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  • Comparing 2 tables column values and copying the next column content to the second table

    - by Sullan
    Hi All.. I am comparing between two tables first column each. If there is find a match i am copying the text from the adjacent cell of the first table to the second table. I am able to compare strings and get the value, but finding it difficult to print it in the second table. I am getting the value in the var "replaceText", but how to print it in the second table ?? Please help... Sample code is as follows.. <script type="text/javascript"> jQuery.noConflict(); jQuery(document).ready(function(){ jQuery('.itemname').each(function(){ var itemName = jQuery(this).text(); jQuery('.comparerow').each(function() { var compareRow = jQuery(this).text(); if (itemName == compareRow) { var replaceText = jQuery(this).next('td').text(); alert(replaceText); } }); }); }); </script> HTML is as follows <table width="100%"><thead> <tr> <th align="left" >Name</th><th>Description</th></tr></thead> <tbody> <tr> <td class="comparerow">IX0001</td> <td class="desc">Desc 1 </td> </tr> <tr> <td class="comparerow">IX0002</td> <td class="desc" >Desc 2 </td> </tr> <tr> <td class="comparerow">IX0003</td> <td class="desc">Desc 3 </td> </tr> <tr> <td class="comparerow">IX0004</td> <td class="desc">Desc 4 </td> </tr> </tbody> </table> <br /> <table width="100%"> <tr> <th>Name</th><th>Description</th> </tr> <tr > <td class="itemname">IX0001</td><td></td> </tr> <tr> <td class="itemname">IX0002</td><td></td> </tr> <tr> <td class="itemname">IX0003</td><td></td> </tr> </table>

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  • Partner Blog Series: PwC Perspectives - The Gotchas, The Do's and Don'ts for IDM Implementations

    - by Tanu Sood
    Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:12.0pt; mso-para-margin-left:0in; line-height:12.0pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial","sans-serif"; mso-ascii-font-family:Arial; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Arial; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} table.MsoTableMediumList1Accent6 {mso-style-name:"Medium List 1 - Accent 6"; mso-tstyle-rowband-size:1; mso-tstyle-colband-size:1; mso-style-priority:65; mso-style-unhide:no; border-top:solid #E0301E 1.0pt; mso-border-top-themecolor:accent6; border-left:none; border-bottom:solid #E0301E 1.0pt; mso-border-bottom-themecolor:accent6; border-right:none; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Georgia","serif"; color:black; mso-themecolor:text1; mso-ansi-language:EN-GB;} table.MsoTableMediumList1Accent6FirstRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:cell-none; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; font-family:"Verdana","sans-serif"; mso-ascii-font-family:Georgia; mso-ascii-theme-font:major-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:major-fareast; mso-hansi-font-family:Georgia; mso-hansi-theme-font:major-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:major-bidi;} table.MsoTableMediumList1Accent6LastRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; color:#968C6D; mso-themecolor:text2; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6FirstCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-column; mso-style-priority:65; mso-style-unhide:no; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6LastCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6OddColumn {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} table.MsoTableMediumList1Accent6OddRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:12.0pt; mso-para-margin-left:0in; line-height:12.0pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial","sans-serif"; mso-ascii-font-family:Arial; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Arial; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} table.MsoTableMediumList1Accent6 {mso-style-name:"Medium List 1 - Accent 6"; mso-tstyle-rowband-size:1; mso-tstyle-colband-size:1; mso-style-priority:65; mso-style-unhide:no; border-top:solid #E0301E 1.0pt; mso-border-top-themecolor:accent6; border-left:none; border-bottom:solid #E0301E 1.0pt; mso-border-bottom-themecolor:accent6; border-right:none; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Georgia","serif"; color:black; mso-themecolor:text1; mso-ansi-language:EN-GB;} table.MsoTableMediumList1Accent6FirstRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:cell-none; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; font-family:"Arial Narrow","sans-serif"; mso-ascii-font-family:Georgia; mso-ascii-theme-font:major-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:major-fareast; mso-hansi-font-family:Georgia; mso-hansi-theme-font:major-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:major-bidi;} table.MsoTableMediumList1Accent6LastRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; color:#968C6D; mso-themecolor:text2; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6FirstCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:first-column; mso-style-priority:65; mso-style-unhide:no; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6LastCol {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:last-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-border-top:1.0pt solid #E0301E; mso-tstyle-border-top-themecolor:accent6; mso-tstyle-border-bottom:1.0pt solid #E0301E; mso-tstyle-border-bottom-themecolor:accent6; mso-ansi-font-weight:bold; mso-bidi-font-weight:bold;} table.MsoTableMediumList1Accent6OddColumn {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-column; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} table.MsoTableMediumList1Accent6OddRow {mso-style-name:"Medium List 1 - Accent 6"; mso-table-condition:odd-row; mso-style-priority:65; mso-style-unhide:no; mso-tstyle-shading:#F7CBC7; mso-tstyle-shading-themecolor:accent6; mso-tstyle-shading-themetint:63;} It is generally accepted among business communities that technology by itself is not a silver bullet to all problems, but when it is combined with leading practices, strategy, careful planning and execution, it can create a recipe for success. This post attempts to highlight some of the best practices along with dos & don’ts that our practice has accumulated over the years in the identity & access management space in general, and also in the context of R2, in particular. Best Practices The following section illustrates the leading practices in “How” to plan, implement and sustain a successful OIM deployment, based on our collective experience. Planning is critical, but often overlooked A common approach to planning an IAM program that we identify with our clients is the three step process involving a current state assessment, a future state roadmap and an executable strategy to get there. It is extremely beneficial for clients to assess their current IAM state, perform gap analysis, document the recommended controls to address the gaps, align future state roadmap to business initiatives and get buy in from all stakeholders involved to improve the chances of success. When designing an enterprise-wide solution, the scalability of the technology must accommodate the future growth of the enterprise and the projected identity transactions over several years. Aligning the implementation schedule of OIM to related information technology projects increases the chances of success. As a baseline, it is recommended to match hardware specifications to the sizing guide for R2 published by Oracle. Adherence to this will help ensure that the hardware used to support OIM will not become a bottleneck as the adoption of new services increases. If your Organization has numerous connected applications that rely on reconciliation to synchronize the access data into OIM, consider hosting dedicated instances to handle reconciliation. Finally, ensure the use of clustered environment for development and have at least three total environments to help facilitate a controlled migration to production. If your Organization is planning to implement role based access control, we recommend performing a role mining exercise and consolidate your enterprise roles to keep them manageable. In addition, many Organizations have multiple approval flows to control access to critical roles, applications and entitlements. If your Organization falls into this category, we highly recommend that you limit the number of approval workflows to a small set. Most Organizations have operations managed across data centers with backend database synchronization, if your Organization falls into this category, ensure that the overall latency between the datacenters when replicating the databases is less than ten milliseconds to ensure that there are no front office performance impacts. Ingredients for a successful implementation During the development phase of your project, there are a number of guidelines that can be followed to help increase the chances for success. Most implementations cannot be completed without the use of customizations. If your implementation requires this, it’s a good practice to perform code reviews to help ensure quality and reduce code bottlenecks related to performance. We have observed at our clients that the development process works best when team members adhere to coding leading practices. Plan for time to correct coding defects and ensure developers are empowered to report their own bugs for maximum transparency. Many organizations struggle with defining a consistent approach to managing logs. This is particularly important due to the amount of information that can be logged by OIM. We recommend Oracle Diagnostics Logging (ODL) as an alternative to be used for logging. ODL allows log files to be formatted in XML for easy parsing and does not require a server restart when the log levels are changed during troubleshooting. Testing is a vital part of any large project, and an OIM R2 implementation is no exception. We suggest that at least one lower environment should use production-like data and connectors. Configurations should match as closely as possible. For example, use secure channels between OIM and target platforms in pre-production environments to test the configurations, the migration processes of certificates, and the additional overhead that encryption could impose. Finally, we ask our clients to perform database backups regularly and before any major change event, such as a patch or migration between environments. In the lowest environments, we recommend to have at least a weekly backup in order to prevent significant loss of time and effort. Similarly, if your organization is using virtual machines for one or more of the environments, it is recommended to take frequent snapshots so that rollbacks can occur in the event of improper configuration. Operate & sustain the solution to derive maximum benefits When migrating OIM R2 to production, it is important to perform certain activities that will help achieve a smoother transition. At our clients, we have seen that splitting the OIM tables into their own tablespaces by categories (physical tables, indexes, etc.) can help manage database growth effectively. If we notice that a client hasn’t enabled the Oracle-recommended indexing in the applicable database, we strongly suggest doing so to improve performance. Additionally, we work with our clients to make sure that the audit level is set to fit the organization’s auditing needs and sometimes even allocate UPA tables and indexes into their own table-space for better maintenance. Finally, many of our clients have set up schedules for reconciliation tables to be archived at regular intervals in order to keep the size of the database(s) reasonable and result in optimal database performance. For our clients that anticipate availability issues with target applications, we strongly encourage the use of the offline provisioning capabilities of OIM R2. This reduces the provisioning process for a given target application dependency on target availability and help avoid broken workflows. To account for this and other abnormalities, we also advocate that OIM’s monitoring controls be configured to alert administrators on any abnormal situations. Within OIM R2, we have begun advising our clients to utilize the ‘profile’ feature to encapsulate multiple commonly requested accounts, roles, and/or entitlements into a single item. By setting up a number of profiles that can be searched for and used, users will spend less time performing the same exact steps for common tasks. We advise our clients to follow the Oracle recommended guides for database and application server tuning which provides a good baseline configuration. It offers guidance on database connection pools, connection timeouts, user interface threads and proper handling of adapters/plug-ins. All of these can be important configurations that will allow faster provisioning and web page response times. Many of our clients have begun to recognize the value of data mining and a remediation process during the initial phases of an implementation (to help ensure high quality data gets loaded) and beyond (to support ongoing maintenance and business-as-usual processes). A successful program always begins with identifying the data elements and assigning a classification level based on criticality, risk, and availability. It should finish by following through with a remediation process. Dos & Don’ts Here are the most common dos and don'ts that we socialize with our clients, derived from our experience implementing the solution. Dos Don’ts Scope the project into phases with realistic goals. Look for quick wins to show success and value to the stake holders. Avoid “boiling the ocean” and trying to integrate all enterprise applications in the first phase. Establish an enterprise ID (universal unique ID across the enterprise) earlier in the program. Avoid major UI customizations that require code changes. Have a plan in place to patch during the project, which helps alleviate any major issues or roadblocks (product and database). Avoid publishing all the target entitlements if you don't anticipate their usage during access request. Assess your current state and prepare a roadmap to address your operations, tactical and strategic goals, align it with your business priorities. Avoid integrating non-production environments with your production target systems. Defer complex integrations to the later phases and take advantage of lessons learned from previous phases Avoid creating multiple accounts for the same user on the same system, if there is an opportunity to do so. Have an identity and access data quality initiative built into your plan to identify and remediate data related issues early on. Avoid creating complex approval workflows that would negative impact productivity and SLAs. Identify the owner of the identity systems with fair IdM knowledge and empower them with authority to make product related decisions. This will help ensure overcome any design hurdles. Avoid creating complex designs that are not sustainable long term and would need major overhaul during upgrades. Shadow your internal or external consulting resources during the implementation to build the necessary product skills needed to operate and sustain the solution. Avoid treating IAM as a point solution and have appropriate level of communication and training plan for the IT and business users alike. Conclusion In our experience, Identity programs will struggle with scope, proper resourcing, and more. We suggest that companies consider the suggestions discussed in this post and leverage them to help enable their identity and access program. This concludes PwC blog series on R2 for the month and we sincerely hope that the information we have shared thus far has been beneficial. For more information or if you have questions, you can reach out to Rex Thexton, Senior Managing Director, PwC and or Dharma Padala, Director, PwC. We look forward to hearing from you. Normal 0 false false false EN-US X-NONE X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:12.0pt; mso-para-margin-left:0in; line-height:12.0pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Arial","sans-serif"; mso-ascii-font-family:Arial; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Arial; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} Meet the Writers: Dharma Padala is a Director in the Advisory Security practice within PwC.  He has been implementing medium to large scale Identity Management solutions across multiple industries including utility, health care, entertainment, retail and financial sectors.   Dharma has 14 years of experience in delivering IT solutions out of which he has been implementing Identity Management solutions for the past 8 years. Praveen Krishna is a Manager in the Advisory Security practice within PwC.  Over the last decade Praveen has helped clients plan, architect and implement Oracle identity solutions across diverse industries.  His experience includes delivering security across diverse topics like network, infrastructure, application and data where he brings a holistic point of view to problem solving. Scott MacDonald is a Director in the Advisory Security practice within PwC.  He has consulted for several clients across multiple industries including financial services, health care, automotive and retail.   Scott has 10 years of experience in delivering Identity Management solutions. John Misczak is a member of the Advisory Security practice within PwC.  He has experience implementing multiple Identity and Access Management solutions, specializing in Oracle Identity Manager and Business Process Engineering Language (BPEL).

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  • SQL Server 2005 - query with case statement

    - by user329266
    Trying to put a single query together to be used eventually in a SQL Server 2005 report. I need to: Pull in all distinct records for values in the "eventid" column for a time frame - this seems to work. For each eventid referenced above, I need to search for all instances of the same eventid to see if there is another record with TaskName like 'review1%'. Again, this seems to work. This is where things get complicated: For each record where TaskName is like review1, I need to see if another record exists with the same eventid and where TaskName='End'. Utimately, I need a count of how many records have TaskName like 'review1%', and then how many have TaskName like 'review1%' AND TaskName='End'. I would think this could be accomplished by setting a new value for each record, and for the eventid, if a record exists with TaskName='End', set to 1, and if not, set to 0. The query below seems to accomplish item #1 above: SELECT eventid, TimeStamp, TaskName, filepath FROM (SELECT eventid, TimeStamp, filepath, TaskName, ROW_NUMBER() OVER(PARTITION BY eventid ORDER BY TimeStamp DESC) AS seq FROM eventrecords where ((TimeStamp >= '2010-4-1 00:00:00.000') and (TimeStamp <= '2010-4-21 00:00:00.000'))) AS T WHERE seq = 1 order by eventid And the query below seems to accomplish #2: SELECT eventid, TimeStamp, TaskName, filepath FROM (SELECT eventid, TimeStamp, filepath, TaskName, ROW_NUMBER() OVER(PARTITION BY eventid ORDER BY TimeStamp DESC) AS seq FROM eventrecords where ((TimeStamp >= '2010-4-1 00:00:00.000') and (TimeStamp <= '2010-4-21 00:00:00.000')) and TaskName like 'Review1%') AS T WHERE seq = 1 order by eventid This will bring back the eventid's that also have a TaskName='End': SELECT eventid, TimeStamp, TaskName, filepath FROM (SELECT eventid, TimeStamp, filepath, TaskName, ROW_NUMBER() OVER(PARTITION BY eventid ORDER BY TimeStamp DESC) AS seq FROM eventrecords where ((TimeStamp >= '2010-4-1 00:00:00.000') and (TimeStamp <= '2010-4-21 00:00:00.000')) and TaskName like 'Review1%') AS T WHERE seq = 1 and eventid in (Select eventid from eventrecords where TaskName = 'End') order by eventid So I've tried the following to TRY to accomplish #3: SELECT eventid, TimeStamp, TaskName, filepath FROM (SELECT eventid, TimeStamp, filepath, TaskName, ROW_NUMBER() OVER(PARTITION BY eventid ORDER BY TimeStamp DESC) AS seq FROM eventrecords where ((TimeStamp >= '2010-4-1 00:00:00.000') and (TimeStamp <= '2010-4-21 00:00:00.000')) and TaskName like 'Review1%') AS T WHERE seq = 1 and case when (eventid in (Select eventid from eventrecords where TaskName = 'End') then 1 else 0) as bit end order by eventid When I try to run this, I get: "Incorrect syntax near the keyword 'then'." Not sure what I'm doing wrong. Haven't seen any examples anywhere quite like this. I should mention that eventrecords has a primary key, but it doesn't seem to help anything when I include it, and I am not permitted to change the table. (ugh) I've received one suggestion to use a cursor and temporary table, but am not sure how badley that would bog down performance when the report is running. Thanks in advance.

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  • How to get physical partition name from iSCSI details on Windows?

    - by Barry Kelly
    I've got a piece of software that needs the name of a partition in \Device\Harddisk2\Partition1 style, as shown e.g. in WinObj. I want to get this partition name from details of the iSCSI connection that underlies the partition. The trouble is that disk order is not fixed - depending on what devices are connected and initialized in what order, it can move around. So suppose I have the portal name (DNS of the iSCSI target), target IQN, etc. I'd like to somehow discover which volumes in the system relate to it, in an automated fashion. I can write some PowerShell WMI queries that get somewhat close to the desired info: PS> get-wmiobject -class Win32_DiskPartition NumberOfBlocks : 204800 BootPartition : True Name : Disk #0, Partition #0 PrimaryPartition : True Size : 104857600 Index : 0 ... From the Name here, I think I can fabricate the corresponding name by adding 1 to the partition number: \Device\Harddisk0\Partition1 - Partition0 appears to be a fake partition mapping to the whole disk. But the above doesn't have enough information to map to the underlying physical device, unless I take a guess based on exact size matching. I can get some info on SCSI devices, but it's not helpful in joining things up (iSCSI target is Nexenta/Solaris COMSTAR): PS> get-wmiobject -class Win32_SCSIControllerDevice __GENUS : 2 __CLASS : Win32_SCSIControllerDevice ... Antecedent : \\COBRA\root\cimv2:Win32_SCSIController.DeviceID="ROOT\\ISCSIPRT\\0000" Dependent : \\COBRA\root\cimv2:Win32_PnPEntity.DeviceID="SCSI\\DISK&VEN_NEXENTA&PROD_COMSTAR... Similarly, I can run queries like these: PS> get-wmiobject -namespace ROOT\WMI -class MSiSCSIInitiator_TargetClass PS> get-wmiobject -namespace ROOT\WMI -class MSiSCSIInitiator_PersistentDevices These guys return information relating to my iSCSI target name and the GUID volume name respectively (a volume name like \\?\Volume{guid-goes-here}), but the GUID volume name is no good to me, and there doesn't appear to be a reliable correspondence between the target name and the volume that I can join on. I simply can't find an easy way of getting from an IQN (e.g. iqn.1992-01.com.example:storage:diskarrays-sn-a8675309) to physical partitions mapped from that target. The way I do it by hand? I start Disk Management, and look for a partition of the correct size, verify that its driver says NEXENTA COMSTAR, and look at the disk number. But even this is unreliable if I have multiple iSCSI volumes of the exact same size. Any suggestions?

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  • CSS div/overflow Question: Why does the first HTML file work but not the second?

    - by kidvid
    Notice how the first HTML/CSS works when you re-size the browser horizontally. It will shrink no further than around 800 pixels, but it will expand as far as you drag the right edge of the browser. It will also correctly overflow the table at the top and scroll it horizontally. The thing I don't like about the first code snippet is where the scrollbar is. I want it to show up within the borders of the fieldset, so even if I narrow the browser down to 800 pixels wide, I can see both the left and right sides of the fieldset's border. The second code snippet is exactly the same as the first except I add another div tag to the mix, inside of the field set and around the grid. Notice how the top fieldset's width won't correctly shrink when you make the viewport of your browser narrower. Any ideas on why it doesn't work, what I can do to get it to work like the first code snippet? I don't think I'm describing this clearly, but if you run the two side by side, and expand and contract the horizontal edge of your browser windows, you'll see the differences between the two. I'm pretty new to CSS and HTML layout, so my understanding of why CSS handles sizing the way it does in some situations is still really confusing to me. Thanks, Adrian Working HTML file: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd"> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"/> <meta http-equiv="Content-Style-Type" content="text/css"></meta> <style type="text/css"> #divBody { margin-top: 5px; top:24px; margin-top: 10px; } #divContainer { top: 5px; position:relative; min-height:100%; #width:expression(document.body.clientWidth < 830? "800": "90%" ); width:90%; min-width: 800px; padding-bottom:70px; } #divMasterGrid { position:relative; margin:5px; top:5px; width:99%; margin:0 auto; overflow-x:scroll; } #divRadioButtonArea { position:relative; top:20px; height:51px; font-size: 12px; width:99%; margin:5px; } </style> <title>TEST TEST</title> </head> <body id="divBody"> <div id="divContainer" class="gridRegion"> <div id="divMasterGrid"> <fieldset style="margin: 5px;"> <legend style="font-size: 12px; color: #000;">Numbers</legend> <table border="1px"> <tr> <td>One </td> <td>Two </td> <td>Three </td> <td>Fout </td> <td>Five </td> <td>Six </td> <td>Seven </td> <td>Eight </td> <td>Nine </td> <td>Ten </td> <td>Eleven </td> <td>Twelve </td> <td>Thirteen </td> <td>Fourteen </td> <td>Fifteen </td> <td>Sixteen </td> <td>Seventeen </td> <td>Eighteen </td> <td>Nineteen </td> <td>Twenty </td> </tr> </table> </fieldset> </div> <div id="divRadioButtonArea"> <fieldset style=" padding-left: 5px;"> <legend style="color: #000; height:auto">Colors</legend> <table style="width:100%;padding-left:5%;padding-right:5%;"> <tr> <td> <input type="radio" name="A" value="Y"/><label>Red</label> </td> <td> <input type="radio" name="O" value="O"/><label>White</label> </td> <td> <input type="radio" name="W"/><label>Blue</label> </td> </tr> </table> </fieldset> </div> </div> </body> </html> Broken HTML file: <!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01//EN" "http://www.w3.org/TR/html4/strict.dtd"> <html> <head> <meta http-equiv="Content-Type" content="text/html; charset=UTF-8"/> <meta http-equiv="Content-Style-Type" content="text/css"></meta> <style type="text/css"> #divBody { margin-top: 5px; top:24px; margin-top: 10px; } #divContainer { top: 5px; position:relative; min-height:100%; #width:expression(document.body.clientWidth < 830? "800": "90%" ); width:90%; min-width: 800px; padding-bottom:70px; } #divTopFieldSet { position:relative; margin:5px; top:5px; width:99%; } #divRadioButtonArea { position:relative; top:20px; height:51px; font-size: 12px; width:99%; margin:5px; } #divTable { position:relative; width:99%; margin:5px auto; overflow-x:scroll; } </style> <title>TEST TEST</title> </head> <body id="divBody"> <div id="divContainer" class="gridRegion"> <div id="divTopFieldSet"> <fieldset style="margin: 5px;"> <legend style="font-size: 12px; color: #000;">Numbers</legend> <div id="divTable"> <table border="1px"> <tr> <td>One </td> <td>Two </td> <td>Three </td> <td>Fout </td> <td>Five </td> <td>Six </td> <td>Seven </td> <td>Eight </td> <td>Nine </td> <td>Ten </td> <td>Eleven </td> <td>Twelve </td> <td>Thirteen </td> <td>Fourteen </td> <td>Fifteen </td> <td>Sixteen </td> <td>Seventeen </td> <td>Eighteen </td> <td>Nineteen </td> <td>Twenty </td> </tr> </table> </div> </fieldset> </div> <div id="divRadioButtonArea"> <fieldset style=" padding-left: 5px;"> <legend style="color: #000; height:auto">Colors</legend> <table style="width:100%;padding-left:5%;padding-right:5%;"> <tr> <td> <input type="radio" name="A" value="Y"/><label>Red</label> </td> <td> <input type="radio" name="O" value="O"/><label>White</label> </td> <td> <input type="radio" name="W"/><label>Blue</label> </td> </tr> </table> </fieldset> </div> </div> </body> </html>

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  • Is it possible to partition more than one way at a time in SQL Server?

    - by meeting_overload
    I'm considering various ways to partition my data in SQL Server. One approach I'm looking at is to partition a particular huge table into 8 partitions, then within each of these partitions to partition on a different partition column. Is this even possible in SQL Server, or am I limited to definining one parition column+function+scheme per table? I'm interested in the more general answer, but this strategy is one I'm considering for Distributed Partitioned View, where I'd partition the data under the first scheme using DPV to distribute the huge amount of data over 8 machines, and then on each machine partition that portion of the full table on another parition key in order to be able to drop (for example) sub-paritions as required.

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  • Need help displaying a table dynamically based on a drop down date selection

    - by Gideon
    I am designing a job rota planner for a company and need help displaying a dynamic table containing the staff details. I have the following tables in MySQL database: Staff, Event, and Job. The staff table holds staff details (staffed, name, address...etc), the Event table (eventide, eventName, Fromdate, Todate...etc) and the Job table holds (Jobid, Jobdate, Eventid(fk), Staffid (fk)). I need to dynamically display the available staff list from the staff table when the user selects the event and the date (3 drop downs: date, month, and year) from a PHP form. I need to display staff members that have not been assigned work on the selected date by checking the Jobdate in the Job table. I have been at this for all day and can't get around it. I am still learning PHP and would surely appreciate any help I can get. My current code displays all staff members when an event is selected: //Create the day pull-down menu. $days = range (1, 31); echo "<Select Name=day Value=''><Option>Day</option>"; foreach ($days as $value) { echo '<option value="'.$value.'">'.$value.'</option>\n'; } echo "</Select>"; echo "</td><td>"; //Create the month pull-down menu echo "<Select Name=month Value=''><Option>Month</option>"; echo "<option value='01'>Jan</option>"; echo "<option value='02'>Feb</option>"; echo "<option value='03'>Mar</option>"; echo "<option value='04'>Apr</option>"; echo "<option value='05'>May</option>"; echo "<option value='06'>Jun</option>"; echo "<option value='07'>Jul</option>"; echo "<option value='08'>Aug</option>"; echo "<option value='09'>Sep</option>"; echo "<option value='10'>Oct</option>"; echo "<option value='11'>Nov</option>"; echo "<option value='12'>Dec</option>"; echo "</select>"; echo "</td><td>"; //Create the year pull-down menu $currentYear = date ("Y"); $years = range ($currentYear, 2020); echo "<Select Name=year Value=''><Option>Year</option>"; foreach ($years as $value) { echo '<option value="'.$value.'">'.$value.'</option>\n'; } echo "</Select>"; echo "</td></tr></table>"; echo "</td><td>"; //echo "<img src='../ETMSimages/etms_staff.png'</img></td><td>"; //construct the available staff list $staffsql = "SELECT StaffId, LastName, FirstName FROM Staff order by StaffId"; $staffResult = mysql_query($staffsql); if ($staffResult){ echo "<p><table cellspacing='1' cellpadding='3'>"; echo "<th colspan=6>List of Available Staff</th>"; echo "</tr><tr><th> Select</th><th>Id</th><th></th><th>Last Name </th><th></th><th>First Name </th></tr>"; while ($staffarray = mysql_fetch_array($staffResult)) { echo "<tr onMouseOver= this.bgColor = 'red' onMouseOut =this.bgColor = 'white' bgcolor= '#FFFFFF'> <td align=center><input type='checkbox' name='selectbox[]' id='selectbox[]' value=".$staffarray['StaffId']."> </td><td align=left>".$staffarray['StaffId']." </td><td>&nbsp&nbsp</td><td align=center>".$staffarray['LastName']." </td><td>&nbsp&nbsp</td><td align=center>".$staffarray['FirstName']." </td></tr>"; } echo "</table>"; } else { echo "<br> The Staff list can not be displayed!"; } echo "</td></tr>"; echo "<tr><td></td>"; echo "<td align=center><input type='submit' name='Submit' value='Assign Staff'>&nbsp&nbsp"; echo "<input type='reset' value='Start Over'>"; echo "</td></tr>"; echo "</table>";

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  • Partitioned Repository for WebCenter Content using Oracle Database 11g

    - by Adao Junior
    One of the biggest challenges for content management solutions is related to the storage management due the high volumes of the unstoppable growing of information. Even if you have storage appliances and a lot of terabytes, thinks like backup, compression, deduplication, storage relocation, encryption, availability could be a nightmare. One standard option that you have with the Oracle WebCenter Content is to store data to the database. And the Oracle Database allows you leverage features like compression, deduplication, encryption and seamless backup. But with a huge volume, the challenge is passed to the DBA to keep the WebCenter Content Database up and running. One solution is the use of DB partitions for your content repository, but what are the implications of this? Can I fit this with my business requirements? Well, yes. It’s up to you how you will manage that, you just need a good plan. During you “storage brainstorm plan” take in your mind what you need, such as storage petabytes of documents? You need everything on-line? There’s a way to logically separate the “good content” from the “legacy content”? The first thing that comes to my mind is to use the creation date of the document, but you need to remember that this document could receive a lot of revisions and maybe you can consider the revision creation date. Your plan can have also complex rules like per Document Type or per a custom metadata like department or an hybrid per date, per DocType and an specific virtual folder. Extrapolation the use, you can have your repository distributed in different servers, different disks, different disk types (Such as ssds, sas, sata, tape,…), separated accordingly your business requirements, separating the “hot” content from the legacy and easily matching your compliance requirements. If you think to use by revision, the simple way is to consider the dId, that is the sequential unique id for every content created using the WebCenter Content or the dLastModified that is the date field of the FileStorage table that contains the date of inclusion of the content to the DB Table using SecureFiles. Using the scenario of partitioned repository using an hierarchical separation by date, we will transform the FileStorage table in an partitioned table using  “Partition by Range” of the dLastModified column (You can use the dId or a join with other tables for other metadata such as dDocType, Security, etc…). The test scenario bellow covers: Previous existent data on the JDBC Storage to be migrated to the new partitioned JDBC Storage Partition by Date Automatically generation of new partitions based on a pre-defined interval (Available only with Oracle Database 11g+) Deduplication and Compression for legacy data Oracle WebCenter Content 11g PS5 (Could present some customizations that do not affect the test scenario) For the test case you need some data stored using JDBC Storage to be the “legacy” data. If you do not have done before, just create an Storage rule pointed to the JDBC Storage: Enable the metadata StorageRule in the UI and upload some documents using this rule. For this test case you can run using the schema owner or an dba user. We will use the schema owner TESTS_OCS. I can’t forgot to tell that this is just a test and you should do a proper backup of your environment. When you use the schema owner, you need some privileges, using the dba user grant the privileges needed: REM Grant privileges required for online redefinition. GRANT EXECUTE ON DBMS_REDEFINITION TO TESTS_OCS; GRANT ALTER ANY TABLE TO TESTS_OCS; GRANT DROP ANY TABLE TO TESTS_OCS; GRANT LOCK ANY TABLE TO TESTS_OCS; GRANT CREATE ANY TABLE TO TESTS_OCS; GRANT SELECT ANY TABLE TO TESTS_OCS; REM Privileges required to perform cloning of dependent objects. GRANT CREATE ANY TRIGGER TO TESTS_OCS; GRANT CREATE ANY INDEX TO TESTS_OCS; In our test scenario we will separate the content as Legacy, Day1, Day2, Day3 and Future. This last one will partitioned automatically using 3 tablespaces in a round robin mode. In a real scenario the partition rule could be per month, per year or any rule that you choose. Table spaces for the test scenario: CREATE TABLESPACE TESTS_OCS_PART_LEGACY DATAFILE 'tests_ocs_part_legacy.dat' SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_DAY1 DATAFILE 'tests_ocs_part_day1.dat' SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_DAY2 DATAFILE 'tests_ocs_part_day2.dat' SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_DAY3 DATAFILE 'tests_ocs_part_day3.dat' SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_ROUND_ROBIN_A 'tests_ocs_part_round_robin_a.dat' DATAFILE SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_ROUND_ROBIN_B 'tests_ocs_part_round_robin_b.dat' DATAFILE SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; CREATE TABLESPACE TESTS_OCS_PART_ROUND_ROBIN_C 'tests_ocs_part_round_robin_c.dat' DATAFILE SIZE 500K AUTOEXTEND ON NEXT 500K MAXSIZE UNLIMITED; Before start, gather optimizer statistics on the actual FileStorage table: EXEC DBMS_STATS.GATHER_TABLE_STATS(USER, 'FileStorage', cascade => TRUE); Now check if is possible execute the redefinition process: EXEC DBMS_REDEFINITION.CAN_REDEF_TABLE('TESTS_OCS', 'FileStorage',DBMS_REDEFINITION.CONS_USE_PK); If no errors messages, you are good to go. Create a Partitioned Interim FileStorage table. You need to create a new table with the partition information to act as an interim table: CREATE TABLE FILESTORAGE_Part ( DID NUMBER(*,0) NOT NULL ENABLE, DRENDITIONID VARCHAR2(30 CHAR) NOT NULL ENABLE, DLASTMODIFIED TIMESTAMP (6), DFILESIZE NUMBER(*,0), DISDELETED VARCHAR2(1 CHAR), BFILEDATA BLOB ) LOB (BFILEDATA) STORE AS SECUREFILE ( ENABLE STORAGE IN ROW NOCACHE LOGGING KEEP_DUPLICATES NOCOMPRESS ) PARTITION BY RANGE (DLASTMODIFIED) INTERVAL (NUMTODSINTERVAL(1,'DAY')) STORE IN (TESTS_OCS_PART_ROUND_ROBIN_A, TESTS_OCS_PART_ROUND_ROBIN_B, TESTS_OCS_PART_ROUND_ROBIN_C) ( PARTITION FILESTORAGE_PART_LEGACY VALUES LESS THAN (TO_DATE('05-APR-2012 12.00.00 AM', 'DD-MON-YYYY HH.MI.SS AM')) TABLESPACE TESTS_OCS_PART_LEGACY LOB (BFILEDATA) STORE AS SECUREFILE ( TABLESPACE TESTS_OCS_PART_LEGACY RETENTION NONE DEDUPLICATE COMPRESS HIGH ), PARTITION FILESTORAGE_PART_DAY1 VALUES LESS THAN (TO_DATE('06-APR-2012 07.25.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) TABLESPACE TESTS_OCS_PART_DAY1 LOB (BFILEDATA) STORE AS SECUREFILE ( TABLESPACE TESTS_OCS_PART_DAY1 RETENTION AUTO KEEP_DUPLICATES COMPRESS ), PARTITION FILESTORAGE_PART_DAY2 VALUES LESS THAN (TO_DATE('06-APR-2012 07.55.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) TABLESPACE TESTS_OCS_PART_DAY2 LOB (BFILEDATA) STORE AS SECUREFILE ( TABLESPACE TESTS_OCS_PART_DAY2 RETENTION AUTO KEEP_DUPLICATES NOCOMPRESS ), PARTITION FILESTORAGE_PART_DAY3 VALUES LESS THAN (TO_DATE('06-APR-2012 07.58.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) TABLESPACE TESTS_OCS_PART_DAY3 LOB (BFILEDATA) STORE AS SECUREFILE ( TABLESPACE TESTS_OCS_PART_DAY3 RETENTION AUTO KEEP_DUPLICATES NOCOMPRESS ) ); After the creation you should see your partitions defined. Note that only the fixed range partitions have been created, none of the interval partition have been created. Start the redefinition process: BEGIN DBMS_REDEFINITION.START_REDEF_TABLE( uname => 'TESTS_OCS' ,orig_table => 'FileStorage' ,int_table => 'FileStorage_PART' ,col_mapping => NULL ,options_flag => DBMS_REDEFINITION.CONS_USE_PK ); END; This operation can take some time to complete, depending how many contents that you have and on the size of the table. Using the DBA user you can check the progress with this command: SELECT * FROM v$sesstat WHERE sid = 1; Copy dependent objects: DECLARE redefinition_errors PLS_INTEGER := 0; BEGIN DBMS_REDEFINITION.COPY_TABLE_DEPENDENTS( uname => 'TESTS_OCS' ,orig_table => 'FileStorage' ,int_table => 'FileStorage_PART' ,copy_indexes => DBMS_REDEFINITION.CONS_ORIG_PARAMS ,copy_triggers => TRUE ,copy_constraints => TRUE ,copy_privileges => TRUE ,ignore_errors => TRUE ,num_errors => redefinition_errors ,copy_statistics => FALSE ,copy_mvlog => FALSE ); IF (redefinition_errors > 0) THEN DBMS_OUTPUT.PUT_LINE('>>> FileStorage to FileStorage_PART temp copy Errors: ' || TO_CHAR(redefinition_errors)); END IF; END; With the DBA user, verify that there's no errors: SELECT object_name, base_table_name, ddl_txt FROM DBA_REDEFINITION_ERRORS; *Note that will show 2 lines related to the constrains, this is expected. Synchronize the interim table FileStorage_PART: BEGIN DBMS_REDEFINITION.SYNC_INTERIM_TABLE( uname => 'TESTS_OCS', orig_table => 'FileStorage', int_table => 'FileStorage_PART'); END; Gather statistics on the new table: EXEC DBMS_STATS.GATHER_TABLE_STATS(USER, 'FileStorage_PART', cascade => TRUE); Complete the redefinition: BEGIN DBMS_REDEFINITION.FINISH_REDEF_TABLE( uname => 'TESTS_OCS', orig_table => 'FileStorage', int_table => 'FileStorage_PART'); END; During the execution the FileStorage table is locked in exclusive mode until finish the operation. After the last command the FileStorage table is partitioned. If you have contents out of the range partition, you should see the new partitions created automatically, not generating an error if you “forgot” to create all the future ranges. You will see something like: You now can drop the FileStorage_PART table: border-bottom-width: 1px; border-bottom-style: solid; text-align: left; border-left-color: silver; border-left-width: 1px; border-left-style: solid; padding-bottom: 4px; line-height: 12pt; background-color: #f4f4f4; margin-top: 20px; margin-right: 0px; margin-bottom: 10px; margin-left: 0px; padding-left: 4px; width: 97.5%; padding-right: 4px; font-family: 'Courier New', Courier, monospace; direction: ltr; max-height: 200px; font-size: 8pt; overflow-x: auto; overflow-y: auto; border-top-color: silver; border-top-width: 1px; border-top-style: solid; cursor: text; border-right-color: silver; border-right-width: 1px; border-right-style: solid; padding-top: 4px; " id="codeSnippetWrapper"> DROP TABLE FileStorage_PART PURGE; To check the FileStorage table is valid and is partitioned, use the command: SELECT num_rows,partitioned FROM user_tables WHERE table_name = 'FILESTORAGE'; You can list the contents of the FileStorage table in a specific partition, per example: SELECT * FROM FileStorage PARTITION (FILESTORAGE_PART_LEGACY) Some useful commands that you can use to check the partitions, note that you need to run using a DBA user: SELECT * FROM DBA_TAB_PARTITIONS WHERE table_name = 'FILESTORAGE';   SELECT * FROM DBA_TABLESPACES WHERE tablespace_name like 'TESTS_OCS%'; After the redefinition process complete you have a new FileStorage table storing all content that has the Storage rule pointed to the JDBC Storage and partitioned using the rule set during the creation of the temporary interim FileStorage_PART table. At this point you can test the WebCenter Content downloading the documents (Original and Renditions). Note that the content could be already in the cache area, take a look in the weblayout directory to see if a file with the same id is there, then click on the web rendition of your test file and see if have created the file and you can open, this means that is all working. The redefinition process can be repeated many times, this allow you test what the better layout, over and over again. Now some interesting maintenance actions related to the partitions: Make an tablespace read only. No issues viewing, the WebCenter Content do not alter the revisions When try to delete an content that is part of an read only tablespace, an error will occurs and the document will not be deleted The only way to prevent errors today is creating an custom component that checks the partitions and if you have an document in an “Read Only” repository, execute the deletion process of the metadata and mark the document to be deleted on the next db maintenance, like a new redefinition. Take an tablespace off-line for archiving purposes or any other reason. When you try open an document that is included in this tablespace will receive an error that was unable to retrieve the content, but the others online tablespaces are not affected. Same behavior when deleting documents. Again, an custom component is the solution. If you have an document “out of range”, the component can show an message that the repository for that document is offline. This can be extended to a option to the user to request to put online again. Moving some legacy content to an offline repository (table) using the Exchange option to move the content from one partition to a empty nonpartitioned table like FileStorage_LEGACY. Note that this option will remove the registers from the FileStorage and will not be able to open the stored content. You always need to keep in mind the indexes and constrains. An redefinition separating the original content (vault) from the renditions and separate by date ate the same time. This could be an option for DAM environments that want to have an special place for the renditions and put the original files in a storage with less performance. The process will be the same, you just need to change the script of the interim table to use composite partitioning. Will be something like: CREATE TABLE FILESTORAGE_RenditionPart ( DID NUMBER(*,0) NOT NULL ENABLE, DRENDITIONID VARCHAR2(30 CHAR) NOT NULL ENABLE, DLASTMODIFIED TIMESTAMP (6), DFILESIZE NUMBER(*,0), DISDELETED VARCHAR2(1 CHAR), BFILEDATA BLOB ) LOB (BFILEDATA) STORE AS SECUREFILE ( ENABLE STORAGE IN ROW NOCACHE LOGGING KEEP_DUPLICATES NOCOMPRESS ) PARTITION BY LIST (DRENDITIONID) SUBPARTITION BY RANGE (DLASTMODIFIED) ( PARTITION Vault VALUES ('primaryFile') ( SUBPARTITION FILESTORAGE_VAULT_LEGACY VALUES LESS THAN (TO_DATE('05-APR-2012 12.00.00 AM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_VAULT_DAY1 VALUES LESS THAN (TO_DATE('06-APR-2012 07.25.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_VAULT_DAY2 VALUES LESS THAN (TO_DATE('06-APR-2012 07.55.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_VAULT_DAY3 VALUES LESS THAN (TO_DATE('06-APR-2012 07.58.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_VAULT_FUTURE VALUES LESS THAN (MAXVALUE) ) ,PARTITION WebLayout VALUES ('webViewableFile') ( SUBPARTITION FILESTORAGE_WEBLAYOUT_LEGACY VALUES LESS THAN (TO_DATE('05-APR-2012 12.00.00 AM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_WEBLAYOUT_DAY1 VALUES LESS THAN (TO_DATE('06-APR-2012 07.25.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_WEBLAYOUT_DAY2 VALUES LESS THAN (TO_DATE('06-APR-2012 07.55.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_WEBLAYOUT_DAY3 VALUES LESS THAN (TO_DATE('06-APR-2012 07.58.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_WEBLAYOUT_FUTURE VALUES LESS THAN (MAXVALUE) ) ,PARTITION Special VALUES ('Special') ( SUBPARTITION FILESTORAGE_SPECIAL_LEGACY VALUES LESS THAN (TO_DATE('05-APR-2012 12.00.00 AM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_SPECIAL_DAY1 VALUES LESS THAN (TO_DATE('06-APR-2012 07.25.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_SPECIAL_DAY2 VALUES LESS THAN (TO_DATE('06-APR-2012 07.55.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_SPECIAL_DAY3 VALUES LESS THAN (TO_DATE('06-APR-2012 07.58.00 PM', 'DD-MON-YYYY HH.MI.SS AM')) LOB (BFILEDATA) STORE AS SECUREFILE , SUBPARTITION FILESTORAGE_SPECIAL_FUTURE VALUES LESS THAN (MAXVALUE) ) )ENABLE ROW MOVEMENT; The next post related to partitioned repository will come with an sample component to handle the possible exceptions when you need to take off line an tablespace/partition or move to another place. Also, we can include some integration to the Retention Management and Records Management. Another subject related to partitioning is the ability to create an FileStore Provider pointed to a different database, raising the level of the distributed storage vs. performance. Let us know if this is important to you or you have an use case not listed, leave a comment. Cross-posted on the blog.ContentrA.com

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  • How to archive data from a table to a local or remote database in SQL 2005 and SQL 2008

    - by simonsabin
    Often you have the need to archive data from a table. This leads to a number of challenges 1. How can you do it without impacting users 2. How can I make it transactionally consistent, i.e. the data I put in the archive is the data I remove from the main table 3. How can I get it to perform well Points 1 is very much tied to point 3. If it doesn't perform well then the delete of data is going to cause lots of locks and thus potentially blocking. For points 1 and 3 refer to my previous posts DELETE-TOP-x-rows-avoiding-a-table-scan and UPDATE-and-DELETE-TOP-and-ORDER-BY---Part2. In essence you need to be removing small chunks of data from your table and you want to do that avoiding a table scan. So that deals with the delete approach but archiving is about inserting that data somewhere else. Well in SQL 2008 they introduced a new feature INSERT over DML (Data Manipulation Language, i.e. SQL statements that change data), or composable DML. The ability to nest DML statements within themselves, so you can past the results of an insert to an update to a merge. I've mentioned this before here SQL-Server-2008---MERGE-and-optimistic-concurrency. This feature is currently limited to being able to consume the results of a DML statement in an INSERT statement. There are many restrictions which you can find here http://msdn.microsoft.com/en-us/library/ms177564.aspx look for the section "Inserting Data Returned From an OUTPUT Clause Into a Table" Even with the restrictions what we can do is consume the OUTPUT from a DELETE and INSERT the results into a table in another database. Note that in BOL it refers to not being able to use a remote table, remote means a table on another SQL instance. To show this working use this SQL to setup two databases foo and fooArchive create database foo go --create the source table fred in database foo select * into foo..fred from sys.objects go create database fooArchive go if object_id('fredarchive',DB_ID('fooArchive')) is null begin     select getdate() ArchiveDate,* into fooArchive..FredArchive from sys.objects where 1=2       end go And then we can use this simple statement to archive the data insert into fooArchive..FredArchive select getdate(),d.* from (delete top (1)         from foo..Fred         output deleted.*) d         go In this statement the delete can be any delete statement you wish so if you are deleting by ids or a range of values then you can do that. Refer to the DELETE-TOP-x-rows-avoiding-a-table-scan post to ensure that your delete is going to perform. The last thing you want to do is to perform 100 deletes each with 5000 records for each of those deletes to do a table scan. For a solution that works for SQL2005 or if you want to archive to a different server then you can use linked servers or SSIS. This example shows how to do it with linked servers. [ONARC-LAP03] is the source server. begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d commit transaction and to prove the transactions work try, you should get the same number of records before and after. select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   begin transaction insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*') d rollback transaction   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive The transactions are very important with this solution. Look what happens when you don't have transactions and an error occurs   select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive   insert into fooArchive..FredArchive select getdate(),d.* from openquery ([ONARC-LAP03],'delete top (1)                     from foo..Fred                     output deleted.*                     raiserror (''Oh doo doo'',15,15)') d                     select (select count(1) from foo..Fred) fred        ,(select COUNT(1) from fooArchive..FredArchive ) fredarchive Before running this think what the result would be. I got it wrong. What seems to happen is that the remote query is executed as a transaction, the error causes that to rollback. However the results have already been sent to the client and so get inserted into the

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  • 64-bit Archives Needed

    - by user9154181
    A little over a year ago, we received a question from someone who was trying to build software on Solaris. He was getting errors from the ar command when creating an archive. At that time, the ar command on Solaris was a 32-bit command. There was more than 2GB of data, and the ar command was hitting the file size limit for a 32-bit process that doesn't use the largefile APIs. Even in 2011, 2GB is a very large amount of code, so we had not heard this one before. Most of our toolchain was extended to handle 64-bit sized data back in the 1990's, but archives were not changed, presumably because there was no perceived need for it. Since then of course, programs have continued to get larger, and in 2010, the time had finally come to investigate the issue and find a way to provide for larger archives. As part of that process, I had to do a deep dive into the archive format, and also do some Unix archeology. I'm going to record what I learned here, to document what Solaris does, and in the hope that it might help someone else trying to solve the same problem for their platform. Archive Format Details Archives are hardly cutting edge technology. They are still used of course, but their basic form hasn't changed in decades. Other than to fix a bug, which is rare, we don't tend to touch that code much. The archive file format is described in /usr/include/ar.h, and I won't repeat the details here. Instead, here is a rough overview of the archive file format, implemented by System V Release 4 (SVR4) Unix systems such as Solaris: Every archive starts with a "magic number". This is a sequence of 8 characters: "!<arch>\n". The magic number is followed by 1 or more members. A member starts with a fixed header, defined by the ar_hdr structure in/usr/include/ar.h. Immediately following the header comes the data for the member. Members must be padded at the end with newline characters so that they have even length. The requirement to pad members to an even length is a dead giveaway as to the age of the archive format. It tells you that this format dates from the 1970's, and more specifically from the era of 16-bit systems such as the PDP-11 that Unix was originally developed on. A 32-bit system would have required 4 bytes, and 64-bit systems such as we use today would probably have required 8 bytes. 2 byte alignment is a poor choice for ELF object archive members. 32-bit objects require 4 byte alignment, and 64-bit objects require 64-bit alignment. The link-editor uses mmap() to process archives, and if the members have the wrong alignment, we have to slide (copy) them to the correct alignment before we can access the ELF data structures inside. The archive format requires 2 byte padding, but it doesn't prohibit more. The Solaris ar command takes advantage of this, and pads ELF object members to 8 byte boundaries. Anything else is padded to 2 as required by the format. The archive header (ar_hdr) represents all numeric values using an ASCII text representation rather than as binary integers. This means that an archive that contains only text members can be viewed using tools such as cat, more, or a text editor. The original designers of this format clearly thought that archives would be used for many file types, and not just for objects. Things didn't turn out that way of course — nearly all archives contain relocatable objects for a single operating system and machine, and are used primarily as input to the link-editor (ld). Archives can have special members that are created by the ar command rather than being supplied by the user. These special members are all distinguished by having a name that starts with the slash (/) character. This is an unambiguous marker that says that the user could not have supplied it. The reason for this is that regular archive members are given the plain name of the file that was inserted to create them, and any path components are stripped off. Slash is the delimiter character used by Unix to separate path components, and as such cannot occur within a plain file name. The ar command hides the special members from you when you list the contents of an archive, so most users don't know that they exist. There are only two possible special members: A symbol table that maps ELF symbols to the object archive member that provides it, and a string table used to hold member names that exceed 15 characters. The '/' convention for tagging special members provides room for adding more such members should the need arise. As I will discuss below, we took advantage of this fact to add an alternate 64-bit symbol table special member which is used in archives that are larger than 4GB. When an archive contains ELF object members, the ar command builds a special archive member known as the symbol table that maps all ELF symbols in the object to the archive member that provides it. The link-editor uses this symbol table to determine which symbols are provided by the objects in that archive. If an archive has a symbol table, it will always be the first member in the archive, immediately following the magic number. Unlike member headers, symbol tables do use binary integers to represent offsets. These integers are always stored in big-endian format, even on a little endian host such as x86. The archive header (ar_hdr) provides 15 characters for representing the member name. If any member has a name that is longer than this, then the real name is written into a special archive member called the string table, and the member's name field instead contains a slash (/) character followed by a decimal representation of the offset of the real name within the string table. The string table is required to precede all normal archive members, so it will be the second member if the archive contains a symbol table, and the first member otherwise. The archive format is not designed to make finding a given member easy. Such operations move through the archive from front to back examining each member in turn, and run in O(n) time. This would be bad if archives were commonly used in that manner, but in general, they are not. Typically, the ar command is used to build an new archive from scratch, inserting all the objects in one operation, and then the link-editor accesses the members in the archive in constant time by using the offsets provided by the symbol table. Both of these operations are reasonably efficient. However, listing the contents of a large archive with the ar command can be rather slow. Factors That Limit Solaris Archive Size As is often the case, there was more than one limiting factor preventing Solaris archives from growing beyond the 32-bit limits of 2GB (32-bit signed) and 4GB (32-bit unsigned). These limits are listed in the order they are hit as archive size grows, so the earlier ones mask those that follow. The original Solaris archive file format can handle sizes up to 4GB without issue. However, the ar command was delivered as a 32-bit executable that did not use the largefile APIs. As such, the ar command itself could not create a file larger than 2GB. One can solve this by building ar with the largefile APIs which would allow it to reach 4GB, but a simpler and better answer is to deliver a 64-bit ar, which has the ability to scale well past 4GB. Symbol table offsets are stored as 32-bit big-endian binary integers, which limits the maximum archive size to 4GB. To get around this limit requires a different symbol table format, or an extension mechanism to the current one, similar in nature to the way member names longer than 15 characters are handled in member headers. The size field in the archive member header (ar_hdr) is an ASCII string capable of representing a 32-bit unsigned value. This places a 4GB size limit on the size of any individual member in an archive. In considering format extensions to get past these limits, it is important to remember that very few archives will require the ability to scale past 4GB for many years. The old format, while no beauty, continues to be sufficient for its purpose. This argues for a backward compatible fix that allows newer versions of Solaris to produce archives that are compatible with older versions of the system unless the size of the archive exceeds 4GB. Archive Format Differences Among Unix Variants While considering how to extend Solaris archives to scale to 64-bits, I wanted to know how similar archives from other Unix systems are to those produced by Solaris, and whether they had already solved the 64-bit issue. I've successfully moved archives between different Unix systems before with good luck, so I knew that there was some commonality. If it turned out that there was already a viable defacto standard for 64-bit archives, it would obviously be better to adopt that rather than invent something new. The archive file format is not formally standardized. However, the ar command and archive format were part of the original Unix from Bell Labs. Other systems started with that format, extending it in various often incompatible ways, but usually with the same common shared core. Most of these systems use the same magic number to identify their archives, despite the fact that their archives are not always fully compatible with each other. It is often true that archives can be copied between different Unix variants, and if the member names are short enough, the ar command from one system can often read archives produced on another. In practice, it is rare to find an archive containing anything other than objects for a single operating system and machine type. Such an archive is only of use on the type of system that created it, and is only used on that system. This is probably why cross platform compatibility of archives between Unix variants has never been an issue. Otherwise, the use of the same magic number in archives with incompatible formats would be a problem. I was able to find information for a number of Unix variants, described below. These can be divided roughly into three tribes, SVR4 Unix, BSD Unix, and IBM AIX. Solaris is a SVR4 Unix, and its archives are completely compatible with those from the other members of that group (GNU/Linux, HP-UX, and SGI IRIX). AIX AIX is an exception to rule that Unix archive formats are all based on the original Bell labs Unix format. It appears that AIX supports 2 formats (small and big), both of which differ in fundamental ways from other Unix systems: These formats use a different magic number than the standard one used by Solaris and other Unix variants. They include support for removing archive members from a file without reallocating the file, marking dead areas as unused, and reusing them when new archive items are inserted. They have a special table of contents member (File Member Header) which lets you find out everything that's in the archive without having to actually traverse the entire file. Their symbol table members are quite similar to those from other systems though. Their member headers are doubly linked, containing offsets to both the previous and next members. Of the Unix systems described here, AIX has the only format I saw that will have reasonable insert/delete performance for really large archives. Everyone else has O(n) performance, and are going to be slow to use with large archives. BSD BSD has gone through 4 versions of archive format, which are described in their manpage. They use the same member header as SVR4, but their symbol table format is different, and their scheme for long member names puts the name directly after the member header rather than into a string table. GNU/Linux The GNU toolchain uses the SVR4 format, and is compatible with Solaris. HP-UX HP-UX seems to follow the SVR4 model, and is compatible with Solaris. IRIX IRIX has 32 and 64-bit archives. The 32-bit format is the standard SVR4 format, and is compatible with Solaris. The 64-bit format is the same, except that the symbol table uses 64-bit integers. IRIX assumes that an archive contains objects of a single ELFCLASS/MACHINE, and any archive containing ELFCLASS64 objects receives a 64-bit symbol table. Although they only use it for 64-bit objects, nothing in the archive format limits it to ELFCLASS64. It would be perfectly valid to produce a 64-bit symbol table in an archive containing 32-bit objects, text files, or anything else. Tru64 Unix (Digital/Compaq/HP) Tru64 Unix uses a format much like ours, but their symbol table is a hash table, making specific symbol lookup much faster. The Solaris link-editor uses archives by examining the entire symbol table looking for unsatisfied symbols for the link, and not by looking up individual symbols, so there would be no benefit to Solaris from such a hash table. The Tru64 ld must use a different approach in which the hash table pays off for them. Widening the existing SVR4 archive symbol tables rather than inventing something new is the simplest path forward. There is ample precedent for this approach in the ELF world. When ELF was extended to support 64-bit objects, the approach was largely to take the existing data structures, and define 64-bit versions of them. We called the old set ELF32, and the new set ELF64. My guess is that there was no need to widen the archive format at that time, but had there been, it seems obvious that this is how it would have been done. The Implementation of 64-bit Solaris Archives As mentioned earlier, there was no desire to improve the fundamental nature of archives. They have always had O(n) insert/delete behavior, and for the most part it hasn't mattered. AIX made efforts to improve this, but those efforts did not find widespread adoption. For the purposes of link-editing, which is essentially the only thing that archives are used for, the existing format is adequate, and issues of backward compatibility trump the desire to do something technically better. Widening the existing symbol table format to 64-bits is therefore the obvious way to proceed. For Solaris 11, I implemented that, and I also updated the ar command so that a 64-bit version is run by default. This eliminates the 2 most significant limits to archive size, leaving only the limit on an individual archive member. We only generate a 64-bit symbol table if the archive exceeds 4GB, or when the new -S option to the ar command is used. This maximizes backward compatibility, as an archive produced by Solaris 11 is highly likely to be less than 4GB in size, and will therefore employ the same format understood by older versions of the system. The main reason for the existence of the -S option is to allow us to test the 64-bit format without having to construct huge archives to do so. I don't believe it will find much use outside of that. Other than the new ability to create and use extremely large archives, this change is largely invisible to the end user. When reading an archive, the ar command will transparently accept either form of symbol table. Similarly, the ELF library (libelf) has been updated to understand either format. Users of libelf (such as the link-editor ld) do not need to be modified to use the new format, because these changes are encapsulated behind the existing functions provided by libelf. As mentioned above, this work did not lift the limit on the maximum size of an individual archive member. That limit remains fixed at 4GB for now. This is not because we think objects will never get that large, for the history of computing says otherwise. Rather, this is based on an estimation that single relocatable objects of that size will not appear for a decade or two. A lot can change in that time, and it is better not to overengineer things by writing code that will sit and rot for years without being used. It is not too soon however to have a plan for that eventuality. When the time comes when this limit needs to be lifted, I believe that there is a simple solution that is consistent with the existing format. The archive member header size field is an ASCII string, like the name, and as such, the overflow scheme used for long names can also be used to handle the size. The size string would be placed into the archive string table, and its offset in the string table would then be written into the archive header size field using the same format "/ddd" used for overflowed names.

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  • How to make my newly created secondary partition accessible?

    - by cipricus
    I have decided to reinstall my Lubuntu OS and to split on the occasion my partition so as to have a secondary one where long-time files would be stored. When trying to install the system onto the smaller one, I was prompted to set a different mount point for the other (different from /). Not knowing what to do I selected /boot for the second and went on installing on the first one. All was ok except that now the larger/secondary (/boot mount point) partition is not visible. In Gparted it is:

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  • find the next due date after today within a group in an Excel PivotTable

    - by Dennis George
    I have got a table set up in one sheet with "transactions". Each row contains a name of a vendor, the amount owed or paid depending on transaction type, and the due date/transaction date. Here is some simplified sample data: Vendor Date Invoice Payment Vendor A 6/30 $200 Vendor A 6/30 ($200) Vendor B 7/5 $500 Vendor B 7/5 ($500) Vendor C 10/28 $50 Vendor A 10/30 $100 Vendor C 11/15 $50 I have already built a PivotTable from that table to group these transactions by vendor and sum the remainder owed. What I'm trying to figure out is how to, for each vendor, get the next due date (min date of the group, excluding dates < Today()), or if there is no next due date then I want to see the max date for that group. Here is what my PivotTable looks like, plus the date column I'd like to add (assuming Today() = 10/23): Vendor Date Owed Vendor B 7/5 - Vendor C 10/28 $100 Vendor A 10/30 $100 I know calling it next due date might not be so accurate if I end up with the date of a payment in that column, but I'm ok with that. tl;dr : I want to find the next earliest date within each group, or the last date. How do I do this?

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  • Error code 1005 (errno: 121) upon create table while restoring MySQL database from a dump

    - by Jonathan
    I have a linux prod machine and a Win7 64bit dev machine. My workflow includes dumping the production MySQL database on the linux machine and restoring it in my local MySQL database on the windows machine (using SQLyog). This worked fine for a long time. Following some trouble, I formatted and reinstalled my windows dev machine. Since then I'm unable to restore the db on it. I keep receiving the following error: Query: CREATE TABLE `auth_group` ( `id` int(11) NOT NULL auto_increment, `name` varchar(80) collate utf8_unicode_ci NOT NULL, PRIMARY KEY (`id`), UNIQUE KEY `name` (`name`) ) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci Error occured at:2010-06-26 17:16:14 Line no.:30 Error Code: 1005 - Can't create table 'ap_site.auth_group' (errno: 121) Notice that this is the first create table statement in the sql dump file. This error occurs both on MySQL Community Server 5.1.41 and 5.1.48 and with SQLyog Community 8.0.4 and 8.5.1. I really don't know what's different in my configuration from before the reinstall and now and why does it have this effect. Restoring from sql dump is something I need to keep on doing, so I need a permanent fix and not a tailored workaround.

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  • Spring-mvc project can't select from a particular mysql table

    - by Dan Ray
    I'm building a Spring-mvc project (using JPA and Hibernate for DB access) that is running just great locally, on my dev box, with a local MySQL database. Now I'm trying to put a snapshot up on a staging server for my client to play with, and I'm having trouble. Tomcat (after some wrestling) deploys my war file without complaint, and I can get some response from the application over the browser. When I hit my main page, which is behind Spring Security authentication, it redirects me to the login page, which works perfectly. I have Security configured to query the database for user details, and that works fine. In fact, a change to a password in the database is reflected in the behavior of the login form, so I'm confident it IS reaching the database and querying the user table. Once authenticated, we go to the first "real" page of the app, and I get a "data access failure" error. The server's console log gets this line (redacted): ERROR org.hibernate.util.JDBCExceptionReporter - SELECT command denied to user 'myDbUser'@'localhost' for table 'asset' However, if I go to MySQL from the shell using exactly the same creds, I have no problem at all selecting from the asset table: [development@tomcat01stg]$ mysql -u myDbUser -pmyDbPwd dbName ... mysql> \s -------------- mysql Ver 14.12 Distrib 5.0.77, for redhat-linux-gnu (i686) using readline 5.1 Connection id: 199 Current database: dbName Current user: myDbUser@localhost ... UNIX socket: /var/lib/mysql/mysql.sock -------------- mysql> select count(*) from asset; +----------+ | count(*) | +----------+ | 19 | +----------+ 1 row in set (0.00 sec) I've broken down my MySQL access settings, cleaned out the user and re-run the grant commands, set up a version of the user from 'localhost' and another from '%', making sure to flush permissions.... Nothing is changing the behavior of this thing. What gives?

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  • Cumulative average using data from multiple rows in an excel table

    - by Aaron E
    I am trying to calculate a cumulative average column on a table I'm making in excel. I use the totals row for the ending cumulative average, but I would like to add a column that gives a cumulative average for each row up to that point. So, if I have 3 rows I want each row to have a column giving the average up to that row and then the ending cumulative average in the totals row. Right now I can't figure this out because I'd be having to reference in a formula rows above and below the current row and I'm unsure about how to go about it because it's a table and not just cells. If it was just cells then I know how to do the formula and copy it down each row, but being that the formula I need depends on whether or not a new row in the table is added or not I keep thinking that my formula would be something like: (Completion rate row 1/n) where n is the number of rows up to that point, here row 1, then ((Completion rate row 1 + Completion rate row 2)/n) for row 2 so n=2, and so on for each new row added. Please advise.

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  • What is the fastest way to clone an INNODB table within the same server?

    - by Vic
    Our development server is a replication slave of our production server. We have a script that developers use if they want to run their applications/bug fixes against fresh data. That script looks like this: dbs=( analytics auth logs users ) server=localhost conn="-h ${server} -u ${username} --password=${password}" # Stop the replication client so we don't encounter weird data. echo "STOP SLAVE" | mysql ${conn} # Bunch of bulk insert optimizations echo "SET autocommit=0" | mysql ${conn} echo "SET unique_checks=0" | mysql ${conn} echo "SET foreign_key_checks=0" | mysql ${conn} # Restore all databases and tables. for sourcedb in ${dbs[*]} do destdb=${prefix}${sourcedb} echo "Dropping database ${destdb}..." echo "DROP DATABASE IF EXISTS ${destdb}" | mysql ${conn} echo "CREATE DATABASE ${destdb}" | mysql ${conn} # First, all the tables. for table in `echo "SHOW FULL TABLES WHERE Table_type <> 'VIEW'" | mysql $conn $sourcedb | tail -n +2`; do if [[ "${table}" != 'BASE' && "${table}" != 'TABLE' && "${table}" != 'VIEW' ]] ; then createTable=`echo "SHOW CREATE TABLE ${table}"|mysql -B -r $conn $sourcedb|tail -n +2|cut -f 2-` echo "Restoring ${destdb}/${table}..." echo "$createTable ;" | mysql $conn $destdb insertData="INSERT INTO ${destdb}.${table} SELECT * FROM ${sourcedb}.${table}" echo "$insertData" | mysql $conn $destdb fi fi done done echo "SET foreign_key_checks=1" | mysql ${conn} echo "SET unique_checks=1" | mysql ${conn} echo "COMMIT" | mysql ${conn} # Restart the replication client echo "START SLAVE" | mysql ${conn} All of these operations are, as I mentioned, within the same server. Is there a faster way to clone the tables I'm not seeing? They're all INNODB tables. Thanks!

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  • Error code 1005 (errno: 121) upon create table while restoring MySQL database from a dump

    - by Jonathan
    I have a linux prod machine and a Win7 64bit dev machine. My workflow includes dumping the production MySQL database on the linux machine and restoring it in my local MySQL database on the windows machine (using SQLyog). This worked fine for a long time. Following some trouble, I formatted and reinstalled my windows dev machine. Since then I'm unable to restore the db on it. I keep receiving the following error: Query: CREATE TABLE `auth_group` ( `id` int(11) NOT NULL auto_increment, `name` varchar(80) collate utf8_unicode_ci NOT NULL, PRIMARY KEY (`id`), UNIQUE KEY `name` (`name`) ) ENGINE=InnoDB AUTO_INCREMENT=2 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci Error occured at:2010-06-26 17:16:14 Line no.:30 Error Code: 1005 - Can't create table 'ap_site.auth_group' (errno: 121) Notice that this is the first create table statement in the sql dump file. This error occurs both on MySQL Community Server 5.1.41 and 5.1.48 and with SQLyog Community 8.0.4 and 8.5.1. I really don't know what's different in my configuration from before the reinstall and now and why does it have this effect. Restoring from sql dump is something I need to keep on doing, so I need a permanent fix and not a tailored workaround.

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  • Problems creating a functioning table

    - by Hoser
    This is a pretty simple SQL query I would assume, but I'm having problems getting it to work. if (object_id('#InfoTable')is not null) Begin Drop Table #InfoTable End create table #InfoTable (NameOfObject varchar(50), NameOfCounter varchar(50), SampledValue float(30), DayStamp datetime) insert into #InfoTable(NameOfObject, NameOfCounter, SampledValue, DayStamp) select vPerformanceRule.ObjectName AS NameOfObject, vPerformanceRule.CounterName AS NameOfCounter, Perf.vPerfRaw.SampleValue AS SampledValue, Perf.vPerfHourly.DateTime AS DayStamp from vPerformanceRule, vPerformanceRuleInstance, Perf.vPerfHourly, Perf.vPerfRaw where (ObjectName like 'Logical Disk' and CounterName like '% Free Space' AND SampleValue > 95 AND SampleValue < 100) order by DayStamp desc select NameOfObject, NameOfCounter, SampledValue, DayStamp from #InfoTable Drop Table #InfoTable I've tried various other forms of syntax, but no matter what I do, I get these error messages. Msg 207, Level 16, State 1, Line 10 Invalid column name 'NameOfObject'. Msg 207, Level 16, State 1, Line 10 Invalid column name 'NameOfCounter'. Msg 207, Level 16, State 1, Line 10 Invalid column name 'SampledValue'. Msg 207, Level 16, State 1, Line 10 Invalid column name 'DayStamp'. Msg 207, Level 16, State 1, Line 22 Invalid column name 'NameOfObject'. Msg 207, Level 16, State 1, Line 22 Invalid column name 'NameOfCounter'. Msg 207, Level 16, State 1, Line 22 Invalid column name 'SampledValue'. Msg 207, Level 16, State 1, Line 22 Invalid column name 'DayStamp'. Line 10 is the first 'insert into' line, and line 22 is the second select line. Any ideas?

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  • How to partition bits in a bit array with less than linear time

    - by SiLent SoNG
    This is an interview question I faced recently. Given an array of 1 and 0, find a way to partition the bits in place so that 0's are grouped together, and 1's are grouped together. It does not matter whether 1's are ahead of 0's or 0's are ahead of 1's. An example input is 101010101, and output is either 111110000 or 000011111. Solve the problem in less than linear time. Make the problem simpler. The input is an integer array, with each element either 1 or 0. Output is the same integer array with integers partitioned well. To me, this is an easy question if it can be solved in O(N). My approach is to use two pointers, starting from both ends of the array. Increases and decreases each pointer; if it does not point to the correct integer, swap the two. int * start = array; int * end = array + length - 1; while (start < end) { // Assume 0 always at the end if (*end == 0) { --end; continue; } // Assume 1 always at the beginning if (*start == 1) { ++start; continue; } swap(*start, *end); } However, the interview insists there is a sub-linear solution. This makes me thinking hard but still not get an answer. Can anyone help on this interview question?

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  • question about quicksort 3 way partition

    - by davit-datuashvili
    i want implement quicksort 3 way partition here is code public class quick3{ public static void quicksort3(int a[],int l,int r){ int k; int v=a[r]; if (r<=l) return; int i=l; int j=r; int p=l-1; int q=r; for (;;) { while (a[++i]<v); while (v<a[--j]) if (j==i) break; if (i>=j) break; swap( a,i, j); if (a[i]==v){ p++; swap(a,p,i);} if (v==a[j]){ q--; swap( a,q,j); } } swap(a,i,r); j=i-1; i=i+1; for (k=1;k<=p;k++,j--) swap(a,k,j); for (k=r-1;k>=q;k--,i++) swap(a,k,i); quicksort3(a,l,j); quicksort3(a,i,r); } public static void main(String[]args){ int a[]=new int[]{4,6,5,9,7,8,3}; quicksort3(a,0,a.length-1); for (int i=0;i<a.length;i++){ System.out.println(a[i]); } } public static void swap(int a[],int i,int j){ int t=a[i]; a[i]=a[j]; a[j]=t; } } after change result is 4 8 7 6 3 5 9 any suggestion?please help

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  • Developing Schema Compare for Oracle (Part 2): Dependencies

    - by Simon Cooper
    In developing Schema Compare for Oracle, one of the issues we came across was the size of the databases. As detailed in my last blog post, we had to allow schema pre-filtering due to the number of objects in a standard Oracle database. Unfortunately, this leads to some quite tricky situations regarding object dependencies. This post explains how we deal with these dependencies. 1. Cross-schema dependencies Say, in the following database, you're populating SchemaA, and synchronizing SchemaA.Table1: SOURCE   TARGET CREATE TABLE SchemaA.Table1 ( Col1 NUMBER REFERENCES SchemaB.Table1(Col1));   CREATE TABLE SchemaA.Table1 ( Col1 VARCHAR2(100) REFERENCES SchemaB.Table1(Col1)); CREATE TABLE SchemaB.Table1 ( Col1 NUMBER PRIMARY KEY);   CREATE TABLE SchemaB.Table1 ( Col1 VARCHAR2(100) PRIMARY KEY); We need to do a rebuild of SchemaA.Table1 to change Col1 from a VARCHAR2(100) to a NUMBER. This consists of: Creating a table with the new schema Inserting data from the old table to the new table, with appropriate conversion functions (in this case, TO_NUMBER) Dropping the old table Rename new table to same name as old table Unfortunately, in this situation, the rebuild will fail at step 1, as we're trying to create a NUMBER column with a foreign key reference to a VARCHAR2(100) column. As we're only populating SchemaA, the naive implementation of the object population prefiltering (sticking a WHERE owner = 'SCHEMAA' on all the data dictionary queries) will generate an incorrect sync script. What we actually have to do is: Drop foreign key constraint on SchemaA.Table1 Rebuild SchemaB.Table1 Rebuild SchemaA.Table1, adding the foreign key constraint to the new table This means that in order to generate a correct synchronization script for SchemaA.Table1 we have to know what SchemaB.Table1 is, and that it also needs to be rebuilt to successfully rebuild SchemaA.Table1. SchemaB isn't the schema that the user wants to synchronize, but we still have to load the table and column information for SchemaB.Table1 the same way as any table in SchemaA. Fortunately, Oracle provides (mostly) complete dependency information in the dictionary views. Before we actually read the information on all the tables and columns in the database, we can get dependency information on all the objects that are either pointed at by objects in the schemas we’re populating, or point to objects in the schemas we’re populating (think about what would happen if SchemaB was being explicitly populated instead), with a suitable query on all_constraints (for foreign key relationships) and all_dependencies (for most other types of dependencies eg a function using another function). The extra objects found can then be included in the actual object population, and the sync wizard then has enough information to figure out the right thing to do when we get to actually synchronize the objects. Unfortunately, this isn’t enough. 2. Dependency chains The solution above will only get the immediate dependencies of objects in populated schemas. What if there’s a chain of dependencies? A.tbl1 -> B.tbl1 -> C.tbl1 -> D.tbl1 If we’re only populating SchemaA, the implementation above will only include B.tbl1 in the dependent objects list, whereas we might need to know about C.tbl1 and D.tbl1 as well, in order to ensure a modification on A.tbl1 can succeed. What we actually need is a graph traversal on the dependency graph that all_dependencies represents. Fortunately, we don’t have to read all the database dependency information from the server and run the graph traversal on the client computer, as Oracle provides a method of doing this in SQL – CONNECT BY. So, we can put all the dependencies we want to include together in big bag with UNION ALL, then run a SELECT ... CONNECT BY on it, starting with objects in the schema we’re populating. We should end up with all the objects that might be affected by modifications in the initial schema we’re populating. Good solution? Well, no. For one thing, it’s sloooooow. all_dependencies, on my test databases, has got over 110,000 rows in it, and the entire query, for which Oracle was creating a temporary table to hold the big bag of graph edges, was often taking upwards of two minutes. This is too long, and would only get worse for large databases. But it had some more fundamental problems than just performance. 3. Comparison dependencies Consider the following schema: SOURCE   TARGET CREATE TABLE SchemaA.Table1 ( Col1 NUMBER REFERENCES SchemaB.Table1(col1));   CREATE TABLE SchemaA.Table1 ( Col1 VARCHAR2(100)); CREATE TABLE SchemaB.Table1 ( Col1 NUMBER PRIMARY KEY);   CREATE TABLE SchemaB.Table1 ( Col1 VARCHAR2(100)); What will happen if we used the dependency algorithm above on the source & target database? Well, SchemaA.Table1 has a foreign key reference to SchemaB.Table1, so that will be included in the source database population. On the target, SchemaA.Table1 has no such reference. Therefore SchemaB.Table1 will not be included in the target database population. In the resulting comparison of the two objects models, what you will end up with is: SOURCE  TARGET SchemaA.Table1 -> SchemaA.Table1 SchemaB.Table1 -> (no object exists) When this comparison is synchronized, we will see that SchemaB.Table1 does not exist, so we will try the following sequence of actions: Create SchemaB.Table1 Rebuild SchemaA.Table1, with foreign key to SchemaB.Table1 Oops. Because the dependencies are only followed within a single database, we’ve tried to create an object that already exists. To fix this we can include any objects found as dependencies in the source or target databases in the object population of both databases. SchemaB.Table1 will then be included in the target database population, and we won’t try and create objects that already exist. All good? Well, consider the following schema (again, only explicitly populating SchemaA, and synchronizing SchemaA.Table1): SOURCE   TARGET CREATE TABLE SchemaA.Table1 ( Col1 NUMBER REFERENCES SchemaB.Table1(col1));   CREATE TABLE SchemaA.Table1 ( Col1 VARCHAR2(100)); CREATE TABLE SchemaB.Table1 ( Col1 NUMBER PRIMARY KEY);   CREATE TABLE SchemaB.Table1 ( Col1 VARCHAR2(100) PRIMARY KEY); CREATE TABLE SchemaC.Table1 ( Col1 NUMBER);   CREATE TABLE SchemaC.Table1 ( Col1 VARCHAR2(100) REFERENCES SchemaB.Table1); Although we’re now including SchemaB.Table1 on both sides of the comparison, there’s a third table (SchemaC.Table1) that we don’t know about that will cause the rebuild of SchemaB.Table1 to fail if we try and synchronize SchemaA.Table1. That’s because we’re only running the dependency query on the schemas we’re explicitly populating; to solve this issue, we would have to run the dependency query again, but this time starting the graph traversal from the objects found in the other database. Furthermore, this dependency chain could be arbitrarily extended.This leads us to the following algorithm for finding all the dependencies of a comparison: Find initial dependencies of schemas the user has selected to compare on the source and target Include these objects in both the source and target object populations Run the dependency query on the source, starting with the objects found as dependents on the target, and vice versa Repeat 2 & 3 until no more objects are found For the schema above, this will result in the following sequence of actions: Find initial dependenciesSchemaA.Table1 -> SchemaB.Table1 found on sourceNo objects found on target Include objects in both source and targetSchemaB.Table1 included in source and target Run dependency query, starting with found objectsNo objects to start with on sourceSchemaB.Table1 -> SchemaC.Table1 found on target Include objects in both source and targetSchemaC.Table1 included in source and target Run dependency query on found objectsNo objects found in sourceNo objects to start with in target Stop This will ensure that we include all the necessary objects to make any synchronization work. However, there is still the issue of query performance; the CONNECT BY on the entire database dependency graph is still too slow. After much sitting down and drawing complicated diagrams, we decided to move the graph traversal algorithm from the server onto the client (which turned out to run much faster on the client than on the server); and to ensure we don’t read the entire dependency graph onto the client we also pull the graph across in bits – we start off with dependency edges involving schemas selected for explicit population, and whenever the graph traversal comes across a dependency reference to a schema we don’t yet know about a thunk is hit that pulls in the dependency information for that schema from the database. We continue passing more dependent objects back and forth between the source and target until no more dependency references are found. This gives us the list of all the extra objects to populate in the source and target, and object population can then proceed. 4. Object blacklists and fast dependencies When we tested this solution, we were puzzled in that in some of our databases most of the system schemas (WMSYS, ORDSYS, EXFSYS, XDB, etc) were being pulled in, and this was increasing the database registration and comparison time quite significantly. After debugging, we discovered that the culprits were database tables that used one of the Oracle PL/SQL types (eg the SDO_GEOMETRY spatial type). These were creating a dependency chain from the database tables we were populating to the system schemas, and hence pulling in most of the system objects in that schema. To solve this we introduced blacklists of objects we wouldn’t follow any dependency chain through. As well as the Oracle-supplied PL/SQL types (MDSYS.SDO_GEOMETRY, ORDSYS.SI_COLOR, among others) we also decided to blacklist the entire PUBLIC and SYS schemas, as any references to those would likely lead to a blow up in the dependency graph that would massively increase the database registration time, and could result in the client running out of memory. Even with these improvements, each dependency query was taking upwards of a minute. We discovered from Oracle execution plans that there were some columns, with dependency information we required, that were querying system tables with no indexes on them! To cut a long story short, running the following query: SELECT * FROM all_tab_cols WHERE data_type_owner = ‘XDB’; results in a full table scan of the SYS.COL$ system table! This single clause was responsible for over half the execution time of the dependency query. Hence, the ‘Ignore slow dependencies’ option was born – not querying this and a couple of similar clauses to drastically speed up the dependency query execution time, at the expense of producing incorrect sync scripts in rare edge cases. Needless to say, along with the sync script action ordering, the dependency code in the database registration is one of the most complicated and most rewritten parts of the Schema Compare for Oracle engine. The beta of Schema Compare for Oracle is out now; if you find a bug in it, please do tell us so we can get it fixed!

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  • Why does Windows 7 have three system partitions?

    - by Ben
    I am using Windows 7, and I wanted to make a System image (using Windows 7), but Windows 7 checked three partitions as System (100 MB + C (install partition) + D (my partition for my files, all programs are installed at C)). I don't want to backup my D partition, but that is not really the point. I don't want Windows messing with my other partitions and making them system. Is there a way to limit Windows 7 just to partition C (install partition)? If there is no way to stop Windows from making other partitions system, can I at least delete the files that make partition D system? PS: All these three partitions are on one physical disk, partitions from other disks aren't treated as System. FACTS: desktop PC, no OEM partitions, I personally have installed Windows 7 (many times) on the C partition. Why is my D partition checked as System partition when I try to create a System Image (using Windows 7 Ultimate built in tool), even though Windows (and all the software) are installed on the C partition? Is there a way to make D "normal" or non-system partition? Here is a picture of how it looks like if I try to create a system image. Once again, why is D also a system partition?

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  • merge cells in one

    - by alkitbi
    $query1 = "select * from linkat_link where emailuser='$email2' or linkname='$domain_name2' ORDER BY date desc LIMIT $From,$PageNO"; now sample show : <table border="1" width="100%"> <tr> <td>linkid</td> <td>catid</td> <td>linkdes</td> <td>price</td> </tr> <tr> <td>1</td> <td>1</td> <td>&nbsp;domain name</td> <td>100</td> </tr> <tr> <td>2</td> <td>1</td> <td>&nbsp;hosting&nbsp; plan one</td> <td>40</td> </tr> <tr> <td>3</td> <td>2</td> <td>&nbsp;domain name</td> <td>20</td> </tr> </table> How do I merge two or more  When there are numbers of cells same on the Table in this way sample? <table border="1" width="100%"> <tr> <td>catid</td> <td>linkdes</td> <td>price</td> </tr> <tr> <td>1</td> <td>linkid(1)- domain namelinkid(2)- hosting&nbsp; plan one</td> <td>10040</td> </tr> <tr> <td>2</td> <td>&nbsp;domain name</td> <td>20</td> </tr> </table>

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  • SQL SERVER – Introduction to SQL Server 2014 In-Memory OLTP

    - by Pinal Dave
    In SQL Server 2014 Microsoft has introduced a new database engine component called In-Memory OLTP aka project “Hekaton” which is fully integrated into the SQL Server Database Engine. It is optimized for OLTP workloads accessing memory resident data. In-memory OLTP helps us create memory optimized tables which in turn offer significant performance improvement for our typical OLTP workload. The main objective of memory optimized table is to ensure that highly transactional tables could live in memory and remain in memory forever without even losing out a single record. The most significant part is that it still supports majority of our Transact-SQL statement. Transact-SQL stored procedures can be compiled to machine code for further performance improvements on memory-optimized tables. This engine is designed to ensure higher concurrency and minimal blocking. In-Memory OLTP alleviates the issue of locking, using a new type of multi-version optimistic concurrency control. It also substantially reduces waiting for log writes by generating far less log data and needing fewer log writes. Points to remember Memory-optimized tables refer to tables using the new data structures and key words added as part of In-Memory OLTP. Disk-based tables refer to your normal tables which we used to create in SQL Server since its inception. These tables use a fixed size 8 KB pages that need to be read from and written to disk as a unit. Natively compiled stored procedures refer to an object Type which is new and is supported by in-memory OLTP engine which convert it into machine code, which can further improve the data access performance for memory –optimized tables. Natively compiled stored procedures can only reference memory-optimized tables, they can’t be used to reference any disk –based table. Interpreted Transact-SQL stored procedures, which is what SQL Server has always used. Cross-container transactions refer to transactions that reference both memory-optimized tables and disk-based tables. Interop refers to interpreted Transact-SQL that references memory-optimized tables. Using In-Memory OLTP In-Memory OLTP engine has been available as part of SQL Server 2014 since June 2013 CTPs. Installation of In-Memory OLTP is part of the SQL Server setup application. The In-Memory OLTP components can only be installed with a 64-bit edition of SQL Server 2014 hence they are not available with 32-bit editions. Creating Databases Any database that will store memory-optimized tables must have a MEMORY_OPTIMIZED_DATA filegroup. This filegroup is specifically designed to store the checkpoint files needed by SQL Server to recover the memory-optimized tables, and although the syntax for creating the filegroup is almost the same as for creating a regular filestream filegroup, it must also specify the option CONTAINS MEMORY_OPTIMIZED_DATA. Here is an example of a CREATE DATABASE statement for a database that can support memory-optimized tables: CREATE DATABASE InMemoryDB ON PRIMARY(NAME = [InMemoryDB_data], FILENAME = 'D:\data\InMemoryDB_data.mdf', size=500MB), FILEGROUP [SampleDB_mod_fg] CONTAINS MEMORY_OPTIMIZED_DATA (NAME = [InMemoryDB_mod_dir], FILENAME = 'S:\data\InMemoryDB_mod_dir'), (NAME = [InMemoryDB_mod_dir], FILENAME = 'R:\data\InMemoryDB_mod_dir') LOG ON (name = [SampleDB_log], Filename='L:\log\InMemoryDB_log.ldf', size=500MB) COLLATE Latin1_General_100_BIN2; Above example code creates files on three different drives (D:  S: and R:) for the data files and in memory storage so if you would like to run this code kindly change the drive and folder locations as per your convenience. Also notice that binary collation was specified as Windows (non-SQL). BIN2 collation is the only collation support at this point for any indexes on memory optimized tables. It is also possible to add a MEMORY_OPTIMIZED_DATA file group to an existing database, use the below command to achieve the same. ALTER DATABASE AdventureWorks2012 ADD FILEGROUP hekaton_mod CONTAINS MEMORY_OPTIMIZED_DATA; GO ALTER DATABASE AdventureWorks2012 ADD FILE (NAME='hekaton_mod', FILENAME='S:\data\hekaton_mod') TO FILEGROUP hekaton_mod; GO Creating Tables There is no major syntactical difference between creating a disk based table or a memory –optimized table but yes there are a few restrictions and a few new essential extensions. Essentially any memory-optimized table should use the MEMORY_OPTIMIZED = ON clause as shown in the Create Table query example. DURABILITY clause (SCHEMA_AND_DATA or SCHEMA_ONLY) Memory-optimized table should always be defined with a DURABILITY value which can be either SCHEMA_AND_DATA or  SCHEMA_ONLY the former being the default. A memory-optimized table defined with DURABILITY=SCHEMA_ONLY will not persist the data to disk which means the data durability is compromised whereas DURABILITY= SCHEMA_AND_DATA ensures that data is also persisted along with the schema. Indexing Memory Optimized Table A memory-optimized table must always have an index for all tables created with DURABILITY= SCHEMA_AND_DATA and this can be achieved by declaring a PRIMARY KEY Constraint at the time of creating a table. The following example shows a PRIMARY KEY index created as a HASH index, for which a bucket count must also be specified. CREATE TABLE Mem_Table ( [Name] VARCHAR(32) NOT NULL PRIMARY KEY NONCLUSTERED HASH WITH (BUCKET_COUNT = 100000), [City] VARCHAR(32) NULL, [State_Province] VARCHAR(32) NULL, [LastModified] DATETIME NOT NULL, ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA); Now as you can see in the above query example we have used the clause MEMORY_OPTIMIZED = ON to make sure that it is considered as a memory optimized table and not just a normal table and also used the DURABILITY Clause= SCHEMA_AND_DATA which means it will persist data along with metadata and also you can notice this table has a PRIMARY KEY mentioned upfront which is also a mandatory clause for memory-optimized tables. We will talk more about HASH Indexes and BUCKET_COUNT in later articles on this topic which will be focusing more on Row and Index storage on Memory-Optimized tables. So stay tuned for that as well. Now as we covered the basics of Memory Optimized tables and understood the key things to remember while using memory optimized tables, let’s explore more using examples to understand the Performance gains using memory-optimized tables. I will be using the database which i created earlier in this article i.e. InMemoryDB in the below Demo Exercise. USE InMemoryDB GO -- Creating a disk based table CREATE TABLE dbo.Disktable ( Id INT IDENTITY, Name CHAR(40) ) GO CREATE NONCLUSTERED INDEX IX_ID ON dbo.Disktable (Id) GO -- Creating a memory optimized table with similar structure and DURABILITY = SCHEMA_AND_DATA CREATE TABLE dbo.Memorytable_durable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO -- Creating an another memory optimized table with similar structure but DURABILITY = SCHEMA_Only CREATE TABLE dbo.Memorytable_nondurable ( Id INT NOT NULL PRIMARY KEY NONCLUSTERED Hash WITH (bucket_count =1000000), Name CHAR(40) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_only) GO -- Now insert 100000 records in dbo.Disktable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Disktable(Name) VALUES('sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Do the same inserts for Memory table dbo.Memorytable_durable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_durable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END -- Now finally do the same inserts for Memory table dbo.Memorytable_nondurable and observe the Time Taken DECLARE @i_t bigint SET @i_t =1 WHILE @i_t<= 100000 BEGIN INSERT INTO dbo.Memorytable_nondurable VALUES(@i_t, 'sachin' + CONVERT(VARCHAR,@i_t)) SET @i_t+=1 END The above 3 Inserts took 1.20 minutes, 54 secs, and 2 secs respectively to insert 100000 records on my machine with 8 Gb RAM. This proves the point that memory-optimized tables can definitely help businesses achieve better performance for their highly transactional business table and memory- optimized tables with Durability SCHEMA_ONLY is even faster as it does not bother persisting its data to disk which makes it supremely fast. Koenig Solutions is one of the few organizations which offer IT training on SQL Server 2014 and all its updates. Now, I leave the decision on using memory_Optimized tables on you, I hope you like this article and it helped you understand  the fundamentals of IN-Memory OLTP . Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Koenig

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  • Css code for the table

    - by Hulk
    Can some one please tell me how to make this table look better <table> <tr><th>Name</th><th>Address</th><th>occupation</th></tr> <tr><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td></tr> <tr><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td></tr> <tr><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td><td><textarea rows=10 cols=15></td></tr> </table> This table is dynamically generated and meaning there could me more rows with td containing textarea. Can any one please sugesst a a css code to beautify this table or may be a link Thanks..

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