strategy, and having long outlived its usefulness, the monster still lives on, occasionally wreaking vengeance on the innocent. Its name is Access; a living synthesis of disparate body parts that is resistant to all attempts at a mercy-killing. In 1986, Microsoft had no database products, and needed one for their new OS/2 operating system, the successor to MSDOS. In 1986, they bought exclusive rights to Sybase DataServer, and were also intent on developing a desktop database to capture Ashton-Tate's dominance of that market, with dbase. This project, first called 'Omega' and later 'Cirrus', eventually spawned two products: Visual Basic in 1991 and Access in late 1992. Whereas Visual Basic battled with PowerBuilder for dominance in the client-server market, Access easily won the desktop database battle, with Dbase III and DataEase falling away. Access did an excellent job of abstracting and simplifying the task of building small database applications in a short amount of time, for a small number of departmental users, and often for a transient requirement. There is an excellent front end and forms generator. We not only see it in Access but parts of it also reappear in SSMS. It's good. A business user can pull together useful reports, without relying on extensive technical support. A skilled Access programmer can deliver a fairly sophisticated application, whilst the traditional client-server programmer is still sharpening his pencil. Even for the SQL Server programmer, the forms generator of Access is useful for sketching out application designs. So far, so good, but here's where the problems start; Access ties together two different products and the backend of Access is the bugbear. The limitations of Jet/ACE are well-known and documented. They range from MDB files that are prone to corruption, especially as they grow in size, pathetic security, and "copy and paste" Backups. The biggest problem though, was an infamous lack of scalability. Because Microsoft never realized how long the product would last, they put little energy into improving the beast. Microsoft 'ate their own dog food' by using Access for Microsoft Exchange and Outlook. They choked on it. For years, scalability and performance problems with Exchange Server have been laid at the door of the Jet Blue engine on which it relies. Substantial development work in Exchange 2010 was required, just in order to improve the engine and storage schema so that it more efficiently handled the reading and writing of mails. The alternative of using SQL Server just never panned out. The Jet engine was designed to limit concurrent users to a small number (10-20). When Access applications outgrew this, bitter experience proved that there really is no easy upgrade path from Access to SQL Server, beyond rewriting the whole lot from scratch. The various initiatives to do this never quite bridged the cultural gulf between Access and a true relational database So, what are the obvious alternatives for small, strategic database applications? I know many users who, for simple 'list maintenance' requirements are very happy using Excel databases. Surely, now that PowerPivot has led the way, it is time for Microsoft to offer a new RAD package for database application development; namely an Excel-based front end for SQL Server Express. In that way, we'll have a powerful and familiar front end, to a scalable database, and a clear upgrade path when an app takes off and needs to go enterprise. Cheers, Tony.

    Read the article

  • MEB: Taking Incremental Backup using last successful backup

    - by Sagar Jauhari
    Introduction In MySQL Enterprise Backup v3.7.0 (MEB 3.7.0) a new option '–incremental-base' was introduced. Using this option a user can take in incremental backup without specifying the '–start-lsn' option. Description of this option can be found here. Instead of '–start-lsn' the user can provide the location of the last full backup or incremental backup using the 'dir:' prefix. MEB would extract the end LSN of this backup from the mysql.backup_history table as well as the backup_variables.txt file (for verification) to use it as the start LSN of the incremental backup. Because of popular demand, in MEB 3.7.1 the option '-incremental-base' has been extended further. The idea is to allow the user to take an incremental backup as easily as possible using the '–incremental-base' option. With the new option MEB queries the backup_history table for the last successful backup and uses its end LSN as the start LSN for the new incremental backup. It should be noted that the last successful backup is used irrespective of the location of the backup. Details A new prefix 'history:' has been introduced for the –incremental-base option and currently the only permissible value is the string "last_backup". So using the new option an incremental backup can be taken with the following command: $ mysqlbackup --incremental --incremental-backup-dir=/media/mysqlbackup-repo/ --incremental-base=history:last_backup backup When MEB attempts to extract the end LSN of the last successful backup from the mysql.backup_history table, it also scans the corresponding backup destination for the old backup and tries to read the meta files at this backup destination. If a valid backup still exists at the backup destination and the meta files can be read, MEB compares the end LSN found in the mysql.backup_history table with the end LSN found in the backup meta files of the old backup. Assuming that the host MySQL server is alive and mysql.backup_history can be accessed by MEB, the behaviour of MEB with respect to verification of the old end LSN can be summarized as follows: If 'BD' is the backup destination of the last successful backup in mysql.backup_history table and 'BHT' is the mysql.backup_history table if can_read_files_at_BD:     if end_lsn_found_at_BD == end_lsn_of_last_backup_in_BHT:         continue_with_backup()     else         return_with_error() else     continue_with_backup() Advantages Apart from ease of usability an important advantage of this option is that the user can do repeated incremental backups without changing the command line. This is possible using the '–with-timestamp' option along with this new option. For example, the following command $ mysqlbackup --with-timestamp --incremental --incremental-backup-dir=/media/mysqlbackup-repo/ --incremental-base=history:last_backup backup  can be used to perform successive incremental backups in the directory /media/mysqlbackup-repo . Limitations The option '--incremental-base=history:last_backup' should not be used when the user takes different kinds of concurrent backups on the same MySQL server (say different partial backups at multiple locations). should not be used after any temporary or experimental backups performed on the server (which where successful!). needs to be used with precaution since any intermediate successful backup without the –no-connection will be used as the base backup for the next incremental backup.  will give an error in case a valid backup exists at the location of the last successful backup and whose end LSN is different from that of the last successful backup found in the backup_history table. Date: 2012-06-19 HTML generated by org-mode 6.33x in emacs 23

    Read the article

  • How the number of indexes built on a table can impact performances?

    - by Davide Mauri
    We all know that putting too many indexes (I’m talking of non-clustered index only, of course) on table may produce performance problems due to the overhead that each index bring to all insert/update/delete operations on that table. But how much? I mean, we all agree – I think – that, generally speaking, having many indexes on a table is “bad”. But how bad it can be? How much the performance will degrade? And on a concurrent system how much this situation can also hurts SELECT performances? If SQL Server take more time to update a row on a table due to the amount of indexes it also has to update, this also means that locks will be held for more time, slowing down the perceived performance of all queries involved. I was quite curious to measure this, also because when teaching it’s by far more impressive and effective to show to attended a chart with the measured impact, so that they can really “feel” what it means! To do the tests, I’ve create a script that creates a table (that has a clustered index on the primary key which is an identity column) , loads 1000 rows into the table (inserting 1000 row using only one insert, instead of issuing 1000 insert of one row, in order to minimize the overhead needed to handle the transaction, that would have otherwise ), and measures the time taken to do it. The process is then repeated 16 times, each time adding a new index on the table, using columns from table in a round-robin fashion. Test are done against different row sizes, so that it’s possible to check if performance changes depending on row size. The result are interesting, although expected. This is the chart showing how much time it takes to insert 1000 on a table that has from 0 to 16 non-clustered indexes. Each test has been run 20 times in order to have an average value. The value has been cleaned from outliers value due to unpredictable performance fluctuations due to machine activity. The test shows that in a  table with a row size of 80 bytes, 1000 rows can be inserted in 9,05 msec if no indexes are present on the table, and the value grows up to 88 (!!!) msec when you have 16 indexes on it This means a impact on performance of 975%. That’s *huge*! Now, what happens if we have a bigger row size? Say that we have a table with a row size of 1520 byte. Here’s the data, from 0 to 16 indexes on that table: In this case we need near 22 msec to insert 1000 in a table with no indexes, but we need more that 500msec if the table has 16 active indexes! Now we’re talking of a 2410% impact on performance! Now we can have a tangible idea of what’s the impact of having (too?) many indexes on a table and also how the size of a row also impact performances. That’s why the golden rule of OLTP databases “few indexes, but good” is so true! (And in fact last week I saw a database with tables with 1700bytes row size and 23 (!!!) indexes on them!) This also means that a too heavy denormalization is really not a good idea (we’re always talking about OLTP systems, keep it in mind), since the performance get worse with the increase of the row size. So, be careful out there, and keep in mind the “equilibrium” is the key world of a database professional: equilibrium between read and write performance, between normalization and denormalization, between to few and too may indexes. PS Tests are done on a VMWare Workstation 7 VM with 2 CPU and 4 GB of Memory. Host machine is a Dell Precsioni M6500 with i7 Extreme X920 Quad-Core HT 2.0Ghz and 16Gb of RAM. Database is stored on a SSD Intel X-25E Drive, Simple Recovery Model, running on SQL Server 2008 R2. If you also want to to tests on your own, you can download the test script here: Open TestIndexPerformance.sql

    Read the article

  • 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.

    Read the article

  • WebLogic Server Performance and Tuning: Part II - Thread Management

    - by Gokhan Gungor
    WebLogic Server, like any other java application server, provides resources so that your applications use them to provide services. Unfortunately none of these resources are unlimited and they must be managed carefully. One of these resources is threads which are pooled to provide better throughput and performance along with the fast response time and to avoid deadlocks. Threads are execution points that WebLogic Server delivers its power and execute work. Managing threads is very important because it may affect the overall performance of the entire system. In previous releases of WebLogic Server 9.0 we had multiple execute queues and user defined thread pools. There were different queues for different type of work which had fixed number of execute threads.  Tuning of this thread pools and finding the proper number of threads was time consuming which required many trials. WebLogic Server 9.0 and the following releases use a single thread pool and a single priority-based execute queue. All type of work is executed in this single thread pool. Its size (thread count) is automatically decreased or increased (self-tuned). The new “self-tuning” system simplifies getting the proper number of threads and utilizing them.Work manager allows your applications to run concurrently in multiple threads. Work manager is a mechanism that allows you to manage and utilize threads and create rules/guidelines to follow when assigning requests to threads. We can set a scheduling guideline or priority a request with a work manager and then associate this work manager with one or more applications. At run-time, WebLogic Server uses these guidelines to assign pending work/requests to execution threads. The position of a request in the execute queue is determined by its priority. There is a default work manager that is provided. The default work manager should be sufficient for most applications. However there can be cases you want to change this default configuration. Your application(s) may be providing services that need mixture of fast response time and long running processes like batch updates. However wrong configuration of work managers can lead a performance penalty while expecting improvement.We can define/configure work managers at;•    Domain Level: config.xml•    Application Level: weblogic-application.xml •    Component Level: weblogic-ejb-jar.xml or weblogic.xml(For a specific web application use weblogic.xml)We can use the following predefined rules/constraints to manage the work;•    Fair Share Request Class: Specifies the average thread-use time required to process requests. The default is 50.•    Response Time Request Class: Specifies a response time goal in milliseconds.•    Context Request Class: Assigns request classes to requests based on context information.•    Min Threads Constraint: Limits the number of concurrent threads executing requests.•    Max Threads Constraint: Guarantees the number of threads the server will allocate to requests.•    Capacity Constraint: Causes the server to reject requests only when it has reached its capacity. Let’s create a work manager for our application for a long running work.Go to WebLogic console and select Environment | Work Managers from the domain structure tree. Click New button and select Work manager and click next. Enter the name for the work manager and click next. Then select the managed server instances(s) or clusters from available targets (the one that your long running application is deployed) and finish. Click on MyWorkManager, and open the Configuration tab and check Ignore Stuck Threads and save. This will prevent WebLogic to tread long running processes (that is taking more than a specified time) as stuck and enable to finish the process.

    Read the article

  • QCon: A practitioner-driven conference for Developers

    - by Ruma Sanyal
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} QCon [http://www.qconsf.com] started yesterday with the 3-day conference from Monday thru Wednesday, followed by 2 days of tutorials on Thursday and Friday. The conference features over 100 speakers in 6 concurrent tracks daily covering the most timely and innovative topics driving the evolution of enterprise software development today. Oracle and its Cloud Application Foundation products are well represented at this event. Yesterday, Joe Huang, responsible for outbound product management of Oracle's Mobile Application Development Framework (ADF Mobile), discussed hybrid mobile development with Java & HTML5 for iOS and Android. If you missed Joe’s session you can download the presentation from here. Michael Kovacs will be talking tomorrow about how to keep your application data highly available. Michael works with Oracle customers in a pre-sales role to help them understand when and how to use Oracle's technology to solve their business problems. His focus is on Java and technologies like WebLogic and Coherence. His session details can be found here. Lastly, we believe in having fun. So don’t miss the Oracle hospitality reception today at the Hyatt Atrium. See you there!   /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif"; mso-fareast-font-family:"Times New Roman";}

    Read the article

  • 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?

    Read the article

  • Fast Data - Big Data's achilles heel

    - by thegreeneman
    At OOW 2013 in Mark Hurd and Thomas Kurian's keynote, they discussed Oracle's Fast Data software solution stack and discussed a number of customers deploying Oracle's Big Data / Fast Data solutions and in particular Oracle's NoSQL Database.  Since that time, there have been a large number of request seeking clarification on how the Fast Data software stack works together to deliver on the promise of real-time Big Data solutions.   Fast Data is a software solution stack that deals with one aspect of Big Data, high velocity.   The software in the Fast Data solution stack involves 3 key pieces and their integration:  Oracle Event Processing, Oracle Coherence, Oracle NoSQL Database.   All three of these technologies address a high throughput, low latency data management requirement.   Oracle Event Processing enables continuous query to filter the Big Data fire hose, enable intelligent chained events to real-time service invocation and augments the data stream to provide Big Data enrichment. Extended SQL syntax allows the definition of sliding windows of time to allow SQL statements to look for triggers on events like breach of weighted moving average on a real-time data stream.    Oracle Coherence is a distributed, grid caching solution which is used to provide very low latency access to cached data when the data is too big to fit into a single process, so it is spread around in a grid architecture to provide memory latency speed access.  It also has some special capabilities to deploy remote behavioral execution for "near data" processing.   The Oracle NoSQL Database is designed to ingest simple key-value data at a controlled throughput rate while providing data redundancy in a cluster to facilitate highly concurrent low latency reads.  For example, when large sensor networks are generating data that need to be captured while analysts are simultaneously extracting the data using range based queries for upstream analytics.  Another example might be storing cookies from user web sessions for ultra low latency user profile management, also leveraging that data using holistic MapReduce operations with your Hadoop cluster to do segmented site analysis.  Understand how NoSQL plays a critical role in Big Data capture and enrichment while simultaneously providing a low latency and scalable data management infrastructure thru clustered, always on, parallel processing in a shared nothing architecture. Learn how easily a NoSQL cluster can be deployed to provide essential services in industry specific Fast Data solutions. See these technologies work together in a demonstration highlighting the salient features of these Fast Data enabling technologies in a location based personalization service. The question then becomes how do these things work together to deliver an end to end Fast Data solution.  The answer is that while different applications will exhibit unique requirements that may drive the need for one or the other of these technologies, often when it comes to Big Data you may need to use them together.   You may have the need for the memory latencies of the Coherence cache, but just have too much data to cache, so you use a combination of Coherence and Oracle NoSQL to handle extreme speed cache overflow and retrieval.   Here is a great reference to how these two technologies are integrated and work together.  Coherence & Oracle NoSQL Database.   On the stream processing side, it is similar as with the Coherence case.  As your sliding windows get larger, holding all the data in the stream can become difficult and out of band data may need to be offloaded into persistent storage.  OEP needs an extreme speed database like Oracle NoSQL Database to help it continue to perform for the real time loop while dealing with persistent spill in the data stream.  Here is a great resource to learn more about how OEP and Oracle NoSQL Database are integrated and work together.  OEP & Oracle NoSQL Database.

    Read the article

  • How can I best implement 'cache until further notice' with memcache in multiple tiers?

    - by ajreal
    the term "client" used here is not referring to client's browser, but client server Before cache workflow 1. client make a HTTP request --> 2. server process --> 3. store parsed results into memcache for next use (cache indefinitely) --> 4. return results to client --> 5. client get the result, store into client's local memcache with TTL After cache workflow 1. another client make a HTTP request --> 2. memcache found return memcache results to client --> 3. client get the result, store into client's local memcache with TTL TTL = time to live Is possible for me to know when the data was updated, and to expire relevant memcache(s) accordingly. However, the pitfalls on client site cache TTL Any data update before the TTL is not pick-up by client memcache. In reverse manner, where there is no update, client memcache still expire after the TTL First request (or concurrent requests) after cache TTL will get throttle as it need to repeat the "Before cache workflow" In the event where client require several HTTP requests on a single web page, it could be very bad in performance. Ideal solution should be client to cache indefinitely until further notice. Here are the three proposals about futher notice Proposal 1 : Make use on HTTP header (current implementation) 1. client sent HTTP request last modified time header 2. server check if last data modified time=last cache time return status 304 3. client based on header to decide further processing GOOD? ---- - save some parsing for client - lesser data transfer BAD? ---- - fire a HTTP request is still slow - server end still need to process lots of requests Proposal 2 : Consistently issue a HTTP request to check all data group last modified time 1. client fire a HTTP request 2. server to return last modified time for all data group 3. client compare local last cache time with the result 4. if data group last cache time < server last modified time then request again for that data group only GOOD? ---- - only fetch what is no up-to-date - less requests for server BAD? ---- - every web page require a HTTP request Proposal 3 : Tell client when new data is available (Push) 1. when server end notice there is a change on a data group 2. notify clients on the changes 3. help clients to fetch again data 4. then reset client local memcache after data is parsed GOOD? ---- - let the cache act/behave like a true cache BAD? ---- - encourage race condition My preference is on proposal 3, and something like Gearman could be ideal Where there is a change, Gearman server to sent the task to multiple clients (workers). Am I crazy? (I know my first question is a bit crazy)

    Read the article

  • Asynchrony in C# 5 (Part II)

    - by javarg
    This article is a continuation of the series of asynchronous features included in the new Async CTP preview for next versions of C# and VB. Check out Part I for more information. So, let’s continue with TPL Dataflow: Asynchronous functions TPL Dataflow Task based asynchronous Pattern Part II: TPL Dataflow Definition (by quote of Async CTP doc): “TPL Dataflow (TDF) is a new .NET library for building concurrent applications. It promotes actor/agent-oriented designs through primitives for in-process message passing, dataflow, and pipelining. TDF builds upon the APIs and scheduling infrastructure provided by the Task Parallel Library (TPL) in .NET 4, and integrates with the language support for asynchrony provided by C#, Visual Basic, and F#.” This means: data manipulation processed asynchronously. “TPL Dataflow is focused on providing building blocks for message passing and parallelizing CPU- and I/O-intensive applications”. Data manipulation is another hot area when designing asynchronous and parallel applications: how do you sync data access in a parallel environment? how do you avoid concurrency issues? how do you notify when data is available? how do you control how much data is waiting to be consumed? etc.  Dataflow Blocks TDF provides data and action processing blocks. Imagine having preconfigured data processing pipelines to choose from, depending on the type of behavior you want. The most basic block is the BufferBlock<T>, which provides an storage for some kind of data (instances of <T>). So, let’s review data processing blocks available. Blocks a categorized into three groups: Buffering Blocks Executor Blocks Joining Blocks Think of them as electronic circuitry components :).. 1. BufferBlock<T>: it is a FIFO (First in First Out) queue. You can Post data to it and then Receive it synchronously or asynchronously. It synchronizes data consumption for only one receiver at a time (you can have many receivers but only one will actually process it). 2. BroadcastBlock<T>: same FIFO queue for messages (instances of <T>) but link the receiving event to all consumers (it makes the data available for consumption to N number of consumers). The developer can provide a function to make a copy of the data if necessary. 3. WriteOnceBlock<T>: it stores only one value and once it’s been set, it can never be replaced or overwritten again (immutable after being set). As with BroadcastBlock<T>, all consumers can obtain a copy of the value. 4. ActionBlock<TInput>: this executor block allows us to define an operation to be executed when posting data to the queue. Thus, we must pass in a delegate/lambda when creating the block. Posting data will result in an execution of the delegate for each data in the queue. You could also specify how many parallel executions to allow (degree of parallelism). 5. TransformBlock<TInput, TOutput>: this is an executor block designed to transform each input, that is way it defines an output parameter. It ensures messages are processed and delivered in order. 6. TransformManyBlock<TInput, TOutput>: similar to TransformBlock but produces one or more outputs from each input. 7. BatchBlock<T>: combines N single items into one batch item (it buffers and batches inputs). 8. JoinBlock<T1, T2, …>: it generates tuples from all inputs (it aggregates inputs). Inputs could be of any type you want (T1, T2, etc.). 9. BatchJoinBlock<T1, T2, …>: aggregates tuples of collections. It generates collections for each type of input and then creates a tuple to contain each collection (Tuple<IList<T1>, IList<T2>>). Next time I will show some examples of usage for each TDF block. * Images taken from Microsoft’s Async CTP documentation.

    Read the article

< Previous Page | 32 33 34 35 36 37 38 39 40 41 42 43  | Next Page >