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• Using VLC to Unicast High Definition Webcam over local gigabit LAN with low/zero delay

  - by Robin Day

  We're setting up a webcam "window" between two offices in the same buildilng. The two PC's are connected to the same gigabit switch. We're using VLC to stream the webcam over HTTP using the following commands. vlc dshow:// :dshow-caching="0" :dshow-size="640x480" :sout=#transcode{vcodec=h264,vb=0,scale=0}:http{mux=ffmpeg{mux=flv},dst=:8080/} :no-sout-rtp-sap :no-sout-standard-sap :ttl=1 :sout-keep vlc http://192.168.0.1:8080 :http-caching="0" Even with the caching set to zero, the delay in the image is a good 2-3 seconds. The CPU usage of each pc is also maxed. I'm guessing it's the transcoding that's causing much of the delay. Can anyone give me some changes to these command lines that will reduce the transcoding power, or send the webcam over a different protocol, or anything that will reduce the delay of the cameras? Bandwidth is not an issue at all as the pc's can be connected to a dedicated switch/vlan if required.

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• How to make sure clients update their browser cache when my website is updated?

  - by user64204

  I am using the HTTP 1.1 Cache-Control header to implement client-side caching. Since I update my website only once a month I would like the CSS and JS files to be cached for 30 days with Cache-Control: max-age=2592000. The problem is that the 30-day period defined by Cache-Control doesn't coincide with the website update cycle, it starts from the moment the users visit the site and ends 30 days later, which means an update could occur in the meantime and users would be running with outdated content for a while, which could break the rendering of the website if for instance the HTML and CSS no longer match. How can I perform client-side caching of content for periods of several days but somehow get users to refresh their CSS/JS files after the website has been updated? One solution I could think of is that if website updates can be schedule, the max-age returned by the server could be decreased every day accordingly so that no matter when people visit the website, the end of caching period would coincide with the update of the website, but changing the server configuration every day goes against one of my sysadmin principles (once it's running, don't touch it).

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• Commit in SQL

  - by PRajkumar

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

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• Best practice for setting Effect parameters in XNA

  - by hichaeretaqua

  I want to ask if there is a best practice for setting Effect parameters in XNA. Or in other words, what exactly happens when I call pass.Apply(). I can imagine multiple scenarios: Each time Apply is called, all effect parameters are transferred to the GPU and therefor it has no real influence how often I set a parameter. Each time Apply is called, only the parameters that got reset are transferred. So caching Set-operations that don't actually set a new value should be avoided. Each time Apply is called, only the parameters that got changed are transferred. So caching Set-operations is useless. This whole questions is bootless because no one of the mentions ways has any noteworthy impact on game performance. So the final question: Is it useful to implement some caching of set operation like: private Matrix _world; public Matrix World { get{ return _world; } set { if (value == world) return; _effect.Parameters["xWorld"].SetValue(value); _world = value; } } Thanking you in anticipation.

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• Boost your infrastructure with Coherence into the Cloud

  - by Nino Guarnacci

  Authors: Nino Guarnacci & Francesco Scarano,  at this URL could be found the original article:  http://blogs.oracle.com/slc/coherence_into_the_cloud_boost. Thinking about the enterprise cloud, come to mind many possible configurations and new opportunities in enterprise environments. Various customers needs that serve as guides to this new trend are often very different, but almost always united by two main objectives: Elasticity of infrastructure both Hardware and Software Investments related to the progressive needs of the current infrastructure Characteristics of innovation and economy. A concrete use case that I worked on recently demanded the fulfillment of two basic requirements of economy and innovation.The client had the need to manage a variety of data cache, which can process complex queries and parallel computational operations, maintaining the caches in a consistent state on different server instances, on which the application was installed.In addition, the customer was looking for a solution that would allow him to manage the likely situations in load peak during certain times of the year.For this reason, the customer requires a replication site, on which convey part of the requests during periods of peak; the desire was, however, to prevent the immobilization of investments in owned hardware-software architectures; so, to respond to this need, it was requested to seek a solution based on Cloud technologies and architectures already offered by the market. Coherence can already now address the requirements of large cache between different nodes in the cluster, providing further technology to search and parallel computing, with the simultaneous use of all hardware infrastructure resources. Moreover, thanks to the functionality of "Push Replication", which can replicate and update the information contained in the cache, even to a site hosted in the cloud, it is satisfied the need to make resilient infrastructure that can be based also on nodes temporarily housed in the Cloud architectures. There are different types of configurations that can be realized using the functionality "Push-Replication" of Coherence. Configurations can be either: Active - Passive  Hub and Spoke Active - Active Multi Master Centralized Replication Whereas the architecture of this particular project consists of two sites (Site 1 and Site Cloud), between which only Site 1 is enabled to write into the cache, it was decided to adopt an Active-Passive Configuration type (Hub and Spoke). If, however, the requirement should change over time, it will be particularly easy to change this configuration in an Active-Active configuration type. Although very simple, the small sample in this post, inspired by the specific project is effective, to better understand the features and capabilities of Coherence and its configurations. Let's create two distinct coherence cluster, located at miles apart, on two different domain contexts, one of them "hosted" at home (on-premise) and the other one hosted by any cloud provider on the network (or just the same laptop to test it :)). These two clusters, which we call Site 1 and Site Cloud, will contain the necessary information, so a simple client can insert data only into the Site 1. On both sites will be subscribed a listener, who listens to the variations of specific objects within the various caches. To implement these features, you need 4 simple classes: CachedResponse.java Represents the POJO class that will be inserted into the cache, and fulfills the task of containing useful information about the hypothetical links navigation ResponseSimulatorHelper.java Represents a link simulator, which has the task of randomly creating objects of type CachedResponse that will be added into the caches CacheCommands.java Represents the model of our example, because it is responsible for receiving instructions from the controller and performing basic operations against the cache, such as insert, delete, update, listening, objects within the cache Shell.java It is our controller, which give commands to be executed within the cache of the two Sites So, summarily, we execute the java class "Shell", asking it to put into the cache 100 objects of type "CachedResponse" through the java class "CacheCommands", then the simulator "ResponseSimulatorHelper" will randomly create new instances of objects "CachedResponse ". Finally, the Shell class will listen to for events occurring within the cache on the Site Cloud, while insertions and deletions are performed on Site 1. Now, we realize the two configurations of two respective sites / cluster: Site 1 and Site Cloud.For the Site 1 we define a cache of type "distributed" with features of "read and write", using the cache class store for the "push replication", a functionality offered by the project "incubator" of Oracle Coherence.For the "Site Cloud" we expect even the definition of “distributed” cache type with tcp proxy feature enabled, so it can receive updates from Site 1.  Coherence Cache Config XML file for "storage node" on "Site 1" site1-prod-cache-config.xml Coherence Cache Config XML file for "storage node" on "Site Cloud" site2-prod-cache-config.xml For two clients "Shell" which will connect respectively to the two clusters we have provided two easy access configurations.  Coherence Cache Config XML file for Shell on "Site 1" site1-shell-prod-cache-config.xml Coherence Cache Config XML file for Shell on "Site Cloud" site2-shell-prod-cache-config.xml Now, we just have to get everything and run our tests. To start at least one "storage" node (which holds the data) for the "Cloud Site", we can run the standard class  provided OOTB by Oracle Coherence com.tangosol.net.DefaultCacheServer with the following parameters and values:-Xmx128m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=true -Dtangosol.coherence.cacheconfig=config/site2-prod-cache-config.xml-Dtangosol.coherence.clusterport=9002-Dtangosol.coherence.site=SiteCloud To start at least one "storage" node (which holds the data) for the "Site 1", we can perform again the standard class provided by Coherence  com.tangosol.net.DefaultCacheServer with the following parameters and values:-Xmx128m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=true -Dtangosol.coherence.cacheconfig=config/site1-prod-cache-config.xml-Dtangosol.coherence.clusterport=9001-Dtangosol.coherence.site=Site1 Then, we start the first client "Shell" for the "Cloud Site", launching the java class it.javac.Shell  using these parameters and values: -Xmx64m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=config/site2-shell-prod-cache-config.xml-Dtangosol.coherence.clusterport=9002-Dtangosol.coherence.site=SiteCloud Finally, we start the second client "Shell" for the "Site 1", re-launching a new instance of class  it.javac.Shell  using  the following parameters and values: -Xmx64m-Xms64m-Dcom.sun.management.jmxremote -Dtangosol.coherence.management=all -Dtangosol.coherence.management.remote=true -Dtangosol.coherence.distributed.localstorage=false -Dtangosol.coherence.cacheconfig=config/site1-shell-prod-cache-config.xml-Dtangosol.coherence.clusterport=9001-Dtangosol.coherence.site=Site1  And now, let’s execute some tests to validate and better understand our configuration. TEST 1The purpose of this test is to load the objects into the "Site 1" cache and seeing how many objects are cached on the "Site Cloud". Within the "Shell" launched with parameters to access the "Site 1", let’s write and run the command: load test/100 Within the "Shell" launched with parameters to access the "Site Cloud" let’s write and run the command: size passive-cache Expected result If all is OK, the first "Shell" has uploaded 100 objects into a cache named "test"; consequently the "push-replication" functionality has updated the "Site Cloud" by sending the 100 objects to the second cluster where they will have been posted into a respective cache, which we named "passive-cache". TEST 2The purpose of this test is to listen to deleting and adding events happening on the "Site 1" and that are replicated within the cache on "Cloud Site". In the "Shell" launched with parameters to access the "Site Cloud" let’s write and run the command: listen passive-cache/name like '%' or a "cohql" query, with your preferred parameters In the "Shell" launched with parameters to access the "Site 1" let’s write and run the following commands: load test/10 load test2/20 delete test/50 Expected result If all is OK, the "Shell" to Site Cloud let us to listen to all the add and delete events within the cache "cache-passive", whose objects satisfy the query condition "name like '%' " (ie, every objects in the cache; you could change the tests and create different queries).Through the Shell to "Site 1" we launched the commands to add and to delete objects on different caches (test and test2). With the "Shell" running on "Site Cloud" we got the evidence (displayed or printed, or in a log file) that its cache has been filled with events and related objects generated by commands executed from the" Shell "on" Site 1 ", thanks to "push-replication" feature.  Other tests can be performed, such as, for example, the subscription to the events on the "Site 1" too, using different "cohql" queries, changing the cache configuration,  to effectively demonstrate both the potentiality and  the versatility produced by these different configurations, even in the cloud, as in our case. More information on how to configure Coherence "Push Replication" can be found in the Oracle Coherence Incubator project documentation at the following link: http://coherence.oracle.com/display/INC10/Home More information on Oracle Coherence "In Memory Data Grid" can be found at the following link: http://www.oracle.com/technetwork/middleware/coherence/overview/index.html To download and execute the whole sources and configurations of the example explained in the above post,  click here to download them; After download the last available version of the Push-Replication Pattern library implementation from the Oracle Coherence Incubator site, and download also the related and required version of Oracle Coherence. For simplicity the required .jarS to execute the example (that can be found into the Push-Replication-Pattern  download and Coherence Distribution download) are: activemq-core-5.3.1.jar activemq-protobuf-1.0.jar aopalliance-1.0.jar coherence-commandpattern-2.8.4.32329.jar coherence-common-2.2.0.32329.jar coherence-eventdistributionpattern-1.2.0.32329.jar coherence-functorpattern-1.5.4.32329.jar coherence-messagingpattern-2.8.4.32329.jar coherence-processingpattern-1.4.4.32329.jar coherence-pushreplicationpattern-4.0.4.32329.jar coherence-rest.jar coherence.jar commons-logging-1.1.jar commons-logging-api-1.1.jar commons-net-2.0.jar geronimo-j2ee-management_1.0_spec-1.0.jar geronimo-jms_1.1_spec-1.1.1.jar http.jar jackson-all-1.8.1.jar je.jar jersey-core-1.8.jar jersey-json-1.8.jar jersey-server-1.8.jar jl1.0.jar kahadb-5.3.1.jar miglayout-3.6.3.jar org.osgi.core-4.1.0.jar spring-beans-2.5.6.jar spring-context-2.5.6.jar spring-core-2.5.6.jar spring-osgi-core-1.2.1.jar spring-osgi-io-1.2.1.jar At this URL could be found the original article: http://blogs.oracle.com/slc/coherence_into_the_cloud_boost Authors: Nino Guarnacci & Francesco Scarano

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• Best practice settings Effect parameters in XNA

  - by hichaeretaqua

  I want to ask if there is a best practice settings effect parameters in XNA. Or in other words, what exactly happens when I call pass.Apply(). I can imagine multiple scenarios: Each time Apply() is called, all effect parameters are transferred to the GPU and therefor it has no real influence how often I set a parameter. Each time Apply() is called, only the parameters that got reset are transferred. So caching Set-operations that don't actually set a new value should be avoided. Each time Apply() is called, only the parameters that got changed are transferred. So caching Set-operations is useless. This whole questions is bootless because no one of the mentions ways has any noteworthy impact on game performance. So the final question: Is it useful to implement some caching of Set-operation like: private Matrix _world; public Matrix World { get{ return _world;} set { if(value == world)return; _effect.Parameters["xWorld"].SetValue(value); _world = value; } Thanking you in anticipation

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• Gotcha when using JavaScript in ADF Regions

  - by Frank Nimphius

  You use the ADF Faces af:resource tag to add or reference JavaScript on a page. However, adding the af:resource tag to a page fragment my not produce the desired result if the script is added as shown below <?xml version='1.0' encoding='UTF-8'?> <jsp:root xmlns:jsp="http://java.sun.com/JSP/Page" version="2.1" xmlns:af="http://xmlns.oracle.com/adf/faces/rich"> <af:resource type="javascript">   function yourMethod(evt){ ... } </af:resource> Adding scripts to a page fragment like this will see the script added for the first page fragment loaded by an ADF region but not for any subsequent fragment navigated to within the context of task flow navigation. The cause of this problem is caching as the af:resource tag is a JSP element and not a lazy loaded JSF component, which makes it a candidate for caching. To solve the problem, move the af:resource tag into a container component like af:panelFormLayout so the script is added when the component is instantiated and added to the page.  <?xml version='1.0' encoding='UTF-8'?> <jsp:root xmlns:jsp="http://java.sun.com/JSP/Page" version="2.1" xmlns:af="http://xmlns.oracle.com/adf/faces/rich"> <af:panelFormLayout> <af:resource type="javascript">   function yourMethod(evt){ ... } </af:resource> </af:panelFormLayout> Magically this then works and prevents browser caching of the script when using page fragments.

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• One of the partion on a usb harddisk cannot automount

  - by holmescn

  It is a very strange problem. My usb harddisk has four partitions, one is primary, the other three are logical (contained within an extended partition). When I plug in the disk, three of the partitions are mounted automatically except one--the first logical partition in the extended partition. Initially I thought it is the problem of system (at that time I used Mint). But after I change to Ubuntu 12.04, the problem wasn't solved. I don't want to add a rule in fstab, and I want to know what happened. The disk is fine, and the partition can be accessed in Windows and mounted manually. result of dmesg | tail: [100933.557649] usb 2-1.2: new high-speed USB device number 4 using ehci_hcd [100933.651891] scsi8 : usb-storage 2-1.2:1.0 [100934.649047] scsi 8:0:0:0: Direct-Access SAMSUNG PQ: 0 ANSI: 0 [100934.650963] sd 8:0:0:0: Attached scsi generic sg2 type 0 [100934.651342] sd 8:0:0:0: [sdb] 625142448 512-byte logical blocks: (320 GB/298 GiB) [100934.651977] sd 8:0:0:0: [sdb] Write Protect is off [100934.651989] sd 8:0:0:0: [sdb] Mode Sense: 03 00 00 00 [100934.652836] sd 8:0:0:0: [sdb] No Caching mode page present [100934.652848] sd 8:0:0:0: [sdb] Assuming drive cache: write through [100934.655354] sd 8:0:0:0: [sdb] No Caching mode page present [100934.655367] sd 8:0:0:0: [sdb] Assuming drive cache: write through [100934.734652] sdb: sdb1 sdb3 < sdb5 sdb6 sdb7 > [100934.737706] sd 8:0:0:0: [sdb] No Caching mode page present [100934.737725] sd 8:0:0:0: [sdb] Assuming drive cache: write through [100934.737731] sd 8:0:0:0: [sdb] Attached SCSI disk result of parted -l: Model: SAMSUNG (scsi) Disk /dev/sdb: 320GB Sector size (logical/physical): 512B/512B Partition Table: msdos Number Start End Size Type File system Flags 1 32.3kB 21.5GB 21.5GB primary ntfs 3 21.5GB 320GB 299GB extended lba 5 21.5GB 129GB 107GB logical ntfs 6 129GB 236GB 107GB logical ntfs 7 236GB 320GB 83.8GB logical ntfs

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• Copy to USB memory stick really slow?

  - by Eloff

  When I copy files to the USB device, it takes much longer than in windows (same usb device, same port) it's faster than USB 1.0 speeds (1MB/s) but much slower than USB 2.0 speeds (12MB/s). To copy 1.8GB takes me over 10 minutes (it should be < 3 min.) I have two identical SanDisk Cruzer 8GB sticks, and I have the same problem with both. I have a super talent 32GB USB SSD in the neighboring port and it works at expected speeds. The problem I seem to see in the GUI is that the progress bar goes to 90% almost instantly, completes to 100% a little slower and then hangs there for 10 minutes. Interrupting the copy at this point seems to result in corruption at the tail end of the file. If I wait for it to complete the copy is successful. Any ideas? dmesg output below: [64059.432309] usb 2-1.2: new high-speed USB device number 5 using ehci_hcd [64059.526419] scsi8 : usb-storage 2-1.2:1.0 [64060.529071] scsi 8:0:0:0: Direct-Access SanDisk Cruzer 1.14 PQ: 0 ANSI: 2 [64060.530834] sd 8:0:0:0: Attached scsi generic sg4 type 0 [64060.531925] sd 8:0:0:0: [sdd] 15633408 512-byte logical blocks: (8.00 GB/7.45 GiB) [64060.533419] sd 8:0:0:0: [sdd] Write Protect is off [64060.533428] sd 8:0:0:0: [sdd] Mode Sense: 03 00 00 00 [64060.534319] sd 8:0:0:0: [sdd] No Caching mode page present [64060.534327] sd 8:0:0:0: [sdd] Assuming drive cache: write through [64060.537988] sd 8:0:0:0: [sdd] No Caching mode page present [64060.537995] sd 8:0:0:0: [sdd] Assuming drive cache: write through [64060.541290] sdd: sdd1 [64060.544617] sd 8:0:0:0: [sdd] No Caching mode page present [64060.544619] sd 8:0:0:0: [sdd] Assuming drive cache: write through [64060.544621] sd 8:0:0:0: [sdd] Attached SCSI removable disk

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• MySQL documentation writer for MEM and Replication wanted!

  - by stefanhinz

  As MySQL is thriving and growing, we're looking for an experienced technical writer located in the UK or Ireland to join the MySQL documentation team. For this job, we need the best and most dedicated people around. You will be part of a geographically distributed documentation team responsible for the technical documentation of all MySQL products. Team members are expected to work independently, requiring discipline and excellent time-management skills as well as the technical facilities and experience to communicate across the Internet. Candidates should be prepared to work intensively with our engineers and support personnel. The overall team is highly distributed across different geographies and time zones. Our source format is DocBook XML. We're not just writing documentation, but also handling publication. This means you should be familiar with DocBook, and willing to learn our publication infrastructure. Your areas of responsibility would initially be MySQL Enterprise Monitor, and MySQL Replication. This means you should be familiar with MySQL in general, and preferably also with the MySQL Enterprise offerings. A MySQL certification will be considered an advantage. Other qualifications you should have: Native English speaker 5 or more years previous experience in writing software documentation Familiarity with distributed working environments and versioning systems such as SVN Comfortable with working on multiple operating systems, particularly Windows, Mac OS X, and Linux Ability to administer own workstations and test environment Excellent written and oral communication skills Ability to provide (online) samples of your work, e.g. books or articles If you're interested, contact me under [email protected]. For reference, the job offer can be viewed here.

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• MySQL documentation writer wanted

  - by stefanhinz

  As MySQL is thriving and growing, we're looking for an experienced technical writer located in Europe or North America to join the MySQL documentation team.For this job, we need the best and most dedicated people around. You will be part of a geographically distributed documentation team responsible for the technical documentation of all MySQL products. Team members are expected to work independently, requiring discipline and excellent time-management skills as well as the technical facilities to communicate across the Internet.Candidates should be prepared to work intensively with our engineers and support personnel. The overall team is highly distributed across different geographies and time zones. Our source format is DocBook XML. We're not just writing documentation, but also handling publication. This means you should be familiar with DocBook, and willing to learn our publication infrastructure.Candidates should therefore be interested not just in writing but also in the technical aspects of publishing documentation. Regarding your initial areas of authoring, those would be MySQL Cluster, MySQL Enterprise Monitor and Backup, and various parts of the MySQL server documentation (also known as the MySQL Reference Manual). This means you should be familiar with MySQL in general, and preferably also with MySQL Cluster and the MySQL Enterprise offerings.Other qualifications: Native English speaker 3 or more years previous experience in writing software documentation Excellent written and oral communication skills Ability to provide (online) samples of your work, e.g. books or articles Curiosity to learn new technologies Familiarity with distributed working environments and versioning systems such as SVN Comfortable with working on multiple operating systems, particularly Windows, Mac OS X, and Linux Ability to administer own workstations and test environment If you're interested, contact me under [email protected].

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• My webpage ignores changes in CSS file

  - by Pavel

  No matter what I change in my .css file, the page remains the same - what's more, neither changing the link tag so that it points to another .css file nor deleting it completely makes no difference. Other changes in html code are applied. The sourcecode of the webpage shows everything as it should be. This behavior started when I redirected the link tag from previous file to the one I use now (plus there have been some changes in the tag while this problem occured, to test the behavior of my webpage); changes in neither file affect the page. For the first time when this happened, this was caused by copies of head tag in included chunks of code (for header, left menu etc. - their head part overrode the head part of the main page) and the problem was solved by removing these redundant heads from these files. But it happened again when I changed the link tag for the next time. I couldn't find any head parts in my included files, but the problem lasts (only solution I can see now is to delete the included files and copy the code directly to the file, but this would mean lots of redundant code). How can I solve this problem, so that my page response to changes in .css files without increasing redundancy? How to ensure that I can change the link to .css file just on one place with no such problems? Do I have to unload the CSS file somehow? I saw this problem both in Firefox and in Chrome. I use PSPad to write the code, just in case it would play role. EDIT: I have cleared browser cache now, and I changed the link to .css files from one to another before, but nothing helped. Now I accept the best answer saying the problem is in caching and I start a related question to find out how to solve the caching issue. If the other question's answers would say that in this case I can be sure that problem isn't in caching (very unlikely, but fail of ordinary methods of caching-problems-solving is unlikely too), I'd update this question and start searching for other possible problems, but now the message seems to be clear: when webpage ignores changes in .css files, caching is to blame.

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• Big Data – Buzz Words: What is MapReduce – Day 7 of 21

  - by Pinal Dave

  In yesterday’s blog post we learned what is Hadoop. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – MapReduce. What is MapReduce? MapReduce was designed by Google as a programming model for processing large data sets with a parallel, distributed algorithm on a cluster. Though, MapReduce was originally Google proprietary technology, it has been quite a generalized term in the recent time. MapReduce comprises a Map() and Reduce() procedures. Procedure Map() performance filtering and sorting operation on data where as procedure Reduce() performs a summary operation of the data. This model is based on modified concepts of the map and reduce functions commonly available in functional programing. The library where procedure Map() and Reduce() belongs is written in many different languages. The most popular free implementation of MapReduce is Apache Hadoop which we will explore tomorrow. Advantages of MapReduce Procedures The MapReduce Framework usually contains distributed servers and it runs various tasks in parallel to each other. There are various components which manages the communications between various nodes of the data and provides the high availability and fault tolerance. Programs written in MapReduce functional styles are automatically parallelized and executed on commodity machines. The MapReduce Framework takes care of the details of partitioning the data and executing the processes on distributed server on run time. During this process if there is any disaster the framework provides high availability and other available modes take care of the responsibility of the failed node. As you can clearly see more this entire MapReduce Frameworks provides much more than just Map() and Reduce() procedures; it provides scalability and fault tolerance as well. A typical implementation of the MapReduce Framework processes many petabytes of data and thousands of the processing machines. How do MapReduce Framework Works? A typical MapReduce Framework contains petabytes of the data and thousands of the nodes. Here is the basic explanation of the MapReduce Procedures which uses this massive commodity of the servers. Map() Procedure There is always a master node in this infrastructure which takes an input. Right after taking input master node divides it into smaller sub-inputs or sub-problems. These sub-problems are distributed to worker nodes. A worker node later processes them and does necessary analysis. Once the worker node completes the process with this sub-problem it returns it back to master node. Reduce() Procedure All the worker nodes return the answer to the sub-problem assigned to them to master node. The master node collects the answer and once again aggregate that in the form of the answer to the original big problem which was assigned master node. The MapReduce Framework does the above Map () and Reduce () procedure in the parallel and independent to each other. All the Map() procedures can run parallel to each other and once each worker node had completed their task they can send it back to master code to compile it with a single answer. This particular procedure can be very effective when it is implemented on a very large amount of data (Big Data). The MapReduce Framework has five different steps: Preparing Map() Input Executing User Provided Map() Code Shuffle Map Output to Reduce Processor Executing User Provided Reduce Code Producing the Final Output Here is the Dataflow of MapReduce Framework: Input Reader Map Function Partition Function Compare Function Reduce Function Output Writer In a future blog post of this 31 day series we will explore various components of MapReduce in Detail. MapReduce in a Single Statement MapReduce is equivalent to SELECT and GROUP BY of a relational database for a very large database. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – HDFS. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• Windows Azure Use Case: Agility

  - by BuckWoody

  This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Agility in this context is defined as the ability to quickly develop and deploy an application. In theory, the speed at which your organization can develop and deploy an application on available hardware is identical to what you could deploy in a distributed environment. But in practice, this is not always the case. Having an option to use a distributed environment can be much faster for the deployment and even the development process. Implementation: When an organization designs code, they are essentially becoming a Software-as-a-Service (SaaS) provider to their own organization. To do that, the IT operations team becomes the Infrastructure-as-a-Service (IaaS) to the development teams. From there, the software is developed and deployed using an Application Lifecycle Management (ALM) process. A simplified view of an ALM process is as follows: Requirements Analysis Design and Development Implementation Testing Deployment to Production Maintenance In an on-premise environment, this often equates to the following process map: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including physical plant, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to on-premise Testing servers. If no server capacity available, more resources procured through standard budgeting and ordering processes. Manual and automated functional, load, security, etc. performed. Deployment to Production Server team involved to select platform and environments with available capacity. If no server capacity available, standard budgeting and procurement process followed. If no server capacity available, systems built, configured and put under standard organizational IT control. Systems configured for proper operating systems, patches, security and virus scans. System maintenance, HA/DR, backups and recovery plans configured and put into place. Maintenance Code changes evaluated and altered according to need. In a distributed computing environment like Windows Azure, the process maps a bit differently: Requirements Business requirements formed by Business Analysts, Developers and Data Professionals. Analysis Feasibility studies, including budget, security, manpower and other resources. Request is placed on the work task list if approved. Design and Development Code written according to organization’s chosen methodology, either on-premise or to multiple development teams on and off premise. Implementation Code checked into main branch. Code forked as needed. Testing Code deployed to Azure. Manual and automated functional, load, security, etc. performed. Deployment to Production Code deployed to Azure. Point in time backup and recovery plans configured and put into place.(HA/DR and automated backups already present in Azure fabric) Maintenance Code changes evaluated and altered according to need. This means that several steps can be removed or expedited. It also means that the business function requesting the application can be held directly responsible for the funding of that request, speeding the process further since the IT budgeting process may not be involved in the Azure scenario. An additional benefit is the “Azure Marketplace”, In effect this becomes an app store for Enterprises to select pre-defined code and data applications to mesh or bolt-in to their current code, possibly saving development time. Resources: Whitepaper download- What is ALM?  http://go.microsoft.com/?linkid=9743693  Whitepaper download - ALM and Business Strategy: http://go.microsoft.com/?linkid=9743690  LiveMeeting Recording on ALM and Windows Azure (registration required, but free): http://www.microsoft.com/uk/msdn/visualstudio/contact-us.aspx?sbj=Developing with Windows Azure (ALM perspective) - 10:00-11:00 - 19th Jan 2011

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• Visual Studio 2010 Best Practices

  - by Etienne Tremblay

  I’d like to thank Packt for providing me with a review version of Visual Studio 2010 Best Practices eBook. In fairness I also know the author Peter having seen him speak at DevTeach on many occasions.  I started by looking at the table of content to see what this book was about, knowing that “best practices” is a real misnomer I wanted to see what they were.  I really like the fact that he starts the book by really saying they are not really best practices but actually recommend practices.  As a Team Foundation Server user I found that chapter 2 was more for the open source crowd and I really skimmed it.  The portion on Branching was well documented, although I’m not a fan of the testing branch myself, but the rest was right on. The section on merge remote changes (bring the outside to you) paradigm is really important and was touched on. Chapter 3 has good solid practices on low level constructs like generics and exceptions. Chapter 4 dives into architectural practices like decoupling, distributed architecture and data based architecture.  DTOs and ORMs are touched on briefly as is NoSQL. Chapter 5 is about deployment and is really a great primer on all the “packaging” technologies like Visual Studio Setup and Deployment (depreciated in 2012), Click Once and WIX the major player outside of commercial solutions.  This is a nice section on how to move from VSSD to WIX this is going to be important in the coming years due to the fact that VS 2012 doesn’t support VSSD. In chapter 6 we dive into automated testing practices, including test coverage, mocking, TDD, SpecDD and Continuous Testing.  Peter covers all those concepts really nicely albeit succinctly. Being a book on recommended practices I find this is really good. I really enjoyed chapter 7 that gave me a lot of great tips to enhance my Visual Studio “experience”.  Tips on organizing projects where good.  Also even though I knew about configurations I like that he put that in there so you can move all your settings to another machine, a lot of people don’t know about that. Quick find and Resharper are also briefly covered.  He touches on macros (depreciated in 2012).  Finally he touches on Continuous Integration a very important concept in today’s ALM landscape. Chapter 8 is all about Parallelization, threads, Async, division of labor, reactive extensions.  All those concepts are touched on and again generalized approaches to those modern problems are giving.       Chapter 9 goes into distributed apps, the most used and accepted practice in the industry for .NET projects the chapter tackles concepts like Scalability, Messaging and Cloud (the flavor of the month of distributed apps, although I think this will stick ;-)).  He also looks a protocols TCP/UDP and how to debug distributed apps.  He touches on logging and health monitoring. Chapter 10 tackles recommended practices for web services starting with implementing WCF services, which goes into all sort of goodness like how to host in IIS or self-host.  How to manual test WCF services, also a section on authentication and authorization.  ASP.NET Web services are also touched on in that chapter All in all a good read, nice tips and accepted practices.  I like the conciseness of the subjects and Peter touches on a lot of things in this book and uses a lot of the current technologies flavors to explain the concepts.   Cheers, ET

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• Orchestrating the Virtual Enterprise, Part I

  - by Kathryn Perry

  A guest post by Jon Chorley, Oracle's Chief Sustainability Officer & Vice President, SCM Product Strategy During the American Industrial Revolution, the Ford Motor Company did it all. It turned raw materials into a showroom full of Model Ts. It owned a steel mill, a glass factory, and an automobile assembly line. The company was both self-sufficient and innovative and went on to become one of the largest and most profitable companies in the world. Nowadays, it's unusual for any business to follow this vertical integration model because its much harder to be best in class across such a wide a range of capabilities and services. Instead, businesses focus on their core competencies and outsource other business functions to specialized suppliers. They exchange vertical integration for collaboration. When done well, all parties benefit from this arrangement and the collaboration leads to the creation of an agile, lean and successful "virtual enterprise." Case in point: For Sun hardware, Oracle outsources most of its manufacturing and all of its logistics to third parties. These are vital activities, but ones where Oracle doesn't have a core competency, so we shift them to business partners who do. Within our enterprise, we always retain the core functions of product development, support, and most of the sales function, because that's what constitutes our core value to our customers. This is a perfect example of a virtual enterprise.  What are the implications of this? It means that we must exchange direct internal control for indirect external collaboration. This fundamentally changes the relative importance of different business processes, the boundaries of security and information sharing, and the relationship of the supply chain systems to the ERP. The challenge is that the systems required to support this virtual paradigm are still mired in "island enterprise" thinking. But help is at hand. Developments such as the Web, social networks, collaboration, and rules-based orchestration offer great potential to fundamentally re-architect supply chain systems to better support the virtual enterprise.  Supply Chain Management Systems in a Virtual Enterprise Historically enterprise software was constructed to automate the ERP - and then the supply chain systems extended the ERP. They were joined at the hip. In virtual enterprises, the supply chain system needs to be ERP agnostic, sitting above each of the ERPs that are distributed across the virtual enterprise - most of which are operating in other businesses. This is vital so that the supply chain system can manage the flow of material and the related information through the multiple enterprises. It has to have strong collaboration tools. It needs to be highly flexible. Users need to be able to see information that's coming from multiple sources and be able to react and respond to events across those sources.  Oracle Fusion Distributed Order Orchestration (DOO) is a perfect example of a supply chain system designed to operate in this virtual way. DOO embraces the idea that a company's fulfillment challenge is a distributed, multi-enterprise problem. It enables users to manage the process and the trading partners in a uniform way and deliver a consistent user experience while operating over a heterogeneous, virtual enterprise. This is a fundamental shift at the core of managing supply chains. It forces virtual enterprises to think architecturally about how best to construct their supply chain systems. In my next post, I will share examples of companies that have made that shift and talk more about the distributed orchestration process.

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• Webcast On-Demand: Building Java EE Apps That Scale

  - by jeckels

  With some awesome work by one of our architects, Randy Stafford, we recently completed a webcast on scaling Java EE apps efficiently. Did you miss it? No problem. We have a replay available on-demand for you. Just hit the '+' sign drop-down for access.Topics include: Domain object caching Service response caching Session state caching JSR-107 HotCache and more! Further, we had several interesting questions asked by our audience, and we thought we'd share a sampling of those here for you - just in case you had the same queries yourself. Enjoy! What is the largest Coherence deployment out there? We have seen deployments with over 500 JVMs in the Coherence cluster, and deployments with over 1000 JVMs using the Coherence jar file, in one system. On the management side there is an ecosystem of monitoring tools from Oracle and third parties with dashboards graphing values from Coherence's JMX instrumentation. For lifecycle management we have seen a lot of custom scripting over the years, but we've also integrated closely with WebLogic to leverage its management ecosystem for deploying Coherence-based applications and managing process life cycles. That integration introduces a new Java EE archive type, the Grid Archive or GAR, which embeds in an EAR and can be seen by a WAR in WebLogic. That integration also doesn't require any extra WebLogic licensing if Coherence is licensed. How is Coherence different from a NoSQL Database like MongoDB? Coherence can be considered a NoSQL technology. It pre-dates the NoSQL movement, having been first released in 2001 whereas the term "NoSQL" was coined in 2009. Coherence has a key-value data model primarily but can also be used for document data models. Coherence manages data in memory currently, though disk persistence is in a future release currently in beta testing. Where the data is managed yields a few differences from the most well-known NoSQL products: access latency is faster with Coherence, though well-known NoSQL databases can manage more data. Coherence also has features that well-known NoSQL database lack, such as grid computing, eventing, and data source integration. Finally Coherence has had 15 years of maturation and hardening from usage in mission-critical systems across a variety of industries, particularly financial services. Can I use Coherence for local caching? Yes, you get additional features beyond just a java.util.Map: you get expiration capabilities, size-limitation capabilities, eventing capabilites, etc. Are there APIs available for GoldenGate HotCache? It's mostly a black box. You configure it, and it just puts objects into your caches. However you can treat it as a glass box, and use Coherence event interceptors to enhance its behavior - and there are use cases for that. Are Coherence caches updated transactionally? Coherence provides several mechanisms for concurrency control. If a project insists on full-blown JTA / XA distributed transactions, Coherence caches can participate as resources. But nobody does that because it's a performance and scalability anti-pattern. At finer granularity, Coherence guarantees strict ordering of all operations (reads and writes) against a single cache key if the operations are done using Coherence's "EntryProcessor" feature. And Coherence has a unique feature called "partition-level transactions" which guarantees atomic writes of multiple cache entries (even in different caches) without requiring JTA / XA distributed transaction semantics.

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• Most efficient way to check for DBNull and then assign to a variable?

  - by ilitirit

  This question comes up occasionally but I haven't seen a satisfactory answer. A typical pattern is (row is a DataRow): if (row["value"] != DBNull.Value) { someObject.Member = row["value"]; } My first question is which is more efficient (I've flipped the condition): row["value"] == DBNull.Value; // Or row["value"] is DBNull; // Or row["value"].GetType() == typeof(DBNull) // Or... any suggestions? This indicates that .GetType() should be faster, but maybe the compiler knows a few tricks I don't? Second question, is it worth caching the value of row["value"] or does the compiler optimize the indexer away anyway? eg. object valueHolder; if (DBNull.Value == (valueHolder = row["value"])) {} Disclaimers: row["value"] exists. I don't know the column index of the column (hence the column name lookup) I'm asking specifically about checking for DBNull and then assignment (not about premature optimization etc). Edit: I benchmarked a few scenarios (time in seconds, 10000000 trials): row["value"] == DBNull.Value: 00:00:01.5478995 row["value"] is DBNull: 00:00:01.6306578 row["value"].GetType() == typeof(DBNull): 00:00:02.0138757 Object.ReferenceEquals has the same performance as "==" The most interesting result? If you mismatch the name of the column by case (eg. "Value" instead of "value", it takes roughly ten times longer (for a string): row["Value"] == DBNull.Value: 00:00:12.2792374 The moral of the story seems to be that if you can't look up a column by it's index, then ensure that the column name you feed to the indexer matches the DataColumn's name exactly. Caching the value also appears to be nearly twice as fast: No Caching: 00:00:03.0996622 With Caching: 00:00:01.5659920 So the most efficient method seems to be: object temp; string variable; if (DBNull.Value != (temp = row["value"]) { variable = temp.ToString(); } This was a good learning experience.

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• Iframe form not submittin in IE but working in Firefox

  - by Younes

  I have got a form that posts values to a page in a wizard. When i'm loading this form in a Iframe everything is working fine in Firefox, it will get me to the second step of the wizard and maintains the values i filled in. When im testing this in Internet Explorer i am not getting to the second step, instead of that it returns me to the first step of the wizard with all fields being blank. When i check this in Fiddler i see that im getting a different response when i'm posting the form in the Iframe from Firefox compared to Internet Explorer. How can i make this work for all browsers? What am I doing wrong? This is what i get back from Fiddler: Firefox Post: Ressult Protocol Host URL Body Caching Content-Type Process Comments Custom 1 302 HTTP www.dmg.eu /brugman/budgetplanner/aanmelden.php 0 no-store, no-cache, must-revalidate, post-check=0, pre-check=0 Expires: Thu, 19 Nov 1981 08:52:00 GMT text/html; charset=UTF-8 firefox:6116 Get: # Result Protocol Host URL Body Caching Content-Type Process Comments Custom 2 200 HTTP www.dmg.eu /brugman/budgetplanner/ 40.677 no-store, no-cache, must-revalidate, post-check=0, pre-check=0 Expires: Thu, 19 Nov 1981 08:52:00 GMT text/html; charset=UTF-8 firefox:6116 Internet Explorer Post: Result Protocol Host URL Body Caching Content-Type Process Comments Custom 73 302 HTTP www.dmg.eu /brugman/budgetplanner/aanmelden.php 0 no-store, no-cache, must-revalidate, post-check=0, pre-check=0 Expires: Thu, 19 Nov 1981 08:52:00 GMT text/html; charset=UTF-8 iexplore:536 Get: Result Protocol Host URL Body Caching Content-Type Process Comments Custom 74 302 HTTP www.dmg.eu /brugman/budgetplanner/ 0 no-store, no-cache, must-revalidate, post-check=0, pre-check=0 Expires: Thu, 19 Nov 1981 08:52:00 GMT text/html; charset=UTF-8 iexplore:536 Hope someone knows what the diff is :).

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• Slow loading of UITableView. How know why?

  - by mamcx

  I have a UITableView that show a long list of data. Use sections and follow the sugestion of http://stackoverflow.com/questions/695814/how-solve-slow-scrolling-in-uitableview . The flow is load a main UITableView & push a second selecting a row from there. However, with 3000 items take 11 seconds to show. I suspect first from the load of the records from sqlite (I preload the first 200). So I cut it to only 50. However, no matter if I preload only 1 or 500, the time is the same. The view is made from IB and all is opaque. I run out of ideas in how detect the problem. I run the Instruments tool but not know what to look. Also, when the user select a cell from the previous UITable, no visual feedback is show (ie: the cell not turn selected) for a while so he thinks he not select it and try several times. Is related to this problem. What to do? NOTE: The problem is only in the actual device: iPod Touch 2d generation Using fmdb as sqlite api Doing the caching in viewDidLoad Using NSDictionary for the caching Using a NSAutoreleasePool for the caching part. Only caching the row ID & mac 4 fields necesary to show the cell data UIView made with interface builder, SDK 2.2.1 Instruments say I use 2.5 MB in the device

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• Orchestrating the Virtual Enterprise

  - by John Murphy

  During the American Industrial Revolution, the Ford Motor Company did it all. It turned raw materials into a showroom full of Model Ts. It owned a steel mill, a glass factory, and an automobile assembly line. The company was both self-sufficient and innovative and went on to become one of the largest and most profitable companies in the world. Nowadays, it's unusual for any business to follow this vertical integration model because its much harder to be best in class across such a wide a range of capabilities and services. Instead, businesses focus on their core competencies and outsource other business functions to specialized suppliers. They exchange vertical integration for collaboration. When done well, all parties benefit from this arrangement and the collaboration leads to the creation of an agile, lean and successful "virtual enterprise." Case in point: For Sun hardware, Oracle outsources most of its manufacturing and all of its logistics to third parties. These are vital activities, but ones where Oracle doesn't have a core competency, so we shift them to business partners who do. Within our enterprise, we always retain the core functions of product development, support, and most of the sales function, because that's what constitutes our core value to our customers. This is a perfect example of a virtual enterprise.  What are the implications of this? It means that we must exchange direct internal control for indirect external collaboration. This fundamentally changes the relative importance of different business processes, the boundaries of security and information sharing, and the relationship of the supply chain systems to the ERP. The challenge is that the systems required to support this virtual paradigm are still mired in "island enterprise" thinking. But help is at hand. Developments such as the Web, social networks, collaboration, and rules-based orchestration offer great potential to fundamentally re-architect supply chain systems to better support the virtual enterprise.  Supply Chain Management Systems in a Virtual Enterprise Historically enterprise software was constructed to automate the ERP - and then the supply chain systems extended the ERP. They were joined at the hip. In virtual enterprises, the supply chain system needs to be ERP agnostic, sitting above each of the ERPs that are distributed across the virtual enterprise - most of which are operating in other businesses. This is vital so that the supply chain system can manage the flow of material and the related information through the multiple enterprises. It has to have strong collaboration tools. It needs to be highly flexible. Users need to be able to see information that's coming from multiple sources and be able to react and respond to events across those sources.  Oracle Fusion Distributed Order Orchestration (DOO) is a perfect example of a supply chain system designed to operate in this virtual way. DOO embraces the idea that a company's fulfillment challenge is a distributed, multi-enterprise problem. It enables users to manage the process and the trading partners in a uniform way and deliver a consistent user experience while operating over a heterogeneous, virtual enterprise. This is a fundamental shift at the core of managing supply chains. It forces virtual enterprises to think architecturally about how best to construct their supply chain systems.  Case in point, almost everyone has ordered from Amazon.com at one time or another. Our orders are as likely to be fulfilled by third parties as they are by Amazon itself. To deliver the order promptly and efficiently, Amazon has to send it to the right fulfillment location and know the availability in that location. It needs to be able to track status of the fulfillment and deal with exceptions. As a virtual enterprise, Amazon's operations, using thousands of trading partners, requires a very different approach to fulfillment than the traditional 'take an order and ship it from your own warehouse' model. Amazon had no choice but to develop a complex, expensive and custom solution to tackle this problem as there used to be no product solution available. Now, other companies who want to follow similar models have a better off-the-shelf choice -- Oracle Distributed Order Orchestration (DOO).  Consider how another of our customers is using our distributed orchestration solution. This major airplane manufacturer has a highly complex business and interacts regularly with the U.S. Government and major airlines. It sits in the middle of an intricate supply chain and needed to improve visibility across its many different entities. Oracle Fusion DOO gives the company an orchestration mechanism so it could improve quality, speed, flexibility, and consistency without requiring an organ transplant of these highly complex legacy systems. Many retailers face the challenge of dealing with brick and mortar, Web, and reseller channels. They all need to be knitted together into a virtual enterprise experience that is consistent for their customers. When a large U.K. grocer with a strong brick and mortar retail operation added an online business, they turned to Oracle Fusion DOO to bring these entities together. Disturbing the Peace with Acquisitions Quite often a company's ERP system is disrupted when it acquires a new company. An acquisition can inject a new set of processes and systems -- or even introduce an entirely new business like Sun's hardware did at Oracle. This challenge has been a driver for some of our DOO customers. A large power management company is using Oracle Fusion DOO to provide the flexibility to rapidly integrate additional products and services into its central fulfillment operation. The Flip Side of Fulfillment Meanwhile, we haven't ignored similar challenges on the supply side of the equation. Specifically, how to manage complex supply in a flexible way when there are multiple trading parties involved? How to manage the supply to suppliers? How to manage critical components that need to merge in a tier two or tier three supply chain? By investing in supply orchestration solutions for the virtual enterprise, we plan to give users better visibility into their network of suppliers to help them drive down costs. We also think this technology and full orchestration process can be applied to the financial side of organizations. An example is transactions that flow through complex internal structures to minimize tax exposure. We can help companies manage those transactions effectively by thinking about the internal organization as a virtual enterprise and bringing the same solution set to this internal challenge.  The Clear Front Runner No other company is investing in solving the virtual enterprise supply chain issues like Oracle is. Oracle is in a unique position to become the gold standard in this market space. We have the infrastructure of Oracle technology. We already have an Oracle Fusion DOO application which embraces the best of what's required in this area. And we're absolutely committed to extending our Fusion solution to other use cases and delivering even more business value.

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• Is your team is a high-performing team?

  As a child I can remember looking out of the car window as my father drove along the Interstate in Florida while seeing prisoners wearing bright orange jump suits and prison guards keeping a watchful eye on them. The prisoners were taking part in a prison road gang. These road gangs were formed to help the state maintain the state highway infrastructure. The prisoner’s primary responsibilities are to pick up trash and debris from the roadway. This is a prime example of a work group or working group used by most prison systems in the United States. Work groups or working groups can be defined as a collection of individuals or entities working together to achieve a specific goal or accomplish a specific set of tasks. Typically these groups are only established for a short period of time and are dissolved once the desired outcome has been achieved. More often than not group members usually feel as though they are expendable to the group and some even dread that they are even in the group. "A team is a small number of people with complementary skills who are committed to a common purpose, performance goals, and approach for which they are mutually accountable." (Katzenbach and Smith, 1993) So how do you determine that a team is a high-performing team?  This can be determined by three base line criteria that include: consistently high quality output, the promotion of personal growth and well being of all team members, and most importantly the ability to learn and grow as a unit. Initially, a team can successfully create high-performing output without meeting all three criteria, however this will erode over time because team members will feel detached from the group or that they are not growing then the quality of the output will decline. High performing teams are similar to work groups because they both utilize a collection of individuals or entities to accomplish tasks. What distinguish a high-performing team from a work group are its characteristics. High-performing teams contain five core characteristics. These characteristics are what separate a group from a team. The five characteristics of a high-performing team include: Purpose, Performance Measures, People with Tasks and Relationship Skills, Process, and Preparation and Practice. A high-performing team is much more than a work group, and typically has a life cycle that can vary from team to team. The standard team lifecycle consists of five states and is comparable to a human life cycle. The five states of a high-performing team lifecycle include: Formulating, Storming, Normalizing, Performing, and Adjourning. The Formulating State of a team is first realized when the team members are first defined and roles are assigned to all members. This initial stage is very important because it can set the tone for the team and can ultimately determine its success or failure. In addition, this stage requires the team to have a strong leader because team members are normally unclear about specific roles, specific obstacles and goals that my lay ahead of them.  Finally, this stage is where most team members initially meet one another prior to working as a team unless the team members already know each other. The Storming State normally arrives directly after the formulation of a new team because there are still a lot of unknowns amongst the newly formed assembly. As a general rule most of the parties involved in the team are still getting used to the workload, pace of work, deadlines and the validity of various tasks that need to be performed by the group.  In this state everything is questioned because there are so many unknowns. Items commonly questioned include the credentials of others on the team, the actual validity of a project, and the leadership abilities of the team leader.  This can be exemplified by looking at the interactions between animals when they first meet.  If we look at a scenario where two people are walking directly toward each other with their dogs. The dogs will automatically enter the Storming State because they do not know the other dog. Typically in this situation, they attempt to define which is more dominating via play or fighting depending on how the dogs interact with each other. Once dominance has been defined and accepted by both dogs then they will either want to play or leave depending on how the dogs interacted and other environmental variables. Once the Storming State has been realized then the Normalizing State takes over. This state is entered by a team once all the questions of the Storming State have been answered and the team has been tested by a few tasks or projects.  Typically, participants in the team are filled with energy, and comradery, and a strong alliance with team goals and objectives.  A high school football team is a perfect example of the Normalizing State when they start their season.  The player positions have been assigned, the depth chart has been filled and everyone is focused on winning each game. All of the players encourage and expect each other to perform at the best of their abilities and are united by competition from other teams. The Performing State is achieved by a team when its history, working habits, and culture solidify the team as one working unit. In this state team members can anticipate specific behaviors, attitudes, reactions, and challenges are seen as opportunities and not problems. Additionally, each team member knows their role in the team’s success, and the roles of others. This is the most productive state of a group and is where all the time invested working together really pays off. If you look at an Olympic figure skating team skate you can easily see how the time spent working together benefits their performance. They skate as one unit even though it is comprised of two skaters. Each skater has their routine completely memorized as well as their partners. This allows them to anticipate each other’s moves on the ice makes their skating look effortless. The final state of a team is the Adjourning State. This state is where accomplishments by the team and each individual team member are recognized. Additionally, this state also allows for reflection of the interactions between team members, work accomplished and challenges that were faced. Finally, the team celebrates the challenges they have faced and overcome as a unit. Currently in the workplace teams are divided into two different types: Co-located and Distributed Teams. Co-located teams defined as the traditional group of people working together in an office, according to Andy Singleton of Assembla. This traditional type of a team has dominated business in the past due to inadequate technology, which forced workers to primarily interact with one another via face to face meetings.  Team meetings are primarily lead by the person with the highest status in the company. Having personally, participated in meetings of this type, usually a select few of the team members dominate the flow of communication which reduces the input of others in group discussions. Since discussions are dominated by a select few individuals the discussions and group discussion are skewed in favor of the individuals who communicate the most in meetings. In addition, Team members might not give their full opinions on a topic of discussion in part not to offend or create controversy amongst the team and can alter decision made in meetings towards those of the opinions of the dominating team members. Distributed teams are by definition spread across an area or subdivided into separate sections. That is exactly what distributed teams when compared to a more traditional team. It is common place for distributed teams to have team members across town, in the next state, across the country and even with the advances in technology over the last 20 year across the world. These teams allow for more diversity compared to the other type of teams because they allow for more flexibility regarding location. A team could consist of a 30 year old male Italian project manager from New York, a 50 year old female Hispanic from California and a collection of programmers from India because technology allows them to communicate as if they were standing next to one another.  In addition, distributed team members consult with more team members prior to making decisions compared to traditional teams, and take longer to come to decisions due to the changes in time zones and cultural events. However, team members feel more empowered to speak out when they do not agree with the team and to notify others of potential issues regarding the work that the team is doing. Virtual teams which are a subset of the distributed team type is changing organizational strategies due to the fact that a team can now in essence be working 24 hrs a day because of utilizing employees in various time zones and locations.  A primary example of this is with customer services departments, a company can have multiple call centers spread across multiple time zones allowing them to appear to be open 24 hours a day while all a employees work from 9AM to 5 PM every day. Virtual teams also allow human resources departments to go after the best talent for the company regardless of where the potential employee works because they will be a part of a virtual team all that is need is the proper technology to be setup to allow everyone to communicate. In addition to allowing employees to work from home, the company can save space and resources by not having to provide a desk for every team member. In fact, those team members that randomly come into the office can actually share one desk amongst multiple people. This is definitely a cost cutting plus given the current state of the economy. One thing that can turn a team into a high-performing team is leadership. High-performing team leaders need to focus on investing in ongoing personal development, provide team members with direction, structure, and resources needed to accomplish their work, make the right interventions at the right time, and help the team manage boundaries between the team and various external parties involved in the teams work. A team leader needs to invest in ongoing personal development in order to effectively manage their team. People have said that attitude is everything; this is very true about leaders and leadership. A team takes on the attitudes and behaviors of its leaders. This can potentially harm the team and the team’s output. Leaders must concentrate on self-awareness, and understanding their team’s group dynamics to fully understand how to lead them. In addition, always learning new leadership techniques from other effective leaders is also very beneficial. Providing team members with direction, structure, and resources that they need to accomplish their work collectively sounds easy, but it is not.  Leaders need to be able to effectively communicate with their team on how their work helps the company reach for its organizational vision. Conversely, the leader needs to allow his team to work autonomously within specific guidelines to turn the company’s vision into a reality.  This being said the team must be appropriately staffed according to the size of the team’s tasks and their complexity. These tasks should be clear, and be meaningful to the company’s objectives and allow for feedback to be exchanged with the leader and the team member and the leader and upper management. Now if the team is properly staffed, and has a clear and full understanding of what is to be done; the company also must supply the workers with the proper tools to achieve the tasks that they are asked to do. No one should be asked to dig a hole without being given a shovel.  Finally, leaders must reward their team members for accomplishments that they achieve. Awards could range from just a simple congratulatory email, a party to close the completion of a large project, or other monetary rewards. Managing boundaries is very important for team leaders because it can alter attitudes of team members and can add undue stress to the team which will force them to loose focus on the tasks at hand for the group. Team leaders should promote communication between team members so that burdens are shared amongst the team and solutions can be derived from hearing the opinions of multiple sources. This also reinforces team camaraderie and working as a unit. Team leaders must manage the type and timing of interventions as to not create an even bigger mess within the team. Poorly timed interventions can really deflate team members and make them question themselves. This could really increase further and undue interventions by the team leader. Typically, the best time for interventions is when the team is just starting to form so that all unproductive behaviors are removed from the team and that it can retain focus on its agenda. If an intervention is effectively executed the team will feel energized about the work that they are doing, promote communication and interaction amongst the group and improve moral overall. High-performing teams are very import to organizations because they consistently produce high quality output and develop a collective purpose for their work. This drive to succeed allows team members to utilize specific talents allowing for growth in these areas.  In addition, these team members usually take on a sense of ownership with their projects and feel that the other team members are irreplaceable. References: http://blog.assembla.com/assemblablog/tabid/12618/bid/3127/Three-ways-to-organize-your-team-co-located-outsourced-or-global.aspx Katzenbach, J.R. & Smith, D.K. (1993). The Wisdom of Teams: Creating the High-performance Organization. Boston: Harvard Business School.

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• What's up with OCFS2?

  - by wcoekaer

  On Linux there are many filesystem choices and even from Oracle we provide a number of filesystems, all with their own advantages and use cases. Customers often confuse ACFS with OCFS or OCFS2 which then causes assumptions to be made such as one replacing the other etc... I thought it would be good to write up a summary of how OCFS2 got to where it is, what we're up to still, how it is different from other options and how this really is a cool native Linux cluster filesystem that we worked on for many years and is still widely used. Work on a cluster filesystem at Oracle started many years ago, in the early 2000's when the Oracle Database Cluster development team wrote a cluster filesystem for Windows that was primarily focused on providing an alternative to raw disk devices and help customers with the deployment of Oracle Real Application Cluster (RAC). Oracle RAC is a cluster technology that lets us make a cluster of Oracle Database servers look like one big database. The RDBMS runs on many nodes and they all work on the same data. It's a Shared Disk database design. There are many advantages doing this but I will not go into detail as that is not the purpose of my write up. Suffice it to say that Oracle RAC expects all the database data to be visible in a consistent, coherent way, across all the nodes in the cluster. To do that, there were/are a few options : 1) use raw disk devices that are shared, through SCSI, FC, or iSCSI 2) use a network filesystem (NFS) 3) use a cluster filesystem(CFS) which basically gives you a filesystem that's coherent across all nodes using shared disks. It is sort of (but not quite) combining option 1 and 2 except that you don't do network access to the files, the files are effectively locally visible as if it was a local filesystem. So OCFS (Oracle Cluster FileSystem) on Windows was born. Since Linux was becoming a very important and popular platform, we decided that we would also make this available on Linux and thus the porting of OCFS/Windows started. The first version of OCFS was really primarily focused on replacing the use of Raw devices with a simple filesystem that lets you create files and provide direct IO to these files to get basically native raw disk performance. The filesystem was not designed to be fully POSIX compliant and it did not have any where near good/decent performance for regular file create/delete/access operations. Cache coherency was easy since it was basically always direct IO down to the disk device and this ensured that any time one issues a write() command it would go directly down to the disk, and not return until the write() was completed. Same for read() any sort of read from a datafile would be a read() operation that went all the way to disk and return. We did not cache any data when it came down to Oracle data files. So while OCFS worked well for that, since it did not have much of a normal filesystem feel, it was not something that could be submitted to the kernel mail list for inclusion into Linux as another native linux filesystem (setting aside the Windows porting code ...) it did its job well, it was very easy to configure, node membership was simple, locking was disk based (so very slow but it existed), you could create regular files and do regular filesystem operations to a certain extend but anything that was not database data file related was just not very useful in general. Logfiles ok, standard filesystem use, not so much. Up to this point, all the work was done, at Oracle, by Oracle developers. Once OCFS (1) was out for a while and there was a lot of use in the database RAC world, many customers wanted to do more and were asking for features that you'd expect in a normal native filesystem, a real "general purposes cluster filesystem". So the team sat down and basically started from scratch to implement what's now known as OCFS2 (Oracle Cluster FileSystem release 2). Some basic criteria were : Design it with a real Distributed Lock Manager and use the network for lock negotiation instead of the disk Make it a Linux native filesystem instead of a native shim layer and a portable core Support standard Posix compliancy and be fully cache coherent with all operations Support all the filesystem features Linux offers (ACL, extended Attributes, quotas, sparse files,...) Be modern, support large files, 32/64bit, journaling, data ordered journaling, endian neutral, we can mount on both endian /cross architecture,.. Needless to say, this was a huge development effort that took many years to complete. A few big milestones happened along the way... OCFS2 was development in the open, we did not have a private tree that we worked on without external code review from the Linux Filesystem maintainers, great folks like Christopher Hellwig reviewed the code regularly to make sure we were not doing anything out of line, we submitted the code for review on lkml a number of times to see if we were getting close for it to be included into the mainline kernel. Using this development model is standard practice for anyone that wants to write code that goes into the kernel and having any chance of doing so without a complete rewrite or.. shall I say flamefest when submitted. It saved us a tremendous amount of time by not having to re-fit code for it to be in a Linus acceptable state. Some other filesystems that were trying to get into the kernel that didn't follow an open development model had a lot harder time and a lot harsher criticism. March 2006, when Linus released 2.6.16, OCFS2 officially became part of the mainline kernel, it was accepted a little earlier in the release candidates but in 2.6.16. OCFS2 became officially part of the mainline Linux kernel tree as one of the many filesystems. It was the first cluster filesystem to make it into the kernel tree. Our hope was that it would then end up getting picked up by the distribution vendors to make it easy for everyone to have access to a CFS. Today the source code for OCFS2 is approximately 85000 lines of code. We made OCFS2 production with full support for customers that ran Oracle database on Linux, no extra or separate support contract needed. OCFS2 1.0.0 started being built for RHEL4 for x86, x86-64, ppc, s390x and ia64. For RHEL5 starting with OCFS2 1.2. SuSE was very interested in high availability and clustering and decided to build and include OCFS2 with SLES9 for their customers and was, next to Oracle, the main contributor to the filesystem for both new features and bug fixes. Source code was always available even prior to inclusion into mainline and as of 2.6.16, source code was just part of a Linux kernel download from kernel.org, which it still is, today. So the latest OCFS2 code is always the upstream mainline Linux kernel. OCFS2 is the cluster filesystem used in Oracle VM 2 and Oracle VM 3 as the virtual disk repository filesystem. Since the filesystem is in the Linux kernel it's released under the GPL v2 The release model has always been that new feature development happened in the mainline kernel and we then built consistent, well tested, snapshots that had versions, 1.2, 1.4, 1.6, 1.8. But these releases were effectively just snapshots in time that were tested for stability and release quality. OCFS2 is very easy to use, there's a simple text file that contains the node information (hostname, node number, cluster name) and a file that contains the cluster heartbeat timeouts. It is very small, and very efficient. As Sunil Mushran wrote in the manual : OCFS2 is an efficient, easily configured, quickly installed, fully integrated and compatible, feature-rich, architecture and endian neutral, cache coherent, ordered data journaling, POSIX-compliant, shared disk cluster file system. Here is a list of some of the important features that are included : Variable Block and Cluster sizes Supports block sizes ranging from 512 bytes to 4 KB and cluster sizes ranging from 4 KB to 1 MB (increments in power of 2). Extent-based Allocations Tracks the allocated space in ranges of clusters making it especially efficient for storing very large files. Optimized Allocations Supports sparse files, inline-data, unwritten extents, hole punching and allocation reservation for higher performance and efficient storage. File Cloning/snapshots REFLINK is a feature which introduces copy-on-write clones of files in a cluster coherent way. Indexed Directories Allows efficient access to millions of objects in a directory. Metadata Checksums Detects silent corruption in inodes and directories. Extended Attributes Supports attaching an unlimited number of name:value pairs to the file system objects like regular files, directories, symbolic links, etc. Advanced Security Supports POSIX ACLs and SELinux in addition to the traditional file access permission model. Quotas Supports user and group quotas. Journaling Supports both ordered and writeback data journaling modes to provide file system consistency in the event of power failure or system crash. Endian and Architecture neutral Supports a cluster of nodes with mixed architectures. Allows concurrent mounts on nodes running 32-bit and 64-bit, little-endian (x86, x86_64, ia64) and big-endian (ppc64) architectures. In-built Cluster-stack with DLM Includes an easy to configure, in-kernel cluster-stack with a distributed lock manager. Buffered, Direct, Asynchronous, Splice and Memory Mapped I/Os Supports all modes of I/Os for maximum flexibility and performance. Comprehensive Tools Support Provides a familiar EXT3-style tool-set that uses similar parameters for ease-of-use. The filesystem was distributed for Linux distributions in separate RPM form and this had to be built for every single kernel errata release or every updated kernel provided by the vendor. We provided builds from Oracle for Oracle Linux and all kernels released by Oracle and for Red Hat Enterprise Linux. SuSE provided the modules directly for every kernel they shipped. With the introduction of the Unbreakable Enterprise Kernel for Oracle Linux and our interest in reducing the overhead of building filesystem modules for every minor release, we decide to make OCFS2 available as part of UEK. There was no more need for separate kernel modules, everything was built-in and a kernel upgrade automatically updated the filesystem, as it should. UEK allowed us to not having to backport new upstream filesystem code into an older kernel version, backporting features into older versions introduces risk and requires extra testing because the code is basically partially rewritten. The UEK model works really well for continuing to provide OCFS2 without that extra overhead. Because the RHEL kernel did not contain OCFS2 as a kernel module (it is in the source tree but it is not built by the vendor in kernel module form) we stopped adding the extra packages to Oracle Linux and its RHEL compatible kernel and for RHEL. Oracle Linux customers/users obviously get OCFS2 included as part of the Unbreakable Enterprise Kernel, SuSE customers get it by SuSE distributed with SLES and Red Hat can decide to distribute OCFS2 to their customers if they chose to as it's just a matter of compiling the module and making it available. OCFS2 today, in the mainline kernel is pretty much feature complete in terms of integration with every filesystem feature Linux offers and it is still actively maintained with Joel Becker being the primary maintainer. Since we use OCFS2 as part of Oracle VM, we continue to look at interesting new functionality to add, REFLINK was a good example, and as such we continue to enhance the filesystem where it makes sense. Bugfixes and any sort of code that goes into the mainline Linux kernel that affects filesystems, automatically also modifies OCFS2 so it's in kernel, actively maintained but not a lot of new development happening at this time. We continue to fully support OCFS2 as part of Oracle Linux and the Unbreakable Enterprise Kernel and other vendors make their own decisions on support as it's really a Linux cluster filesystem now more than something that we provide to customers. It really just is part of Linux like EXT3 or BTRFS etc, the OS distribution vendors decide. Do not confuse OCFS2 with ACFS (ASM cluster Filesystem) also known as Oracle Cloud Filesystem. ACFS is a filesystem that's provided by Oracle on various OS platforms and really integrates into Oracle ASM (Automatic Storage Management). It's a very powerful Cluster Filesystem but it's not distributed as part of the Operating System, it's distributed with the Oracle Database product and installs with and lives inside Oracle ASM. ACFS obviously is fully supported on Linux (Oracle Linux, Red Hat Enterprise Linux) but OCFS2 independently as a native Linux filesystem is also, and continues to also be supported. ACFS is very much tied into the Oracle RDBMS, OCFS2 is just a standard native Linux filesystem with no ties into Oracle products. Customers running the Oracle database and ASM really should consider using ACFS as it also provides storage/clustered volume management. Customers wanting to use a simple, easy to use generic Linux cluster filesystem should consider using OCFS2. To learn more about OCFS2 in detail, you can find good documentation on http://oss.oracle.com/projects/ocfs2 in the Documentation area, or get the latest mainline kernel from http://kernel.org and read the source. One final, unrelated note - since I am not always able to publicly answer or respond to comments, I do not want to selectively publish comments from readers. Sometimes I forget to publish comments, sometime I publish them and sometimes I would publish them but if for some reason I cannot publicly comment on them, it becomes a very one-sided stream. So for now I am going to not publish comments from anyone, to be fair to all sides. You are always welcome to email me and I will do my best to respond to technical questions, questions about strategy or direction are sometimes not possible to answer for obvious reasons.

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• Why should I use Amazon Route 53 over my registrar's DNS servers?

  - by Abtin Forouzandeh

  I am building a site that I anticipate will have high usage. Currently, my registrar (GoDaddy) is handling DNS. However, Amazon's Route 53 looks interesting. They promise high speed and offer globally distributed DNS servers and a programmable interface. While GoDaddy doesn't offer a programmable interface, I assume their servers are geographically distributed as well. What are the main reasons I should opt to use Amazon Route 53 over free registrar-based DNS?

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• turn off disable the performance cache

  - by jessie

  OK I run a streaming website and my CMS is giving me an error when uploading videos "Failed To Find Flength File" ok so I did some research. The answer I got from the coder was below. I did do all that, but the only thing I could not do is turn off what he refers to as performance cache, talked about in the last sentence... I am on a Cent OS Assuming the script is set up properly, you are probably dealing with some kind of write-caching. Some servers perform write-caching which prevents writing out the flength file or the entire CGITemp file during the upload. The flength file or the CGITemp file do not actually hit the disk until the upload is complete, making it worthless for reporting on progress during the upload. This may be fixed using a .htaccess file assuming your host supports them. Here is a link to an excellent tutorial on using .htaccess files. I strongly recommend giving it a quick read before attempting to install your own .htaccess file. 1. A mod_security module for Apache. To fix it just create a file called .htaccess (that's a period followed by "htaccess") and put the following lines in that file. Upload the file into the directory where the Uber-Uploader CGI ".pl" scripts resides, or in some directory above it (like your server's DOCUMENT_ROOT, i.e. the top-level of your webspace). htaccess files must be uploaded as ASCII mode, not BINARY. You may need to CHMOD the htaccess file to 644 or (RW-R--R--). # Turn off mod_security filtering. SecFilterEngine Off # The below probably isn't needed, # but better safe than sorry. SecFilterScanPOST Off If the above method does not work, try putting the following lines into the file SetEnvIfNoCase Content-Type \ "^multipart/form-data;" "MODSEC_NOPOSTBUFFERING=Do not buffer file uploads" mod_gzip_on No 2. "Performance Cache" enabled on OS X SERVER. If you're running OS X Server and the progress bar isn't working, it could be because of "performance caching." Apparently if ANY of your hosted sites are using performance caching, then by default, all sites (domains) will attempt to. The fix then is to disable the performance cache on all hosted sites.

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