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  • Using Node.js as an accelerator for WCF REST services

    - by Elton Stoneman
    Node.js is a server-side JavaScript platform "for easily building fast, scalable network applications". It's built on Google's V8 JavaScript engine and uses an (almost) entirely async event-driven processing model, running in a single thread. If you're new to Node and your reaction is "why would I want to run JavaScript on the server side?", this is the headline answer: in 150 lines of JavaScript you can build a Node.js app which works as an accelerator for WCF REST services*. It can double your messages-per-second throughput, halve your CPU workload and use one-fifth of the memory footprint, compared to the WCF services direct.   Well, it can if: 1) your WCF services are first-class HTTP citizens, honouring client cache ETag headers in request and response; 2) your services do a reasonable amount of work to build a response; 3) your data is read more often than it's written. In one of my projects I have a set of REST services in WCF which deal with data that only gets updated weekly, but which can be read hundreds of times an hour. The services issue ETags and will return a 304 if the client sends a request with the current ETag, which means in the most common scenario the client uses its local cached copy. But when the weekly update happens, then all the client caches are invalidated and they all need the same new data. Then the service will get hundreds of requests with old ETags, and they go through the full service stack to build the same response for each, taking up threads and processing time. Part of that processing means going off to a database on a separate cloud, which introduces more latency and downtime potential.   We can use ASP.NET output caching with WCF to solve the repeated processing problem, but the server will still be thread-bound on incoming requests, and to get the current ETags reliably needs a database call per request. The accelerator solves that by running as a proxy - all client calls come into the proxy, and the proxy routes calls to the underlying REST service. We could use Node as a straight passthrough proxy and expect some benefit, as the server would be less thread-bound, but we would still have one WCF and one database call per proxy call. But add some smart caching logic to the proxy, and share ETags between Node and WCF (so the proxy doesn't even need to call the servcie to get the current ETag), and the underlying service will only be invoked when data has changed, and then only once - all subsequent client requests will be served from the proxy cache.   I've built this as a sample up on GitHub: NodeWcfAccelerator on sixeyed.codegallery. Here's how the architecture looks:     The code is very simple. The Node proxy runs on port 8010 and all client requests target the proxy. If the client request has an ETag header then the proxy looks up the ETag in the tag cache to see if it is current - the sample uses memcached to share ETags between .NET and Node. If the ETag from the client matches the current server tag, the proxy sends a 304 response with an empty body to the client, telling it to use its own cached version of the data. If the ETag from the client is stale, the proxy looks for a local cached version of the response, checking for a file named after the current ETag. If that file exists, its contents are returned to the client as the body in a 200 response, which includes the current ETag in the header. If the proxy does not have a local cached file for the service response, it calls the service, and writes the WCF response to the local cache file, and to the body of a 200 response for the client. So the WCF service is only troubled if both client and proxy have stale (or no) caches.   The only (vaguely) clever bit in the sample is using the ETag cache, so the proxy can serve cached requests without any communication with the underlying service, which it does completely generically, so the proxy has no notion of what it is serving or what the services it proxies are doing. The relative path from the URL is used as the lookup key, so there's no shared key-generation logic between .NET and Node, and when WCF stores a tag it also stores the "read" URL against the ETag so it can be used for a reverse lookup, e.g:   Key Value /WcfSampleService/PersonService.svc/rest/fetch/3 "28cd4796-76b8-451b-adfd-75cb50a50fa6" "28cd4796-76b8-451b-adfd-75cb50a50fa6" /WcfSampleService/PersonService.svc/rest/fetch/3    In Node we read the cache using the incoming URL path as the key and we know that "28cd4796-76b8-451b-adfd-75cb50a50fa6" is the current ETag; we look for a local cached response in /caches/28cd4796-76b8-451b-adfd-75cb50a50fa6.body (and the corresponding .header file which contains the original service response headers, so the proxy response is exactly the same as the underlying service). When the data is updated, we need to invalidate the ETag cache – which is why we need the reverse lookup in the cache. In the WCF update service, we don't need to know the URL of the related read service - we fetch the entity from the database, do a reverse lookup on the tag cache using the old ETag to get the read URL, update the new ETag against the URL, store the new reverse lookup and delete the old one.   Running Apache Bench against the two endpoints gives the headline performance comparison. Making 1000 requests with concurrency of 100, and not sending any ETag headers in the requests, with the Node proxy I get 102 requests handled per second, average response time of 975 milliseconds with 90% of responses served within 850 milliseconds; going direct to WCF with the same parameters, I get 53 requests handled per second, mean response time of 1853 milliseconds, with 90% of response served within 3260 milliseconds. Informally monitoring server usage during the tests, Node maxed at 20% CPU and 20Mb memory; IIS maxed at 60% CPU and 100Mb memory.   Note that the sample WCF service does a database read and sleeps for 250 milliseconds to simulate a moderate processing load, so this is *not* a baseline Node-vs-WCF comparison, but for similar scenarios where the  service call is expensive but applicable to numerous clients for a long timespan, the performance boost from the accelerator is considerable.     * - actually, the accelerator will work nicely for any HTTP request, where the URL (path + querystring) uniquely identifies a resource. In the sample, there is an assumption that the ETag is a GUID wrapped in double-quotes (e.g. "28cd4796-76b8-451b-adfd-75cb50a50fa6") – which is the default for WCF services. I use that assumption to name the cache files uniquely, but it is a trivial change to adapt to other ETag formats.

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  • Kill a tree, save your website? Content strategy in action, part III

    - by Roger Hart
    A lot has been written about how driving content strategy from within an organisation is hard. And that's true. Red Gate is pretty receptive to new ideas, so although I've not had a total walk in the park, it's been a hike with charming scenery. But I'm one of the lucky ones. Lots of people are involved in content, and depending on your organisation some of those people might be the kind who'll gleefully call themselves "stakeholders". People holding a stake generally want to stick it through something's heart and bury it at a crossroads. Winning them over is not always easy. (Richard Ingram has made a nice visual summary of how this can feel - Content strategy Snakes & ladders - pdf ) So yes, a lot of content strategy advocates are having a hard time. And sure, we've got a nice opportunity to get together and have a hug and a cry, but in the interim we could use a hand. What to do? My preferred approach is, I'll confess, brutal. I'd like nothing so much as to take a scorched earth approach to our website. Burn it, salt the ground, and build the new one right: focusing on clearly delineated business and user content goals, and instrumented so we can tell if we're doing it right. I'm never getting buy-in for that, but a boy can dream. So how about just getting buy-in for some small, tenable improvements? Easier, but still non-trivial. I sat down for a chat with our marketing and design guys. It seemed like a good place to start, even if they weren't up for my "Ctrl-A + Delete"  solution. We talked through some of this stuff, and we pretty much agreed that our content is a bit more broken than we'd ideally like. But to get everybody on board, the problems needed visibility. Doing a visual content inventory Print out the internet. Make a Wall Of Content. Seriously. If you've already done a content inventory, you know your architecture, and you know the scale of the problem. But it's quite likely that very few other people do. So make it big and visual. I'm going to carbon hell, but it seems to be working. This morning, I printed out a tiny, tiny part of our website: the non-support content pertaining to SQL Compare I made big, visual, A3 blowups of each page, and covered a wall with them. A page per web page, spread over something like 6M x 2M, with metrics, right in front of people. Even if nobody reads it (and they are doing) the sheer scale is shocking. 53 pages, all told. Some are redundant, some outdated, some trivial, a few fantastic, and frighteningly many that are great ideas delivered not-quite-right. You have to stand quite far away to get it all in your field of vision. For a lot of today, a whole bunch of folks have been gawping in amazement, talking each other through it, peering at the details, and generally getting excited about content. Developers, sales guys, our CEO, the marketing folks - they're engaged. Will it last? I make no promises. But this sort of wave of interest is vital to getting a content strategy project kicked off. While the content strategist is a saucer-eyed orphan in the cupboard under the stairs, they're not getting a whole lot done. Of course, just printing the site won't necessarily cut it. You have to know your content, and be able to talk about it. Ideally, you'll also have page view and time-on-page metrics. One of the most powerful things you can do is, when people are staring at your wall of content, ask them what they think half of it is for. Pretty soon, you've made a case for content strategy. We're also going to get folks to mark it up - cover it with notes and post-its, let us know how they feel about our content. I'll be blogging about how that goes, but it's exciting. Different business functions have different needs from content, so the more exposure the content gets, and the more feedback, the more you know about those needs. Fingers crossed for awesome.

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  • HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database

    - by Jane Story
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} When working with a Hyperion Profitability and Cost Management (HPCM) Standard Costing application, there can often be a requirement to check data or allocated results using reporting tools e.g Smartview. To do this, you are retrieving data directly from the Essbase databases related to your HPCM model. For information, running reports is covered in Chapter 9 of the HPCM User documentation. The aim of this blog is to provide a quick guide to finding this data for reporting in the HPCM generated Essbase database in v11.1.2.2.x of HPCM. In order to retrieve data from an HPCM generated Essbase database, it is important to understand each of the following dimensions in the Essbase database and where data is located within them: Measures dimension – identifies Measures AllocationType dimension – identifies Direct Allocation Data or Genealogy Allocation data Point Of View (POV) dimensions – there must be at least one, maximum of four. Business dimensions: Stage Business dimensions – these will be identified by the Stage prefix. Intra-Stage dimension – these will be identified by the _Intra suffix. Essbase outlines and reporting is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s02.html For additional details on reporting measures, please review this section of the documentation:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/apas03.html Reporting requirements in HPCM quite often start with identifying non balanced items in the Stage Balancing report. The following documentation link provides help with identifying some of the items within the Stage Balancing report:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/generatestagebalancing.html The following are some types of data upon which you may want to report: Stage Data: Direct Input Assigned Input Data Assigned Output Data Idle Cost/Revenue Unassigned Cost/Revenue Over Driven Cost/Revenue Direct Allocation Data Genealogy Allocation Data Stage Data Stage Data consists of: Direct Input i.e. input data, the starting point of your allocation e.g. in Stage 1 Assigned Input Data i.e. the cost/revenue received from a prior stage (i.e. stage 2 and higher). Assigned Output Data i.e. for each stage, the data that will be assigned forward is assigned post stage data. Reporting on this data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s03.html Dimension Selection Measures Direct Input: CostInput RevenueInput Assigned Input (from previous stages): CostReceivedPriorStage RevenueReceivedPriorStage Assigned Output (to subsequent stages): CostAssignedPostStage RevenueAssignedPostStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the stage business dimensions for the stage you wish to see the Stage data for. All other Dimensions NoMember Idle/Unassigned/OverDriven To view Idle, Unassigned or Overdriven Costs/Revenue, first select which stage for which you want to view this data. If multiple Stages have unassigned/idle, resolve the earliest first and re-run the calculation as differences in early stages will create unassigned/idle in later stages. Dimension Selection Measures Idle: IdleCost IdleRevenue Unassigned: UnAssignedCost UnAssignedRevenue Overdriven: OverDrivenCost OverDrivenRevenue AllocationType DirectAllocation POV One member from each POV dimension Dimensions in the Stage with Unassigned/ Idle/OverDriven Cost All the Stage Business dimensions in the Stage with Unassigned/Idle/Overdriven. Zoom in on each dimension to find the individual members to find which members have Unassigned/Idle/OverDriven data. All other Dimensions NoMember Direct Allocation Data Direct allocation data shows the data received by a destination intersection from a source intersection where a direct assignment(s) exists. Reporting on direct allocation data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s04.html You would select the following to report direct allocation data Dimension Selection Measures CostReceivedPriorStage AllocationType DirectAllocation POV One member from each POV dimension Stage Business Dimensions Any members for the SOURCE stage business dimensions and the DESTINATION stage business dimensions for the direct allocations for the stage you wish to report on. All other Dimensions NoMember Genealogy Allocation Data Genealogy allocation data shows the indirect data relationships between stages. Genealogy calculations run in the HPCM Reporting database only. Reporting on genealogy data is explained in the documentation here:http://docs.oracle.com/cd/E17236_01/epm.1112/hpm_user/ch09s05.html Dimension Selection Measures CostReceivedPriorStage AllocationType GenealogyAllocation (IndirectAllocation in 11.1.2.1 and prior versions) POV One member from each POV dimension Stage Business Dimensions Any stage business dimension members from the STARTING stage in Genealogy Any stage business dimension members from the INTERMEDIATE stage(s) in Genealogy Any stage business dimension members from the ENDING stage in Genealogy All other Dimensions NoMember Notes If you still don’t see data after checking the above, please check the following Check the calculation has been run. Here are couple of indicators that might help them with that. Note the size of essbase cube before and after calculations ensure that a calculation was run against the database you are examing. Export the essbase data to a text file to confirm that some data exists. Examine the date and time on task area to see when, if any, calculations were run and what choices were used (e.g. Genealogy choices) If data does not exist in places where they are expecting, it could be that No calculations/genealogy were run No calculations were successfully run The model/data at feeder location were either absent or incompatible, resulting in no allocation e.g no driver data. Smartview Invocation from HPCM From version 11.1.2.2.350 of HPCM (this version will be GA shortly), it is possible to directly invoke Smartview from HPCM. There is guided navigation before the Smartview invocation and it is then possible to see the selected value(s) in SmartView. Click to Download HPCM 11.1.2.2.x - How to find data in an HPCM Standard Costing database (Right click or option-click the link and choose "Save As..." to download this pdf file)

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  • Big Data Matters with ODI12c

    - by Madhu Nair
    contributed by Mike Eisterer On October 17th, 2013, Oracle announced the release of Oracle Data Integrator 12c (ODI12c).  This release signifies improvements to Oracle’s Data Integration portfolio of solutions, particularly Big Data integration. Why Big Data = Big Business Organizations are gaining greater insights and actionability through increased storage, processing and analytical benefits offered by Big Data solutions.  New technologies and frameworks like HDFS, NoSQL, Hive and MapReduce support these benefits now. As further data is collected, analytical requirements increase and the complexity of managing transformations and aggregations of data compounds and organizations are in need for scalable Data Integration solutions. ODI12c provides enterprise solutions for the movement, translation and transformation of information and data heterogeneously and in Big Data Environments through: The ability for existing ODI and SQL developers to leverage new Big Data technologies. A metadata focused approach for cataloging, defining and reusing Big Data technologies, mappings and process executions. Integration between many heterogeneous environments and technologies such as HDFS and Hive. Generation of Hive Query Language. Working with Big Data using Knowledge Modules  ODI12c provides developers with the ability to define sources and targets and visually develop mappings to effect the movement and transformation of data.  As the mappings are created, ODI12c leverages a rich library of prebuilt integrations, known as Knowledge Modules (KMs).  These KMs are contextual to the technologies and platforms to be integrated.  Steps and actions needed to manage the data integration are pre-built and configured within the KMs.  The Oracle Data Integrator Application Adapter for Hadoop provides a series of KMs, specifically designed to integrate with Big Data Technologies.  The Big Data KMs include: Check Knowledge Module Reverse Engineer Knowledge Module Hive Transform Knowledge Module Hive Control Append Knowledge Module File to Hive (LOAD DATA) Knowledge Module File-Hive to Oracle (OLH-OSCH) Knowledge Module  Nothing to beat an Example: To demonstrate the use of the KMs which are part of the ODI Application Adapter for Hadoop, a mapping may be defined to move data between files and Hive targets.  The mapping is defined by dragging the source and target into the mapping, performing the attribute (column) mapping (see Figure 1) and then selecting the KM which will govern the process.  In this mapping example, movie data is being moved from an HDFS source into a Hive table.  Some of the attributes, such as “CUSTID to custid”, have been mapped over. Figure 1  Defining the Mapping Before the proper KM can be assigned to define the technology for the mapping, it needs to be added to the ODI project.  The Big Data KMs have been made available to the project through the KM import process.   Generally, this is done prior to defining the mapping. Figure 2  Importing the Big Data Knowledge Modules Following the import, the KMs are available in the Designer Navigator. v\:* {behavior:url(#default#VML);} o\:* {behavior:url(#default#VML);} w\:* {behavior:url(#default#VML);} .shape {behavior:url(#default#VML);} Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";} Figure 3  The Project View in Designer, Showing Installed IKMs Once the KM is imported, it may be assigned to the mapping target.  This is done by selecting the Physical View of the mapping and examining the Properties of the Target.  In this case MOVIAPP_LOG_STAGE is the target of our mapping. Figure 4  Physical View of the Mapping and Assigning the Big Data Knowledge Module to the Target Alternative KMs may have been selected as well, providing flexibility and abstracting the logical mapping from the physical implementation.  Our mapping may be applied to other technologies as well. The mapping is now complete and is ready to run.  We will see more in a future blog about running a mapping to load Hive. To complete the quick ODI for Big Data Overview, let us take a closer look at what the IKM File to Hive is doing for us.  ODI provides differentiated capabilities by defining the process and steps which normally would have to be manually developed, tested and implemented into the KM.  As shown in figure 5, the KM is preparing the Hive session, managing the Hive tables, performing the initial load from HDFS and then performing the insert into Hive.  HDFS and Hive options are selected graphically, as shown in the properties in Figure 4. Figure 5  Process and Steps Managed by the KM What’s Next Big Data being the shape shifting business challenge it is is fast evolving into the deciding factor between market leaders and others. Now that an introduction to ODI and Big Data has been provided, look for additional blogs coming soon using the Knowledge Modules which make up the Oracle Data Integrator Application Adapter for Hadoop: Importing Big Data Metadata into ODI, Testing Data Stores and Loading Hive Targets Generating Transformations using Hive Query language Loading Oracle from Hadoop Sources For more information now, please visit the Oracle Data Integrator Application Adapter for Hadoop web site, http://www.oracle.com/us/products/middleware/data-integration/hadoop/overview/index.html Do not forget to tune in to the ODI12c Executive Launch webcast on the 12th to hear more about ODI12c and GG12c. Normal 0 false false false EN-US ZH-TW X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Calibri","sans-serif"; mso-bidi-font-family:"Times New Roman";}

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  • NVIDIA x server - "sudo nvidia config" does not generate a working 'xorg.config'

    - by Mike
    I am over 18 hours deep on this challenge. I got to this point and am stuck. very stuck. Maybe you can figure it out? Ubuntu Version 12.04 LTS with all the updates installed. Problem: The default settings in "etc/X11/xorg.conf" that are generated by the "nvidia-xconfig" tool, do not allow the NVIDIA x server to connect to the driver in my "System Settings Additional Driver window". (that's how I understand it. Lots of information below). Symptoms of Problem "System Settings Additional Driver" window has drivers, but the nvidia x server cannot connect/utilize any of the 4 drivers. the drivers are activated, but not in use. When I go to "System Tools Administration NVIDIA x server settings" I get an error that basically tells me to create a default file to initialize the NVIDIA X server (screen shot below). This is the messages the terminal gives after running a "sudo nvidia-xconfig" command for the first time. It seems that the generated file by the tool i just ran is generating a bad/unusable file: If I run the "sudo nvidia-xconfig" command again, I wont get an error the second time. However when I reboot, the default file that is generated (etc/X11/xorg.conf) simply puts the screen resolution at 800 x 600 (or something big like that). When I try to go to NVIDIA x server settings I am greeted with the same screen as the screen shot as in symptom 2 (no option to change the resolution). If I try to go to "system settings display" there are no other resolutions to choose from. At this point I must delete the newly minted "xorg.conf" and reinstate the original in its place. Here are the contents of the "xorg.conf" that is generated first (the one missing required information): # nvidia-xconfig: X configuration file generated by nvidia-xconfig # nvidia-xconfig: version 304.88 (buildmeister@swio-display-x86-rhel47-06) Wed Mar 27 15:32:58 PDT 2013 Section "ServerLayout" Identifier "Layout0" Screen 0 "Screen0" InputDevice "Keyboard0" "CoreKeyboard" InputDevice "Mouse0" "CorePointer" EndSection Section "Files" EndSection Section "InputDevice" # generated from default Identifier "Mouse0" Driver "mouse" Option "Protocol" "auto" Option "Device" "/dev/psaux" Option "Emulate3Buttons" "no" Option "ZAxisMapping" "4 5" EndSection Section "InputDevice" # generated from default Identifier "Keyboard0" Driver "kbd" EndSection Section "Monitor" Identifier "Monitor0" VendorName "Unknown" ModelName "Unknown" HorizSync 28.0 - 33.0 VertRefresh 43.0 - 72.0 Option "DPMS" EndSection Section "Device" Identifier "Device0" Driver "nvidia" VendorName "NVIDIA Corporation" EndSection Section "Screen" Identifier "Screen0" Device "Device0" Monitor "Monitor0" DefaultDepth 24 SubSection "Display" Depth 24 EndSubSection EndSection Hardware: I ran the "lspci|grep VGA". There results are: 00:02.0 VGA compatible controller: Intel Corporation 2nd Generation Core Processor Family Integrated Graphics Controller (rev 09) 01:00.0 VGA compatible controller: NVIDIA Corporation GF108 [Quadro 1000M] (rev a1) More Hardware info: Ram: 16GB CPU: Intel Core i7-2720QM @2.2GHz * 8 Other: 64 bit. This is a triple boot computer and not a VM. Attempts With Not Success on My End: 1) Tried to append the "xorg.conf" with what I perceive is missing information and obviously it didn't fly. 2) All the other stuff I tried got me to this point. 3) See if this link is helpful to you (I barely get it, but i get enough knowing that a smarter person might find this useful): http://manpages.ubuntu.com/manpages/lucid/man1/nvidia-xconfig.1.html 4) I am completely new to Linux (40 hours over past week), but not to programming. However I am very serious about changing over to Linux. When you respond (I hope someone responds...) please respond in a way that a person new to Linux can understand. 5) By the way, the reason I am in this mess is because I MUST have a second monitor running from my laptop, and "System Settings Display" doesn't recognize my second display. I know it is possible to make the second display work in my system, because when I boot from the install CD, I perform work on the native laptop monitor, but the second monitor shows a purple screen with Ubuntu in the middle, so I know the VGA port is sending a signal out. If this is too much for you to tackle please suggest an alternative method to get a second display. I don't want to go to windows but I cannot have a single display. I am really fudged here. I hope some smart person can help. Thanks in advance. Mike. **********************EDIT #1********************** More Details About Graphics Card I was asked "which brand of nvidia-card do you have exactly?" Here is what I did to provide more info (maybe relevant, maybe not, but here is everything): 1) Took my Lenovo W520 right apart to see if there is an identifier on the actual card. However I realized that if I get deep enough to take a look, the laptop "won't like it". so I put it back together. Figuring out the card this way is not an option for me right now. 2) (My computer is triple boot) I logged into Win7 and ran 'dxdiag' command. here is the screen shot: 3) I tried to look on the lenovo website for more details... but no luck. I took a look at my receipts and here is info form receipt: System Unit: W520 NVIDIA Quadro 1000M 2GB 4) In win7 I went to the NVIDIA website and used the option to have my card 'scanned' by a Java applet to determine the latest update for my card. I tried the same with Ubuntu but I can't get the applet to run. Here is the recommended driver from from the NVIDIA Applet for my card for Win7 (I hope this shines some light on the specifics of the card): Quadro/NVS/Tesla/GRID Desktop Driver Release R319 Version: 320.00 WHQL Release Date: 3.5.2013 5) Also I went on the NVIDIA driver search and looked through every possible combination of product type + product series + product to find all the combinations that yield a 1000M card. My card is: Product Type: Quadro Product Series: Quadro Series (Notebooks) Product: 1000M ***********************EDIT #2******************* Additional Symptoms Another question that generated more symptoms I previously didn't mention was: "After generating xorg.conf by nvidia-xconfig, go to additional drivers, do you see nvidia-304?" 1) I took a screen shot of the "additional drivers" right after generating xorg.conf by nvidia-xconfig. Here it is: 2) Then I did a reboot. Now Ubuntu is 600 x 800 resolution. When I logged in after the computer came up I got an error (which I always get after generating xorg.conf by nvidia-xconfig and rebooting) 3) To finally answer the question - No. There is no "NVIDIA-304" driver. Screen shot of additional drivers after generating xorg.conf by nvidia-xconfig and rebooting : At this point I revert to the original xorg.conf and delete the xorg.conf generated by Nvidia.

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  • How to Use RDA to Generate WLS Thread Dumps At Specified Intervals?

    - by Daniel Mortimer
    Introduction There are many ways to generate a thread dump of a WebLogic Managed Server. For example, take a look at: Taking Thread Dumps - [an excellent blog post on the Middleware Magic site]or  Different ways to take thread dumps in WebLogic Server (Document 1098691.1) There is another method - use Remote Diagnostic Agent! The solution described below is not documented, but it is relatively straightforward to execute. One advantage of using RDA to collect the thread dumps is RDA will also collect configuration, log files, network, system, performance information at the same time. Instructions 1. Not familiar with Remote Diagnostic Agent? Take a look at my previous blog "Resolve SRs Faster Using RDA - Find the Right Profile" 2. Choose a profile, which includes the WebLogic Server data collection modules (for example the profile "WebLogicServer"). At RDA setup time you should see the prompt below: ------------------------------------------------------------------------------- S301WLS: Collects Oracle WebLogic Server Information ------------------------------------------------------------------------------- Enter the location of the directory where the domains to analyze are located (For example in UNIX, <BEA Home>/user_projects/domains or <Middleware Home>/user_projects/domains) Hit 'Return' to accept the default (/oracle/11AS/Middleware/user_projects/domains) > For a successful WLS connection, ensure that the domain Admin Server is up and running. Data Collection Type:   1  Collect for a single server (offline mode)   2  Collect for a single server (using WLS connection)   3  Collect for multiple servers (using WLS connection) Enter the item number Hit 'Return' to accept the default (1) > 2 Choose option 2 or 3. Note: Collect for a single server or multiple servers using WLS connection means that RDA will attempt to connect to execute online WLST commands against the targeted server(s). The thread dumps are collected using the WLST function - "threadDumps()". If WLST cannot connect to the managed server, RDA will proceed to collect other data and ignore the request to collect thread dumps. If in the final output you see no Thread Dump menu item, then it's likely that the managed server is in a state which prevents new connections to it. If faced with this scenario, you would have to employ alternative methods for collecting thread dumps. 3. The RDA setup will create a setup.cfg file in the RDA_HOME directory. Open this file in an editor. You will find the following parameters which govern the number of thread dumps and thread dump interval. #N.Number of thread dumps to capture WREQ_THREAD_DUMP=10 #N.Thread dump interval WREQ_THREAD_DUMP_INTERVAL=5000 The example lines above show the default settings. In other words, RDA will collect 10 thread dumps at 5000 millisecond (5 second) intervals. You may want to change this to something like: #N.Number of thread dumps to capture WREQ_THREAD_DUMP=10 #N.Thread dump interval WREQ_THREAD_DUMP_INTERVAL=30000 However, bear in mind, that such change will increase the total amount of time it takes for RDA to complete its run. 4. Once you are happy with the setup.cfg, run RDA. RDA will collect, render, generate and package all files in the output directory. 5. For ease of viewing, open up the RDA Start html file - "xxxx__start.htm". The thread dumps can be found under the WLST Collections for the target managed server(s). See screenshots belowScreenshot 1:RDA Start Page - Main Index Screenshot 2: Managed Server Sub Index Screenshot 3: WLST Collections Screenshot 4: Thread Dump Page - List of dump file links Screenshot 5: Thread Dump Dat File Link Additional Comment: A) You can view the thread dump files within the RDA Start Page framework, but most likely you will want to download the dat files for in-depth analysis via thread dump analysis tools such as: Thread Dump Analyzer -  Samurai - a GUI based tail , thread dump analysis tool If you are new to thread dump analysis - take a look at this recorded Support Advisor Webcast  Oracle WebLogic Server: Diagnosing Performance Issues through Java Thread Dumps[Slidedeck from webcast in PDF format]B) I have logged a couple of enhancement requests for the RDA Development Team to consider: Add timestamp to dump file links, dat filename and at the top of the body of the dat file Package the individual thread dumps in a zip so all dump files can be conveniently downloaded in one go.

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  • Nashorn, the rhino in the room

    - by costlow
    Nashorn is a new runtime within JDK 8 that allows developers to run code written in JavaScript and call back and forth with Java. One advantage to the Nashorn scripting engine is that is allows for quick prototyping of functionality or basic shell scripts that use Java libraries. The previous JavaScript runtime, named Rhino, was introduced in JDK 6 (released 2006, end of public updates Feb 2013). Keeping tradition amongst the global developer community, "Nashorn" is the German word for rhino. The Java platform and runtime is an intentional home to many languages beyond the Java language itself. OpenJDK’s Da Vinci Machine helps coordinate work amongst language developers and tool designers and has helped different languages by introducing the Invoke Dynamic instruction in Java 7 (2011), which resulted in two major benefits: speeding up execution of dynamic code, and providing the groundwork for Java 8’s lambda executions. Many of these improvements are discussed at the JVM Language Summit, where language and tool designers get together to discuss experiences and issues related to building these complex components. There are a number of benefits to running JavaScript applications on JDK 8’s Nashorn technology beyond writing scripts quickly: Interoperability with Java and JavaScript libraries. Scripts do not need to be compiled. Fast execution and multi-threading of JavaScript running in Java’s JRE. The ability to remotely debug applications using an IDE like NetBeans, Eclipse, or IntelliJ (instructions on the Nashorn blog). Automatic integration with Java monitoring tools, such as performance, health, and SIEM. In the remainder of this blog post, I will explain how to use Nashorn and the benefit from those features. Nashorn execution environment The Nashorn scripting engine is included in all versions of Java SE 8, both the JDK and the JRE. Unlike Java code, scripts written in nashorn are interpreted and do not need to be compiled before execution. Developers and users can access it in two ways: Users running JavaScript applications can call the binary directly:jre8/bin/jjs This mechanism can also be used in shell scripts by specifying a shebang like #!/usr/bin/jjs Developers can use the API and obtain a ScriptEngine through:ScriptEngine engine = new ScriptEngineManager().getEngineByName("nashorn"); When using a ScriptEngine, please understand that they execute code. Avoid running untrusted scripts or passing in untrusted/unvalidated inputs. During compilation, consider isolating access to the ScriptEngine and using Type Annotations to only allow @Untainted String arguments. One noteworthy difference between JavaScript executed in or outside of a web browser is that certain objects will not be available. For example when run outside a browser, there is no access to a document object or DOM tree. Other than that, all syntax, semantics, and capabilities are present. Examples of Java and JavaScript The Nashorn script engine allows developers of all experience levels the ability to write and run code that takes advantage of both languages. The specific dialect is ECMAScript 5.1 as identified by the User Guide and its standards definition through ECMA international. In addition to the example below, Benjamin Winterberg has a very well written Java 8 Nashorn Tutorial that provides a large number of code samples in both languages. Basic Operations A basic Hello World application written to run on Nashorn would look like this: #!/usr/bin/jjs print("Hello World"); The first line is a standard script indication, so that Linux or Unix systems can run the script through Nashorn. On Windows where scripts are not as common, you would run the script like: jjs helloWorld.js. Receiving Arguments In order to receive program arguments your jjs invocation needs to use the -scripting flag and a double-dash to separate which arguments are for jjs and which are for the script itself:jjs -scripting print.js -- "This will print" #!/usr/bin/jjs var whatYouSaid = $ARG.length==0 ? "You did not say anything" : $ARG[0] print(whatYouSaid); Interoperability with Java libraries (including 3rd party dependencies) Another goal of Nashorn was to allow for quick scriptable prototypes, allowing access into Java types and any libraries. Resources operate in the context of the script (either in-line with the script or as separate threads) so if you open network sockets and your script terminates, those sockets will be released and available for your next run. Your code can access Java types the same as regular Java classes. The “import statements” are written somewhat differently to accommodate for language. There is a choice of two styles: For standard classes, just name the class: var ServerSocket = java.net.ServerSocket For arrays or other items, use Java.type: var ByteArray = Java.type("byte[]")You could technically do this for all. The same technique will allow your script to use Java types from any library or 3rd party component and quickly prototype items. Building a user interface One major difference between JavaScript inside and outside of a web browser is the availability of a DOM object for rendering views. When run outside of the browser, JavaScript has full control to construct the entire user interface with pre-fabricated UI controls, charts, or components. The example below is a variation from the Nashorn and JavaFX guide to show how items work together. Nashorn has a -fx flag to make the user interface components available. With the example script below, just specify: jjs -fx -scripting fx.js -- "My title" #!/usr/bin/jjs -fx var Button = javafx.scene.control.Button; var StackPane = javafx.scene.layout.StackPane; var Scene = javafx.scene.Scene; var clickCounter=0; $STAGE.title = $ARG.length>0 ? $ARG[0] : "You didn't provide a title"; var button = new Button(); button.text = "Say 'Hello World'"; button.onAction = myFunctionForButtonClicking; var root = new StackPane(); root.children.add(button); $STAGE.scene = new Scene(root, 300, 250); $STAGE.show(); function myFunctionForButtonClicking(){   var text = "Click Counter: " + clickCounter;   button.setText(text);   clickCounter++;   print(text); } For a more advanced post on using Nashorn to build a high-performing UI, see JavaFX with Nashorn Canvas example. Interoperable with frameworks like Node, Backbone, or Facebook React The major benefit of any language is the interoperability gained by people and systems that can read, write, and use it for interactions. Because Nashorn is built for the ECMAScript specification, developers familiar with JavaScript frameworks can write their code and then have system administrators deploy and monitor the applications the same as any other Java application. A number of projects are also running Node applications on Nashorn through Project Avatar and the supported modules. In addition to the previously mentioned Nashorn tutorial, Benjamin has also written a post about Using Backbone.js with Nashorn. To show the multi-language power of the Java Runtime, there is another interesting example that unites Facebook React and Clojure on JDK 8’s Nashorn. Summary Nashorn provides a simple and fast way of executing JavaScript applications and bridging between the best of each language. By making the full range of Java libraries to JavaScript applications, and the quick prototyping style of JavaScript to Java applications, developers are free to work as they see fit. Software Architects and System Administrators can take advantage of one runtime and leverage any work that they have done to tune, monitor, and certify their systems. Additional information is available within: The Nashorn Users’ Guide Java Magazine’s article "Next Generation JavaScript Engine for the JVM." The Nashorn team’s primary blog or a very helpful collection of Nashorn links.

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  • The Internet of Things Is Really the Internet of People

    - by HCM-Oracle
    By Mark Hurd - Originally Posted on LinkedIn As I speak with CEOs around the world, our conversations invariably come down to this central question: Can we change our corporate cultures and the ways we train and reward our people as rapidly as new technology is changing the work we do, the products we make and how we engage with customers? It’s a critical consideration given today’s pace of disruption, which already is straining traditional management models and HR strategies. Winning companies will bring innovation and vision to their employees and partners by attracting people who will thrive in this emerging world of relentless data, predictive analytics and unlimited what-if scenarios. So, where are we going to find employees who are as familiar with complex data as I am with orderly financial statements and business plans? I’m not just talking about high-end data scientists who most certainly will sit at or near the top of the new decision-making pyramid. Global organizations will need creative and motivated people who will devote their time to manipulating, reviewing, analyzing, sorting and reshaping data to drive business and delight customers. This might seem evident, but my conversations with business people across the globe indicate that only a small number of companies get it. In the past few years, executives have been busy keeping pace with seismic upheavals, including the rise of social customer engagement, the rapid acceleration of product-development cycles and the relentless move to mobile-first. But all of that, I think, is the start of an uphill climb to the top of a roller-coaster. Today, about 10 billion devices across the globe are connected to the Internet. In a couple of years, that number will probably double, and not because we will have bought 10 billion more computers, smart phones and tablets. This unprecedented explosion of Big Data is being triggered by the Internet of Things, which is another way of saying that the numerous intelligent devices touching our everyday lives are all becoming interconnected. Home appliances, food, industrial equipment, pets, pharmaceutical products, pallets, cars, luggage, packaged goods, athletic equipment, even clothing will be streaming data. Some data will provide important information about how to run our businesses and lead healthier lives. Much of it will be extraneous. How does a CEO cope with this unimaginable volume and velocity of data, much less harness it to excite and delight customers? Here are three things CEOs must do to tackle this challenge: 1) Take care of your employees, take care of your customers. Larry Ellison recently noted that the two most important priorities for any CEO today revolve around people: Taking care of your employees and taking care of your customers. Companies in today’s hypercompetitive business environment simply won’t be able to survive unless they’ve got world-class people at all levels of the organization. CEOs must demonstrate a commitment to employees by becoming champions for HR systems that empower every employee to fully understand his or her job, how it ties into the corporate framework, what’s expected of them, what training is available, and how they can use an embedded social network to communicate, collaborate and excel. Over the next several years, many of the world’s top industrialized economies will see a turnover in the workforce on an unprecedented scale. Across the United States, Europe, China and Japan, the “baby boomer” generation will be retiring and, by 2020, we’ll see turnovers in those regions ranging from 10 to 30 percent. How will companies replace all that brainpower, experience and know-how? How will CEOs perpetuate the best elements of their corporate cultures in the midst of this profound turnover? The challenge will be daunting, but it can be met with world-class HR technology. As companies begin replacing up to 30 percent of their workforce, they will need thousands of new types of data-native workers to exploit the Internet of Things in the service of the Internet of People. The shift in corporate mindset here can’t be overstated. The CEO has to be at the forefront of this new way of recruiting, training, motivating, aligning and developing truly 21-century talent. 2) Start thinking today about the Internet of People. Some forward-looking companies have begun pursuing the “democratization of data.” This allows more people within a company greater access to data that can help them make better decisions, move more quickly and keep pace with the changing interests and demands of their customers. As a result, we’ve seen organizations flatten out, growing numbers of well-informed people authorized to make decisions without corporate approval and a movement of engagement away from headquarters to the point of contact with the customer. These are profound changes, and I’m a huge proponent. As I think about what the next few years will bring as companies become deluged with unprecedented streams of data, I’m convinced that we’ll need dramatically different organizational structures, decision-making models, risk-management profiles and reward systems. For example, if a car company’s marketing department mines incoming data to determine that customers are shifting rapidly toward neon-green models, how many layers of approval, review, analysis and sign-off will be needed before the factory starts cranking out more neon-green cars? Will we continue to have organizations where too many people are empowered to say “No” and too few are allowed to say “Yes”? If so, how will those companies be able to compete in a world in which customers have more choices, instant access to more information and less loyalty than ever before? That’s why I think CEOs need to begin thinking about this problem right now, not in a year or two when competitors are already reshaping their organizations to match the marketplace’s new realities. 3) Partner with universities to help create a new type of highly skilled workers. Several years ago, universities introduced new undergraduate as well as graduate-level programs in analytics and informatics as the business need for deeper insights into the booming world of data began to explode. Today, as the growth rate of data continues to soar, we know that the Internet of Things will only intensify that growth. Moreover, as Big Data fuels insights that can be shaped into products and services that generate revenue, the demand for data scientists and data specialists will go on unabated. Beyond that top-level expertise, companies are going to need data-native thinkers at all levels of the organization. Where will this new type of worker come from? I think it’s incumbent on the business community to collaborate with universities to develop new curricula designed to turn out graduates who can capitalize on the data-driven world that the Internet of Things is surely going to create. These new workers will create opportunities to help their companies in fields as diverse as product design, customer service, marketing, manufacturing and distribution. They will become innovative leaders in fashioning an entirely new type of workforce and organizational structure optimized to fully exploit the Internet of Things so that it becomes a high-value enabler of the Internet of People. Mark Hurd is President of Oracle Corporation and a member of the company's Board of Directors. He joined Oracle in 2010, bringing more than 30 years of technology industry leadership, computer hardware expertise, and executive management experience to his role with the company. As President, Mr. Hurd oversees the corporate direction and strategy for Oracle's global field operations, including marketing, sales, consulting, alliances and channels, and support. He focuses on strategy, leadership, innovation, and customers.

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  • PASS Summit 2011 &ndash; Part III

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

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  • Guide to MySQL & NoSQL, Webinar Q&A

    - by Mat Keep
    0 0 1 959 5469 Homework 45 12 6416 14.0 Normal 0 false false false EN-US JA 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-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} Yesterday we ran a webinar discussing the demands of next generation web services and how blending the best of relational and NoSQL technologies enables developers and architects to deliver the agility, performance and availability needed to be successful. Attendees posted a number of great questions to the MySQL developers, serving to provide additional insights into areas like auto-sharding and cross-shard JOINs, replication, performance, client libraries, etc. So I thought it would be useful to post those below, for the benefit of those unable to attend the webinar. Before getting to the Q&A, there are a couple of other resources that maybe useful to those looking at NoSQL capabilities within MySQL: - On-Demand webinar (coming soon!) - Slides used during the webinar - Guide to MySQL and NoSQL whitepaper  - MySQL Cluster demo, including NoSQL interfaces, auto-sharing, high availability, etc.  So here is the Q&A from the event  Q. Where does MySQL Cluster fit in to the CAP theorem? A. MySQL Cluster is flexible. A single Cluster will prefer consistency over availability in the presence of network partitions. A pair of Clusters can be configured to prefer availability over consistency. A full explanation can be found on the MySQL Cluster & CAP Theorem blog post.  Q. Can you configure the number of replicas? (the slide used a replication factor of 1) Yes. A cluster is configured by an .ini file. The option NoOfReplicas sets the number of originals and replicas: 1 = no data redundancy, 2 = one copy etc. Usually there's no benefit in setting it >2. Q. Interestingly most (if not all) of the NoSQL databases recommend having 3 copies of data (the replication factor).    Yes, with configurable quorum based Reads and writes. MySQL Cluster does not need a quorum of replicas online to provide service. Systems that require a quorum need > 2 replicas to be able to tolerate a single failure. Additionally, many NoSQL systems take liberal inspiration from the original GFS paper which described a 3 replica configuration. MySQL Cluster avoids the need for a quorum by using a lightweight arbitrator. You can configure more than 2 replicas, but this is a tradeoff between incrementally improved availability, and linearly increased cost. Q. Can you have cross node group JOINS? Wouldn't that run into the risk of flooding the network? MySQL Cluster 7.2 supports cross nodegroup joins. A full cross-join can require a large amount of data transfer, which may bottleneck on network bandwidth. However, for more selective joins, typically seen with OLTP and light analytic applications, cross node-group joins give a great performance boost and network bandwidth saving over having the MySQL Server perform the join. Q. Are the details of the benchmark available anywhere? According to my calculations it results in approx. 350k ops/sec per processor which is the largest number I've seen lately The details are linked from Mikael Ronstrom's blog The benchmark uses a benchmarking tool we call flexAsynch which runs parallel asynchronous transactions. It involved 100 byte reads, of 25 columns each. Regarding the per-processor ops/s, MySQL Cluster is particularly efficient in terms of throughput/node. It uses lock-free minimal copy message passing internally, and maximizes ID cache reuse. Note also that these are in-memory tables, there is no need to read anything from disk. Q. Is access control (like table) planned to be supported for NoSQL access mode? Currently we have not seen much need for full SQL-like access control (which has always been overkill for web apps and telco apps). So we have no plans, though especially with memcached it is certainly possible to turn-on connection-level access control. But specifically table level controls are not planned. Q. How is the performance of memcached APi with MySQL against memcached+MySQL or any other Object Cache like Ecache with MySQL DB? With the memcache API we generally see a memcached response in less than 1 ms. and a small cluster with one memcached server can handle tens of thousands of operations per second. Q. Can .NET can access MemcachedAPI? Yes, just use a .Net memcache client such as the enyim or BeIT memcache libraries. Q. Is the row level locking applicable when you update a column through memcached API? An update that comes through memcached uses a row lock and then releases it immediately. Memcached operations like "INCREMENT" are actually pushed down to the data nodes. In most cases the locks are not even held long enough for a network round trip. Q. Has anyone published an example using something like PHP? I am assuming that you just use the PHP memcached extension to hook into the memcached API. Is that correct? Not that I'm aware of but absolutely you can use it with php or any of the other drivers Q. For beginner we need more examples. Take a look here for a fully worked example Q. Can I access MySQL using Cobol (Open Cobol) or C and if so where can I find the coding libraries etc? A. There is a cobol implementation that works well with MySQL, but I do not think it is Open Cobol. Also there is a MySQL C client library that is a standard part of every mysql distribution Q. Is there a place to go to find help when testing and/implementing the NoSQL access? If using Cluster then you can use the [email protected] alias or post on the MySQL Cluster forum Q. Are there any white papers on this?  Yes - there is more detail in the MySQL Guide to NoSQL whitepaper If you have further questions, please don’t hesitate to use the comments below!

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  • Configuration "diff" across Oracle WebCenter Sites instances

    - by Mark Fincham-Oracle
    Problem Statement With many Oracle WebCenter Sites environments - how do you know if the various configuration assets and settings are in sync across all of those environments? Background At Oracle we typically have a "W" shaped set of environments.  For the "Production" environments we typically have a disaster recovery clone as well and sometimes additional QA environments alongside the production management environment. In the case of www.java.com we have 10 different environments. All configuration assets/settings (CSElements, Templates, Start Menus etc..) start life on the Development Management environment and are then published downstream to other environments as part of the software development lifecycle. Ensuring that each of these 10 environments has the same set of Templates, CSElements, StartMenus, TreeTabs etc.. is impossible to do efficiently without automation. Solution Summary  The solution comprises of two components. A JSON data feed from each environment. A simple HTML page that consumes these JSON data feeds.  Data Feed: Create a JSON WebService on each environment. The WebService is no more than a SiteEntry + CSElement. The CSElement queries various DB tables to obtain details of the assets/settings returning this data in a JSON feed. Report: Create a simple HTML page that uses JQuery to fetch the JSON feed from each environment and display the results in a table. Since all assets (CSElements, Templates etc..) are published between environments they will have the same last modified date. If the last modified date of an asset is different in the JSON feed or is mising from an environment entirely then highlight that in the report table. Example Solution Details Step 1: Create a Site Entry + CSElement that outputs JSON Site Entry & CSElement Setup  The SiteEntry should be uncached so that the most recent configuration information is returned at all times. In the CSElement set the contenttype accordingly: Step 2: Write the CSElement Logic The basic logic, that we repeat for each asset or setting that we are interested in, is to query the DB using <ics:sql> and then loop over the resultset with <ics:listloop>. For example: <ics:sql sql="SELECT name,updateddate FROM Template WHERE status != 'VO'" listname="TemplateList" table="Template" /> "templates": [ <ics:listloop listname="TemplateList"> {"name":"<ics:listget listname="TemplateList"  fieldname="name"/>", "modified":"<ics:listget listname="TemplateList"  fieldname="updateddate"/>"}, </ics:listloop> ], A comprehensive list of SQL queries to fetch each configuration asset/settings can be seen in the appendix at the end of this article. For the generation of the JSON data structure you could use Jettison (the library ships with the 11.1.1.8 version of the product), native Java 7 capabilities or (as the above example demonstrates) you could roll-your-own JSON output but that is not advised. Step 3: Create an HTML Report The JavaScript logic looks something like this.. 1) Create a list of JSON feeds to fetch: ENVS['dev-mgmngt'] = 'http://dev-mngmnt.example.com/sites/ContentServer?d=&pagename=settings.json'; ENVS['dev-dlvry'] = 'http://dev-dlvry.example.com/sites/ContentServer?d=&pagename=settings.json';  ENVS['test-mngmnt'] = 'http://test-mngmnt.example.com/sites/ContentServer?d=&pagename=settings.json';  ENVS['test-dlvry'] = 'http://test-dlvry.example.com/sites/ContentServer?d=&pagename=settings.json';   2) Create a function to get the JSON feeds: function getDataForEnvironment(url){ return $.ajax({ type: 'GET', url: url, dataType: 'jsonp', beforeSend: function (jqXHR, settings){ jqXHR.originalEnv = env; jqXHR.originalUrl = url; }, success: function(json, status, jqXHR) { console.log('....success fetching: ' + jqXHR.originalUrl); // store the returned data in ALLDATA ALLDATA[jqXHR.originalEnv] = json; }, error: function(jqXHR, status, e) { console.log('....ERROR: Failed to get data from [' + url + '] ' + status + ' ' + e); } }); } 3) Fetch each JSON feed: for (var env in ENVS) { console.log('Fetching data for env [' + env +'].'); var promisedData = getDataForEnvironment(ENVS[env]); promisedData.success(function (data) {}); }  4) For each configuration asset or setting create a table in the report For example, CSElements: 1) Get a list of unique CSElement names from all of the returned JSON data. 2) For each unique CSElement name, create a row in the table  3) Select 1 environment to represent the master or ideal state (e.g. "Everything should be like Production Delivery") 4) For each environment, compare the last modified date of this envs CSElement to the master. Highlight any differences in last modified date or missing CSElements. 5) Repeat...    Appendix This section contains various SQL statements that can be used to retrieve configuration settings from the DB.  Templates  <ics:sql sql="SELECT name,updateddate FROM Template WHERE status != 'VO'" listname="TemplateList" table="Template" /> CSElements <ics:sql sql="SELECT name,updateddate FROM CSElement WHERE status != 'VO'" listname="CSEList" table="CSElement" /> Start Menus <ics:sql sql="select sm.id, sm.cs_name, sm.cs_description, sm.cs_assettype, sm.cs_assetsubtype, sm.cs_itemtype, smr.cs_rolename, p.name from StartMenu sm, StartMenu_Sites sms, StartMenu_Roles smr, Publication p where sm.id=sms.ownerid and sm.id=smr.cs_ownerid and sms.pubid=p.id order by sm.id" listname="startList" table="Publication,StartMenu,StartMenu_Roles,StartMenu_Sites"/>  Publishing Configurations <ics:sql sql="select id, name, description, type, dest, factors from PubTarget" listname="pubTargetList" table="PubTarget" /> Tree Tabs <ics:sql sql="select tt.id, tt.title, tt.tooltip, p.name as pubname, ttr.cs_rolename, ttsect.name as sectname from TreeTabs tt, TreeTabs_Roles ttr, TreeTabs_Sect ttsect,TreeTabs_Sites ttsites LEFT JOIN Publication p  on p.id=ttsites.pubid where p.id is not null and tt.id=ttsites.ownerid and ttsites.pubid=p.id and tt.id=ttr.cs_ownerid and tt.id=ttsect.ownerid order by tt.id" listname="treeTabList" table="TreeTabs,TreeTabs_Roles,TreeTabs_Sect,TreeTabs_Sites,Publication" />  Filters <ics:sql sql="select name,description,classname from Filters" listname="filtersList" table="Filters" /> Attribute Types <ics:sql sql="select id,valuetype,name,updateddate from AttrTypes where status != 'VO'" listname="AttrList" table="AttrTypes" /> WebReference Patterns <ics:sql sql="select id,webroot,pattern,assettype,name,params,publication from WebReferencesPatterns" listname="WebRefList" table="WebReferencesPatterns" /> Device Groups <ics:sql sql="select id,devicegroupsuffix,updateddate,name from DeviceGroup" listname="DeviceList" table="DeviceGroup" /> Site Entries <ics:sql sql="select se.id,se.name,se.pagename,se.cselement_id,se.updateddate,cse.rootelement from SiteEntry se LEFT JOIN CSElement cse on cse.id = se.cselement_id where se.status != 'VO'" listname="SiteList" table="SiteEntry,CSElement" /> Webroots <ics:sql sql="select id,name,rooturl,updatedby,updateddate from WebRoot" listname="webrootList" table="WebRoot" /> Page Definitions <ics:sql sql="select pd.id, pd.name, pd.updatedby, pd.updateddate, pd.description, pdt.attributeid, pa.name as nameattr, pdt.requiredflag, pdt.ordinal from PageDefinition pd, PageDefinition_TAttr pdt, PageAttribute pa where pd.status != 'VO' and pa.id=pdt.attributeid and pdt.ownerid=pd.id order by pd.id,pdt.ordinal" listname="pageDefList" table="PageDefinition,PageAttribute,PageDefinition_TAttr" /> FW_Application <ics:sql sql="select id,name,updateddate from FW_Application where status != 'VO'" listname="FWList" table="FW_Application" /> Custom Elements <ics:sql sql="select elementname from ElementCatalog where elementname like 'CustomElements%'" listname="elementList" table="ElementCatalog" />

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  • Das T5-4 TPC-H Ergebnis naeher betrachtet

    - by Stefan Hinker
    Inzwischen haben vermutlich viele das neue TPC-H Ergebnis der SPARC T5-4 gesehen, das am 7. Juni bei der TPC eingereicht wurde.  Die wesentlichen Punkte dieses Benchmarks wurden wie gewohnt bereits von unserer Benchmark-Truppe auf  "BestPerf" zusammengefasst.  Es gibt aber noch einiges mehr, das eine naehere Betrachtung lohnt. Skalierbarkeit Das TPC raet von einem Vergleich von TPC-H Ergebnissen in unterschiedlichen Groessenklassen ab.  Aber auch innerhalb der 3000GB-Klasse ist es interessant: SPARC T4-4 mit 4 CPUs (32 Cores mit 3.0 GHz) liefert 205,792 QphH. SPARC T5-4 mit 4 CPUs (64 Cores mit 3.6 GHz) liefert 409,721 QphH. Das heisst, es fehlen lediglich 1863 QphH oder 0.45% zu 100% Skalierbarkeit, wenn man davon ausgeht, dass die doppelte Anzahl Kerne das doppelte Ergebnis liefern sollte.  Etwas anspruchsvoller, koennte man natuerlich auch einen Faktor von 2.4 erwarten, wenn man die hoehere Taktrate mit beruecksichtigt.  Das wuerde die Latte auf 493901 QphH legen.  Dann waere die SPARC T5-4 bei 83%.  Damit stellt sich die Frage: Was hat hier nicht skaliert?  Vermutlich der Plattenspeicher!  Auch hier lohnt sich eine naehere Betrachtung: Plattenspeicher Im Bericht auf BestPerf und auch im Full Disclosure Report der TPC stehen einige interessante Details zum Plattenspeicher und der Konfiguration.   In der Konfiguration der SPARC T4-4 wurden 12 2540-M2 Arrays verwendet, die jeweils ca. 1.5 GB/s Durchsatz liefert, insgesamt also eta 18 GB/s.  Dabei waren die Arrays offensichtlich mit jeweils 2 Kabeln pro Array direkt an die 24 8GBit FC-Ports des Servers angeschlossen.  Mit den 2x 8GBit Ports pro Array koennte man so ein theoretisches Maximum von 2GB/s erreichen.  Tatsaechlich wurden 1.5GB/s geliefert, was so ziemlich dem realistischen Maximum entsprechen duerfte. Fuer den Lauf mit der SPARC T5-4 wurden doppelt so viele Platten verwendet.  Dafuer wurden die 2540-M2 Arrays mit je einem zusaetzlichen Plattentray erweitert.  Mit dieser Konfiguration wurde dann (laut BestPerf) ein Maximaldurchsatz von 33 GB/s erreicht - nicht ganz das doppelte des SPARC T4-4 Laufs.  Um tatsaechlich den doppelten Durchsatz (36 GB/s) zu liefern, haette jedes der 12 Arrays 3 GB/s ueber seine 4 8GBit Ports liefern muessen.  Im FDR stehen nur 12 dual-port FC HBAs, was die Verwendung der Brocade FC Switches erklaert: Es wurden alle 4 8GBit ports jedes Arrays an die Switches angeschlossen, die die Datenstroeme dann in die 24 16GBit HBA ports des Servers buendelten.  Das theoretische Maximum jedes Storage-Arrays waere nun 4 GB/s.  Wenn man jedoch den Protokoll- und "Realitaets"-Overhead mit einrechnet, sind die tatsaechlich gelieferten 2.75 GB/s gar nicht schlecht.  Mit diesen Zahlen im Hinterkopf ist die Verdopplung des SPARC T4-4 Ergebnisses eine gute Leistung - und gleichzeitig eine gute Erklaerung, warum nicht bis zum 2.4-fachen skaliert wurde. Nebenbei bemerkt: Weder die SPARC T4-4 noch die SPARC T5-4 hatten in der gemessenen Konfiguration irgendwelche Flash-Devices. Mitbewerb Seit die T4 Systeme auf dem Markt sind, bemuehen sich unsere Mitbewerber redlich darum, ueberall den Eindruck zu hinterlassen, die Leistung des SPARC CPU-Kerns waere weiterhin mangelhaft.  Auch scheinen sie ueberzeugt zu sein, dass (ueber)grosse Caches und hohe Taktraten die einzigen Schluessel zu echter Server Performance seien.  Wenn ich mir nun jedoch die oeffentlichen TPC-H Ergebnisse ansehe, sehe ich dies: TPC-H @3000GB, Non-Clustered Systems System QphH SPARC T5-4 3.6 GHz SPARC T5 4/64 – 2048 GB 409,721.8 SPARC T4-4 3.0 GHz SPARC T4 4/32 – 1024 GB 205,792.0 IBM Power 780 4.1 GHz POWER7 8/32 – 1024 GB 192,001.1 HP ProLiant DL980 G7 2.27 GHz Intel Xeon X7560 8/64 – 512 GB 162,601.7 Kurz zusammengefasst: Mit 32 Kernen (mit 3 GHz und 4MB L3 Cache), liefert die SPARC T4-4 mehr QphH@3000GB ab als IBM mit ihrer 32 Kern Power7 (bei 4.1 GHz und 32MB L3 Cache) und auch mehr als HP mit einem 64 Kern Intel Xeon System (2.27 GHz und 24MB L3 Cache).  Ich frage mich, wo genau SPARC hier mangelhaft ist? Nun koennte man natuerlich argumentieren, dass beide Ergebnisse nicht gerade neu sind.  Nun, in Ermangelung neuerer Ergebnisse kann man ja mal ein wenig spekulieren: IBMs aktueller Performance Report listet die o.g. IBM Power 780 mit einem rPerf Wert von 425.5.  Ein passendes Nachfolgesystem mit Power7+ CPUs waere die Power 780+ mit 64 Kernen, verfuegbar mit 3.72 GHz.  Sie wird mit einem rPerf Wert von  690.1 angegeben, also 1.62x mehr.  Wenn man also annimmt, dass Plattenspeicher nicht der limitierende Faktor ist (IBM hat mit 177 SSDs getestet, sie duerfen das gerne auf 400 erhoehen) und IBMs eigene Leistungsabschaetzung zugrunde legt, darf man ein theoretisches Ergebnis von 311398 QphH@3000GB erwarten.  Das waere dann allerdings immer noch weit von dem Ergebnis der SPARC T5-4 entfernt, und gerade in der von IBM so geschaetzen "per core" Metric noch weniger vorteilhaft. In der x86-Welt sieht es nicht besser aus.  Leider gibt es von Intel keine so praktischen rPerf-Tabellen.  Daher muss ich hier fuer eine Schaetzung auf SPECint_rate2006 zurueckgreifen.  (Ich bin kein grosser Fan von solchen Kreuz- und Querschaetzungen.  Insb. SPECcpu ist nicht besonders geeignet, um Datenbank-Leistung abzuschaetzen, da fast kein IO im Spiel ist.)  Das o.g. HP System wird bei SPEC mit 1580 CINT2006_rate gelistet.  Das bis einschl. 2013-06-14 beste Resultat fuer den neuen Intel Xeon E7-4870 mit 8 CPUs ist 2180 CINT2006_rate.  Das ist immerhin 1.38x besser.  (Wenn man nur die Taktrate beruecksichtigen wuerde, waere man bei 1.32x.)  Hier weiter zu rechnen, ist muessig, aber fuer die ungeduldigen Leser hier eine kleine tabellarische Zusammenfassung: TPC-H @3000GB Performance Spekulationen System QphH* Verbesserung gegenueber der frueheren Generation SPARC T4-4 32 cores SPARC T4 205,792 2x SPARC T5-464 cores SPARC T5 409,721 IBM Power 780 32 cores Power7 192,001 1.62x IBM Power 780+ 64 cores Power7+  311,398* HP ProLiant DL980 G764 cores Intel Xeon X7560 162,601 1.38x HP ProLiant DL980 G780 cores Intel Xeon E7-4870    224,348* * Keine echten Resultate  - spekulative Werte auf der Grundlage von rPerf (Power7+) oder SPECint_rate2006 (HP) Natuerlich sind IBM oder HP herzlich eingeladen, diese Werte zu widerlegen.  Aber stand heute warte ich noch auf aktuelle Benchmark Veroffentlichungen in diesem Datensegment. Was koennen wir also zusammenfassen? Es gibt einige Hinweise, dass der Plattenspeicher der begrenzende Faktor war, der die SPARC T5-4 daran hinderte, auf jenseits von 2x zu skalieren Der Mythos, dass SPARC Kerne keine Leistung bringen, ist genau das - ein Mythos.  Wie sieht es umgekehrt eigentlich mit einem TPC-H Ergebnis fuer die Power7+ aus? Cache ist nicht der magische Performance-Schalter, fuer den ihn manche Leute offenbar halten. Ein System, eine CPU-Architektur und ein Betriebsystem jenseits einer gewissen Grenze zu skalieren ist schwer.  In der x86-Welt scheint es noch ein wenig schwerer zu sein. Was fehlt?  Nun, das Thema Preis/Leistung ueberlasse ich gerne den Verkaeufern ;-) Und zu guter Letzt: Nein, ich habe mich nicht ins Marketing versetzen lassen.  Aber manchmal kann ich mich einfach nicht zurueckhalten... Disclosure Statements The views expressed on this blog are my own and do not necessarily reflect the views of Oracle. TPC-H, QphH, $/QphH are trademarks of Transaction Processing Performance Council (TPC). For more information, see www.tpc.org, results as of 6/7/13. Prices are in USD. SPARC T5-4 409,721.8 QphH@3000GB, $3.94/QphH@3000GB, available 9/24/13, 4 processors, 64 cores, 512 threads; SPARC T4-4 205,792.0 QphH@3000GB, $4.10/QphH@3000GB, available 5/31/12, 4 processors, 32 cores, 256 threads; IBM Power 780 QphH@3000GB, 192,001.1 QphH@3000GB, $6.37/QphH@3000GB, available 11/30/11, 8 processors, 32 cores, 128 threads; HP ProLiant DL980 G7 162,601.7 QphH@3000GB, $2.68/QphH@3000GB available 10/13/10, 8 processors, 64 cores, 128 threads. SPEC and the benchmark names SPECfp and SPECint are registered trademarks of the Standard Performance Evaluation Corporation. Results as of June 18, 2013 from www.spec.org. HP ProLiant DL980 G7 (2.27 GHz, Intel Xeon X7560): 1580 SPECint_rate2006; HP ProLiant DL980 G7 (2.4 GHz, Intel Xeon E7-4870): 2180 SPECint_rate2006,

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  • Do you know your ADF "grace period?"

    - by Chris Muir
    What does the term "support" mean to you in context of vendors such as Oracle giving your organization support with our products? Over the last few weeks I'm taken a straw poll to discuss this very question with customers, and I've received a wide array of answers much to my surprise (which I've paraphrased): "Support means my staff can access dedicated resources to assist them solve problems" "Support means I can call Oracle at anytime to request assistance" "Support means we can expect fixes and patches to bugs in Oracle software" The last expectation is the one I'd like to focus on in this post, keep it in mind while reading this blog. From Oracle's perspective as we're in the business of support, we in fact offer numerous services which are captured on the table in the following page. As the text under the table indicates, you should consult the relevant Oracle Lifetime Support brochures to understand the length of time Oracle will support Oracle products. As I'm a product manager for ADF that sits under the FMW tree of Oracle products, let's consider ADF in particular. The FMW brochure is found here. On page 8 and 9 you'll see the current "Application Development Framework 11gR1 (11.1.1.x)" and "Application Development Framework 11gR2 (11.1.2)" releases are supported out to 2017 for Extended Support. This timeframe is pretty standard for Oracle's current released products, though as new releases roll in we should see those dates extended. On page 8 of the PDF note the comment at the end of this page that refers to the Oracle Support document 209768.1: For more-detailed information on bug fix and patch release policies, please refer to the “Error Correction Support Policy” on MyOracle Support. This policy document is important as it introduces Oracle's Error Correction Support Policy which addresses "patches and fixes". You can find it attached the previous Oracle Support document 209768.1. Broadly speaking while Oracle does provide "generalized support" up to 2017 for ADF, the Error Correction Support Policy dictates when Oracle will provide "patches and fixes" for Oracle software, and this is where the concept of the "grace period" comes in. As Oracle releases different versions of Oracle software, say 11.1.1.4.0, you are fully supported for patches and fixes for that specific version. However when we release the next version, say 11.1.1.5.0, Oracle provides at minimum of 3 months to a maximum of 1 year "grace period" where we'll continue to provide patches and fixes for the previous version. This gives you time to move from 11.1.1.4.0 to 11.1.1.5.0 without being unsupported for patches and fixes. The last paragraph does generalize as I've attempted to highlight the concept of the grace period rather than the specific dates for any version. For specific ADF and FMW versions and their respective grace periods and when they terminated you must visit Oracle Support Note 1290894.1. I'd like to include a screenshot here of the relevant table from that Oracle Support Note but as it is will be frequently updated it's better I force you to visit that note. Be careful to heed the comment in the note: According to policy, the Grace Period has passed because a newer Patch Set has been released for more than a year. Its important to note that the Lifetime Support Policy and Error Correction Support Policy documents are the single source of truth, subject to change, and will provide exceptions when required. This My Oracle Support document is providing a summary of the Grace Period dates and time lines for planning purposes. So remember to return to the policy document for all definitions, note 1290894.1 is a summary only and not guaranteed to be up to date or correct. A last point from Oracle's perspective. Why doesn't Oracle provide patches and fixes for all releases as long as they're supported? Amongst other reasons, it's a matter of practicality. Consider JDeveloper 10.1.3 released in 2005. JDeveloper 10.1.3 is still currently supported to 2017, but since that version was released there has been just under 20 newer releases of JDeveloper. Now multiply that across all Oracle's products and imagine the number of releases Oracle would have to provide fixes and patches for, and maintain environments to test them, build them, staff to write them and more, it's simple beyond the capabilities of even a large software vendor like Oracle. So the "grace period" restricts that patches and fixes window to something manageable. In conclusion does the concept of the "grace period" matter to you? If you define support as "getting assistance from Oracle" then maybe not. But if patches and fixes are important to you, then you need to understand the "grace period" and operate within the bounds of Oracle's Error Correction Support Policy. Disclaimer: this blog post was written July 2012. Oracle Support policies do change from time to time so the emphasis is on you to double check the facts presented in this blog.

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  • How to Customize Fonts and Colors for Gnome Panels in Ubuntu Linux

    - by The Geek
    Earlier this week we showed you how to make the Gnome Panels totally transparent, but you really need some customized fonts and colors to make the effect work better. Here’s how to do it. This article is the first part of a multi-part series on how to customize the Ubuntu desktop, written by How-To Geek reader and ubergeek, Omar Hafiz. Changing the Gnome Colors the Easy Way You’ll first need to install Gnome Color Chooser which is available in the default repositories (the package name is gnome-color-chooser). Then go to System > Preferences > Gnome Color Chooser to launch the program. When you see all these tabs you immediately know that Gnome Color Chooser does not only change the font color of the panel, but also the color of the fonts all over Ubuntu, desktop icons, and many other things as well. Now switch to the panel tab, here you can control every thing about your panels. You can change font, font color, background and background color of the panels and start menus. Tick the “Normal” option and choose the color you want for the panel font. If you want you can change the hover color of the buttons on the panel by too. A little below the color option is the font options, this includes the font, font size, and the X and Y positioning of the font. The first two options are pretty straight forward, they change the typeface and the size. The X-Padding and Y-Padding may confuse you but they are interesting, they may give a nice look for your panels by increasing the space between items on your panel like this: X-Padding:   Y-Padding:   The bottom half of the window controls the look of your start menus which is the Applications, Places, and Systems menus. You can customize them just the way you did with the panel.   Alright, this was the easy way to change the font of your panels. Changing the Gnome Theme Colors the Command-Line Way The other hard (not so hard really) way will be changing the configuration files that tell your panel how it should look like. In your Home Folder, press Ctrl+H to show the hidden files, now find the file “.gtkrc-2.0”, open it and insert this line in it. If there are any other lines in the file leave them intact. include “/home/<username>/.gnome2/panel-fontrc” Don’t forget to replace the <user_name> with you user account name. When done close and save the file. Now navigate the folder “.gnome2” from your Home Folder and create a new file and name it “panel-fontrc”. Open the file you just created with a text editor and paste the following in it: style “my_color”{fg[NORMAL] = “#FF0000”}widget “*PanelWidget*” style “my_color”widget “*PanelApplet*” style “my_color” This text will make the font red. If you want other colors you’ll need to replace the Hex value/HTML Notation (in this case #FF0000) with the value of the color you want. To get the hex value you can use GIMP, Gcolor2 witch is available in the default repositories or you can right-click on your panel > Properties > Background tab then click to choose the color you want and copy the Hex value. Don’t change any other thing in the text. When done, save and close. Now press Alt+F2 and enter “killall gnome-panel” to force it to restart or you can log out and login again. Most of you will prefer the first way of changing the font and color for it’s ease of applying and because it gives you much more options but, some may not have the ability/will to download and install a new program on their machine or have reasons of their own for not to using it, that’s why we provided the two way. Latest Features How-To Geek ETC How to Enable User-Specific Wireless Networks in Windows 7 How to Use Google Chrome as Your Default PDF Reader (the Easy Way) How To Remove People and Objects From Photographs In Photoshop Ask How-To Geek: How Can I Monitor My Bandwidth Usage? Internet Explorer 9 RC Now Available: Here’s the Most Interesting New Stuff Here’s a Super Simple Trick to Defeating Fake Anti-Virus Malware The Splendiferous Array of Culinary Tools [Infographic] Add a Real-Time Earth Wallpaper App to Ubuntu with xplanetFX The Citroen GT – An Awesome Video Game Car Brought to Life [Video] Final Man vs. Machine Round of Jeopardy Unfolds; Watson Dominates Give Chromium-Based Browser Desktop Notifications a Native System Look in Ubuntu Chrome Time Track Is a Simple Task Time Tracker

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  • Automating deployments with the SQL Compare command line

    - by Jonathan Hickford
    In my previous article, “Five Tips to Get Your Organisation Releasing Software Frequently” I looked at how teams can automate processes to speed up release frequency. In this post, I’m looking specifically at automating deployments using the SQL Compare command line. SQL Compare compares SQL Server schemas and deploys the differences. It works very effectively in scenarios where only one deployment target is required – source and target databases are specified, compared, and a change script is automatically generated and applied. But if multiple targets exist, and pressure to increase the frequency of releases builds, this solution quickly becomes unwieldy.   This is where SQL Compare’s command line comes into its own. I’ve put together a PowerShell script that loops through the Servers table and pulls out the server and database, these are then passed to sqlcompare.exe to be used as target parameters. In the example the source database is a scripts folder, a folder structure of scripted-out database objects used by both SQL Source Control and SQL Compare. The script can easily be adapted to use schema snapshots.     -- Create a DeploymentTargets database and a Servers table CREATE DATABASE DeploymentTargets GO USE DeploymentTargets GO CREATE TABLE [dbo].[Servers]( [id] [int] IDENTITY(1,1) NOT NULL, [serverName] [nvarchar](50) NULL, [environment] [nvarchar](50) NULL, [databaseName] [nvarchar](50) NULL, CONSTRAINT [PK_Servers] PRIMARY KEY CLUSTERED ([id] ASC) ) GO -- Now insert your target server and database details INSERT INTO dbo.Servers ( serverName , environment , databaseName) VALUES ( N'myserverinstance' , N'myenvironment1' , N'mydb1') INSERT INTO dbo.Servers ( serverName , environment , databaseName) VALUES ( N'myserverinstance' , N'myenvironment2' , N'mydb2') Here’s the PowerShell script you can adapt for yourself as well. # We're holding the server names and database names that we want to deploy to in a database table. # We need to connect to that server to read these details $serverName = "" $databaseName = "DeploymentTargets" $authentication = "Integrated Security=SSPI" #$authentication = "User Id=xxx;PWD=xxx" # If you are using database authentication instead of Windows authentication. # Path to the scripts folder we want to deploy to the databases $scriptsPath = "SimpleTalk" # Path to SQLCompare.exe $SQLComparePath = "C:\Program Files (x86)\Red Gate\SQL Compare 10\sqlcompare.exe" # Create SQL connection string, and connection $ServerConnectionString = "Data Source=$serverName;Initial Catalog=$databaseName;$authentication" $ServerConnection = new-object system.data.SqlClient.SqlConnection($ServerConnectionString); # Create a Dataset to hold the DataTable $dataSet = new-object "System.Data.DataSet" "ServerList" # Create a query $query = "SET NOCOUNT ON;" $query += "SELECT serverName, environment, databaseName " $query += "FROM dbo.Servers; " # Create a DataAdapter to populate the DataSet with the results $dataAdapter = new-object "System.Data.SqlClient.SqlDataAdapter" ($query, $ServerConnection) $dataAdapter.Fill($dataSet) | Out-Null # Close the connection $ServerConnection.Close() # Populate the DataTable $dataTable = new-object "System.Data.DataTable" "Servers" $dataTable = $dataSet.Tables[0] #For every row in the DataTable $dataTable | FOREACH-OBJECT { "Server Name: $($_.serverName)" "Database Name: $($_.databaseName)" "Environment: $($_.environment)" # Compare the scripts folder to the database and synchronize the database to match # NB. Have set SQL Compare to abort on medium level warnings. $arguments = @("/scripts1:$($scriptsPath)", "/server2:$($_.serverName)", "/database2:$($_.databaseName)", "/AbortOnWarnings:Medium") # + @("/sync" ) # Commented out the 'sync' parameter for safety, write-host $arguments & $SQLComparePath $arguments "Exit Code: $LASTEXITCODE" # Some interesting variations # Check that every database matches a folder. # For example this might be a pre-deployment step to validate everything is at the same baseline state. # Or a post deployment script to validate the deployment worked. # An exit code of 0 means the databases are identical. # # $arguments = @("/scripts1:$($scriptsPath)", "/server2:$($_.serverName)", "/database2:$($_.databaseName)", "/Assertidentical") # Generate a report of the difference between the folder and each database. Generate a SQL update script for each database. # For example use this after the above to generate upgrade scripts for each database # Examine the warnings and the HTML diff report to understand how the script will change objects # #$arguments = @("/scripts1:$($scriptsPath)", "/server2:$($_.serverName)", "/database2:$($_.databaseName)", "/ScriptFile:update_$($_.environment+"_"+$_.databaseName).sql", "/report:update_$($_.environment+"_"+$_.databaseName).html" , "/reportType:Interactive", "/showWarnings", "/include:Identical") } It’s worth noting that the above example generates the deployment scripts dynamically. This approach should be problem-free for the vast majority of changes, but it is still good practice to review and test a pre-generated deployment script prior to deployment. An alternative approach would be to pre-generate a single deployment script using SQL Compare, and run this en masse to multiple targets programmatically using sqlcmd, or using a tool like SQL Multi Script.  You can use the /ScriptFile, /report, and /showWarnings flags to generate change scripts, difference reports and any warnings.  See the commented out example in the PowerShell: #$arguments = @("/scripts1:$($scriptsPath)", "/server2:$($_.serverName)", "/database2:$($_.databaseName)", "/ScriptFile:update_$($_.environment+"_"+$_.databaseName).sql", "/report:update_$($_.environment+"_"+$_.databaseName).html" , "/reportType:Interactive", "/showWarnings", "/include:Identical") There is a drawback of running a pre-generated deployment script; it assumes that a given database target hasn’t drifted from its expected state. Often there are (rightly or wrongly) many individuals within an organization who have permissions to alter the production database, and changes can therefore be made outside of the prescribed development processes. The consequence is that at deployment time, the applied script has been validated against a target that no longer represents reality. The solution here would be to add a check for drift prior to running the deployment script. This is achieved by using sqlcompare.exe to compare the target against the expected schema snapshot using the /Assertidentical flag. Should this return any differences (sqlcompare.exe Exit Code 79), a drift report is outputted instead of executing the deployment script.  See the commented out example. # $arguments = @("/scripts1:$($scriptsPath)", "/server2:$($_.serverName)", "/database2:$($_.databaseName)", "/Assertidentical") Any checks and processes that should be undertaken prior to a manual deployment, should also be happen during an automated deployment. You might think about triggering backups prior to deployment – even better, automate the verification of the backup too.   You can use SQL Compare’s command line interface along with PowerShell to automate multiple actions and checks that you need in your deployment process. Automation is a practical solution where multiple targets and a higher release cadence come into play. As we know, with great power comes great responsibility – responsibility to ensure that the necessary checks are made so deployments remain trouble-free.  (The code sample supplied in this post automates the simple dynamic deployment case – if you are considering more advanced automation, e.g. the drift checks, script generation, deploying to large numbers of targets and backup/verification, please email me at [email protected] for further script samples or if you have further questions)

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  • 10 tape technology features that make you go hmm.

    - by Karoly Vegh
    A week ago an Oracle/StorageTek Tape Specialist, Christian Vanden Balck, visited Vienna, and agreed to visit customers to do techtalks and update them about the technology boom going around tape. I had the privilege to attend some of his sessions and noted the information and features that took the customers by surprise and made them think. Allow me to share the top 10: I. StorageTek as a brand: StorageTek is one of he strongest names in the Tape field. The brand itself was valued so much by customers that even after Sun Microsystems acquiring StorageTek and the Oracle acquiring Sun the brand lives on with all the Oracle tapelibraries are officially branded StorageTek.See http://www.oracle.com/us/products/servers-storage/storage/tape-storage/overview/index.html II. Disk information density limitations: Disk technology struggles with information density. You haven't seen the disk sizes exploding lately, have you? That's partly because there are physical limits on a disk platter. The size is given, the number of platters is limited, they just can't grow, and are running out of physical area to write to. Now, in a T10000C tape cartridge we have over 1000m long tape. There you go, you have got your physical space and don't need to stuff all that data crammed together. You can write in a reliable pattern, and have space to grow too. III. Oracle has a market share of 62% worldwide in recording head manufacturing. That's right. If you are running LTO drives, with a good chance you rely on StorageTek production. That's two out of three LTO recording heads produced worldwide.  IV. You can store 1 Exabyte data in a single tape library. Yes, an Exabyte. That is 1000 Petabytes. Or, a million Terabytes. A thousand million GigaBytes. You can store that in a stacked StorageTek SL8500 tapelibrary. In one SL8500 you can put 10.000 T10000C cartridges, that store 10TB data (compressed). You can stack 10 of these SL8500s together. Boom. 1000.000 TB.(n.b.: stacking means interconnecting the libraries. Yes, cartridges are moved between the stacked libraries automatically.)  V. EMC: 'Tape doesn't suck after all. We moved on.': Do you remember the infamous 'Tape sucks, move on' Datadomain slogan? Of course they had to put it that way, having only had disk products. But here's a fun fact: on the EMCWorld 2012 there was a major presence of a Tape-tech company - EMC, in a sudden burst of sanity is embracing tape again. VI. The miraculous T10000C: Oracle StorageTek has developed an enterprise-grade tapedrive and cartridge, the T10000C. With awesome numbers: The Cartridge: Native 5TB capacity, 10TB with compression Over a kilometer long tape within the cartridge. And it's locked when unmounted, no rattling of your data.  Replaced the metalparticles datalayer with BaFe (bariumferrite) - metalparticles lose around 7% of magnetism within 30 days. BaFe does not. Yes we employ solid-state physicists doing R&D on demagnetisation in our labs. Can be partitioned, storage tiering within the cartridge!  The Drive: 2GB Cache Encryption implemented in HW - no performance hit 252 MB/s native sustained data rate, beats disk technology by far. Not to mention peak throughput.  Leading the tape while never touching the data side of it, protecting your data physically too Data integritiy checking (CRC recalculation) on tape within the drive without having to read it back to the server reordering data from tape-order, delivering it back in application-order  writing 32 tracks at once, reading them back for CRC check at once VII. You only use 20% of your data on a regular basis. The rest 80% is just lying around for years. On continuously spinning disks. Doubly consuming energy (power+cooling), blocking diskstorage capacity. There is a solution called SAM (Storage Archive Manager) that provides you a filesystem unifying disk and tape, moving data on-demand and for clients transparently between the different storage tiers. You can share these filesystems with NFS or CIFS for clients, and enjoy the low TCO of tape. Tapes don't spin. They sit quietly in their slots, storing 10TB data, using no energy, producing no heat, automounted when a client accesses their data.See: http://www.oracle.com/us/products/servers-storage/storage/storage-software/storage-archive-manager/overview/index.html VIII. HW supported for three decades: Did you know that the original PowderHorn library was released in '87 and has been only discontinued in 2010? That is over two decades of supported operation. Tape libraries are - just like the data carrying on tapecartridges - built for longevity. Oh, and the T10000C cartridge has 30-year archival life for long-term retention.  IX. Tape is easy to manage: Have you heard of Tape Storage Analytics? It is a central graphical tool to summarize, monitor, analyze dataflow, health and performance of drives and libraries, see: http://www.oracle.com/us/products/servers-storage/storage/tape-storage/tape-analytics/overview/index.html X. The next generation: The T10000B drives were able to reuse the T10000A cartridges and write on them even more data. On the same cartridges. We call this investment protection, and this is very important for Oracle for the future too. We usually support two generations of cartridges together. The current drive is a T10000C. (...I know I promised to enlist 10, but I got still two more I really want to mention. Allow me to work around the problem: ) X++. The TallBots, the robots moving around the cartridges in the StorageTek library from tapeslots to the drives are cableless. Cables, belts, chains running to moving parts in a library cause maintenance downtimes. So StorageTek eliminated them. The TallBots get power, commands, even firmwareupgrades through the rails they are running on. Also, the TallBots don't just hook'n'pull the tapes out of their slots, they actually grip'n'lift them out. No friction, no scratches, no zillion little plastic particles floating around in the library, in the drives, on your data. (X++)++: Tape beats SSDs and Disks. In terms of throughput (252 MB/s), in terms of TCO: disks cause around 290x more power and cooling, in terms of capacity: 10TB on a single media and soon more.  So... do you need to store large amounts of data? Are you legally bound to archive it for dozens of years? Would you benefit from automatic storage tiering? Have you got large mediachunks to be streamed at times? Have you got power and cooling issues in the growing datacenters? Do you find EMC's 180° turn of tape attitude interesting, but appreciate it at the same time? With all that, you aren't alone. The most data on this planet is stored on tape. Tape is coming. Big time.

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  • External File Upload Optimizations for Windows Azure

    - by rgillen
    [Cross posted from here: http://rob.gillenfamily.net/post/External-File-Upload-Optimizations-for-Windows-Azure.aspx] I’m wrapping up a bit of the work we’ve been doing on data movement optimizations for cloud computing and the latest set of data yielded some interesting points I thought I’d share. The work done here is not really rocket science but may, in some ways, be slightly counter-intuitive and therefore seemed worthy of posting. Summary: for those who don’t like to read detailed posts or don’t have time, the synopsis is that if you are uploading data to Azure, block your data (even down to 1MB) and upload in parallel. Set your block size based on your source file size, but if you must choose a fixed value, use 1MB. Following the above will result in significant performance gains… upwards of 10x-24x and a reduction in overall file transfer time of upwards of 90% (eg, uploading a 1GB file averaged 46.37 minutes prior to optimizations and averaged 1.86 minutes afterwards). Detail: For those of you who want more detail, or think that the claims at the end of the preceding paragraph are over-reaching, what follows is information and code supporting these claims. As the title would indicate, these tests were run from our research facility pointing to the Azure cloud (specifically US North Central as it is physically closest to us) and do not represent intra-cloud results… we have performed intra-cloud tests and the overall results are similar in notion but the data rates are significantly different as well as the tipping points for the various block sizes… this will be detailed separately). We started by building a very simple console application that would loop through a directory and upload each file to Azure storage. This application used the shipping storage client library from the 1.1 version of the azure tools. The only real variation from the client library is that we added code to collect and record the duration (in ms) and size (in bytes) for each file transferred. The code is available here. We then created a directory that had a collection of files for the following sizes: 2KB, 32KB, 64KB, 128KB, 512KB, 1MB, 5MB, 10MB, 25MB, 50MB, 100MB, 250MB, 500MB, 750MB, and 1GB (50 files for each size listed). These files contained randomly-generated binary data and do not benefit from compression (a separate discussion topic). Our file generation tool is available here. The baseline was established by running the application described above against the directory containing all of the data files. This application uploads the files in a random order so as to avoid transferring all of the files of a given size sequentially and thereby spreading the affects of periodic Internet delays across the collection of results.  We then ran some scripts to split the resulting data and generate some reports. The raw data collected for our non-optimized tests is available via the links in the Related Resources section at the bottom of this post. For each file size, we calculated the average upload time (and standard deviation) and the average transfer rate (and standard deviation). As you likely are aware, transferring data across the Internet is susceptible to many transient delays which can cause anomalies in the resulting data. It is for this reason that we randomized the order of source file processing as well as executed the tests 50x for each file size. We expect that these steps will yield a sufficiently balanced set of results. Once the baseline was collected and analyzed, we updated the test harness application with some methods to split the source file into user-defined block sizes and then to upload those blocks in parallel (using the PutBlock() method of Azure storage). The parallelization was handled by simply relying on the Parallel Extensions to .NET to provide a Parallel.For loop (see linked source for specific implementation details in Program.cs, line 173 and following… less than 100 lines total). Once all of the blocks were uploaded, we called PutBlockList() to assemble/commit the file in Azure storage. For each block transferred, the MD5 was calculated and sent ensuring that the bits that arrived matched was was intended. The timer for the blocked/parallelized transfer method wraps the entire process (source file splitting, block transfer, MD5 validation, file committal). A diagram of the process is as follows: We then tested the affects of blocking & parallelizing the transfers by running the updated application against the same source set and did a parameter sweep on the block size including 256KB, 512KB, 1MB, 2MB, and 4MB (our assumption was that anything lower than 256KB wasn’t worth the trouble and 4MB is the maximum size of a block supported by Azure). The raw data for the parallel tests is available via the links in the Related Resources section at the bottom of this post. This data was processed and then compared against the single-threaded / non-optimized transfer numbers and the results were encouraging. The Excel version of the results is available here. Two semi-obvious points need to be made prior to reviewing the data. The first is that if the block size is larger than the source file size you will end up with a “negative optimization” due to the overhead of attempting to block and parallelize. The second is that as the files get smaller, the clock-time cost of blocking and parallelizing (overhead) is more apparent and can tend towards negative optimizations. For this reason (and is supported in the raw data provided in the linked worksheet) the charts and dialog below ignore source file sizes less than 1MB. (click chart for full size image) The chart above illustrates some interesting points about the results: When the block size is smaller than the source file, performance increases but as the block size approaches and then passes the source file size, you see decreasing benefit to the point of negative gains (see the values for the 1MB file size) For some of the moderately-sized source files, small blocks (256KB) are best As the size of the source file gets larger (see values for 50MB and up), the smallest block size is not the most efficient (presumably due, at least in part, to the increased number of blocks, increased number of individual transfer requests, and reassembly/committal costs). Once you pass the 250MB source file size, the difference in rate for 1MB to 4MB blocks is more-or-less constant The 1MB block size gives the best average improvement (~16x) but the optimal approach would be to vary the block size based on the size of the source file.    (click chart for full size image) The above is another view of the same data as the prior chart just with the axis changed (x-axis represents file size and plotted data shows improvement by block size). It again highlights the fact that the 1MB block size is probably the best overall size but highlights the benefits of some of the other block sizes at different source file sizes. This last chart shows the change in total duration of the file uploads based on different block sizes for the source file sizes. Nothing really new here other than this view of the data highlights the negative affects of poorly choosing a block size for smaller files.   Summary What we have found so far is that blocking your file uploads and uploading them in parallel results in significant performance improvements. Further, utilizing extension methods and the Task Parallel Library (.NET 4.0) make short work of altering the shipping client library to provide this functionality while minimizing the amount of change to existing applications that might be using the client library for other interactions.   Related Resources Source code for upload test application Source code for random file generator ODatas feed of raw data from non-optimized transfer tests Experiment Metadata Experiment Datasets 2KB Uploads 32KB Uploads 64KB Uploads 128KB Uploads 256KB Uploads 512KB Uploads 1MB Uploads 5MB Uploads 10MB Uploads 25MB Uploads 50MB Uploads 100MB Uploads 250MB Uploads 500MB Uploads 750MB Uploads 1GB Uploads Raw Data OData feeds of raw data from blocked/parallelized transfer tests Experiment Metadata Experiment Datasets Raw Data 256KB Blocks 512KB Blocks 1MB Blocks 2MB Blocks 4MB Blocks Excel worksheet showing summarizations and comparisons

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  • 12c??? - Active Data Guard Far Sync

    - by Jian Zhang(??)
    ?? ================ Active Data Guard Far Sync?Oracle 12c????(???Far Sync Standby),Far Sync?????????????(Primary Database)?????????Far Sync??,??(Primary Database) ??(synchronous)??redo?Far Sync??,??Far Sync????redo??(asynchronous)???????(Standby Database)???????????????????????Far Sync????????,init?????????,???????? ??redo ????Maximum Availability??,???????????(Primary Database)?????????Far Sync??,??(Primary Database)??(synchronous)??redo?Far Sync??,???????(zero data loss),?????Far Sync????,??????,??????????????Far Sync????redo??(asynchronous)???????(Standby Database)? ??redo ????Maximum Performance??,???????????(Primary Database)?????????Far Sync??,??(Primary Database) ????redo?Far Sync??,??Far Sync???????redo?????????(Standby Database)????????????????(Standby Database)??redo???(offload)? Far Sync????Data Guard ????(role transitions)????,?switchover/failover?????12c????? ???????Data Guard ????,?switchover/failover,???????????????Far Sync??,??Far Sync???????????????????? ???Far Sync???????,??????????????2?Far Sync??,???????? ???????Far Sync????? Far Sync??? ================ ????Far Sync ================ 1. ??Data Guard,???11.2??,??????«Active Database Duplication for A standby database» 2. ????Far Sync??,Far Sync????????,init?????????,???????? ??Far Sync???????,?????: SQL> ALTER DATABASE CREATE FAR SYNC INSTANCE CONTROLFILE AS '/tmp/controlfs01.ctl'; 3. ????redo?????Far Sync??,????LOG_ARCHIVE_DEST_2??: LOG_ARCHIVE_DEST_2='SERVICE=dg12cfs SYNC AFFIRM MAX_FAILURE=1 ALTERNATE=LOG_ARCHIVE_DEST_3 VALID_FOR=(ONLINE_LOGFILES,PRIMARY_ROLE) DB_UNIQUE_NAME=dg12cfs' 4. ??Far Sync??????redo???,??Far Sync??LOG_ARCHIVE_DEST_2??: LOG_ARCHIVE_DEST_2='SERVICE=dg12cs ASYNC VALID_FOR=(STANDBY_LOGFILES,STANDBY_ROLE) DB_UNIQUE_NAME=dg12cs' 5. ????Far Sync???????,??????????????2?Far Sync??? 6. ???????: SQL> select * from  V$DATAGUARD_CONFIG; DB_UNIQUE_NAME       PARENT_DBUN       DEST_ROLE         CURRENT_SCN     CON_ID ------------------------------ ------------------------------     ----------------- ----------- ---------- dg12cfs                        dg12cp          FAR SYNC INSTANCE      682995          0 dg12cs                         dg12cfs         PHYSICAL STANDBY       682995          0 dg12cp                        NONE             PRIMARY DATABASE      683138          0 ????????????????:Oracle_12c_Active_Data_Guard_Far_Sync_v1.pdf

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  • The Future of Project Management is Social

    - by Natalia Rachelson
    Normal 0 false false false EN-US X-NONE X-NONE MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0in 5.4pt 0in 5.4pt; mso-para-margin:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} A guest post by Kazim Isfahani, Director, Product Marketing, Oracle Rapid Ascent. Breakneck Speed. Lightning Fast. Perhaps even overwhelming. No matter which set of adjectives we use to describe it, social media’s rise into the enterprise mainstream has been unprecedented. Indeed, the big 4 social media powerhouses (Facebook, Google+, LinkedIn, and Twitter), have nearly 2 Billion users between them. You may be asking (as you should really) “That’s all well and good for the consumer, but for me at my company, what’s your point? Beyond the fact that I can check and post updates, that is.” Good question, kind sir. Impact of Social and Collaboration on Project Management I’ll dovetail this discussion to the project management realm, since that’s what I’m writing about. Speed is a big challenge for project-driven organizations. Anything that can help speed up project delivery - be it a new product introduction effort or a geographical expansion project - fast is a good thing. So where does this whole social thing fit particularly since there are already a host of tools to help with traditional project execution? The fact is companies have seen improvements in their productivity by deploying departmental collaboration and other social-oriented solutions. McKinsey’s survey on social tools shows we have reached critical scale: 72% of respondents report that their companies use at least one and over 40% say they are using social networks and blogs. We don’t hear as much about the impact of social media technologies at the project and project manager level, but that does not mean there is none. Consider the new hire. The type of individual entering the workforce and executing on projects is a generation of worker expecting visually appealing, easy to use and easy to understand technology meshing hand-in-hand with business processes. Consider the project manager. The social era has enhanced the role that the project manager must play. Today’s project manager must be a supreme communicator, an influencer, a sympathizer, a negotiator, and still manage to keep all stakeholders in the loop on project progress. Social tools play a significant role in this effort. Now consider the impact to the project team. The way that a project team functions has changed, with newer, social oriented technologies making the process of information dissemination and team communications much more fluid. It’s clear that a shift is occurring where “social” is intersecting with project management. The Rise of Social Project Management We refer to the melding of project management and social networking as Social Project Management. Social Project Management is based upon the philosophy that the project team is one part of an integrated whole, and that valuable and unique abilities exist within the larger organization. For this reason, Social Project Management systems should be integrated into the collaborative platform(s) of an organization, allowing communication to proceed outside the project boundaries. What makes social project management "social" is an implicit awareness where distributed teams build connected links in ways that were previously restricted to teams that were co-located. Just as critical, Social Project Management embraces the vision of seamless online collaboration within a project team, but also provides for, (and enhances) the use of rigorous project management techniques. Social Project Management acknowledges that projects (particularly large projects) are a social activity - people doing work with people, for other people, with commitments to yet other people. The more people (larger projects), the more interpersonal the interactions, and the more social affects the project. The Epitome of Social - Fusion Project Portfolio Management If I take this one level further to discuss Fusion Project Portfolio Management, the notion of Social Project Management is on full display. With Fusion Project Portfolio Management, project team members have a single place for interaction on projects and access to any other resources working within the Fusion ERP applications. This allows team members the opportunity to be informed with greater participation and provide better information. The application’s the visual appeal, and highly graphical nature makes it easy to navigate information. The project activity stream adds to the intuitive user experience. The goal of productivity is pervasive throughout Fusion Project Portfolio Management. Field research conducted with Oracle customers and partners showed that users needed a way to stay in the context of their core transactions and yet easily access social networking tools. This is manifested in the application so when a user executes a business process, they not only have the transactional application at their fingertips, but also have things like e-mail, SMS, text, instant messaging, chat – all providing a number of different ways to interact with people and/or groups of people, both internal and external to the project and enterprise. But in the end, connecting people is relatively easy. The larger issue is finding a way to serve up relevant, system-generated, actionable information, in real time, which will allow for more streamlined execution on key business processes. Fusion Project Portfolio Management’s design concept enables users to create project communities, establish discussion threads, manage event calendars as well as deliver project based work spaces to organize communications within the context of a project – all within a secure business environment. We’d love to hear from you and get your thoughts and ideas about how Social Project Management is impacting your organization. To learn more about Oracle Fusion Project Portfolio Management, please visit this link

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  • Implications of Java 6 End of Public Updates for EBS Users

    - by Steven Chan (Oracle Development)
    The Support Roadmap for Oracle Java is published here: Oracle Java SE Support Roadmap The latest updates to that page (as of Sept. 19, 2012) state (emphasis added): Java SE 6 End of Public Updates Notice After February 2013, Oracle will no longer post updates of Java SE 6 to its public download sites. Existing Java SE 6 downloads already posted as of February 2013 will remain accessible in the Java Archive on Oracle Technology Network. Developers and end-users are encouraged to update to more recent Java SE versions that remain available for public download. For enterprise customers, who need continued access to critical bug fixes and security fixes as well as general maintenance for Java SE 6 or older versions, long term support is available through Oracle Java SE Support . What does this mean for Oracle E-Business Suite users? EBS users fall under the category of "enterprise users" above.  Java is an integral part of the Oracle E-Business Suite technology stack, so EBS users will continue to receive Java SE 6 updates after February 2013. In other words, nothing will change for EBS users after February 2013.  EBS users will continue to receive critical bug fixes and security fixes as well as general maintenance for Java SE 6. These Java SE 6 updates will be made available to EBS users for the Extended Support periods documented in the Oracle Lifetime Support policy document for Oracle Applications (PDF): EBS 11i Extended Support ends November 2013 EBS 12.0 Extended Support ends January 2015 EBS 12.1 Extended Support ends December 2018 Will EBS users be forced to upgrade to JRE 7 for Windows desktop clients? No. This upgrade will be highly recommended but currently remains optional. JRE 6 will be available to Windows users to run with EBS for the duration of your respective EBS Extended Support period.  Updates will be delivered via My Oracle Support, where you can continue to receive critical bug fixes and security fixes as well as general maintenance for JRE 6 desktop clients.  The certification of Oracle E-Business Suite with JRE 7 (for desktop clients accessing EBS Forms-based content) is in its final stages.  If you plan to upgrade your EBS desktop clients to JRE 7 when that certification is released, you can get a head-start on that today. Coexistence of JRE 6 and JRE 7 on Windows desktops The upgrade to JRE 7 will be highly recommended for EBS users, but some users may need to run both JRE 6 and 7 on their Windows desktops for reasons unrelated to the E-Business Suite. Most EBS configurations with IE and Firefox use non-static versioning by default. JRE 7 will be invoked instead of JRE 6 if both are installed on a Windows desktop. For more details, see "Appendix B: Static vs. Non-static Versioning and Set Up Options" in Notes 290801.1 and 393931.1. Applying Updates to JRE 6 and JRE 7 to Windows desktops Auto-update will keep JRE 7 up-to-date for Windows users with JRE 7 installed. Auto-update will only keep JRE 7 up-to-date for Windows users with both JRE 6 and 7 installed.  JRE 6 users are strongly encouraged to apply the latest Critical Patch Updates as soon as possible after each release. The Jave SE CPUs will be available via My Oracle Support.  EBS users can find more information about JRE 6 and 7 updates here: Information Center: Installation & Configuration for Oracle Java SE (Note 1412103.2) The dates for future Java SE CPUs can be found on the Critical Patch Updates, Security Alerts and Third Party Bulletin.  An RSS feed is available on that site for those who would like to be kept up-to-date. What will Mac users need? Oracle will provide updates to JRE 7 for Mac OS X users. EBS users running Macs will need to upgrade to JRE 7 to receive JRE updates. The certification of Oracle E-Business Suite with JRE 7 for Mac-based desktop clients accessing EBS Forms-based content is underway. Mac users waiting for that certification may find this article useful: How to Reenable Apple Java 6 Plug-in for Mac EBS Users Will EBS users be forced to upgrade to JDK 7 for EBS application tier servers? No. This upgrade will be highly recommended but will be optional for EBS application tier servers running on Windows, Linux, and Solaris.  You can choose to remain on JDK 6 for the duration of your respective EBS Extended Support period.  If you remain on JDK 6, you will continue to receive critical bug fixes and security fixes as well as general maintenance for JDK 6. The certification of Oracle E-Business Suite with JDK 7 for EBS application tier servers on Windows, Linux, and Solaris as well as other platforms such as IBM AIX and HP-UX is planned.  Customers running platforms other than Windows, Linux, and Solaris should refer to their Java vendors's sites for more information about their support policies. Related Articles Planning Bulletin for JRE 7: What EBS Customers Can Do Today EBS 11i and 12.1 Support Timeline Changes Frequently Asked Questions about Latest EBS Support Changes Critical Patch Updates During EBS 11i Exception to Sustaining Support Period

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  • Benchmarking MySQL Replication with Multi-Threaded Slaves

    - by Mat Keep
    0 0 1 1145 6530 Homework 54 15 7660 14.0 Normal 0 false false false EN-US JA 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-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:Cambria; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-ansi-language:EN-US;} The objective of this benchmark is to measure the performance improvement achieved when enabling the Multi-Threaded Slave enhancement delivered as a part MySQL 5.6. As the results demonstrate, Multi-Threaded Slaves delivers 5x higher replication performance based on a configuration with 10 databases/schemas. For real-world deployments, higher replication performance directly translates to: · Improved consistency of reads from slaves (i.e. reduced risk of reading "stale" data) · Reduced risk of data loss should the master fail before replicating all events in its binary log (binlog) The multi-threaded slave splits processing between worker threads based on schema, allowing updates to be applied in parallel, rather than sequentially. This delivers benefits to those workloads that isolate application data using databases - e.g. multi-tenant systems deployed in cloud environments. Multi-Threaded Slaves are just one of many enhancements to replication previewed as part of the MySQL 5.6 Development Release, which include: · Global Transaction Identifiers coupled with MySQL utilities for automatic failover / switchover and slave promotion · Crash Safe Slaves and Binlog · Optimized Row Based Replication · Replication Event Checksums · Time Delayed Replication These and many more are discussed in the “MySQL 5.6 Replication: Enabling the Next Generation of Web & Cloud Services” Developer Zone article  Back to the benchmark - details are as follows. Environment The test environment consisted of two Linux servers: · one running the replication master · one running the replication slave. Only the slave was involved in the actual measurements, and was based on the following configuration: - Hardware: Oracle Sun Fire X4170 M2 Server - CPU: 2 sockets, 6 cores with hyper-threading, 2930 MHz. - OS: 64-bit Oracle Enterprise Linux 6.1 - Memory: 48 GB Test Procedure Initial Setup: Two MySQL servers were started on two different hosts, configured as replication master and slave. 10 sysbench schemas were created, each with a single table: CREATE TABLE `sbtest` (    `id` int(10) unsigned NOT NULL AUTO_INCREMENT,    `k` int(10) unsigned NOT NULL DEFAULT '0',    `c` char(120) NOT NULL DEFAULT '',    `pad` char(60) NOT NULL DEFAULT '',    PRIMARY KEY (`id`),    KEY `k` (`k`) ) ENGINE=InnoDB DEFAULT CHARSET=latin1 10,000 rows were inserted in each of the 10 tables, for a total of 100,000 rows. When the inserts had replicated to the slave, the slave threads were stopped. The slave data directory was copied to a backup location and the slave threads position in the master binlog noted. 10 sysbench clients, each configured with 10 threads, were spawned at the same time to generate a random schema load against each of the 10 schemas on the master. Each sysbench client executed 10,000 "update key" statements: UPDATE sbtest set k=k+1 WHERE id = <random row> In total, this generated 100,000 update statements to later replicate during the test itself. Test Methodology: The number of slave workers to test with was configured using: SET GLOBAL slave_parallel_workers=<workers> Then the slave IO thread was started and the test waited for all the update queries to be copied over to the relay log on the slave. The benchmark clock was started and then the slave SQL thread was started. The test waited for the slave SQL thread to finish executing the 100k update queries, doing "select master_pos_wait()". When master_pos_wait() returned, the benchmark clock was stopped and the duration calculated. The calculated duration from the benchmark clock should be close to the time it took for the SQL thread to execute the 100,000 update queries. The 100k queries divided by this duration gave the benchmark metric, reported as Queries Per Second (QPS). Test Reset: The test-reset cycle was implemented as follows: · the slave was stopped · the slave data directory replaced with the previous backup · the slave restarted with the slave threads replication pointer repositioned to the point before the update queries in the binlog. The test could then be repeated with identical set of queries but a different number of slave worker threads, enabling a fair comparison. The Test-Reset cycle was repeated 3 times for 0-24 number of workers and the QPS metric calculated and averaged for each worker count. MySQL Configuration The relevant configuration settings used for MySQL are as follows: binlog-format=STATEMENT relay-log-info-repository=TABLE master-info-repository=TABLE As described in the test procedure, the slave_parallel_workers setting was modified as part of the test logic. The consequence of changing this setting is: 0 worker threads:    - current (i.e. single threaded) sequential mode    - 1 x IO thread and 1 x SQL thread    - SQL thread both reads and executes the events 1 worker thread:    - sequential mode    - 1 x IO thread, 1 x Coordinator SQL thread and 1 x Worker thread    - coordinator reads the event and hands it to the worker who executes 2+ worker threads:    - parallel execution    - 1 x IO thread, 1 x Coordinator SQL thread and 2+ Worker threads    - coordinator reads events and hands them to the workers who execute them Results Figure 1 below shows that Multi-Threaded Slaves deliver ~5x higher replication performance when configured with 10 worker threads, with the load evenly distributed across our 10 x schemas. This result is compared to the current replication implementation which is based on a single SQL thread only (i.e. zero worker threads). Figure 1: 5x Higher Performance with Multi-Threaded Slaves The following figure shows more detailed results, with QPS sampled and reported as the worker threads are incremented. The raw numbers behind this graph are reported in the Appendix section of this post. Figure 2: Detailed Results As the results above show, the configuration does not scale noticably from 5 to 9 worker threads. When configured with 10 worker threads however, scalability increases significantly. The conclusion therefore is that it is desirable to configure the same number of worker threads as schemas. Other conclusions from the results: · Running with 1 worker compared to zero workers just introduces overhead without the benefit of parallel execution. · As expected, having more workers than schemas adds no visible benefit. Aside from what is shown in the results above, testing also demonstrated that the following settings had a very positive effect on slave performance: relay-log-info-repository=TABLE master-info-repository=TABLE For 5+ workers, it was up to 2.3 times as fast to run with TABLE compared to FILE. Conclusion As the results demonstrate, Multi-Threaded Slaves deliver significant performance increases to MySQL replication when handling multiple schemas. This, and the other replication enhancements introduced in MySQL 5.6 are fully available for you to download and evaluate now from the MySQL Developer site (select Development Release tab). You can learn more about MySQL 5.6 from the documentation  Please don’t hesitate to comment on this or other replication blogs with feedback and questions. Appendix – Detailed Results

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  • WebLogic JDBC Use of Oracle Wallet for SSL

    - by Steve Felts
    Introduction Secure Sockets Layer (SSL) can be used to secure the connection between the middle tier “client”, WebLogic Server (WLS) in this case, and the Oracle database server.  Data between WLS and database can be encrypted.  The server can be authenticated so you have proof that the database can be trusted by validating a certificate from the server.  The client can be authenticated so that the database only accepts connections from clients that it trusts. Similar to the discussion in an earlier article about using the Oracle wallet for database credentials, the Oracle wallet can also be used with SSL to store the keys and certificates.  By using it correctly, clear text passwords can be eliminated from the JDBC configuration and client/server configuration can be simplified by sharing the wallet across multiple datasources. There is a very good Oracle Technical White Paper on using SSL with the Oracle thin driver at http://www.oracle.com/technetwork/database/enterprise-edition/wp-oracle-jdbc-thin-ssl-130128.pdf [LINK1].  The link http://www.oracle.com/technetwork/middleware/weblogic/index-087556.html [LINK2] describes how to use WebLogic Server with Oracle JDBC Driver SSL. The information in this article is a guide on what steps need to be taken in the variety of available options; use the links above for details. SSL from the driver to the database server is basically turned on by specifying a protocol of “tcps” in the URL.  However, there is a fair amount of setup needed.  Also remember that there is an overhead in performance. Creating the wallets The common use cases are 1. “data encryption and server-only authentication”, requiring just a trust store, or 2. “data encryption and authentication of both tiers” (client and server), requiring a trust store and a key store. It is recommended to use the auto-login wallet type so that clear text passwords are not needed in the datasource configuration to open the wallet.  The store type for an auto-login wallet is “SSO” (Single Sign On), not “JKS” or “PKCS12” as in [LINK2].  The file name is “cwallet.sso”. Wallets are created using the orapki tool.  They need to be created based on the usage (encryption and/or authentication).  This is discussed in detail in [LINK1] in Appendix B or in the Advanced Security Administrator’s Guide of the Database documentation. Database Server Configuration It is necessary to update the sqlnet.ora and listener.ora files with the directory location of the wallet using WALLET_LOCATION.  These files also indicate whether or not SSL_CLIENT_AUTHENTICATION is being used (true or false). The Oracle Listener must also be configured to use the TCPS protocol.  The recommended port is 2484. LISTENER = (ADDRESS_LIST= (ADDRESS=(PROTOCOL=tcps)(HOST=servername)(PORT=2484))) WebLogic Server Classpath The WebLogic Server CLASSPATH must have three additional security files. The files that need to be added to the WLS CLASSPATH are $MW_HOME/modules/com.oracle.osdt_cert_1.0.0.0.jar $MW_HOME/modules/com.oracle.osdt_core_1.0.0.0.jar $MW_HOME/modules/com.oracle.oraclepki_1.0.0.0.jar One way to do this is to add them to PRE_CLASSPATH environment variable for use with the standard WebLogic scripts. Setting the Oracle Security Provider It’s necessary to enable the Oracle PKI provider on the client side.  This can either be done statically by updating the java.security file under the JRE or dynamically by setting it in a WLS startup class using java.security.Security.insertProviderAt(new oracle.security.pki.OraclePKIProvider (), 3); See the full example of the startup class in [LINK2]. Datasource Configuration When creating a WLS datasource, set the PROTOCOL in the URL to tcps as in the following. jdbc:oracle:thin:@(DESCRIPTION=(ADDRESS=(PROTOCOL=tcps)(HOST=host)(PORT=port))(CONNECT_DATA=(SERVICE_NAME=myservice))) For encryption and server authentication, use the datasource connection properties: - javax.net.ssl.trustStore=location of wallet file on the client - javax.net.ssl.trustStoreType=”SSO” For client authentication, use the datasource connection properties: - javax.net.ssl.keyStore=location of wallet file on the client - javax.net.ssl.keyStoreType=”SSO” Note that the driver connection properties for the wallet require a file name, not a directory name. Active GridLink ONS over SSL For completeness, there is another SSL usage for WLS datasources.  The communication with the Oracle Notification Service (ONS) for load balancing information and node up/down events can use SSL also. Create an auto-login wallet and use the wallet on the client and server.  The following is a sample sequence to create a test wallet for use with ONS. orapki wallet create -wallet ons -auto_login -pwd ONS_Wallet orapki wallet add -wallet ons -dn "CN=ons_test,C=US" -keysize 1024 -self_signed -validity 9999 -pwd ONS_Wallet orapki wallet export -wallet ons -dn "CN=ons_test,C=US" -cert ons/cert.txt -pwd ONS_Wallet On the database server side, it’s necessary to define the walletfile directory in the file $CRS_HOME/opmn/conf/ons.config and run onsctl stop/start. When configuring an Active GridLink datasource, the connection to the ONS must be defined.  In addition to the host and port, the wallet file directory must be specified.  By not giving a password, a SSO wallet is assumed. Summary To use SSL with the Oracle thin driver without any clear text passwords, use an SSO Oracle Wallet.  SSL support in the Oracle thin driver is available starting in 10g Release 2.

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  • Announcing Solaris Technical Track at NLUUG Spring Conference on Operating Systems

    - by user9135656
    The Netherlands Unix Users Group (NLUUG) is hosting a full-day technical Solaris track during its spring 2012 conference. The official announcement page, including registration information can be found at the conference page.This year, the NLUUG spring conference focuses on the base of every computing platform; the Operating System. Hot topics like Cloud Computing and Virtualization; the massive adoption of mobile devices that have their special needs in the OS they run but that at the same time put the challenge of massive scalability onto the internet; the upspring of multi-core and multi-threaded chips..., all these developments cause the Operating System to still be a very interesting area where all kinds of innovations have taken and are taking place.The conference will focus specifically on: Linux, BSD Unix, AIX, Windows and Solaris. The keynote speech will be delivered by John 'maddog' Hall, infamous promotor and supporter of UNIX-based Operating Systems. He will talk the audience through several decades of Operating Systems developments, and share many stories untold so far. To make the conference even more interesting, a variety of talks is offered in 5 parallel tracks, covering new developments in and  also collaboration  between Linux, the BSD's, AIX, Solaris and Windows. The full-day Solaris technical track covers all innovations that have been delivered in Oracle Solaris 11. Deeply technically-skilled presenters will talk on a variety of topics. Each topic will first be introduced at a basic level, enabling visitors to attend to the presentations individually. Attending to the full day will give the audience a comprehensive overview as well as more in-depth understanding of the most important new features in Solaris 11.NLUUG Spring Conference details:* Date and time:        When : April 11 2012        Start: 09:15 (doors open: 8:30)        End  : 17:00, (drinks and snacks served afterwards)* Venue:        Nieuwegein Business Center        Blokhoeve 1             3438 LC Nieuwegein              The Nederlands          Tel     : +31 (0)30 - 602 69 00        Fax     : +31 (0)30 - 602 69 01        Email   : [email protected]        Route   : description - (PDF, Dutch only)* Conference abstracts and speaker info can be found here.* Agenda for the Solaris track: Note: talks will be in English unless marked with 'NL'.1.      Insights to Solaris 11         Joerg Moellenkamp - Solaris Technical Specialist         Oracle Germany2.      Lifecycle management with Oracle Solaris 11         Detlef Drewanz - Solaris Technical Specialist         Oracle Germany3.      Solaris 11 Networking - Crossbow Project        Andrew Gabriel - Solaris Technical Specialist        Oracle UK4.      ZFS: Data Integrity and Security         Darren Moffat - Senior Principal Engineer, Solaris Engineering         Oracle UK5.      Solaris 11 Zones and Immutable Zones (NL)         Casper Dik - Senior Staff Engineer, Software Platforms         Oracle NL6.      Experiencing Solaris 11 (NL)         Patrick Ale - UNIX Technical Specialist         UPC Broadband, NLTalks are 45 minutes each.There will be a "Solaris Meeting point" during the conference where people can meet-up, chat with the speakers and with fellow Solaris enthousiasts, and where live demos or other hands-on experiences can be shared.The official announcement page, including registration information can be found at the conference page on the NLUUG website. This site also has a complete list of all abstracts for all talks.Please register on the NLUUG website.

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  • Silverlight 4 Twitter Client &ndash; Part 7

    - by Max
    Download this article as a PDF Welcome back :) This week we are going to look at something more exciting and a much required feature for any twitter client – auto refresh so as to show new status updates. We are going to achieve this using Silverlight 4 Timers and a bit and refresh our datagrid every 2 minutes to show new updates. We will do this so that we do only minimal request to the twitter api, so that twitter does not block us – there is a limit of 150 request an hour. Let us get started now. Also we will get the profile user id hyperlinked, so that when ever the user click on it, we will take them to their twitter page. Also it was a pain to always run this application by pressing F5, then it would open in a browser you would have to right click uninstall and install it again to see any changes. All this and yet we were not able to debug it :( Now there is a solution for this to run a silverlight application directly out of browser and yet have the debug feature. Super cool, here is how. Right on the Silverlight project and go to debug and then select the Out-Of-Browser application option and choose the *.Web project. Then just right click on the SL project and set as Startup Project. There you go, now every time you press F5, it will automatically run out of browser and still have the debug options. I go to know about this after some binging. Now let us jump to the core straight away. 1) To get the user id hyperlinked, we need to have a DataGridTemplateColumn and within that have a HyperLinkButton. The code for this will  be <data:DataGridTemplateColumn> <data:DataGridTemplateColumn.CellTemplate> <DataTemplate> <HyperlinkButton Click="HyperlinkButton_Click" Content="{Binding UserName}" TargetName="_blank" ></HyperlinkButton> </DataTemplate> </data:DataGridTemplateColumn.CellTemplate> </data:DataGridTemplateColumn> 2) Now let us look at how we are getting this done by looking into HyperlinkButton_Click event handler. There we will dynamically set the NavigateUri to the twitter page. I tried to do this using some binding, eval like stuff as in ASP.NET, but no luck! private void HyperlinkButton_Click(object sender, RoutedEventArgs e) { HyperlinkButton hb = (HyperlinkButton)e.OriginalSource; hb.NavigateUri = new Uri("http://twitter.com/" + hb.Content.ToString(), UriKind.Absolute); } 3) Now we need to switch on our Timer right in the OnNavigated to event on our SL page. So we need to modify our OnNavigated event to some thing like below: protected override void OnNavigatedTo(NavigationEventArgs e) { image1.Source = new BitmapImage(new Uri(GlobalVariable.profileImage, UriKind.Absolute)); this.Title = GlobalVariable.getUserName() + " - Home"; if (!GlobalVariable.isLoggedin()) this.NavigationService.Navigate(new Uri("/Login", UriKind.Relative)); else { currentGrid = "Timeline-Grid"; TwitterCredentialsSubmit(); myDispatcherTimer.Interval = new TimeSpan(0, 0, 0, 60, 0); myDispatcherTimer.Tick += new EventHandler(Each_Tick); myDispatcherTimer.Start(); } } I use a global string – here it is currentGrid variable to indicate what is bound in the datagrid so that after every timer tick, I can rebind the latest data to it again. Like I will only rebind the friends timeline again if the data grid currently holds it and I’ll only rebind the respective list status again in the data grid, if already a list status is bound to the data grid. In the above timer code, its set to trigger the Each_Tick event handler every 1 minute (60 seconds). TimeSpan takes in (days, hours, minutes, seconds, milliseconds). 4) Now we need to set the list name in the currentGrid variable when a list button is clicked. So add the code line below to the list button event handler currentGrid = currentList = b.Content.ToString(); 5) Now let us see how Each_Tick event handler is implemented. public void Each_Tick(object o, EventArgs sender) { if (!currentGrid.Equals("Timeline-Grid")) getListStatuses(currentGrid); else { WebRequest.RegisterPrefix("https://", System.Net.Browser.WebRequestCreator.ClientHttp); WebClient myService = new WebClient(); myService.AllowReadStreamBuffering = true; myService.UseDefaultCredentials = false; myService.Credentials = new NetworkCredential(GlobalVariable.getUserName(), GlobalVariable.getPassword()); myService.DownloadStringCompleted += new DownloadStringCompletedEventHandler(TimelineRequestCompleted); myService.DownloadStringAsync(new Uri("https://twitter.com/statuses/friends_timeline.xml")); } } If the data grid hold friends timeline, I just use the same bit of code we had already to bind the friends timeline to the data grid. Copy Paste. But if it is some list timeline that is bound in the datagrid, I then call the getListStatus method with the currentGrid string which will actually be holding the list name. 6) I wanted to make the hyperlinks inside the status message as hyperlinks and when the user clicks on it, we can then open that link. I tried using a convertor and using a regex to recognize a url and wrap it up with a href, but that is not gonna work in silverlight textblock :( Anyways that convertor code is in the zip file. 7) You can get the complete project files from here. 8) Please comment below for your doubts, suggestions, improvements. I will try to reply as early as possible. Thanks for all your support. Technorati Tags: Silverlight 4,Datagrid,Twitter API,Silverlight Timer

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  • Using Transaction Logging to Recover Post-Archived Essbase data

    - by Keith Rosenthal
    Data recovery is typically performed by restoring data from an archive.  Data added or removed since the last archive took place can also be recovered by enabling transaction logging in Essbase.  Transaction logging works by writing transactions to a log store.  The information in the log store can then be recovered by replaying the log store entries in sequence since the last archive took place.  The following information is recorded within a transaction log entry: Sequence ID Username Start Time End Time Request Type A request type can be one of the following categories: Calculations, including the default calculation as well as both server and client side calculations Data loads, including data imports as well as data loaded using a load rule Data clears as well as outline resets Locking and sending data from SmartView and the Spreadsheet Add-In.  Changes from Planning web forms are also tracked since a lock and send operation occurs during this process. You can use the Display Transactions command in the EAS console or the query database MAXL command to view the transaction log entries. Enabling Transaction Logging Transaction logging can be enabled at the Essbase server, application or database level by adding the TRANSACTIONLOGLOCATION essbase.cfg setting.  The following is the TRANSACTIONLOGLOCATION syntax: TRANSACTIONLOGLOCATION [appname [dbname]] LOGLOCATION NATIVE ENABLE | DISABLE Note that you can have multiple TRANSACTIONLOGLOCATION entries in the essbase.cfg file.  For example: TRANSACTIONLOGLOCATION Hyperion/trlog NATIVE ENABLE TRANSACTIONLOGLOCATION Sample Hyperion/trlog NATIVE DISABLE The first statement will enable transaction logging for all Essbase applications, and the second statement will disable transaction logging for the Sample application.  As a result, transaction logging will be enabled for all applications except the Sample application. A location on a physical disk other than the disk where ARBORPATH or the disk files reside is recommended to optimize overall Essbase performance. Configuring Transaction Log Replay Although transaction log entries are stored based on the LOGLOCATION parameter of the TRANSACTIONLOGLOCATION essbase.cfg setting, copies of data load and rules files are stored in the ARBORPATH/app/appname/dbname/Replay directory to optimize the performance of replaying logged transactions.  The default is to archive client data loads, but this configuration setting can be used to archive server data loads (including SQL server data loads) or both client and server data loads. To change the type of data to be archived, add the TRANSACTIONLOGDATALOADARCHIVE configuration setting to the essbase.cfg file.  Note that you can have multiple TRANSACTIONLOGDATALOADARCHIVE entries in the essbase.cfg file to adjust settings for individual applications and databases. Replaying the Transaction Log and Transaction Log Security Considerations To replay the transactions, use either the Replay Transactions command in the EAS console or the alter database MAXL command using the replay transactions grammar.  Transactions can be replayed either after a specified log time or using a range of transaction sequence IDs. The default when replaying transactions is to use the security settings of the user who originally performed the transaction.  However, if that user no longer exists or that user's username was changed, the replay operation will fail. Instead of using the default security setting, add the REPLAYSECURITYOPTION essbase.cfg setting to use the security settings of the administrator who performs the replay operation.  REPLAYSECURITYOPTION 2 will explicitly use the security settings of the administrator performing the replay operation.  REPLAYSECURITYOPTION 3 will use the administrator security settings if the original user’s security settings cannot be used. Removing Transaction Logs and Archived Replay Data Load and Rules Files Transaction logs and archived replay data load and rules files are not automatically removed and are only removed manually.  Since these files can consume a considerable amount of space, the files should be removed on a periodic basis. The transaction logs should be removed one database at a time instead of all databases simultaneously.  The data load and rules files associated with the replayed transactions should be removed in chronological order from earliest to latest.  In addition, do not remove any data load and rules files with a timestamp later than the timestamp of the most recent archive file. Partitioned Database Considerations For partitioned databases, partition commands such as synchronization commands cannot be replayed.  When recovering data, the partition changes must be replayed manually and logged transactions must be replayed in the correct chronological order. If the partitioned database includes any @XREF commands in the calc script, the logged transactions must be selectively replayed in the correct chronological order between the source and target databases. References For additional information, please see the Oracle EPM System Backup and Recovery Guide.  For EPM 11.1.2.2, the link is http://docs.oracle.com/cd/E17236_01/epm.1112/epm_backup_recovery_1112200.pdf

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