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• Looking for advice on Hyper-v storage replication

  - by Notre1

  I am designing a 2-host Hyper-V R2 cluster with 6-10 guests stored on a SMB iSCSI SAN device (probably Promise VessRAID). I will be getting at least two of the SAN devices and need to eliminate the storage a single point of failure. Ideally, that would involve real-time failover for the storage, like the Windows failover clustering does for the hosts. This design will be used at around six of our sites, and I would like to allow for us to eventually setup a cluster at colocation site and replicate each site's VMs there for DR. (Ideally a live multi-site cluster, but a manual import of the VMs would be fine for this sort of DR.) The tools that come with enterprise SANs, like EMC and NetApp, seem to be the most commonly used items for a Hyper-V cluster, but I can't afford their prices with my budget. Outside of them, the two tools that seem to be most common for Hyper-V storage replication are SteelEye (now SIOS) DataKeeper Cluster Edition and Double-Take Availability. Originally, I was planning on using Clustered Shared Volume(s) (CSV), but it seems like replication support for these is either not available or brand new in both these products. It looks like CSVs are supported in Double-Take 5.22, see this discussion, but I don't think I want to run something that new in production. Right now, it seems like the best option for me is not to implement CSVs, implement some sort of storage replication, and upgrade to CSVs at a later date once replicating them is more mature. I would love to have live migration, and CSVs are not required for live migration if you are using one LUN per VM, so I guess this is what I'll do. I would prefer to stick to the using the Microsoft Windows Server and Hyper-V tools and features as much as possible. From that standpoint, SteelEye looks more appealing than Double-Take because they make the DataKeeper volume(s) available to the Failover Clustering Manager and then failover clustering is all configured and managed through the native Microsoft tools. Double-Take says that "clustered Hyper-V hosts are not supported," and Double-Take Availability itself seems to be what is used for the actual clustering and failover. Does anyone know if any of these replication tools work with more than two hosts in the cluster? All the information I can find on the web only uses two hosts in their examples. Are there any better tools than SteelEye and Double-Take for doing what I am trying to do, which is eliminate the storage as as single point of failure? Neverfail, AppAssure, and DataCore all seem to offer similar functionality, but they don't seems to be as popular as SteelEye and Double-Take. I have seen a number of people suggest using Starwind iSCSI SAN software for the shared storage, which includes replication (and CSV replication at that). There are a couple of reasons I have not seriously considered this route: 1) The company I work for is exclusively a Dell shop and Dell does not have any servers with that I can pack with more than six 3.5" SATA drives. 2) In the future, it could be advantegous for us to not be locked into a particular brand or type of storage and third-party replication softwares all allow replication to heterogeneous storage devices. I am pretty new to iSCSI and clustering, so please let me know if it looks like I am planning something that goes against best practices or overlooking/missing something.

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• Looking for advice on Hyper-v storage replication

  - by Notre1

  I am designing a 2-host Hyper-V R2 cluster with 6-10 guests stored on a SMB iSCSI SAN device (probably Promise VessRAID). I will be getting at least two of the SAN devices and need to eliminate the storage a single point of failure. Ideally, that would involve real-time failover for the storage, like the Windows failover clustering does for the hosts. This design will be used at around six of our sites, and I would like to allow for us to eventually setup a cluster at colocation site and replicate each site's VMs there for DR. (Ideally a live multi-site cluster, but a manual import of the VMs would be fine for this sort of DR.) The tools that come with enterprise SANs, like EMC and NetApp, seem to be the most commonly used items for a Hyper-V cluster, but I can't afford their prices with my budget. Outside of them, the two tools that seem to be most common for Hyper-V storage replication are SteelEye (now SIOS) DataKeeper Cluster Edition and Double-Take Availability. Originally, I was planning on using Clustered Shared Volume(s) (CSV), but it seems like replication support for these is either not available or brand new in both these products. It looks like CSVs are supported in Double-Take 5.22, see this discussion, but I don't think I want to run something that new in production. Right now, it seems like the best option for me is not to implement CSVs, implement some sort of storage replication, and upgrade to CSVs at a later date once replicating them is more mature. I would love to have live migration, and CSVs are not required for live migration if you are using one LUN per VM, so I guess this is what I'll do. I would prefer to stick to the using the Microsoft Windows Server and Hyper-V tools and features as much as possible. From that standpoint, SteelEye looks more appealing than Double-Take because they make the DataKeeper volume(s) available to the Failover Clustering Manager and then failover clustering is all configured and managed through the native Microsoft tools. Double-Take says that "clustered Hyper-V hosts are not supported," and Double-Take Availability itself seems to be what is used for the actual clustering and failover. Does anyone know if any of these replication tools work with more than two hosts in the cluster? All the information I can find on the web only uses two hosts in their examples. Are there any better tools than SteelEye and Double-Take for doing what I am trying to do, which is eliminate the storage as as single point of failure? Neverfail, AppAssure, and DataCore all seem to offer similar functionality, but they don't seems to be as popular as SteelEye and Double-Take. I have seen a number of people suggest using Starwind iSCSI SAN software for the shared storage, which includes replication (and CSV replication at that). There are a couple of reasons I have not seriously considered this route: 1) The company I work for is exclusively a Dell shop and Dell does not have any servers with that I can pack with more than six 3.5" SATA drives. 2) In the future, it could be advantegous for us to not be locked into a particular brand or type of storage and third-party replication softwares all allow replication to heterogeneous storage devices. I am pretty new to iSCSI and clustering, so please let me know if it looks like I am planning something that goes against best practices or overlooking/missing something.

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• An XEvent a Day (8 of 31) – Targets Week – synchronous_event_counter

  - by Jonathan Kehayias

  Yesterday’s post, Targets Week - Bucketizers , looked at the bucketizer Targets in Extended Events and how they can be used to simplify analysis and perform more targeted analysis based on their output.  Today’s post will be fairly short, by comparison to the previous posts, while we look at the synchronous_event_counter target, which can be used to test the impact of an Event Session without actually incurring the cost of Event collection. What is the synchronous_event_counter? The synchronous_event_count...(read more)

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• SQL SERVER – Maximize Database Performance with DB Optimizer – SQL in Sixty Seconds #054

  - by Pinal Dave

  Performance tuning is an interesting concept and everybody evaluates it differently. Every developer and DBA have different opinion about how one can do performance tuning. I personally believe performance tuning is a three step process Understanding the Query Identifying the Bottleneck Implementing the Fix While, we are working with large database application and it suddenly starts to slow down. We are all under stress about how we can get back the database back to normal speed. Most of the time we do not have enough time to do deep analysis of what is going wrong as well what will fix the problem. Our primary goal at that time is to just fix the database problem as fast as we can. However, here is one very important thing which we need to keep in our mind is that when we do quick fix, it should not create any further issue with other parts of the system. When time is essence and we want to do deep analysis of our system to give us the best solution we often tend to make mistakes. Sometimes we make mistakes as we do not have proper time to analysis the entire system. Here is what I do when I face such a situation – I take the help of DB Optimizer. It is a fantastic tool and does superlative performance tuning of the system. Everytime when I talk about performance tuning tool, the initial reaction of the people is that they do not want to try this as they believe it requires lots of the learning of the tool before they use it. It is absolutely not true with the case of the DB optimizer. It is a very easy to use and self intuitive tool. Once can get going with the product, in no time. Here is a quick video I have build where I demonstrate how we can identify what index is missing for query and how we can quickly create the index. Entire three steps of the query tuning are completed in less than 60 seconds. If you are into performance tuning and query optimization you should download DB Optimizer and give it a go. Let us see the same concept in following SQL in Sixty Seconds Video: You can Download DB Optimizer and reproduce the same Sixty Seconds experience. Related Tips in SQL in Sixty Seconds: Performance Tuning – Part 1 of 2 – Getting Started and Configuration Performance Tuning – Part 2 of 2 – Analysis, Detection, Tuning and Optimizing What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Interview Questions and Answers, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Identity

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• what is the difference between ltsp-server and ltsp-server-standalone packages?

  - by Dhani DDn

  what is the difference between ltsp-server and ltsp-server-standalone packages? and what packages i must use for setting up ltsp-cluster root server. according to this link https://help.ubuntu.com/community/UbuntuLTSP/LTSP-Cluster the root server use the ltsp-server and dhcp3-server packages .. but i think ltsp-server-standalone and isc-dhcp-server packages is the newer one .... is that okay if i use ltsp-server-standalone and isc-dhcp-server instead ? sorry newbie question

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• Clustering for Mere Mortals (Pt 3)

  - by Geoff N. Hiten

  The Controller Now we get to the meat of the matter.  You want a virtual cluster, the first thing you have to do is create your own portable domain.  Start with a plain vanilla install of Windows 2003 R2 Standard on a semi-default VM. (1 GB RAM, 2 cores, 2 NICs, 128GB dynamically expanding VHD file).  I chose this because it had the smallest disk and memory footprint of any current supported Microsoft Server product.  I created the VM with a single dynamically expanding VHD, one fixed 16 GB VHD, and two NICs.  One NIC is connected to the outside world and the other one is part of an internal-only network.  The first NIC is set up as a DHCP client.  We will get to the other one later. I actually tried this with Windows 2008 R2, but it failed miserably.  Not sure whether it was 2008 R2 or the fact I tried to use cloned VMs in the cluster.  Clustering is one place where NewSID would really come in handy.  Too bad Microsoft bought and buried it. Load and Patch the OS (hence the need for the outside connection).This is a good time to go get dinner.  Maybe a movie too.  There are close to a hundred patches that need to be downloaded and applied.  Avoiding that mess was why I put so much time into trying to get the 2008 R2 version working.  Maybe next time.  Don’t forget to add the extensions for VMLite (or whatever virtualization product you prefer). Set a fixed IP address on the internal-only NIC.  Do not give it a gateway.  Put the same IP address for the NIC and for the DNS Server.  This IP should be in a range that is never available on your public network.  You will need all the addresses in the range available.  See the previous post for the exact settings I used. I chose 10.97.230.1 as the server.  The rest of the 10.97.230 range is what I will use later.  For the curious, those numbers are based on elements of my home address.  Not truly random, but good enough for this project. Do not bridge the network connections.  I never allowed the cluster nodes direct access to any public network. Format the fixed VHD and leave it alone for now. Promote the VM to a Domain Controller.  If you have never done this, don’t worry.  The only meaningful decision is what to call the new domain.  I prefer a bogus name that does not correspond to a real Top-Level Domain (TLD).  .com, .biz., .net, .org  are all TLDs that we know and love.  I chose .test as the TLD since it is descriptive AND it does not exist in the real world.  The domain is called MicroAD.  This gives me MicroAD.Test as my domain. During the promotion process, you will be prompted to install DNS as part of the Domain creation process.  You want to accept this option.  The installer will automatically assign this DNS server as the authoritative owner of the MicroAD.test DNS domain (not to be confused with the MicroAD.test Active Directory domain.) For the rest of the DCPROMO process, just accept the defaults. Now let’s make our IP address management easy.  Add the DHCP Role to the server.  Add the server (10.97.230.1 in this case) as the default gateway to assign to DHCP clients.  Here is where you have to be VERY careful and bind it ONLY to the Internal NIC.  Trust me, your network admin will NOT like an extra DHCP server “helping” out on her network.  Go ahead and create a range of 10-20 IP Addresses in your scope.  You might find other uses for a pocket domain controller <cough> Mirroring </cough> than just for building a cluster.  And Clustering in SQL 2008 and Windows 2008 R2 fully supports DHCP addresses. Now we have three of the five key roles ready.  Two more to go. Next comes file sharing.  Since your cluster node VMs will not have access to any outside, you have to have some way to get files into these VMs.  I simply go to the root of C: and create a “Shared” folder.  I then share it out and grant full control to “Everyone” to both the share and to the underlying NTFS folder.   This will be immensely useful for Service Packs, demo databases, and any other software that isn’t packaged as an ISO that we can mount to the VM. Finally we need to create a block-level multi-connect storage device.  The kind folks at Starwinds Software (http://www.starwindsoftware.com/) graciously gave me a non-expiring demo license for expressly this purpose.  Their iSCSI SAN software lets you create an iSCSI target from nearly any storage medium.  Refreshingly, their product does exactly what they say it does.  Thanks. Remember that 16 GB VHD file?  That is where we are going to carve into our LUNs.  I created an iSCSI folder off the root, just so I can keep everything organized.  I then carved 5 ea. 2 GB iSCSI targets from that folder.  I chose a fixed VHD for performance.  I tried this earlier with a dynamically expanding VHD, but too many layers of abstraction and sparseness combined to make it unusable even for a demo.  Stick with a fixed VHD so there is a one-to-one mapping between abstract and physical storage.  If you read the previous post, you know what I named these iSCSI LUNs and why.  Yes, I do have some left over space.  Always leave yourself room for future growth or options. This gets us up to where we can actually build the nodes and install SQL.  As with most clusters, the real work happens long before the individual nodes get installed and configured.  At least it does if you want the cluster to be a true high-availability platform.

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• Clustering for Mere Mortals (Pt3)

  - by Geoff N. Hiten

  The Controller Now we get to the meat of the matter.  You want a virtual cluster, the first thing you have to do is create your own portable domain.  IStart with a plain vanilla install of Windows 2003 R2 Standard on a semi-default VM. (1 GB RAM, 2 cores, 2 NICs, 128GB dynamically expanding VHD file).  I chose this because it had the smallest disk and memory footprint of any current supported Microsoft Server product.  I created the VM with a single dynamically expanding VHD, one fixed 16 GB VHD, and two NICs.  One NIC is connected to the outside world and the other one is part of an internal-only network.  The first NIC is set up as a DHCP client.  We will get to the other one later. I actually tried this with Windows 2008 R2, but it failed miserably.  Not sure whether it was 2008 R2 or the fact I tried to use cloned VMs in the cluster.  Clustering is one place where NewSID would really come in handy.  Too bad Microsoft bought and buried it. Load and Patch the OS (hence the need for the outside connection).This is a good time to go get dinner.  Maybe a movie too.  There are close to a hundred patches that need to be downloaded and applied.  Avoiding that mess was why I put so much time into trying to get the 2008 R2 version working.  Maybe next time.  Don’t forget to add the extensions for VMLite (or whatever virtualization product you prefer). Set a fixed IP address on the internal-only NIC.  Do not give it a gateway.  Put the same IP address for the NIC and for the DNS Server.  This IP should be in a range that is never available on your public network.  You will need all the addresses in the range available.  See the previous post for the exact settings I used. I chose 10.97.230.1 as the server.  The rest of the 10.97.230 range is what I will use later.  For the curious, those numbers are based on elements of my home address.  Not truly random, but good enough for this project. Do not bridge the network connections.  I never allowed the cluster nodes direct access to any public network. Format the fixed VHD and leave it alone for now. Promote the VM to a Domain Controller.  If you have never done this, don’t worry.  The only meaningful decision is what to call the new domain.  I prefer a bogus name that does not correspond to a real Top-Level Domain (TLD).  .com, .biz., .net, .org  are all TLDs that we know and love.  I chose .test as the TLD since it is descriptive AND it does not exist in the real world.  The domain is called MicroAD.  This gives me MicroAD.Test as my domain. During the promotion process, you will be prompted to install DNS as part of the Domain creation process.  You want to accept this option.  The installer will automatically assign this DNS server as the authoritative owner of the MicroAD.test DNS domain (not to be confused with the MicroAD.test Active Directory domain.) For the rest of the DCPROMO process, just accept the defaults. Now let’s make our IP address management easy.  Add the DHCP Role to the server.  Add the server (10.97.230.1 in this case) as the default gateway to assign to DHCP clients.  Here is where you have to be VERY careful and bind it ONLY to the Internal NIC.  Trust me, your network admin will NOT like an extra DHCP server “helping” out on her network.  Go ahead and create a range of 10-20 IP Addresses in your scope.  You might find other uses for a pocket domain controller <cough> Mirroring </cough> than just for building a cluster.  And Clustering in SQL 2008 and Windows 2008 R2 fully supports DHCP addresses. Now we have three of the five key roles ready.  Two more to go. Next comes file sharing.  Since your cluster node VMs will not have access to any outside, you have to have some way to get files into these VMs.  I simply go to the root of C: and create a “Shared” folder.  I then share it out and grant full control to “Everyone” to both the share and to the underlying NTFS folder.   This will be immensely useful for Service Packs, demo databases, and any other software that isn’t packaged as an ISO that we can mount to the VM. Finally we need to create a block-level multi-connect storage device.  The kind folks at Starwinds Software (http://www.starwindsoftware.com/) graciously gave me a non-expiring demo license for expressly this purpose.  Their iSCSI SAN software lets you create an iSCSI target from nearly any storage medium.  Refreshingly, their product does exactly what they say it does.  Thanks. Remember that 16 GB VHD file?  That is where we are going to carve into our LUNs.  I created an iSCSI folder off the root, just so I can keep everything organized.  I then carved 5 ea. 2 GB iSCSI targets from that folder.  I chose a fixed VHD for performance.  I tried this earlier with a dynamically expanding VHD, but too many layers of abstraction and sparseness combined to make it unusable even for a demo.  Stick with a fixed VHD so there is a one-to-one mapping between abstract and physical storage.  If you read the previous post, you know what I named these iSCSI LUNs and why.  Yes, I do have some left over space.  Always leave yourself room for future growth or options. This gets us up to where we can actually build the nodes and install SQL.  As with most clusters, the real work happens long before the individual nodes get installed and configured.  At least it does if you want the cluster to be a true high-availability platform.

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• BigData and Customer Experience: Happy Together

  - by Isabel F. Peñuelas

  The two big buzzes of the year may lay closer than it appears. Both concepts intersect at various points: BigData and Return of Investment of Marketing Campaigns On a recent post Big Data Is The Future Of Marketing Jeff Dachis explains very clearly how “Big data analytics finally allows marketers to identify, measure, and manage what is positively impacting their Brand”. Regression analysis applied to big data volumes coming from social media will substitute the failed attempts to justify marketing investments on social media in terms of followers and likes, he continues, “the measurement models applied by marketers on TV Campaigns don´t work on social”, we need to study the data with fresh eyes and maybe then we will start understanding and measuring brand engagemet. Social CRM and BigData The real value of Social CRM start by analyzing mass of big data from social media in order of applying social intelligence techniques that allow us to classify new customer niches and communities and define appropriated strategies to contact potential customers. Gartner Says that the Market for Social CRM is on pace to surpass $1 Billion in Revenue by Year-End 2012 but in words of Zach Hofer-Shall, Analyst at Forrester Research “Social customer relationship management is hard” (The Social CRM Arms Race Heats ). To succeed brands need three things: Investing in new social tools, investing in consultancy and investing in infrastructure for massive data storage and analysis. Neither CeX or BigData are easy and cheap wins. But what are the customer benefits of such investments? Big Data and Brand Engagement Time is the most valuable asset of todays consumers: tired of information overload, exhausted by the terabytes of offering, anxious because of not having the same fast multichannel experience with their services’ marketers or preferred goods providers than the one they found on their social media. Yes, I know you have read this before- me too. But is real. The motto of the Customer Experience philosophy of providing a consistent experience through multiple touchpoints that makes the relationship customer/brand easier and valuable finds it basis on understanding customer/s preferences and context for which BigData analysis is another imperative. In summary, I believe that using BigData Analysis in combination with appropriated CeX strategies and technologies is a promising direction for achieving: efficiency and marketing cost-savings; growing the customer base; and increasing customer conversion and retention. In a world: The Direction of Future Marketing.

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• J2EE Applications, SPARC T4, Solaris Containers, and Resource Pools

  - by user12620111

  I've obtained a substantial performance improvement on a SPARC T4-2 Server running a J2EE Application Server Cluster by deploying the cluster members into Oracle Solaris Containers and binding those containers to cores of the SPARC T4 Processor. This is not a surprising result, in fact, it is consistent with other results that are available on the Internet. See the "references", below, for some examples. Nonetheless, here is a summary of my configuration and results. (1.0) Before deploying a J2EE Application Server Cluster into a virtualized environment, many decisions need to be made. I'm not claiming that all of the decisions that I have a made will work well for every environment. In fact, I'm not even claiming that all of the decisions are the best possible for my environment. I'm only claiming that of the small sample of configurations that I've tested, this is the one that is working best for me. Here are some of the decisions that needed to be made: (1.1) Which virtualization option? There are several virtualization options and isolation levels that are available. Options include: Hard partitions:  Dynamic Domains on Sun SPARC Enterprise M-Series Servers Hypervisor based virtualization such as Oracle VM Server for SPARC (LDOMs) on SPARC T-Series Servers OS Virtualization using Oracle Solaris Containers Resource management tools in the Oracle Solaris OS to control the amount of resources an application receives, such as CPU cycles, physical memory, and network bandwidth. Oracle Solaris Containers provide the right level of isolation and flexibility for my environment. To borrow some words from my friends in marketing, "The SPARC T4 processor leverages the unique, no-cost virtualization capabilities of Oracle Solaris Zones"  (1.2) How to associate Oracle Solaris Containers with resources? There are several options available to associate containers with resources, including (a) resource pool association (b) dedicated-cpu resources and (c) capped-cpu resources. I chose to create resource pools and associate them with the containers because I wanted explicit control over the cores and virtual processors.  (1.3) Cluster Topology? Is it best to deploy (a) multiple application servers on one node, (b) one application server on multiple nodes, or (c) multiple application servers on multiple nodes? After a few quick tests, it appears that one application server per Oracle Solaris Container is a good solution. (1.4) Number of cluster members to deploy? I chose to deploy four big 64-bit application servers. I would like go back a test many 32-bit application servers, but that is left for another day. (2.0) Configuration tested. (2.1) I was using a SPARC T4-2 Server which has 2 CPU and 128 virtual processors. To understand the physical layout of the hardware on Solaris 10, I used the OpenSolaris psrinfo perl script available at http://hub.opensolaris.org/bin/download/Community+Group+performance/files/psrinfo.pl: test# ./psrinfo.pl -pv The physical processor has 8 cores and 64 virtual processors (0-63) The core has 8 virtual processors (0-7)   The core has 8 virtual processors (8-15)   The core has 8 virtual processors (16-23)   The core has 8 virtual processors (24-31)   The core has 8 virtual processors (32-39)   The core has 8 virtual processors (40-47)   The core has 8 virtual processors (48-55)   The core has 8 virtual processors (56-63)     SPARC-T4 (chipid 0, clock 2848 MHz) The physical processor has 8 cores and 64 virtual processors (64-127)   The core has 8 virtual processors (64-71)   The core has 8 virtual processors (72-79)   The core has 8 virtual processors (80-87)   The core has 8 virtual processors (88-95)   The core has 8 virtual processors (96-103)   The core has 8 virtual processors (104-111)   The core has 8 virtual processors (112-119)   The core has 8 virtual processors (120-127)     SPARC-T4 (chipid 1, clock 2848 MHz) (2.2) The "before" test: without processor binding. I started with a 4-member cluster deployed into 4 Oracle Solaris Containers. Each container used a unique gigabit Ethernet port for HTTP traffic. The containers shared a 10 gigabit Ethernet port for JDBC traffic. (2.3) The "after" test: with processor binding. I ran one application server in the Global Zone and another application server in each of the three non-global zones (NGZ):  (3.0) Configuration steps. The following steps need to be repeated for all three Oracle Solaris Containers. (3.1) Stop AppServers from the BUI. (3.2) Stop the NGZ. test# ssh test-z2 init 5 (3.3) Enable resource pools: test# svcadm enable pools (3.4) Create the resource pool: test# poolcfg -dc 'create pool pool-test-z2' (3.5) Create the processor set: test# poolcfg -dc 'create pset pset-test-z2' (3.6) Specify the maximum number of CPU's that may be addd to the processor set: test# poolcfg -dc 'modify pset pset-test-z2 (uint pset.max=32)' (3.7) bash syntax to add Virtual CPUs to the processor set: test# (( i = 64 )); while (( i < 96 )); do poolcfg -dc "transfer to pset pset-test-z2 (cpu $i)"; (( i = i + 1 )) ; done (3.8) Associate the resource pool with the processor set: test# poolcfg -dc 'associate pool pool-test-z2 (pset pset-test-z2)' (3.9) Tell the zone to use the resource pool that has been created: test# zonecfg -z test-z1 set pool=pool-test-z2 (3.10) Boot the Oracle Solaris Container test# zoneadm -z test-z2 boot (3.11) Save the configuration to /etc/pooladm.conf test# pooladm -s (4.0) Results. Using the resource pools improves both throughput and response time: (5.0) References: System Administration Guide: Oracle Solaris Containers-Resource Management and Oracle Solaris Zones Capitalizing on large numbers of processors with WebSphere Portal on Solaris WebSphere Application Server and T5440 (Dileep Kumar's Weblog)  http://www.brendangregg.com/zones.html Reuters Market Data System, RMDS 6 Multiple Instances (Consolidated), Performance Test Results in Solaris, Containers/Zones Environment on Sun Blade X6270 by Amjad Khan, 2009.

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• MySQL and Hadoop Integration - Unlocking New Insight

  - by Mat Keep

  “Big Data” offers the potential for organizations to revolutionize their operations. With the volume of business data doubling every 1.2 years, analysts and business users are discovering very real benefits when integrating and analyzing data from multiple sources, enabling deeper insight into their customers, partners, and business processes. As the world’s most popular open source database, and the most deployed database in the web and cloud, MySQL is a key component of many big data platforms, with Hadoop vendors estimating 80% of deployments are integrated with MySQL. The new Guide to MySQL and Hadoop presents the tools enabling integration between the two data platforms, supporting the data lifecycle from acquisition and organisation to analysis and visualisation / decision, as shown in the figure below The Guide details each of these stages and the technologies supporting them: Acquire: Through new NoSQL APIs, MySQL is able to ingest high volume, high velocity data, without sacrificing ACID guarantees, thereby ensuring data quality. Real-time analytics can also be run against newly acquired data, enabling immediate business insight, before data is loaded into Hadoop. In addition, sensitive data can be pre-processed, for example healthcare or financial services records can be anonymized, before transfer to Hadoop. Organize: Data is transferred from MySQL tables to Hadoop using Apache Sqoop. With the MySQL Binlog (Binary Log) API, users can also invoke real-time change data capture processes to stream updates to HDFS. Analyze: Multi-structured data ingested from multiple sources is consolidated and processed within the Hadoop platform. Decide: The results of the analysis are loaded back to MySQL via Apache Sqoop where they inform real-time operational processes or provide source data for BI analytics tools. So how are companies taking advantage of this today? As an example, on-line retailers can use big data from their web properties to better understand site visitors’ activities, such as paths through the site, pages viewed, and comments posted. This knowledge can be combined with user profiles and purchasing history to gain a better understanding of customers, and the delivery of highly targeted offers. Of course, it is not just in the web that big data can make a difference. Every business activity can benefit, with other common use cases including: - Sentiment analysis; - Marketing campaign analysis; - Customer churn modeling; - Fraud detection; - Research and Development; - Risk Modeling; - And more. As the guide discusses, Big Data is promising a significant transformation of the way organizations leverage data to run their businesses. MySQL can be seamlessly integrated within a Big Data lifecycle, enabling the unification of multi-structured data into common data platforms, taking advantage of all new data sources and yielding more insight than was ever previously imaginable. Download the guide to MySQL and Hadoop integration to learn more. I'd also be interested in hearing about how you are integrating MySQL with Hadoop today, and your requirements for the future, so please use the comments on this blog to share your insights.

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• New Whitepaper: Oracle WebLogic Clustering

  - by ACShorten

  A new whitepaper is available that outlines the concepts and steps on implementing web application server clustering using the Oracle Utilities Application Framework and Oracle WebLogic Server. The whitepaper include the following: A short discussion on the concepts of clustering How to setup a cluster using Oracle WebLogic's utilities How to configure the Oracle Utilities Application Framework to take advantage of clustering How to deploy the Oracle Utilities Application based products in a clustered environment Common cluster operations The whitepaper is available from My Oracle Support at Doc Id: 1334558.1.

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• #MDX in London and speculation about future books

  - by Marco Russo (SQLBI)

  Chris Webb, who wrote the Expert Cube Development with Microsoft SQL Server 2008 Analysis Services book with me and Alberto , is preparing another Introduction to MDX course in London, this time from October 26th to 28th. It is now a three day course (previously it was two day) and you can find every other detail here . You might be wondering whether we are writing something else... well, we don't have plan to release a new edition of the Analysis Services book - after all, all the content of the...(read more)

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• Understanding Data Science: Recent Studies

  - by Joe Lamantia

  If you need such a deeper understanding of data science than Drew Conway's popular venn diagram model, or Josh Wills' tongue in cheek characterization, "Data Scientist (n.): Person who is better at statistics than any software engineer and better at software engineering than any statistician." two relatively recent studies are worth reading.   'Analyzing the Analyzers,' an O'Reilly e-book by Harlan Harris, Sean Patrick Murphy, and Marck Vaisman, suggests four distinct types of data scientists -- effectively personas, in a design sense -- based on analysis of self-identified skills among practitioners.  The scenario format dramatizes the different personas, making what could be a dry statistical readout of survey data more engaging.  The survey-only nature of the data,  the restriction of scope to just skills, and the suggested models of skill-profiles makes this feel like the sort of exercise that data scientists undertake as an every day task; collecting data, analyzing it using a mix of statistical techniques, and sharing the model that emerges from the data mining exercise.  That's not an indictment, simply an observation about the consistent feel of the effort as a product of data scientists, about data science.  And the paper 'Enterprise Data Analysis and Visualization: An Interview Study' by researchers Sean Kandel, Andreas Paepcke, Joseph Hellerstein, and Jeffery Heer considers data science within the larger context of industrial data analysis, examining analytical workflows, skills, and the challenges common to enterprise analysis efforts, and identifying three archetypes of data scientist.  As an interview-based study, the data the researchers collected is richer, and there's correspondingly greater depth in the synthesis.  The scope of the study included a broader set of roles than data scientist (enterprise analysts) and involved questions of workflow and organizational context for analytical efforts in general.  I'd suggest this is useful as a primer on analytical work and workers in enterprise settings for those who need a baseline understanding; it also offers some genuinely interesting nuggets for those already familiar with discovery work. We've undertaken a considerable amount of research into discovery, analytical work/ers, and data science over the past three years -- part of our programmatic approach to laying a foundation for product strategy and highlighting innovation opportunities -- and both studies complement and confirm much of the direct research into data science that we conducted. There were a few important differences in our findings, which I'll share and discuss in upcoming posts.

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• Using The Data Mining Query Task in SSIS

  SQL Server Integration Services (SSIS) is a Business Intelligence tool which can be used by database developers or administrators to perform Extract, Transform & Load (ETL) operations. In my previous article Using Analysis Services Processing Task & Analysis Services ... [Read Full Article]

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• Slicing the EDG

  - by Antony Reynolds

  Different SOA Domain Configurations In this blog entry I would like to introduce three different configurations for a SOA environment.  I have omitted load balancers and OTD/OHS as they introduce a whole new round of discussion.  For each possible deployment architecture I have identified some of the advantages. Super Domain This is a single EDG style domain for everything needed for SOA/OSB.   It extends the standard EDG slightly but otherwise assumes a single “super” domain. This is basically the SOA EDG.  I have broken out JMS servers and Coherence servers to improve scalability and reduce dependencies. Key Points Separate JMS allows those servers to be kept up separately from rest of SOA Domain, allowing JMS clients to post messages even if rest of domain is unavailable. JMS servers are only used to host application specific JMS destinations, SOA/OSB JMS destinations remain in relevant SOA/OSB managed servers. Separate Coherence servers allow OSB cache to be offloaded from OSB servers. Use of Coherence by other components as a shared infrastructure data grid service. Coherence cluster may be managed by WLS but more likely run as a standalone Coherence cluster. Benefits Single Administration Point (1 Admin Server) Closely follows EDG with addition of application specific JMS servers and standalone Coherence servers for OSB caching and application specific caches. Coherence grid can be scaled independent of OSB/SOA. JMS queues provide for inter-application communication. Drawbacks Patching is an all or nothing affair. Startup time for SOA may be slow if large number of composites deployed. Multiple Domains This extends the EDG into multiple domains, allowing separate management and update of these domains.  I see this type of configuration quite often with customers, although some don't have OWSM, others don't have separate Coherence etc. SOA & BAM are kept in the same domain as little benefit is obtained by separating them. Key Points Separate JMS allows those servers to be kept up separately from rest of SOA Domain, allowing JMS clients to post messages even if other domains are unavailable. JMS servers are only used to host application specific JMS destinations, SOA/OSB JMS destinations remain in relevant SOA/OSB managed servers. Separate Coherence servers allow OSB cache to be offloaded from OSB servers. Use of Coherence by other components as a shared infrastructure data grid service. Coherence cluster may be managed by WLS but more likely run as a standalone Coherence cluster. Benefits Follows EDG but in separate domains and with addition of application specific JMS servers and standalone Coherence servers for OSB caching and application specific caches. Coherence grid can be scaled independent of OSB/SOA. JMS queues provide for inter-application communication. Patch lifecycle of OSB/SOA/JMS are no longer lock stepped. JMS may be kept running independently of other domains allowing applications to insert messages fro later consumption by SOA/OSB. OSB may be kept running independent of other domains, allowing service virtualization to continue independent of other domains availability. All domains use same OWSM policy store (MDS-WSM). Drawbacks Multiple domains to manage and configure. Multiple Admin servers (single view requires use of Grid Control) Multiple Admin servers/WSM clusters waste resources. Additional homes needed to enjoy benefits of separate patching. Cross domain trust needs setting up to simplify cross domain interactions. Startup time for SOA may be slow if large number of composites deployed. Shared Service Environment This model extends the previous multiple domain arrangement to provide a true shared service environment.This extends the previous model by allowing multiple additional SOA domains and/or other domains to take advantage of the shared services.  Only one non-shared domain is shown, but there could be multiple, allowing groups of applications to share patching independent of other application groups. Key Points Separate JMS allows those servers to be kept up separately from rest of SOA Domain, allowing JMS clients to post messages even if other domains are unavailable. JMS servers are only used to host application specific JMS destinations, SOA/OSB JMS destinations remain in relevant SOA/OSB managed servers. Separate Coherence servers allow OSB cache to be offloaded from OSB servers. Use of Coherence by other components as a shared infrastructure data grid service Coherence cluster may be managed by WLS but more likely run as a standalone Coherence cluster. Shared SOA Domain hosts Human Workflow Tasks BAM Common "utility" composites Single OSB domain provides "Enterprise Service Bus" All domains use same OWSM policy store (MDS-WSM) Benefits Follows EDG but in separate domains and with addition of application specific JMS servers and standalone Coherence servers for OSB caching and application specific caches. Coherence grid can be scaled independent of OSB/SOA. JMS queues provide for inter-application communication. Patch lifecycle of OSB/SOA/JMS are no longer lock stepped. JMS may be kept running independently of other domains allowing applications to insert messages fro later consumption by SOA/OSB. OSB may be kept running independent of other domains, allowing service virtualization to continue independent of other domains availability. All domains use same OWSM policy store (MDS-WSM). Supports large numbers of deployed composites in multiple domains. Single URL for Human Workflow end users. Single URL for BAM end users. Drawbacks Multiple domains to manage and configure. Multiple Admin servers (single view requires use of Grid Control) Multiple Admin servers/WSM clusters waste resources. Additional homes needed to enjoy benefits of separate patching. Cross domain trust needs setting up to simplify cross domain interactions. Human Workflow needs to be specially configured to point to shared services domain. Summary The alternatives in this blog allow for patching to have different impacts, depending on the model chosen.  Each organization must decide the tradeoffs for itself.  One extreme is to go for the shared services model and have one domain per SOA application.  This requires a lot of administration of the multiple domains.  The other extreme is to have a single super domain.  This makes the entire enterprise susceptible to an outage at the same time due to patching or other domain level changes.  Hopefully this blog will help your organization choose the right model for you.

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• WildPackets Monitors Diverse Networks

  WildPackets offers portable network analysis products which are designed for use on enterprise networks and in test and measurement labs, plus distributed network analysis solutions for enterprise-wide applications.

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• Parent-child hierarchies and unary operators in PowerPivot

  - by Marco Russo (SQLBI)

  Alberto wrote an excellent post describing how to implement the Unary Operator feature (which is present in Analysis Services) in PowerPivot (there was a previous post about parent-child hierarchies, too). I have to say that the solution is not so easy to implement as in Analysis Services, but it just works and, from a practical point of view, it is not so difficult to implement if you understand how it works and accept its limitations (only sum and subtractions are supported). I think that many...(read more)

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• Search Engine Optimizing

  Search Engine Optimization is a process by which a web site is improved so that it can be more easily found by search engines, rank higher and be found by its target audience. The main components to SEO are: keyword analysis, content analysis, title and meta tags, relevant link building, search engine submission, and maintenance. Below are steps in the process.

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• Powerful Lessons in Data from the Presidential Election

  - by Christina McKeon

  Now that we’ve had a few days to recover from the U.S. presidential election, it’s a good time to take a step back from politics and look for the customer experience lessons that we can take away. The most powerful lesson is that when you know more about your base, you will have an advantage over your competition. That advantage will translate into you winning and your competition losing. Michael Scherer of TIME was given access to Obama’s data analysts two days before the election. His account is documented in Inside the Secret World of the Data Crunchers Who Helped Obama Win. What we learned from Scherer’s inside view is how well Obama’s team did in getting the right data, analyzing it, and acting on it. This data team recognized how critical it was to break down data silos within the campaign. As Scherer noted, they created “a single system that merged information from pollsters, fundraisers, field workers, consumer databases, and social-media and mobile contacts with the main Democratic voter files in the swing states.” The Obama analysis was so meticulous that they knew which celebrity and which type of celebrity event would help them maximize campaign contributions. With a single system, their data models became more precise. They determined which messages were more successful with specific demographic groups and that who made the calls mattered. Data analysis also led to many other changes in Obama’s campaign including a new ad buying strategy, using social media and applications to tap into supporters’ friends, and using new social news sites. While we did not have that same inside view into Romney’s campaign, much of the post-mortem coverage indicates that Romney’s team did not have the right analysis. As Peter Hamby of CNN wrote in Analysis: Why Romney Lost, “Romney officials had modeled an electorate that looked something like a mix of 2004 and 2008….” That historical data did not account for the changing demographics in the U.S. Does your organization approach data like the Obama or Romney team? Do you really know your base? How well can you predict what is going to happen in your business? If you haven’t already put together a strategy and plan to know more, this week’s civics lesson is a powerful reason to do it sooner rather than later. Your competitors are probably thinking the same thing that you are!

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• Botnet Malware Sleeps Eight Months Activation, Child Concerns

  Daily Safety Check experts used a computer forensic analysis of a significant botnet that consisted of Carberp and SpyEye malware to come up with the details for their report. The analysis found that the botnet profiled the behavior of the slave computers it infected, similar to surveillance techniques used by law enforcement agencies, for an average of eight months. During the eight months, the botnet analyzed each computer's users and assigned ratings to certain activities to form a complete profile for each. Doing so allowed those behind the scheme to determine which were the most favora...

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• Tissue Specific Electrochemical Fingerprinting on the NetBeans Platform

  - by Geertjan

  Proteomics and metalloproteomics are rapidly developing interdisciplinary fields providing enormous amounts of data to be classified, evaluated, and interpreted. Approaches offered by bioinformatics and also by biostatistical data analysis and treatment are therefore becoming increasingly relevant. A bioinformatics tool has been developed at universities in Prague and Brno, in the Czech Republic, for analysis and visualization in this domain, on the NetBeans Platform: More info:  http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0049654

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• Feature: Lead with Intelligence

  Business efficiency depends on business decisions, and business decisions depend on current, accurate information and powerful analysis. See how Oracle data warehousing, business intelligence, and enterprise performance management solutions deliver the information, analysis, and efficiencies to propel your business ahead of the competition.

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• Solaris Web Magazine JP ?????

  - by kazun

  #midashi{ font-size:120%; border-left: 8px solid #FF0000;/*??????????????????*/ border-bottom:dotted 1px #cccccc;/*?????????????*/ width:515px;/*??????*/ line-height: 26px;/*h3?????*/ padding-left: 5px;/*?????????*/ color:#333333; /*????*/ font-weight:bold; } .select{ padding-top:2px; padding-left: 3px;/*?????????*/ font-size:10px; color:#999999; display: block; } #midashi2{ font-size:120%; border-left: 8px solid #FF0000;/*??????????????????*/ border-bottom:dotted 1px #cccccc;/*?????????????*/ width:205px;/*??????*/ line-height: 26px;/*h3?????*/ padding-left: 5px;/*?????????*/ color:#333333; /*????*/ font-weight:bold; } .select{ padding-top:2px; padding-left: 3px;/*?????????*/ font-size:10px; color:#999999; display: block; } ???? ????????:Oracle OpenWorld Tokyo 2012 ?????? ????:?????????????????:???????Oracle Solaris Studio 12.3? ???? Oracle Solaris ???????????????????? Oracle OpenWorld Tokyo 2012 ?????? Oracle Solaris 11 ?????????:?Oracle Solaris 11 ?????·????·??? ?2???? ?????????????????:???????Oracle Solaris Studio 12.3? ????? ???? ??????????????????????? Oracle Solaris Oracle Solaris Studio Oracle Solaris Cluster ????? ???? Oracle Technology Network ??????????????????????????????? Oracle Solaris 11 Oracle Solaris 10 Oracle Solaris Cluster Enterprise Edition Oracle Solaris Studio OTN? ????/????  ?????????#4?6/15(?)??? 2012/5/21 Oracle Solaris ??????? #3 2012/5/23 ?83? ????! ???????? ~Oracle x Sun ?6?: Solaris 10 ?? Solaris 11 ?????????????(Slideshare) ?????? Solaris 11 Solaris 10 Oracle Solaris Cluster Oracle Solaris Studio Oracle Linux OTN? ??????????? ?????????? Oracle Solaris ????????????????????????????????????????????????? ???????????????????????????????????????????????? OTN ???? ?????? ????? ?????? ???? Oracle Software Delivery Cloud My Oracle Support ????????? Oracle PartnerNetwork Oracle Solaris Knowledge Zone ????????? Solaris ?????? Oracle|Sun ????????? Oracle Japan (??????) Oracle University ????? Oracle Solaris 11 ?????? Oracle Solaris 11 ??????????? Sun Cluster for Hign Availability ???????? ???????? ?????????? Server / Storage System ????

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• ???????/???MySQL?????? ??????

  - by Yusuke.Yamamoto

  ????? ??:2011/07/25 ??:??????/?? MySQL ??????????????????????????????Associate?Administrator?Developer?Cluster ?????????????????????????????????????????????????? MySQL 5 Certified Associate ?? / ????????????????MySQL 5 Developer Certified Professional ?? / ????????????????MySQL 5 Database Administrator Certified Professional ?? / ????????????????MySQL 5.1 Cluster Database Administrator Certified Expert ?? / ???????????????? ????????? ????????????????? http://otndnld.oracle.co.jp/ondemand/otn-seminar/movie/20110725MySQL_Cert.wmv http://www.oracle.com/technetwork/jp/ondemand/db-new/20110725-ou-cert-455765-ja.pdf

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• ?!Solaris ??20??? ????Solaris 11.1????????!

  - by OTN-J Master

  Solaris 11.1 ??????????? US OTN???????????????????????????????Solaris 11.1??????????? (OTN Japan???????????????????????????????) ???????Oracle Solaris ?????????????????????????????????????????????????????????????????????????????Solaris 11??????????????300???????????????10?4??Oracle OpenWorld?????Solaris 11.1?????????(??????????)?????????????Solaris?????20????????20??????????????????? ???????????????????????OS??????????????????????????Solaris 11.1????? ?????????????2012?11?7???8:00????Oracle Solaris 11.1?????Oracle Solaris Cluster???????·????·???????????????????????Solaris??20??????????????Solaris??????????????Oracle Solaris 11.1??Oracle Solarus Cluster???????????????????????11?8???1?????????????????????????????????Solaris?????????????????·???????????????????

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