Search Results

Search found 4349 results on 174 pages for 'eisa partition'.

Page 170/174 | < Previous Page | 166 167 168 169 170 171 172 173 174  | Next Page >

• What’s New for Oracle Commerce? Executive QA with John Andrews, VP Product Management, Oracle Commerce

  - by Katrina Gosek

  Oracle Commerce was for the fifth time positioned as a leader by Gartner in the Magic Quadrant for E-Commerce. This inspired me to sit down with Oracle Commerce VP of Product Management, John Andrews to get his perspective on what continues to make Oracle a leader in the industry and what’s new for Oracle Commerce in 2013. Q: Why do you believe Oracle Commerce continues to be a leader in the industry? John: Oracle has a great acquisition strategy – it brings best-of-breed technologies into the product fold and then continues to grow and innovate them. This is particularly true with products unified into the Oracle Commerce brand. Oracle acquired ATG in late 2010 – and then Endeca in late 2011. This means that under the hood of Oracle Commerce you have market-leading technologies for cross-channel commerce and customer experience, both designed and developed in direct response to the unique challenges online businesses face. And we continue to innovate on capabilities core to what our customers need to be successful – contextual and personalized experience delivery, merchant-inspired tools, and architecture for performance and scalability. Q: It’s not a slow moving industry. What are you doing to keep the pace of innovation at Oracle Commerce? John: Oracle owes our customers the most innovative commerce capabilities. By unifying the core components of ATG and Endeca we are delivering on this promise. Oracle Commerce is continuing to innovate and redefine how commerce is done and in a way that drive business results and keeps customers coming back for experiences tailored just for them. Our January and May 2013 releases not only marked the seventh significant releases for the solution since the acquisitions of ATG and Endeca, we also continue to demonstrate rapid and significant progress on the unification of commerce and customer experience capabilities of the two commerce technologies. Q: Can you tell us what was notable about these latest releases under the Oracle Commerce umbrella? John: Specifically, our latest product innovations give businesses selling online the ability to get to market faster with more personalized commerce experiences in the following ways: Mobile: the latest Commerce Reference Application in this release offers a wider range of examples for online businesses to leverage for iOS development and specifically new iPad reference capabilities. This release marks the first release of the iOS Universal application that serves both the iPhone and iPad devices from a single download or binary. Business users can now drive page content management and layout of search results and category pages, as well as create additional storefront elements such as categories, facets / dimensions, and breadcrumbs through Experience Manager tools. Cross-Channel Commerce: key commerce platform capabilities have been added to support cross-channel commerce, including an expanded inventory model to maintain inventory for stores, pickup in stores and Web-based returns. Online businesses with in-store operations can now offer advanced shipping options on the web and make returns and exchange logic easily available on the web. Multi-Site Capabilities: significant enhancements to the Commerce Platform multi-site architecture that allows business users to quickly launch and manage multiple sites on the same cluster and share data, carts, and other components. First introduced in 2010, with this latest release business users can now partition or share customer profiles, control users’ site-based access, and manage personalization assets using site groups. Internationalization: continued language support and enhancements for business user tools as well and search and navigation. Guided Search now supports 35 total languages with 11 new languages (including Danish, Arabic, Norwegian, Serbian Cyrillic) added in this release. Commerce Platform tools now include localized support for 17 locales with 4 new languages (Danish, Portuguese (European), Finnish, and Thai). No development or customization is required in order for business users to use the applications in any of these supported languages. Business Tool Experience: valuable new Commerce Merchandising features include a new workflow for making emergency changes quickly and increased visibility into promotions rules and qualifications in preview mode. Oracle Commerce business tools continue to become more and more feature rich to provide intuitive, easy- to-use (yet powerful) capabilities to allow business users to manage content and the shopping experience. Commerce & Experience Unification: demonstrable unification of commerce and customer experience capabilities include – productized cartridges that provide supported integration between the Commerce Platform and Experience Management tools, cross-channel returns, Oracle Service Cloud integration, and integrated iPad application. The mission guiding our product development is to deliver differentiated, personalized user experiences across any device in a contextual manner – and to give the business the best tools to tune and optimize those user experiences to meet their business objectives. We also need to do this in a way that makes it operationally efficient for the business, keeping the overall total cost of ownership low – yet also allows the business to expand, whether it be to new business models, geographies or brands. To learn more about the latest Oracle Commerce releases and mission, visit the links below: • Hear more from John about the Oracle Commerce mission • Hear from Oracle Commerce customers • Documentation on the new releases • Listen to the Oracle ATG Commerce 10.2 Webcast • Listen to the Oracle Endeca Commerce 3.1.2 Webcast

  Read the article

• Parallelism in .NET – Part 8, PLINQ’s ForAll Method

  - by Reed

  Parallel LINQ extends LINQ to Objects, and is typically very similar.  However, as I previously discussed, there are some differences.  Although the standard way to handle simple Data Parellelism is via Parallel.ForEach, it’s possible to do the same thing via PLINQ. PLINQ adds a new method unavailable in standard LINQ which provides new functionality… LINQ is designed to provide a much simpler way of handling querying, including filtering, ordering, grouping, and many other benefits.  Reading the description in LINQ to Objects on MSDN, it becomes clear that the thinking behind LINQ deals with retrieval of data.  LINQ works by adding a functional programming style on top of .NET, allowing us to express filters in terms of predicate functions, for example. PLINQ is, generally, very similar.  Typically, when using PLINQ, we write declarative statements to filter a dataset or perform an aggregation.  However, PLINQ adds one new method, which provides a very different purpose: ForAll. The ForAll method is defined on ParallelEnumerable, and will work upon any ParallelQuery<T>.  Unlike the sequence operators in LINQ and PLINQ, ForAll is intended to cause side effects.  It does not filter a collection, but rather invokes an action on each element of the collection. At first glance, this seems like a bad idea.  For example, Eric Lippert clearly explained two philosophical objections to providing an IEnumerable<T>.ForEach extension method, one of which still applies when parallelized.  The sole purpose of this method is to cause side effects, and as such, I agree that the ForAll method “violates the functional programming principles that all the other sequence operators are based upon”, in exactly the same manner an IEnumerable<T>.ForEach extension method would violate these principles.  Eric Lippert’s second reason for disliking a ForEach extension method does not necessarily apply to ForAll – replacing ForAll with a call to Parallel.ForEach has the same closure semantics, so there is no loss there. Although ForAll may have philosophical issues, there is a pragmatic reason to include this method.  Without ForAll, we would take a fairly serious performance hit in many situations.  Often, we need to perform some filtering or grouping, then perform an action using the results of our filter.  Using a standard foreach statement to perform our action would avoid this philosophical issue: // Filter our collection var filteredItems = collection.AsParallel().Where( i => i.SomePredicate() ); // Now perform an action foreach (var item in filteredItems) { // These will now run serially item.DoSomething(); } .csharpcode, .csharpcode pre { font-size: small; color: black; font-family: consolas, "Courier New", courier, monospace; background-color: #ffffff; /*white-space: pre;*/ } .csharpcode pre { margin: 0em; } .csharpcode .rem { color: #008000; } .csharpcode .kwrd { color: #0000ff; } .csharpcode .str { color: #006080; } .csharpcode .op { color: #0000c0; } .csharpcode .preproc { color: #cc6633; } .csharpcode .asp { background-color: #ffff00; } .csharpcode .html { color: #800000; } .csharpcode .attr { color: #ff0000; } .csharpcode .alt { background-color: #f4f4f4; width: 100%; margin: 0em; } .csharpcode .lnum { color: #606060; } This would cause a loss in performance, since we lose any parallelism in place, and cause all of our actions to be run serially. We could easily use a Parallel.ForEach instead, which adds parallelism to the actions: // Filter our collection var filteredItems = collection.AsParallel().Where( i => i.SomePredicate() ); // Now perform an action once the filter completes Parallel.ForEach(filteredItems, item => { // These will now run in parallel item.DoSomething(); }); This is a noticeable improvement, since both our filtering and our actions run parallelized.  However, there is still a large bottleneck in place here.  The problem lies with my comment “perform an action once the filter completes”.  Here, we’re parallelizing the filter, then collecting all of the results, blocking until the filter completes.  Once the filtering of every element is completed, we then repartition the results of the filter, reschedule into multiple threads, and perform the action on each element.  By moving this into two separate statements, we potentially double our parallelization overhead, since we’re forcing the work to be partitioned and scheduled twice as many times. This is where the pragmatism comes into play.  By violating our functional principles, we gain the ability to avoid the overhead and cost of rescheduling the work: // Perform an action on the results of our filter collection .AsParallel() .Where( i => i.SomePredicate() ) .ForAll( i => i.DoSomething() ); The ability to avoid the scheduling overhead is a compelling reason to use ForAll.  This really goes back to one of the key points I discussed in data parallelism: Partition your problem in a way to place the most work possible into each task.  Here, this means leaving the statement attached to the expression, even though it causes side effects and is not standard usage for LINQ. This leads to my one guideline for using ForAll: The ForAll extension method should only be used to process the results of a parallel query, as returned by a PLINQ expression. Any other usage scenario should use Parallel.ForEach, instead.

  Read the article

• Configure Oracle SOA JMSAdatper to Work with WLS JMS Topics

  - by fip

  The WebLogic JMS Topic are typically running in a WLS cluster. So as your SOA composites that receive these Topic messages. In some situation, the two clusters are the same while in others they are sepearate. The composites in SOA cluster are subscribers to the JMS Topic in WebLogic cluster. As nature of JMS Topic is meant to distribute the same copy of messages to all its subscribers, two questions arise immediately when it comes to load balancing the JMS Topic messages against the SOA composites: How to assure all of the SOA cluster members receive different messages instead of the same (duplicate) messages, even though the SOA cluster members are all subscribers to the Topic? How to make sure the messages are evenly distributed (load balanced) to SOA cluster members? Here we will walk through how to configure the JMS Topic, the JmsAdapter connection factory, as well as the composite so that the JMS Topic messages will be evenly distributed to same composite running off different SOA cluster nodes without causing duplication. 2. The typical configuration In this typical configuration, we achieve the load balancing of JMS Topic messages to JmsAdapters by configuring a partitioned distributed topic along with sharable subscriptions. You can reference the documentation for explanation of PDT. And this blog posting does a very good job to visually explain how this combination of configurations would message load balancing among clients of JMS Topics. Our job is to apply this configuration in the context of SOA JMS Adapters. To do so would involve the following steps: Step A. Configure JMS Topic to be UDD and PDT, at the WebLogic cluster that house the JMS Topic Step B. Configure JCA Connection Factory with proper ServerProperties at the SOA cluster Step C. Reference the JCA Connection Factory and define a durable subscriber name, at composite's JmsAdapter (or the *.jca file) Here are more details of each step: Step A. Configure JMS Topic to be UDD and PDT, You do this at the WebLogic cluster that house the JMS Topic. You can follow the instructions at Administration Console Online Help to create a Uniform Distributed Topic. If you use WebLogic Console, then at the same administration screen you can specify "Distribution Type" to be "Uniform", and the Forwarding policy to "Partitioned", which would make the JMS Topic Uniform Distributed Destination and a Partitioned Distributed Topic, respectively Step B: Configure ServerProperties of JCA Connection Factory You do this step at the SOA cluster. This step is to make the JmsAdapter that connect to the JMS Topic through this JCA Connection Factory as a certain type of "client". When you configure the JCA Connection Factory for the JmsAdapter, you define the list of properties in FactoryProperties field, in a semi colon separated list: ClientID=myClient;ClientIDPolicy=UNRESTRICTED;SubscriptionSharingPolicy=SHARABLE;TopicMessageDistributionAll=false You can refer to Chapter 8.4.10 Accessing Distributed Destinations (Queues and Topics) on the WebLogic Server JMS of the Adapter User Guide for the meaning of these properties. Please note: Except for ClientID, other properties such as the ClientIDPolicy=UNRESTRICTED, SubscriptionSharingPolicy=SHARABLE and TopicMessageDistributionAll=false are all default settings for the JmsAdapter's connection factory. Therefore you do NOT have to explicitly specify them explicitly. All you need to do is the specify the ClientID. The ClientID is different from the subscriber ID that we are to discuss in the later steps. To make it simple, you just need to remember you need to specify the client ID and make it unique per connection factory. Here is the example setting: Step C. Reference the JCA Connection Factory and define a durable subscriber name, at composite's JmsAdapter (or the *.jca file) In the following example, the value 'MySubscriberID-1' was given as the value of property 'DurableSubscriber': <adapter-config name="subscribe" adapter="JMS Adapter" wsdlLocation="subscribe.wsdl" xmlns="http://platform.integration.oracle/blocks/adapter/fw/metadata"> <connection-factory location="eis/wls/MyTestUDDTopic" UIJmsProvider="WLSJMS" UIConnectionName="ateam-hq24b"/> <endpoint-activation portType="Consume_Message_ptt" operation="Consume_Message"> <activation-spec className="oracle.tip.adapter.jms.inbound.JmsConsumeActivationSpec"> <property name="DurableSubscriber" value="MySubscriberID-1"/> <property name="PayloadType" value="TextMessage"/> <property name="UseMessageListener" value="false"/> <property name="DestinationName" value="jms/MyTestUDDTopic"/> </activation-spec> </endpoint-activation> </adapter-config> You can set the durable subscriber name either at composite's JmsAdapter wizard,or by directly editing the JmsAdapter's *.jca file within the Composite project. 2.The "atypical" configurations: For some systems, there may be restrictions that do not allow the afore mentioned "typical" configurations be applied. For examples, some deployments may be required to configure the JMS Topic to be Replicated Distributed Topic rather than Partition Distributed Topic. We would like to discuss those scenarios here: Configuration A: The JMS Topic is NOT PDT In this case, you need to define the message selector 'NOT JMS_WL_DDForwarded' in the adapter's *.jca file, to filter out those "replicated" messages. Configuration B. The ClientIDPolicy=RESTRICTED In this case, you need separate factories for different composites. More accurately, you need separate factories for different *.jca file of JmsAdapter. References: Managing Durable Subscription WebLogic JMS Partitioned Distributed Topics and Shared Subscriptions JMS Troubleshooting: Configuring JMS Message Logging: Advanced Programming with Distributed Destinations Using the JMS Destination Availability Helper API

  Read the article

• Wireless cuts out on Toshiba Satellite S7208

  - by alecRN

  I recently got a Toshiba Satellite L875-S7208 with Windows 7 preinstalled. I installed Ubuntu 12.04 LTS dual boot to the same Windows partition. However, usually 15 minutes or less after booting, the wifi connection dies. Here's some hopefully relevant information: lspci -knn 00:00.0 Host bridge [0600]: Intel Corporation 2nd Generation Core Processor Family DRAM Controller [8086:0104] (rev 09) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: agpgart-intel 00:02.0 VGA compatible controller [0300]: Intel Corporation 2nd Generation Core Processor Family Integrated Graphics Controller [8086:0116] (rev 09) Subsystem: Toshiba America Info Systems Device [1179:fb40] Kernel driver in use: i915 Kernel modules: i915 00:14.0 USB controller [0c03]: Intel Corporation Panther Point USB xHCI Host Controller [8086:1e31] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: xhci_hcd 00:16.0 Communication controller [0780]: Intel Corporation Panther Point MEI Controller #1 [8086:1e3a] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: mei Kernel modules: mei 00:1a.0 USB controller [0c03]: Intel Corporation Panther Point USB Enhanced Host Controller #2 [8086:1e2d] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: ehci_hcd 00:1b.0 Audio device [0403]: Intel Corporation Panther Point High Definition Audio Controller [8086:1e20] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb40] Kernel driver in use: snd_hda_intel Kernel modules: snd-hda-intel 00:1c.0 PCI bridge [0604]: Intel Corporation Panther Point PCI Express Root Port 1 [8086:1e10] (rev c4) Kernel driver in use: pcieport Kernel modules: shpchp 00:1c.1 PCI bridge [0604]: Intel Corporation Panther Point PCI Express Root Port 2 [8086:1e12] (rev c4) Kernel driver in use: pcieport Kernel modules: shpchp 00:1c.2 PCI bridge [0604]: Intel Corporation Panther Point PCI Express Root Port 3 [8086:1e14] (rev c4) Kernel driver in use: pcieport Kernel modules: shpchp 00:1d.0 USB controller [0c03]: Intel Corporation Panther Point USB Enhanced Host Controller #1 [8086:1e26] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: ehci_hcd 00:1f.0 ISA bridge [0601]: Intel Corporation Panther Point LPC Controller [8086:1e59] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel modules: iTCO_wdt 00:1f.2 SATA controller [0106]: Intel Corporation Panther Point 6 port SATA Controller [AHCI mode] [8086:1e03] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel driver in use: ahci 00:1f.3 SMBus [0c05]: Intel Corporation Panther Point SMBus Controller [8086:1e22] (rev 04) Subsystem: Toshiba America Info Systems Device [1179:fb41] Kernel modules: i2c-i801 02:00.0 Network controller [0280]: Realtek Semiconductor Co., Ltd. RTL8188CE 802.11b/g/n WiFi Adapter [10ec:8176] (rev 01) Subsystem: Realtek Semiconductor Co., Ltd. Device [10ec:8211] Kernel driver in use: rtl8192ce Kernel modules: rtl8192ce 03:00.0 Ethernet controller [0200]: Realtek Semiconductor Co., Ltd. RTL8101E/RTL8102E PCI Express Fast Ethernet controller [10ec:8136] (rev 05) Subsystem: Toshiba America Info Systems Device [1179:fb37] Kernel driver in use: r8169 Kernel modules: r8169 lsmod Module Size Used by snd_hda_codec_hdmi 32474 1 snd_hda_codec_realtek 224066 1 joydev 17693 0 rfcomm 47604 0 bnep 18281 2 bluetooth 180104 10 rfcomm,bnep parport_pc 32866 0 ppdev 17113 0 arc4 12529 2 snd_hda_intel 33773 3 snd_hda_codec 127706 3 snd_hda_codec_hdmi,snd_hda_codec_realtek,snd_hda_intel snd_hwdep 13668 1 snd_hda_codec snd_pcm 97188 3 snd_hda_codec_hdmi,snd_hda_intel,snd_hda_codec snd_seq_midi 13324 0 snd_rawmidi 30748 1 snd_seq_midi snd_seq_midi_event 14899 1 snd_seq_midi snd_seq 61896 2 snd_seq_midi,snd_seq_midi_event snd_timer 29990 2 snd_pcm,snd_seq snd_seq_device 14540 3 snd_seq_midi,snd_rawmidi,snd_seq psmouse 87692 0 serio_raw 13211 0 rtl8192ce 84826 0 rtl8192c_common 75767 1 rtl8192ce rtlwifi 111202 1 rtl8192ce mac80211 506816 3 rtl8192ce,rtl8192c_common,rtlwifi snd 78855 16 snd_hda_codec_hdmi,snd_hda_codec_realtek,snd_hda_intel,snd_hda_codec,snd_hwdep,snd_pcm,snd_rawmidi,snd_seq,snd_timer,snd_seq_device sparse_keymap 13890 0 uvcvideo 72627 0 videodev 98259 1 uvcvideo v4l2_compat_ioctl32 17128 1 videodev mac_hid 13253 0 mei 41616 0 wmi 19256 0 soundcore 15091 1 snd i915 472941 3 snd_page_alloc 18529 2 snd_hda_intel,snd_pcm drm_kms_helper 46978 1 i915 cfg80211 205544 2 rtlwifi,mac80211 drm 242038 4 i915,drm_kms_helper i2c_algo_bit 13423 1 i915 video 19596 1 i915 lp 17799 0 parport 46562 3 parport_pc,ppdev,lp r8169 62099 0 ums_realtek 18248 0 uas 18180 0 usb_storage 49198 1 ums_realtek dmesg | grep firmware [ 15.692951] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 16.240881] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 452.419288] rtl8192c_common:rtl92c_firmware_selfreset(): 8051 reset fail. [ 458.572211] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 465.440640] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 472.337617] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 479.175471] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 485.978582] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 492.764893] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 499.579348] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 506.386934] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 513.209545] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 519.991365] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 526.778375] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 533.629695] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 540.426004] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 547.238125] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 554.024434] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 560.854794] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 567.678160] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 574.494666] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 581.336653] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 588.157710] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 595.221122] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 602.047429] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 608.829534] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 615.639079] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 622.454991] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 629.273231] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 636.056613] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 642.858096] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 649.640753] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 657.184094] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 664.008018] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 670.838639] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 677.675418] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 684.507255] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 691.310994] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 698.095325] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 704.914509] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin [ 711.725178] rtl8192c_common: Loading firmware file rtlwifi/rtl8192cfw.bin uname -r 3.2.0-29-generic ifconfig eth0 Link encap:Ethernet HWaddr 4c:72:b9:59:6c:61 inet addr:192.168.0.11 Bcast:192.168.0.255 Mask:255.255.255.0 inet6 addr: fe80::4e72:b9ff:fe59:6c61/64 Scope:Link UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1 RX packets:4447 errors:0 dropped:0 overruns:0 frame:0 TX packets:2762 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:3671147 (3.6 MB) TX bytes:335133 (335.1 KB) Interrupt:42 Base address:0x2000 lo Link encap:Local Loopback inet addr:127.0.0.1 Mask:255.0.0.0 inet6 addr: ::1/128 Scope:Host UP LOOPBACK RUNNING MTU:16436 Metric:1 RX packets:515 errors:0 dropped:0 overruns:0 frame:0 TX packets:515 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:83153 (83.1 KB) TX bytes:83153 (83.1 KB) wlan0 Link encap:Ethernet HWaddr 74:e5:43:32:47:95 UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:280 errors:0 dropped:0 overruns:0 frame:0 TX packets:51 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:32958 (32.9 KB) TX bytes:10431 (10.4 KB)

  Read the article

• DBCC CHECKDB (BatmanDb, REPAIR_ALLOW_DATA_LOSS) &ndash; Are you Feeling Lucky?

  - by David Totzke

  I’m currently working for a client on a PowerBuilder to WPF migration.  It’s one of those “I could tell you, but I’d have to kill you” kind of clients and the quick-lime pits are currently occupied by the EMC tech…but I’ve said too much already. At approximately 3 or 4 pm that day users of the Batman[1] application here in Gotham[1] started to experience problems accessing the application.  Batman[2] is a document management system here that also integrates with the ERP system.  Very little goes on here that doesn’t involve Batman in some way.  The errors being received seemed to point to network issues (TCP protocol error, connection forcibly closed by the remote host etc…) but the real issue was much more insidious. Connecting to the database via SSMS and performing selects on certain tables underlying the application areas that were having problems started to reveal the issue.  You couldn’t do a SELECT * FROM MyTable without it bombing and giving the same error noted above.  A run of DBCC CHECKDB revealed 14 tables with corruption.  One of the tables with issues was the Document table.  Pretty central to a “document management” system.  Information was obtained from IT that a single drive in the SAN went bad in the night.  A new drive was in place and was working fine.  The partition that held the Batman database is configured for RAID Level 5 so a single drive failure shouldn’t have caused any trouble and yet, the database is corrupted.  They do hourly incremental backups here so the first thing done was to try a restore.  A restore of the most recent backup failed so they worked backwards until they hit a good point.  This successful restore was for a backup at 3AM – a full day behind.  This time also roughly corresponds with the time the SAN started to report the drive failure.  The plot thickens… I got my hands on the output from DBCC CHECKDB and noticed a pattern.  What’s sad is that nobody that should have noticed the pattern in the DBCC output did notice.  There was a rush to do things to try and recover the data before anybody really understood what was wrong with it in the first place.  Cooler heads must prevail in these circumstances and some investigation should be done and a plan of action laid out or you could end up making things worse[3].  DBCC CHECKDB also told us that: repair_allow_data_loss is the minimum repair level for the errors found by DBCC CHECKDB Yikes.  That means that the database is so messed up that you’re definitely going to lose some stuff when you repair it to get it back to a consistent state.  All the more reason to do a little more investigation into the problem.  Rescuing this database is preferable to having to export all of the data possible from this database into a new one.  This is a fifteen year old application with about seven hundred tables.  There are TRIGGERS everywhere not to mention the referential integrity constraints to deal with.  Only fourteen of the tables have an issue.  We have a good backup that is missing the last 24 hours of business which means we could have a “do-over” of yesterday but that’s not a very palatable option either. All of the affected tables had TEXT columns and all of the errors were about LOB data types and orphaned off-row data which basically means TEXT, IMAGE or NTEXT columns.  If we did a SELECT on an affected table and excluded those columns, we got all of the rows.  We exported that data into a separate database.  Things are looking up.  Working on a copy of the production database we then ran DBCC CHECKDB with REPAIR_ALLOW_DATA_LOSS and that “fixed” everything up.   The allow data loss option will delete the bad rows.  This isn’t too horrible as we have all of those rows minus the text fields from out earlier export.  Now I could LEFT JOIN to the exported data to find the missing rows and INSERT them minus the TEXT column data. We had the restored data from the good 3AM backup that we could now JOIN to and, with fingers crossed, recover the missing TEXT column information.  We got lucky in that all of the affected rows were old and in the end we didn’t lose anything.  :O  All of the row counts along the way worked out and it looks like we dodged a major bullet here. We’ve heard back from EMC and it turns out the SAN firmware that they were running here is apparently buggy.  This thing is only a couple of months old.  Grrr…. They dispatched a technician that night to come and update it .  That explains why RAID didn’t save us. All-in-all this could have been a lot worse.  Given the root cause here, they basically won the lottery in not losing anything. Here are a few links to some helpful posts on the SQL Server Engine blog.  I love the title of the first one: Which part of 'REPAIR_ALLOW_DATA_LOSS' isn't clear? CHECKDB (Part 8): Can repair fix everything? (in fact, read the whole series) Ta da! Emergency mode repair (we didn’t have to resort to this one thank goodness)   Dave Just because I can…   [1] Names have been changed to protect the guilty. [2] I'm Batman. [3] And if I'm the coolest head in the room, you've got even bigger problems...

  Read the article

• Is Linear Tape File System (LTFS) Best For Transportable Storage?

  - by rickramsey

  Those of us in tape storage engineering take a lot of pride in what we do, but understand that tape is the right answer to a storage problem only some of the time. And, unfortunately for a storage medium with such a long history, it has built up a few preconceived notions that are no longer valid. When I hear customers debate whether to implement tape vs. disk, one of the common strikes against tape is its perceived lack of usability. If you could go back a few generations of corporate acquisitions, you would discover that StorageTek engineers recognized this problem and started developing a solution where a tape drive could look just like a memory stick to a user. The goal was to not have to care about where files were on the cartridge, but to simply see the list of files that were on the tape, and click on them to open them up. Eventually, our friends in tape over at IBM built upon our work at StorageTek and Sun Microsystems and released the Linear Tape File System (LTFS) feature for the current LTO5 generation of tape drives as an open specification. LTFS is really a wonderful feature and we’re proud to have taken part in its beginnings and, as you’ll soon read, its future. Today we offer LTFS-Open Edition, which is free for you to use in your in Oracle Enterprise Linux 5.5 environment - not only on your LTO5 drives, but also on your Oracle StorageTek T10000C drives. You can download it free from Oracle and try it out. LTFS does exactly what its forefathers imagined. Now you can see immediately which files are on a cartridge. LTFS does this by splitting a cartridge into two partitions. The first holds all of the necessary metadata to create a directory structure for you to easily view the contents of the cartridge. The second partition holds all of the files themselves. When tape media is loaded onto a drive, a complete file system image is presented to the user. Adding files to a cartridge can be as simple as a drag-and-drop just as you do today on your laptop when transferring files from your hard drive to a thumb drive or with standard POSIX file operations. You may be thinking all of this sounds nice, but asking, “when will I actually use it?” As I mentioned at the beginning, tape is not the right solution all of the time. However, if you ever need to physically move data between locations, tape storage with LTFS should be your most cost-effective and reliable answer. I will give you a few use cases examples of when LTFS can be utilized. Media and Entertainment (M&E), Oil and Gas (O&G), and other industries have a strong need for their storage to be transportable. For example, an O&G company hunting for new oil deposits in remote locations takes very large underground seismic images which need to be shipped back to a central data center. M&E operations conduct similar activities when shooting video for productions. M&E companies also often transfers files to third-parties for editing and other activities. These companies have three highly flawed options for transporting data: electronic transfer, disk storage transport, or tape storage transport. The first option, electronic transfer, is impractical because of the expense of the bandwidth required to transfer multi-terabyte files reliably and efficiently. If there’s one place that has bandwidth, it’s your local post office so many companies revert to physically shipping storage media. Typically, M&E companies rely on transporting disk storage between sites even though it, too, is expensive. Tape storage should be the preferred format because as IDC points out, “Tape is more suitable for physical transportation of large amounts of data as it is less vulnerable to mechanical damage during transportation compared with disk" (See note 1, below). However, tape storage has not been used in the past because of the restrictions created by proprietary formats. A tape may only be readable if both the sender and receiver have the same proprietary application used to write the file. In addition, the workflows may be slowed by the need to read the entire tape cartridge during recall. LTFS solves both of these problems, clearing the way for tape to become the standard platform for transferring large files. LTFS is open and, as long as you’ve downloaded the free reader from our website or that of anyone in the LTO consortium, you can read the data. So if a movie studio ships a scene to a third-party partner to add, for example, sounds effects or a music score, it doesn’t have to care what technology the third-party has. If it’s written back to an LTFS-formatted tape cartridge, it can be read. Some tape vendors like to claim LTFS is a “standard,” but beauty is in the eye of the beholder. It’s a specification at this point, not a standard. That said, we’re already seeing application vendors create functionality to write in an LTFS format based on the specification. And it’s my belief that both customers and the tape storage industry will see the most benefit if we all follow the same path. As such, we have volunteered to lead the way in making LTFS a standard first with the Storage Network Industry Association (SNIA), and eventually through to standard bodies such as American National Standards Institute (ANSI). Expect to hear good news soon about our efforts. So, if storage transportability is one of your requirements, I recommend giving LTFS a look. It makes tape much more user-friendly and it’s free, which allows tape to maintain all of its cost advantages over disk! Note 1 - IDC Report. April, 2011. “IDC’s Archival Storage Solutions Taxonomy, 2011” - Brian Zents Website Newsletter Facebook Twitter

  Read the article

• How to UEFI install Ubuntu 12.10?

  - by Geezanansa

  Running a newer FM1 motherboard which is using an AMD 3870k APU with a new 1TB HDD. Following the advice in the motherboard manual and https://help.ubuntu.com/community/UEFI have now got to grub option screen for UEFI install. see http://imgur.com/VW5vz The dvd.iso being used is Ubuntu 12.10 desktop amd64 from ubuntu .com. The hdd has had a gpt partition table made for, by using gparted when in a live desktop session when booted in bios mode. (*edit/update: Although the old cd updates on running it is an old kernel and it did make a gpt but that version of gparted uses fdisk whereas gdisk is required to make gpt. Think am going to have to spend more time here http://www.dedoimedo.com/computers/gparted.html lol Using the gparted from 12.10 live session to make partitions; following the guidance regarding this at https://help.ubuntu.com/community/UEFI#Creating_an_EFI_partition, but can only boot to grub option screen http://imgur.com/VW5vz when 12.10 options to "try ubuntu" or "install ubuntu" are selected they give errors as described below*) but after making the gpt decided to leave it unformatted/unallocated space with the intention of using installer to set up partitions. update-originally but gparted now sees hdd as http://imgur.com/hFIvm as described above. *Booting live dvd in EFI mode gives "Secure Boot not installed" just before grub kernel option list with the option to "install ubuntu" but get "can not read cd/0" and "the kernel must be loaded first" errors; when that option is selected. Any pointers on how to get installer going for UEFI install would be good. Thanks in advance. update: Hopefully these screenshots can help better highlight where i am going wrong or if there is something else going on http://imgur.com/g30RB, http://imgur.com/VW5vz, http://imgur.com/31E0q, http://imgur.com/bnuaG, http://imgur.com/y4KGu, http://imgur.com/3u2QE, http://imgur.com/n9lN3, http://imgur.com/FEKvz, http://imgur.com/hFIvm, update: Thank you fernando garcia for pointing me in the right direction to start the process of elimantion. What i have done since asking question is a little home work starting here http://askubuntu.com/faq#bounty and here http://askubuntu.com/questions/how-to-ask. Looking at other similar questions was good fun and found this 12.10 UEFI Secure Boot install the most relative in helping getting ubuntu to uefi install on my system. In response to wolverine's question this article was referred to http://web.dodds.net/~vorlon/wiki/blog/SecureBoot_in_Ubuntu_12.10/ This article in the first sentence gives a link to http://www.ubuntu.com/download which is where i downloaded the 12.10 desktop amd64 .iso(and others) but have been unable to do a efi install of ubuntu on this system and as this is a new system have ended up just going with bios installer running which at least puts my mind at ease that i have not bricked my new mobo.(had to do a clrcmos and flash to latest bios version) So it possibly could be the bios settings or the bios version being used that is problem. To try and eliminate bios version i can not get to post screen in order to id bios version being used. Pressing tab to show post instead of logo and trying to pausebreak to catch post is proving difficult. If logo screen in bios is disabled just get black screen no post shown and pressing tab does not show post. Appreciate using appropriate bios settings and latest 12.10 release should simply get uefi installer running when selected from the grub list (nice graphic details in Identifying if computer boots the cd in efi mode section at https://help.ubuntu.com/community/UEFI#Identifying_if_the_computer_boots_the_CD_in_EFI_mode) And to confirm the hdd is booting in efi mode https://help.ubuntu.com/community/UEFI#Identifying_if_the_computer_boots_the_HDD_in_EFI_mode running the command [ -d /sys/firmware/efi ] && echo "EFI boot on HDD" || echo "Legacy boot on HDD" gave Legacy boot on HDD This is as expected because i allowed the bios installer (which was 12.04 desktop amd64 after trying 12.10 desktop amd64 in efi mode) to run to get a working installation. Which is not what was intended or wished for but wanted to get a working os to bench test new mobo i.e. prove it is working. There are other options as in installing other bootmanagers/loaders but do not wish to do so as shim should get grub2 going that is after secure boot has been signed.(Now got rough idea what should happen just it aint happening. Is it possible ahci drivers are required?) Will post boot info script url of the updated config/setup. The original question asked seems irrelevant to what is being said in this update but as the problem is not resolved will keep on trying efi installing! i.e the problem is same as when question asked just trying to update. Have tried to edit and update the best i can!

  Read the article

• Better documentation for tasks waiting on resources

  - by SQLOS Team

  The sys.dm_os_waiting_tasks DMV contains a wealth of useful information about tasks waiting on a resource, but until now detailed information about the resource being consumed - sys.dm_os_waiting_tasks.resource_description - hasn't been documented, apart from a rather self-evident "Description of the resource that is being consumed."   Thanks to a recent Connect suggestion this column will get more information added. Here is a summary of the possible values that can appear in this column - Note this information is current for SQL Server 2008 R2 and Denali:   Thread-pool resource owner:•       threadpool id=scheduler<hex-address> Parallel query resource owner:•       exchangeEvent id={Port|Pipe}<hex-address> WaitType=<exchange-wait-type> nodeId=<exchange-node-id> Exchange-wait-type can be one of the following.•       e_waitNone•       e_waitPipeNewRow•       e_waitPipeGetRow•       e_waitSynchronizeConsumerOpen•       e_waitPortOpen•       e_waitPortClose•       e_waitRange Lock resource owner:<type-specific-description> id=lock<lock-hex-address> mode=<mode> associatedObjectId=<associated-obj-id>               <type-specific-description> can be:• For DATABASE: databaselock subresource=<databaselock-subresource> dbid=<db-id>• For FILE: filelock fileid=<file-id> subresource=<filelock-subresource> dbid=<db-id>• For OBJECT: objectlock lockPartition=<lock-partition-id> objid=<obj-id> subresource=<objectlock-subresource> dbid=<db-id>• For PAGE: pagelock fileid=<file-id> pageid=<page-id> dbid=<db-id> subresource=<pagelock-subresource>• For Key: keylock  hobtid=<hobt-id> dbid=<db-id>• For EXTENT: extentlock fileid=<file-id> pageid=<page-id> dbid=<db-id>• For RID: ridlock fileid=<file-id> pageid=<page-id> dbid=<db-id>• For APPLICATION: applicationlock hash=<hash> databasePrincipalId=<role-id> dbid=<db-id>• For METADATA: metadatalock subresource=<metadata-subresource> classid=<metadatalock-description> dbid=<db-id>• For HOBT: hobtlock hobtid=<hobt-id> subresource=<hobt-subresource> dbid=<db-id>• For ALLOCATION_UNIT: allocunitlock hobtid=<hobt-id> subresource=<alloc-unit-subresource> dbid=<db-id> <mode> can be:• Sch-S• Sch-M• S• U• X• IS• IU• IX• SIU• SIX• UIX• BU• RangeS-S• RangeS-U• RangeI-N• RangeI-S• RangeI-U• RangeI-X• RangeX-S• RangeX-U• RangeX-X External resource owner:•       External ExternalResource=<wait-type> Generic resource owner:•       TransactionMutex TransactionInfo Workspace=<workspace-id>•       Mutex•       CLRTaskJoin•       CLRMonitorEvent•       CLRRWLockEvent•       resourceWait Latch resource owner:•       <db-id>:<file-id>:<page-in-file>•       <GUID>•       <latch-class> (<latch-address>)   Further Information Slava Oks's weblog: sys.dm_os_waiting_tasks.Informit.com: Identifying Blocking Using sys.dm_os_waiting_tasks - Ken Henderson   - Guy

  Read the article

• NoSQL Java API for MySQL Cluster: Questions & Answers

  - by Mat Keep

  The MySQL Cluster engineering team recently ran a live webinar, available now on-demand demonstrating the ClusterJ and ClusterJPA NoSQL APIs for MySQL Cluster, and how these can be used in building real-time, high scale Java-based services that require continuous availability. Attendees asked a number of great questions during the webinar, and I thought it would be useful to share those here, so others are also able to learn more about the Java NoSQL APIs. First, a little bit about why we developed these APIs and why they are interesting to Java developers. ClusterJ and Cluster JPA ClusterJ is a Java interface to MySQL Cluster that provides either a static or dynamic domain object model, similar to the data model used by JDO, JPA, and Hibernate. A simple API gives users extremely high performance for common operations: insert, delete, update, and query. ClusterJPA works with ClusterJ to extend functionality, including - Persistent classes - Relationships - Joins in queries - Lazy loading - Table and index creation from object model By eliminating data transformations via SQL, users get lower data access latency and higher throughput. In addition, Java developers have a more natural programming method to directly manage their data, with a complete, feature-rich solution for Object/Relational Mapping. As a result, the development of Java applications is simplified with faster development cycles resulting in accelerated time to market for new services. MySQL Cluster offers multiple NoSQL APIs alongside Java: - Memcached for a persistent, high performance, write-scalable Key/Value store, - HTTP/REST via an Apache module - C++ via the NDB API for the lowest absolute latency. Developers can use SQL as well as NoSQL APIs for access to the same data set via multiple query patterns – from simple Primary Key lookups or inserts to complex cross-shard JOINs using Adaptive Query Localization Marrying NoSQL and SQL access to an ACID-compliant database offers developers a number of benefits. MySQL Cluster’s distributed, shared-nothing architecture with auto-sharding and real time performance makes it a great fit for workloads requiring high volume OLTP. Users also get the added flexibility of being able to run real-time analytics across the same OLTP data set for real-time business insight. OK – hopefully you now have a better idea of why ClusterJ and JPA are available. Now, for the Q&A. Q & A Q. Why would I use Connector/J vs. ClusterJ? A. Partly it's a question of whether you prefer to work with SQL (Connector/J) or objects (ClusterJ). Performance of ClusterJ will be better as there is no need to pass through the MySQL Server. A ClusterJ operation can only act on a single table (e.g. no joins) - ClusterJPA extends that capability Q. Can I mix different APIs (ie ClusterJ, Connector/J) in our application for different query types? A. Yes. You can mix and match all of the API types, SQL, JDBC, ODBC, ClusterJ, Memcached, REST, C++. They all access the exact same data in the data nodes. Update through one API and new data is instantly visible to all of the others. Q. How many TCP connections would a SessionFactory instance create for a cluster of 8 data nodes? A. SessionFactory has a connection to the mgmd (management node) but otherwise is just a vehicle to create Sessions. Without using connection pooling, a SessionFactory will have one connection open with each data node. Using optional connection pooling allows multiple connections from the SessionFactory to increase throughput. Q. Can you give details of how Cluster J optimizes sharding to enhance performance of distributed query processing? A. Each data node in a cluster runs a Transaction Coordinator (TC), which begins and ends the transaction, but also serves as a resource to operate on the result rows. While an API node (such as a ClusterJ process) can send queries to any TC/data node, there are performance gains if the TC is where most of the result data is stored. ClusterJ computes the shard (partition) key to choose the data node where the row resides as the TC. Q. What happens if we perform two primary key lookups within the same transaction? Are they sent to the data node in one transaction? A. ClusterJ will send identical PK lookups to the same data node. Q. How is distributed query processing handled by MySQL Cluster ? A. If the data is split between data nodes then all of the information will be transparently combined and passed back to the application. The session will connect to a data node - typically by hashing the primary key - which then interacts with its neighboring nodes to collect the data needed to fulfil the query. Q. Can I use Foreign Keys with MySQL Cluster A. Support for Foreign Keys is included in the MySQL Cluster 7.3 Early Access release Summary The NoSQL Java APIs are packaged with MySQL Cluster, available for download here so feel free to take them for a spin today! Key Resources MySQL Cluster on-line demo  MySQL ClusterJ and JPA On-demand webinar  MySQL ClusterJ and JPA documentation MySQL ClusterJ and JPA whitepaper and tutorial

  Read the article

• System will not boot without USB thumb drive inserted

  - by agent154

  I've had this issue before when trying out Linux Mint, but I was unable to get any assistance. I was then lead to believe that it was a problem related to Mint, and not grub. I installed Ubuntu 12.04 tonight on a second partition alongside Windows 7. I installed from a USB stick, and everything went peachy until I rebooted without the stick in my tower. It now says: error: no such device: 20cec6ca-4024-4237-84c3-2dba3c851497 grub rescue > I've verified via ls -l /dev/disk/by-uuid that my drive where Ubuntu is installed matches the UUID that supposedly doesn't exist. The UUID of my thumb drive when inserted happens to be 06B3-9C68. There is no mention of my USB drive's UUID anywhere in /boot/grub/grub.cfg I've also tried to re-install GRUB after booting into my system, removing the stick, and running grub-install /dev/sda. It still happens, and I cannot boot without the USB drive inserted into the computer. And what really gets my goat is that the boot order of my system is CDROMHard DriveUSB. It's not even reaching the USB to try to boot from it, so why does it matter that it's not there? Edit: Also, I ran grub-config without the stick in followed by another grub-install. Still no go. FWIW, here's my grub.cfg file: # # DO NOT EDIT THIS FILE # # It is automatically generated by grub-mkconfig using templates # from /etc/grub.d and settings from /etc/default/grub # ### BEGIN /etc/grub.d/00_header ### if [ -s $prefix/grubenv ]; then set have_grubenv=true load_env fi set default="0" if [ "${prev_saved_entry}" ]; then set saved_entry="${prev_saved_entry}" save_env saved_entry set prev_saved_entry= save_env prev_saved_entry set boot_once=true fi function savedefault { if [ -z "${boot_once}" ]; then saved_entry="${chosen}" save_env saved_entry fi } function recordfail { set recordfail=1 if [ -n "${have_grubenv}" ]; then if [ -z "${boot_once}" ]; then save_env recordfail; fi; fi } function load_video { insmod vbe insmod vga insmod video_bochs insmod video_cirrus } insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 if loadfont /usr/share/grub/unicode.pf2 ; then set gfxmode=auto load_video insmod gfxterm insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 set locale_dir=($root)/boot/grub/locale set lang=en_CA insmod gettext fi terminal_output gfxterm if [ "${recordfail}" = 1 ]; then set timeout=-1 else set timeout=10 fi ### END /etc/grub.d/00_header ### ### BEGIN /etc/grub.d/05_debian_theme ### set menu_color_normal=white/black set menu_color_highlight=black/light-gray if background_color 44,0,30; then clear fi ### END /etc/grub.d/05_debian_theme ### ### BEGIN /etc/grub.d/10_linux ### function gfxmode { set gfxpayload="$1" if [ "$1" = "keep" ]; then set vt_handoff=vt.handoff=7 else set vt_handoff= fi } if [ ${recordfail} != 1 ]; then if [ -e ${prefix}/gfxblacklist.txt ]; then if hwmatch ${prefix}/gfxblacklist.txt 3; then if [ ${match} = 0 ]; then set linux_gfx_mode=keep else set linux_gfx_mode=text fi else set linux_gfx_mode=text fi else set linux_gfx_mode=keep fi else set linux_gfx_mode=text fi export linux_gfx_mode if [ "$linux_gfx_mode" != "text" ]; then load_video; fi menuentry 'Ubuntu, with Linux 3.2.0-25-generic-pae' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 linux /boot/vmlinuz-3.2.0-25-generic-pae root=UUID=20cec6ca-4024-4237-84c3-d2ba3c851497 ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-25-generic-pae } menuentry 'Ubuntu, with Linux 3.2.0-25-generic-pae (recovery mode)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 echo 'Loading Linux 3.2.0-25-generic-pae ...' linux /boot/vmlinuz-3.2.0-25-generic-pae root=UUID=20cec6ca-4024-4237-84c3-d2ba3c851497 ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-25-generic-pae } submenu "Previous Linux versions" { menuentry 'Ubuntu, with Linux 3.2.0-23-generic-pae' --class ubuntu --class gnu-linux --class gnu --class os { recordfail gfxmode $linux_gfx_mode insmod gzio insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 linux /boot/vmlinuz-3.2.0-23-generic-pae root=UUID=20cec6ca-4024-4237-84c3-d2ba3c851497 ro quiet splash $vt_handoff initrd /boot/initrd.img-3.2.0-23-generic-pae } menuentry 'Ubuntu, with Linux 3.2.0-23-generic-pae (recovery mode)' --class ubuntu --class gnu-linux --class gnu --class os { recordfail insmod gzio insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 echo 'Loading Linux 3.2.0-23-generic-pae ...' linux /boot/vmlinuz-3.2.0-23-generic-pae root=UUID=20cec6ca-4024-4237-84c3-d2ba3c851497 ro recovery nomodeset echo 'Loading initial ramdisk ...' initrd /boot/initrd.img-3.2.0-23-generic-pae } } ### END /etc/grub.d/10_linux ### ### BEGIN /etc/grub.d/20_linux_xen ### ### END /etc/grub.d/20_linux_xen ### ### BEGIN /etc/grub.d/20_memtest86+ ### menuentry "Memory test (memtest86+)" { insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 linux16 /boot/memtest86+.bin } menuentry "Memory test (memtest86+, serial console 115200)" { insmod part_msdos insmod ext2 set root='(hd1,msdos5)' search --no-floppy --fs-uuid --set=root 20cec6ca-4024-4237-84c3-d2ba3c851497 linux16 /boot/memtest86+.bin console=ttyS0,115200n8 } ### END /etc/grub.d/20_memtest86+ ### ### BEGIN /etc/grub.d/30_os-prober ### menuentry "Windows 7 (loader) (on /dev/sda1)" --class windows --class os { insmod part_msdos insmod ntfs set root='(hd0,msdos1)' search --no-floppy --fs-uuid --set=root 9014706714705268 chainloader +1 } ### END /etc/grub.d/30_os-prober ### ### BEGIN /etc/grub.d/40_custom ### # This file provides an easy way to add custom menu entries. Simply type the # menu entries you want to add after this comment. Be careful not to change # the 'exec tail' line above. ### END /etc/grub.d/40_custom ### ### BEGIN /etc/grub.d/41_custom ### if [ -f $prefix/custom.cfg ]; then source $prefix/custom.cfg; fi ### END /etc/grub.d/41_custom ###

  Read the article

• 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.

  Read the article

• Running a Mongo Replica Set on Azure VM Roles

  - by Elton Stoneman

  Originally posted on: http://geekswithblogs.net/EltonStoneman/archive/2013/10/15/running-a-mongo-replica-set-on-azure-vm-roles.aspxSetting up a MongoDB Replica Set with a bunch of Azure VMs is straightforward stuff. Here’s a step-by-step which gets you from 0 to fully-redundant 3-node document database in about 30 minutes (most of which will be spent waiting for VMs to fire up). First, create yourself 3 VM roles, which is the minimum number of nodes you need for high availability. You can use any OS that Mongo supports. This guide uses Windows but the only difference will be the mechanism for starting the Mongo service when the VM starts (Windows Service, daemon etc.) While the VMs are provisioning, download and install Mongo locally, so you can set up the replica set with the Mongo shell. We’ll create our replica set from scratch, doing one machine at a time (if you have a single node you want to upgrade to a replica set, it’s the same from step 3 onwards): 1. Setup Mongo Log into the first node, download mongo and unzip it to C:. Rename the folder to remove the version – so you have c:\MongoDB\bin etc. – and create a new folder for the logs, c:\MongoDB\logs. 2. Setup your data disk When you initialize a node in a replica set, Mongo pre-allocates a whole chunk of storage to use for data replication. It will use up to 5% of your data disk, so if you use a Windows VM image with a defsault 120Gb disk and host your data on C:, then Mongo will allocate 6Gb for replication. And that takes a while. Instead you can create yourself a new partition by shrinking down the C: drive in Computer Management, by say 10Gb, and then creating a new logical disk for your data from that spare 10Gb, which will be allocated as E:. Create a new folder, e:\data. 3. Start Mongo When that’s done, start a command line, point to the mongo binaries folder, install Mongo as a Windows Service, running in replica set mode, and start the service: cd c:\mongodb\bin mongod -logpath c:\mongodb\logs\mongod.log -dbpath e:\data -replSet TheReplicaSet –install net start mongodb 4. Open the ports Mongo uses port 27017 by default, so you need to allow access in the machine and in Azure. In the VM, open Windows Firewall and create a new inbound rule to allow access via port 27017. Then in the Azure Management Console for the VM role, under the Configure tab add a new rule, again to allow port 27017. 5. Initialise the replica set Start up your local mongo shell, connecting to your Azure VM, and initiate the replica set: c:\mongodb\bin\mongo sc-xyz-db1.cloudapp.net rs.initiate() This is the bit where the new node (at this point the only node) allocates its replication files, so if your data disk is large, this can take a long time (if you’re using the default C: drive with 120Gb, it may take so long that rs.initiate() never responds. If you’re sat waiting more than 20 minutes, start another instance of the mongo shell pointing to the same machine to check on it). Run rs.conf() and you should see one node configured. 6. Fix the host name for the primary – *don’t miss this one* For the first node in the replica set, Mongo on Windows doesn’t populate the full machine name. Run rs.conf() and the name of the primary is sc-xyz-db1, which isn’t accessible to the outside world. The replica set configuration needs the full DNS name of every node, so you need to manually rename it in your shell, which you can do like this: cfg = rs.conf() cfg.members[0].host = ‘sc-xyz-db1.cloudapp.net:27017’ rs.reconfig(cfg) When that returns, rs.conf() will have your full DNS name for the primary, and the other nodes will be able to connect. At this point you have a working database, so you can start adding documents, but there’s no replication yet. 7. Add more nodes For the next two VMs, follow steps 1 through to 4, which will give you a working Mongo database on each node, which you can add to the replica set from the shell with rs.add(), using the full DNS name of the new node and the port you’re using: rs.add(‘sc-xyz-db2.cloudapp.net:27017’) Run rs.status() and you’ll see your new node in STARTUP2 state, which means its initializing and replicating from the PRIMARY. Repeat for your third node: rs.add(‘sc-xyz-db3.cloudapp.net:27017’) When all nodes are finished initializing, you will have a PRIMARY and two SECONDARY nodes showing in rs.status(). Now you have high availability, so you can happily stop db1, and one of the other nodes will become the PRIMARY with no loss of data or service. Note – the process for AWS EC2 is exactly the same, but with one important difference. On the Azure Windows Server 2012 base image, the MongoDB release for 64-bit 2008R2+ works fine, but on the base 2012 AMI that release keeps failing with a UAC permission error. The standard 64-bit release is fine, but it lacks some optimizations that are in the 2008R2+ version.

  Read the article

• How do I install on an UEFI Asus 1215b netbook?

  - by Tarek

  I'm trying to install Ubuntu 11.10 on a UEFI netbook Asus 1215b using an USB stick. I created a fat32 efi partition of 100MB, 2GB swap, and 2 ext4 partitions (for root (/ ) and /home, respectively). While installing, Ubuntu switches to CLI and starts running efibootmgr. After a few commands (sadly I don't have a screen grab), it stops displaying text but it's still running judging by the HDD led. Then, there's a weird graphic glitch and the screen turns off (HDD led still indicating activity). Finally, it just stops, but doesn't turn off. Not even a hard reboot works (holding down the power button a few secs). I have to plug the netbook off and remove the battery. After that, it still doesn't boot Ubuntu... Anyway, what can I do? I'm considering following the footsteps here and here. Edit: here is the syslog $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] BUG: unable to handle kernel paging request at 00000000ffe1867c $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] IP: [<ffff880066d44c1f>] 0xffff880066d44c1e $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] PGD 14ecc067 PUD 0 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Oops: 0000 [#1] SMP $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] CPU 0 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Modules linked in: cryptd aes_x86_64 ufs qnx4 hfsplus hfs minix ntfs msdos xfs reiserfs jfs bnep parport_pc rfcomm dm_crypt ppdev bluetooth lp parport joydev eeepc_wmi asus_wmi sparse_keymap uvcvideo videodev v4l2_compat_ioctl32 snd_hda_codec_realtek snd_seq_midi snd_hda_codec_hdmi snd_hda_intel snd_hda_codec arc4 snd_rawmidi snd_hwdep psmouse snd_pcm snd_seq_midi_event ath9k serio_raw sp5100_tco i2c_piix4 k10temp snd_seq mac80211 snd_timer ath9k_common ath9k_hw snd_seq_device ath snd cfg80211 soundcore snd_page_alloc binfmt_misc squashfs overlayfs nls_iso8859_1 nls_cp437 vfat fat dm_raid45 xor dm_mirror dm_region_hash dm_log btrfs zlib_deflate libcrc32c usb_storage uas radeon video ahci libahci ttm drm_kms_helper drm wmi i2c_algo_bit atl1c $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Pid: 28432, comm: efibootmgr Not tainted 3.0.0-12-generic #20-Ubuntu ASUSTeK Computer INC. 1215B/1215B $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RIP: 0010:[<ffff880066d44c1f>] [<ffff880066d44c1f>] 0xffff880066d44c1e $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RSP: 0018:ffff88005e2cbab0 EFLAGS: 00010082 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RAX: 00000000ffe1867c RBX: 0000000000000009 RCX: 00000000ffe1867c $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RDX: 0000000000000000 RSI: ffff88005e2cbbea RDI: ffff88005e2cbb40 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RBP: 00000000ffe1867c R08: 0000000000000000 R09: 0000000000000084 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] R10: ffffc9001101ff83 R11: ffffc90011018685 R12: 0000000000000001 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] R13: 0000000000000000 R14: ffffc9001101867c R15: ffff88005e2cbbe1 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] FS: 00007f9cdde13720(0000) GS:ffff880066a00000(0000) knlGS:0000000000000000 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] CS: 0010 DS: 0000 ES: 0000 CR0: 0000000080050033 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] CR2: 00000000ffe1867c CR3: 000000002dace000 CR4: 00000000000006f0 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] DR0: 0000000000000000 DR1: 0000000000000000 DR2: 0000000000000000 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] DR3: 0000000000000000 DR6: 00000000ffff0ff0 DR7: 0000000000000400 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Process efibootmgr (pid: 28432, threadinfo ffff88005e2ca000, task ffff880014f0dc80) $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Stack: $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] ffffc90011010000 ffff88005e2cbac8 0000000000010000 ffff880066d4401d $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] 000000000000007c ffff880009e84400 0000000000000090 ffff880066d45738 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] ffffc9001101867c ffff880066d4331c 0000000000000009 ffffc9001101867b $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Call Trace: $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff815e9efe>] ? _raw_spin_lock+0xe/0x20 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff811d9c2d>] ? open+0x10d/0x1b0 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff8116554b>] ? __dentry_open+0x2bb/0x320 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff811d9b20>] ? bin_vma_open+0x70/0x70 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff815e9efe>] ? _raw_spin_lock+0xe/0x20 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff811849ee>] ? vfsmount_lock_local_unlock+0x1e/0x30 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff8104303b>] ? efi_call5+0x4b/0x80 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff81042a7f>] ? virt_efi_set_variable+0x2f/0x40 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff814bb125>] ? efivar_create+0x1e5/0x280 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff811d9d63>] ? write+0x93/0x190 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff811d9de4>] ? write+0x114/0x190 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff81167813>] ? vfs_write+0xb3/0x180 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff81167b3a>] ? sys_write+0x4a/0x90 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] [<ffffffff815f22c2>] ? system_call_fastpath+0x16/0x1b $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] Code: ec 01 75 f0 41 bc 01 00 00 00 e8 e5 fb ff ff e8 e4 fc ff ff 33 c0 44 0f b7 c0 66 3b c3 73 20 41 0f b7 c0 41 0f b7 d0 03 c5 8b c8 <8a> 00 42 38 04 3a 75 0a 66 45 03 c4 66 44 3b c3 72 e2 33 c0 66 $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RIP [<ffff880066d44c1f>] 0xffff880066d44c1e $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] RSP <ffff88005e2cbab0> $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] CR2: 00000000ffe1867c $Oct 21 01:05:17 ubuntu kernel: [ 1220.544009] ---[ end trace 493844b002da4787 ]---

  Read the article

• Planning an Event&ndash;SPS NYC

  - by MOSSLover

  I bet some of you were wondering why I am not going to any events for the most part in June and July (aside from volunteering at SPS Chicago).  Well I basically have no life for the next 2 months.  We are approaching the 11th hour of SharePoint Saturday New York City.  The event is slated to have 350 to 400 attendees.  This is second year in a row I’ve helped run it with Jason Gallicchio.  It’s amazingly crazy how much effort this event requires versus Kansas City.  It’s literally 2x the volume of attendees, speakers, and sponsors plus don’t even get me started about volunteers.  So here is a bit of the break down… We have 30 volunteers+ that Tasha Scott from the Hampton Roads Area will be managing the day of the event to do things like timing the speakers, handing out food, making sure people don’t walk into the event that did not sign up until we get a count for fire code, registering people, watching the sharpees, watching the prizes, making sure attendees get to the right place,  opening and closing the partition in the big room, moving chairs, moving furniture, etc…Then there is Jason, Greg, and I who will be making sure that the speakers, sponsors, and everything is going smoothly in the background.  We need to make sure that everything is setup properly and in the right spot.  We also need to make sure signs are printed, schedules are created, bags are stuffed with sponsor material.  Plus we need to send out emails to sponsors reminding them to send us the right information to post on the site for charity sessions, send us boxes with material to stuff bags, and we need to make sure that Michael Lotter gets there information for invoicing.  We also need to check that Michael has invoiced everyone and who has paid, because we can’t order anything for the event without money.  Once people have paid we need to setup food orders, speaker and volunteer dinners, buy prizes, buy bags, buy speakers/volunteer/organizer shirts, etc…During this process we need all the abstracts from speakers, all the bios, pictures, shirt sizes, and other items so we can create schedules and order items.  We also need to keep track of who is attending the dinner the night before for volunteers and speakers and make sure we don’t hit capacity.  Then there is attendee tracking and making sure that we don’t hit too many attendees.  We need to make sure that attendees know where to go and what to do.  We have to make all kinds of random supply lists during this process and keep on track with a variety of lists and emails plus conference calls.  All in all it’s a lot of work and I am trying to keep track of it all the top so that we don’t duplicate anything or miss anything.  So basically all in all if you don’t see me around for another month don’t worry I do exist. Right now if you look at what I’m doing I am traveling every Monday morning and Thursday night back and forth to Washington DC from New Jersey.  Every night I am working on organizational stuff for SharePoint Saturday New York City.  Every Tuesday night we are running an event conference call.  Every weekend I am either with family or my boyfriend and cat trying hard not to touch the event.  So all my time is pretty much work, event, and family/boyfriend.  I have 0 bandwidth for anything in the community.  If you compound that with my severe allergy problems in DC and a doctor’s appointment every month plus a new med once a week I’m lucky I am still standing and walking.  So basically once July 30th hits hopefully Jason Gallicchio, Greg Hurlman, and myself will be able to breathe a little easier.  If I forget to do this thank you Greg and Jason.  Thank you Tom Daly.  Thank you Michael Lotter.  Thank you Tasha Scott.  Thank you Kevin Griffin.  Thank you all the volunteers, speakers, sponsors, and attendees who will and have made this event a success.  Hopefully, we have enough time until next year to regroup, recharge, and make the event grow bigger in a different venue.  Awesome job everyone we sole out within 3 days of registration and we still have several weeks to go.  Right now the waitlist is at 49 people with room to grow.  If you attend the event thank all these guys I mentioned above for making it possible.  It’s going to be awesome I know it but I probably won’t remember half of it due to the blur of things that we will all be taking care of the day of the event.  Catch you all in the end of July/Early August where I will attempt to post something useful and clever and possibly while wearing a fez. Technorati Tags: SPS NYC,SharePoint Saturday,SharePoint Saturday New York City

  Read the article

• Columnstore Case Study #2: Columnstore faster than SSAS Cube at DevCon Security

  - by aspiringgeek

  Preamble This is the second in a series of posts documenting big wins encountered using columnstore indexes in SQL Server 2012 & 2014.  Many of these can be found in my big deck along with details such as internals, best practices, caveats, etc.  The purpose of sharing the case studies in this context is to provide an easy-to-consume quick-reference alternative. See also Columnstore Case Study #1: MSIT SONAR Aggregations Why Columnstore? As stated previously, If we’re looking for a subset of columns from one or a few rows, given the right indexes, SQL Server can do a superlative job of providing an answer. If we’re asking a question which by design needs to hit lots of rows—DW, reporting, aggregations, grouping, scans, etc., SQL Server has never had a good mechanism—until columnstore. Columnstore indexes were introduced in SQL Server 2012. However, they're still largely unknown. Some adoption blockers existed; yet columnstore was nonetheless a game changer for many apps.  In SQL Server 2014, potential blockers have been largely removed & they're going to profoundly change the way we interact with our data.  The purpose of this series is to share the performance benefits of columnstore & documenting columnstore is a compelling reason to upgrade to SQL Server 2014. The Customer DevCon Security provides home & business security services & has been in business for 135 years. I met DevCon personnel while speaking to the Utah County SQL User Group on 20 February 2012. (Thanks to TJ Belt (b|@tjaybelt) & Ben Miller (b|@DBADuck) for the invitation which serendipitously coincided with the height of ski season.) The App: DevCon Security Reporting: Optimized & Ad Hoc Queries DevCon users interrogate a SQL Server 2012 Analysis Services cube via SSRS. In addition, the SQL Server 2012 relational back end is the target of ad hoc queries; this DW back end is refreshed nightly during a brief maintenance window via conventional table partition switching. SSRS, SSAS, & MDX Conventional relational structures were unable to provide adequate performance for user interaction for the SSRS reports. An SSAS solution was implemented requiring personnel to ramp up technically, including learning enough MDX to satisfy requirements. Ad Hoc Queries Even though the fact table is relatively small—only 22 million rows & 33GB—the table was a typical DW table in terms of its width: 137 columns, any of which could be the target of ad hoc interrogation. As is common in DW reporting scenarios such as this, it is often nearly to optimize for such queries using conventional indexing. DevCon DBAs & developers attended PASS 2012 & were introduced to the marvels of columnstore in a session presented by Klaus Aschenbrenner (b|@Aschenbrenner) The Details Classic vs. columnstore before-&-after metrics are impressive. Scenario Conventional Structures Columnstore ? SSRS via SSAS 10 - 12 seconds 1 second >10x Ad Hoc 5-7 minutes (300 - 420 seconds) 1 - 2 seconds >100x Here are two charts characterizing this data graphically.  The first is a linear representation of Report Duration (in seconds) for Conventional Structures vs. Columnstore Indexes.  As is so often the case when we chart such significant deltas, the linear scale doesn’t expose some the dramatically improved values corresponding to the columnstore metrics.  Just to make it fair here’s the same data represented logarithmically; yet even here the values corresponding to 1 –2 seconds aren’t visible.  The Wins Performance: Even prior to columnstore implementation, at 10 - 12 seconds canned report performance against the SSAS cube was tolerable. Yet the 1 second performance afterward is clearly better. As significant as that is, imagine the user experience re: ad hoc interrogation. The difference between several minutes vs. one or two seconds is a game changer, literally changing the way users interact with their data—no mental context switching, no wondering when the results will appear, no preoccupation with the spinning mind-numbing hurry-up-&-wait indicators.  As we’ve commonly found elsewhere, columnstore indexes here provided performance improvements of one, two, or more orders of magnitude. Simplified Infrastructure: Because in this case a nonclustered columnstore index on a conventional DW table was faster than an Analysis Services cube, the entire SSAS infrastructure was rendered superfluous & was retired. PASS Rocks: Once again, the value of attending PASS is proven out. The trip to Charlotte combined with eager & enquiring minds let directly to this success story. Find out more about the next PASS Summit here, hosted this year in Seattle on November 4 - 7, 2014. DevCon BI Team Lead Nathan Allan provided this unsolicited feedback: “What we found was pretty awesome. It has been a game changer for us in terms of the flexibility we can offer people that would like to get to the data in different ways.” Summary For DW, reports, & other BI workloads, columnstore often provides significant performance enhancements relative to conventional indexing.  I have documented here, the second in a series of reports on columnstore implementations, results from DevCon Security, a live customer production app for which performance increased by factors of from 10x to 100x for all report queries, including canned queries as well as reducing time for results for ad hoc queries from 5 - 7 minutes to 1 - 2 seconds. As a result of columnstore performance, the customer retired their SSAS infrastructure. I invite you to consider leveraging columnstore in your own environment. Let me know if you have any questions.

  Read the article

• ODI 12c - Aggregating Data

  - by David Allan

  This posting will look at the aggregation component that was introduced in ODI 12c. For many ETL tool users this shouldn't be a big surprise, its a little different than ODI 11g but for good reason. You can use this component for composing data with relational like operations such as sum, average and so forth. Also, Oracle SQL supports special functions called Analytic SQL functions, you can use a specially configured aggregation component or the expression component for these now in ODI 12c. In database systems an aggregate transformation is a transformation where the values of multiple rows are grouped together as input on certain criteria to form a single value of more significant meaning - that's exactly the purpose of the aggregate component. In the image below you can see the aggregate component in action within a mapping, for how this and a few other examples are built look at the ODI 12c Aggregation Viewlet here - the viewlet illustrates a simple aggregation being built and then some Oracle analytic SQL such as AVG(EMP.SAL) OVER (PARTITION BY EMP.DEPTNO) built using both the aggregate component and the expression component. In 11g you used to just write the aggregate expression directly on the target, this made life easy for some cases, but it wan't a very obvious gesture plus had other drawbacks with ordering of transformations (agg before join/lookup. after set and so forth) and supporting analytic SQL for example - there are a lot of postings from creative folks working around this in 11g - anything from customizing KMs, to bypassing aggregation analysis in the ODI code generator. The aggregate component has a few interesting aspects. 1. Firstly and foremost it defines the attributes projected from it - ODI automatically will perform the grouping all you do is define the aggregation expressions for those columns aggregated. In 12c you can control this automatic grouping behavior so that you get the code you desire, so you can indicate that an attribute should not be included in the group by, that's what I did in the analytic SQL example using the aggregate component. 2. The component has a few other properties of interest; it has a HAVING clause and a manual group by clause. The HAVING clause includes a predicate used to filter rows resulting from the GROUP BY clause. Because it acts on the results of the GROUP BY clause, aggregation functions can be used in the HAVING clause predicate, in 11g the filter was overloaded and used for both having clause and filter clause, this is no longer the case. If a filter is after an aggregate, it is after the aggregate (not sometimes after, sometimes having).  3. The manual group by clause let's you use special database grouping grammar if you need to. For example Oracle has a wealth of highly specialized grouping capabilities for data warehousing such as the CUBE function. If you want to use specialized functions like that you can manually define the code here. The example below shows the use of a manual group from an example in the Oracle database data warehousing guide where the SUM aggregate function is used along with the CUBE function in the group by clause. The SQL I am trying to generate looks like the following from the data warehousing guide; SELECT channel_desc, calendar_month_desc, countries.country_iso_code,       TO_CHAR(SUM(amount_sold), '9,999,999,999') SALES$ FROM sales, customers, times, channels, countries WHERE sales.time_id=times.time_id AND sales.cust_id=customers.cust_id AND   sales.channel_id= channels.channel_id  AND customers.country_id = countries.country_id  AND channels.channel_desc IN   ('Direct Sales', 'Internet') AND times.calendar_month_desc IN   ('2000-09', '2000-10') AND countries.country_iso_code IN ('GB', 'US') GROUP BY CUBE(channel_desc, calendar_month_desc, countries.country_iso_code); I can capture the source datastores, the filters and joins using ODI's dataset (or as a traditional flow) which enables us to incrementally design the mapping and the aggregate component for the sum and group by as follows; In the above mapping you can see the joins and filters declared in ODI's dataset, allowing you to capture the relationships of the datastores required in an entity-relationship style just like ODI 11g. The mix of ODI's declarative design and the common flow design provides for a familiar design experience. The example below illustrates flow design (basic arbitrary ordering) - a table load where only the employees who have maximum commission are loaded into a target. The maximum commission is retrieved from the bonus datastore and there is a look using employees as the driving table and only those with maximum commission projected. Hopefully this has given you a taster for some of the new capabilities provided by the aggregate component in ODI 12c. In summary, the actions should be much more consistent in behavior and more easily discoverable for users, the use of the components in a flow graph also supports arbitrary designs and the tool (rather than the interface designer) takes care of the realization using ODI's knowledge modules. Interested to know if a deep dive into each component is interesting for folks. Any thoughts? 

  Read the article

• ROracle support for TimesTen In-Memory Database

  - by Sam Drake

  Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

  Read the article

• boot issues - long delay, then "gave up waiting for root device"

  - by chazomaticus

  I've had this issue on and off for about two years now. I noticed it on a new (custom built) machine running 10.04 when that first came out, but then it went away until a few months ago. I've gone through a number of hard drive changes but I can't say specifically what if anything I changed hardware-wise to make it stop or start happening. I had assumed upgrading to a modern Ubuntu version would fix the issue, so I installed 12.04 beta on a spare partition last night, but it's still happening. Here's the issue. After grub loads and I select a kernel to boot, the screen goes blank save for a blinking cursor. It sits in this state for many long minutes before it finally gives up and gives me an initramfs shell with the message gave up waiting for root device (and lists the /dev/disk/by-uuid/... path it was waiting for) but no other specific diagnostic information. Now, here's the tricky part. For one, the problem is intermittent - sometimes it progresses from the blinking cursor to the Ubuntu splash boot screen in a few seconds, and once it gets that far it always continues booting fine. The really bizarre thing is that I can "force" it to "find" the root device by repeatedly pressing the space bar and hitting the machine's power button. If I tap those enough, eventually I will notice the hard drive light coming on, at which point it will always continue the boot process after a few seconds. Interestingly, if I wait slightly too long before pressing the power button (30s?), as soon as I press it I get the gave up waiting message and the initramfs shell. I've tried setting up /etc/fstab (and the grub menu.lst or whatever it's called nowadays) to use device names (e.g. /dev/sda1) instead of UUIDs, but I get the same effect just with the device name, not UUID, in the error message. I should also mention that when I boot to Windows 7, there is no issue. It boots slowly all the time just by virtue of being Windows, but it never hangs indefinitely. This would seem to indicate it's a problem in Ubuntu, not the hardware. It's pretty annoying to have to babysit the computer every time it boots. Any ideas? I'm at a loss. Not even sure how to diagnose the issue. Thanks! EDIT: Here's some dmesg output from 10.04. The 15 second gap is where it was doing nothing. I pressed the power button and space bar a few times, and the stuff at 16 seconds happened. Not sure what any of it means. [ 1.320250] scsi18 : ahci [ 1.320294] scsi19 : ahci [ 1.320320] ata19: SATA max UDMA/133 abar m8192@0xfd4fe000 port 0xfd4fe100 ir q 18 [ 1.320323] ata20: SATA max UDMA/133 abar m8192@0xfd4fe000 port 0xfd4fe180 ir q 18 [ 1.403886] usb 2-4: new high speed USB device using ehci_hcd and address 4 [ 1.562558] usb 2-4: configuration #1 chosen from 1 choice [ 16.477824] ata16: SATA link down (SStatus 0 SControl 300) [ 16.477843] ata19: SATA link down (SStatus 0 SControl 300) [ 16.477857] ata3: SATA link down (SStatus 0 SControl 300) [ 16.477895] ata15: SATA link down (SStatus 0 SControl 300) [ 16.477906] ata20: SATA link down (SStatus 0 SControl 300) [ 16.477977] ata17: SATA link down (SStatus 0 SControl 300) [ 16.478003] ata12: SATA link down (SStatus 0 SControl 300) [ 16.478046] ata13: SATA link down (SStatus 0 SControl 300) [ 16.478063] ata14: SATA link down (SStatus 0 SControl 300) [ 16.478108] ata11: SATA link down (SStatus 0 SControl 300) [ 16.478123] ata18: SATA link up 1.5 Gbps (SStatus 113 SControl 300) [ 16.478127] ata6: SATA link down (SStatus 0 SControl 300) [ 16.478157] ata5: SATA link down (SStatus 0 SControl 300) [ 16.478193] ata18.00: ATAPI: MARVELL VIRTUALL, 1.09, max UDMA/66 After that, it took its sweet time, and I had to keep hitting space bar to coax it along. Here's some more dmesg output from a little later in the boot process: [ 17.982291] input: BTC USB Multimedia Keyboard as /devices/pci0000:00/0000:00 :13.0/usb5/5-2/5-2:1.0/input/input4 [ 17.982335] generic-usb 0003:046E:5506.0002: input,hidraw1: USB HID v1.10 Key board [BTC USB Multimedia Keyboard] on usb-0000:00:13.0-2/input0 [ 18.005211] input: BTC USB Multimedia Keyboard as /devices/pci0000:00/0000:00 :13.0/usb5/5-2/5-2:1.1/input/input5 [ 18.005274] generic-usb 0003:046E:5506.0003: input,hiddev96,hidraw2: USB HID v1.10 Device [BTC USB Multimedia Keyboard] on usb-0000:00:13.0-2/input1 [ 22.484906] EXT4-fs (sda6): INFO: recovery required on readonly filesystem [ 22.484910] EXT4-fs (sda6): write access will be enabled during recovery [ 22.548542] EXT4-fs (sda6): recovery complete [ 22.549074] EXT4-fs (sda6): mounted filesystem with ordered data mode [ 32.516772] Adding 20482832k swap on /dev/sda5. Priority:-1 extents:1 across:20482832k [ 32.742540] udev: starting version 151 [ 33.002004] Bluetooth: Atheros AR30xx firmware driver ver 1.0 [ 33.008135] parport_pc 00:09: reported by Plug and Play ACPI [ 33.008186] parport0: PC-style at 0x378, irq 7 [PCSPP,TRISTATE] [ 33.012076] lp: driver loaded but no devices found [ 33.037271] ppdev: user-space parallel port driver [ 33.090256] lp0: using parport0 (interrupt-driven). Any clues in there?

  Read the article

• ROracle support for TimesTen In-Memory Database

  - by Sherry LaMonica

  Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

  Read the article

• Developing Schema Compare for Oracle (Part 6): 9i Query Performance

  - by Simon Cooper

  All throughout the EAP and beta versions of Schema Compare for Oracle, our main request was support for Oracle 9i. After releasing version 1.0 with support for 10g and 11g, our next step was then to get version 1.1 of SCfO out with support for 9i. However, there were some significant problems that we had to overcome first. This post will concentrate on query execution time. When we first tested SCfO on a 9i server, after accounting for various changes to the data dictionary, we found that database registration was taking a long time. And I mean a looooooong time. The same database that on 10g or 11g would take a couple of minutes to register would be taking upwards of 30 mins on 9i. Obviously, this is not ideal, so a poke around the query execution plans was required. As an example, let's take the table population query - the one that reads ALL_TABLES and joins it with a few other dictionary views to get us back our list of tables. On 10g, this query takes 5.6 seconds. On 9i, it takes 89.47 seconds. The difference in execution plan is even more dramatic - here's the (edited) execution plan on 10g: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 108K| 939 || 1 | SORT ORDER BY | | 108K| 939 || 2 | NESTED LOOPS OUTER | | 108K| 938 ||* 3 | HASH JOIN RIGHT OUTER | | 103K| 762 || 4 | VIEW | ALL_EXTERNAL_LOCATIONS | 2058 | 3 ||* 20 | HASH JOIN RIGHT OUTER | | 73472 | 759 || 21 | VIEW | ALL_EXTERNAL_TABLES | 2097 | 3 ||* 34 | HASH JOIN RIGHT OUTER | | 39920 | 755 || 35 | VIEW | ALL_MVIEWS | 51 | 7 || 58 | NESTED LOOPS OUTER | | 39104 | 748 || 59 | VIEW | ALL_TABLES | 6704 | 668 || 89 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2025 | 5 || 106 | VIEW | ALL_PART_TABLES | 277 | 11 |------------------------------------------------------------------------------- And the same query on 9i: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 16P| 55G|| 1 | SORT ORDER BY | | 16P| 55G|| 2 | NESTED LOOPS OUTER | | 16P| 862M|| 3 | NESTED LOOPS OUTER | | 5251G| 992K|| 4 | NESTED LOOPS OUTER | | 4243M| 2578 || 5 | NESTED LOOPS OUTER | | 2669K| 1440 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 ||* 50 | VIEW PUSHED PREDICATE | ALL_TAB_COMMENTS | 2043 | ||* 66 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_TABLES | 1777K| ||* 80 | VIEW PUSHED PREDICATE | ALL_EXTERNAL_LOCATIONS | 1744K| ||* 96 | VIEW | ALL_PART_TABLES | 852K| |------------------------------------------------------------------------------- Have a look at the cost column. 10g's overall query cost is 939, and 9i is 55,000,000,000 (or more precisely, 55,496,472,769). It's also having to process far more data. What on earth could be causing this huge difference in query cost? After trawling through the '10g New Features' documentation, we found item 1.9.2.21. Before 10g, Oracle advised that you do not collect statistics on data dictionary objects. From 10g, it advised that you do collect statistics on the data dictionary; for our queries, Oracle therefore knows what sort of data is in the dictionary tables, and so can generate an efficient execution plan. On 9i, no statistics are present on the system tables, so Oracle has to use the Rule Based Optimizer, which turns most LEFT JOINs into nested loops. If we force 9i to use hash joins, like 10g, we get a much better plan: -------------------------------------------------------------------------------| Id | Operation | Name | Bytes | Cost |-------------------------------------------------------------------------------| 0 | SELECT STATEMENT | | 7587K| 3704 || 1 | SORT ORDER BY | | 7587K| 3704 ||* 2 | HASH JOIN OUTER | | 7587K| 822 ||* 3 | HASH JOIN OUTER | | 5262K| 616 ||* 4 | HASH JOIN OUTER | | 2980K| 465 ||* 5 | HASH JOIN OUTER | | 710K| 432 ||* 6 | HASH JOIN OUTER | | 398K| 302 || 7 | VIEW | ALL_TABLES | 342K| 276 || 29 | VIEW | ALL_MVIEWS | 51 | 20 || 50 | VIEW | ALL_PART_TABLES | 852K| 104 || 78 | VIEW | ALL_TAB_COMMENTS | 2043 | 14 || 93 | VIEW | ALL_EXTERNAL_LOCATIONS | 1744K| 31 || 106 | VIEW | ALL_EXTERNAL_TABLES | 1777K| 28 |------------------------------------------------------------------------------- That's much more like it. This drops the execution time down to 24 seconds. Not as good as 10g, but still an improvement. There are still several problems with this, however. 10g introduced a new join method - a right outer hash join (used in the first execution plan). The 9i query optimizer doesn't have this option available, so forcing a hash join means it has to hash the ALL_TABLES table, and furthermore re-hash it for every hash join in the execution plan; this could be thousands and thousands of rows. And although forcing hash joins somewhat alleviates this problem on our test systems, there's no guarantee that this will improve the execution time on customers' systems; it may even increase the time it takes (say, if all their tables are partitioned, or they've got a lot of materialized views). Ideally, we would want a solution that provides a speedup whatever the input. To try and get some ideas, we asked some oracle performance specialists to see if they had any ideas or tips. Their recommendation was to add a hidden hook into the product that allowed users to specify their own query hints, or even rewrite the queries entirely. However, we would prefer not to take that approach; as well as a lot of new infrastructure & a rewrite of the population code, it would have meant that any users of 9i would have to spend some time optimizing it to get it working on their system before they could use the product. Another approach was needed. All our population queries have a very specific pattern - a base table provides most of the information we need (ALL_TABLES for tables, or ALL_TAB_COLS for columns) and we do a left join to extra subsidiary tables that fill in gaps (for instance, ALL_PART_TABLES for partition information). All the left joins use the same set of columns to join on (typically the object owner & name), so we could re-use the hash information for each join, rather than re-hashing the same columns for every join. To allow us to do this, along with various other performance improvements that could be done for the specific query pattern we were using, we read all the tables individually and do a hash join on the client. Fortunately, this 'pure' algorithmic problem is the kind that can be very well optimized for expected real-world situations; as well as storing row data we're not using in the hash key on disk, we use very specific memory-efficient data structures to store all the information we need. This allows us to achieve a database population time that is as fast as on 10g, and even (in some situations) slightly faster, and a memory overhead of roughly 150 bytes per row of data in the result set (for schemas with 10,000 tables in that means an extra 1.4MB memory being used during population). Next: fun with the 9i dictionary views.

  Read the article

• IIS7 web farm - local or shared content?

  - by rbeier

  We're setting up an IIS7 web farm with two servers. Should each server have its own local copy of the content, or should they pull content directly from a UNC share? What are the pros and cons of each approach? We currently have a single live server WEB1, with content stored locally on a separate partition. A job periodically syncs WEB1 to a standby server WEB2, using robocopy for content and msdeploy for config. If WEB1 goes down, Nagios notifies us, and we manually run a script to move the IP addresses to WEB2's network interface. Both servers are actually VMs running on separate VMWare ESX 4 hosts. The servers are domain-joined. We have around 50-60 live sites on WEB1 - mostly ASP.NET, with a few that are just static HTML. Most are low-traffic "microsites". A few have moderate traffic, but none are massive. We'd like to change this so both WEB1 and WEB2 are actively serving content. This is mainly for reliability - if WEB1 goes down, we don't want to have to manually intervene to fail things over. Spreading the load is also nice, but the load is not high enough right now for us to need this. We're planning to configure our firewall to balance traffic across the two servers. It will detect when a server goes down and will send all the traffic to the remaining live server. We're planning to use sticky sessions for now... eventually we may move to SQL Server session state and stateless load balancing. But we need a way for the servers to share content. We were originally planning to move all the content to a UNC share. Our storage provider says they can set up a highly available SMB share for us. So if we go the UNC route, the storage shouldn't be a single point of failure. But we're wondering about the downsides to this approach: We'll need to change the physical paths for each site and virtual directory. There are also some projects that have absolute paths in their web.config files - we'll have to update those as well. We'll need to create a domain user for the web servers to access the share, and grant that user appropriate permissions. I haven't looked into this yet - I'm not sure if the application pool identity needs to be changed to this user, or if there's another way to tell IIS to use this account when connecting to the share. Sites will no longer be able to access their content if there's ever an Active Directory problem. In general, it just seems a lot more complicated, with more moving parts that could break. Our storage provider would create a volume for us on their redundant SAN. If I understand correctly, this SAN volume would be mounted on a VM running in their redundant VMWare environment; this VM would then expose the SMB share to our web servers. On the other hand, a benefit of the shared content approach is that we'd only need to deploy code to one place, and there would never be a temporary inconsistency between multiple copies of the content. This thread is pretty interesting, though some of these people are working at a much larger scale. I've just been discussing content so far, but we also need to think about configuration. I don't know if we can just use DFS replication for the applicationHost.config and other files, or if it's best to use the shared configuration feature with the config on a UNC share. What do you think? Thanks for your help, Richard

  Read the article

• Windows 7 Boot to VHD using a VHD clone of the system drive

  - by daveh551

  This seems like a not too difficult problem, and, after several hurdles, I'm maddeningly close. But I can't quite get there. I'm running Windows 7 in development shop. I want to start using VS2010 to work on some stuff that won't be released for awhile. My boss said no beta code on the production machine, but I could run VS2010 for this project IF I could do it in an isolated environment, like a virtual PC. Well, I've used the beta and RC of Win7 on VPC's before, and it was painfully slow because of the VPC environment. But everyone has been singing the praises of Windows 7's boot-to-VHD capability, where only the disk is virtualized, and you're actually running on the hardware. Supposed to be little slower, but nowhere near the speed penalty of VPC. I've spent a fair amount of time getting everything installed the way I want it. So I figured, I'll just clone my system drive using Disk2VHD, and boot off of that, and then install VS2010 onto that. (I keep most of my user data, including all my projects, in a separate partition, so that wouldn't have to be duplicated and would still be available.) Well, I had some difficulties with that, owing mainly to the fact that I was using an old version of Disk2VHD - (get the latest if you're going to try it.) But I did finally get it to boot. (Scott Hanselman has a good blog post on boot to VHD). But it wasn't exactly what I was expecting or hoping for. What I expected was that the VHD would become the C: drive, and the original (physical) C: drive would be either hidden or mounted under a different letter, and thus isolated and protected from any changes. What you actually get is that the VHD becomes the D: drive AND you boot from the D: drive, BUT your original C: drive is still there. Which is sort of okay EXCEPT that the Registry on the VHD is a clone of the Registry on C: drive, and includes many hard-coded references to C:. So the result is that some things come from (and modify) D: (the VHD), but some things come from (and modify) C:. (If you open a cmd prompt and do a SET to look at your environment variables, you will see a mixture of D:\ and C:\ paths.) So I don't really have an isolated environment. Most importantly, %ProgramFiles% is still set to C:\Program Files. What I really need is a tool that can access the registry files on the mounted VHD AS FILES, not as registry entries, and do a global search and replace on all the C:\ in strings to D:. I haven't found such a program. (I've tried to do it with a program called Registry Replace, but, even when running as Administrator, there are certain entries that the Registry won't let you change.) Does anyone know of one? Or any other solution to my problem (other than starting from scratch with a clean VHD and installing Win7 and all my programs on it.)?

  Read the article

• Splitting a raidctl mirror safely

  - by milkfilk

  I have a Sun T5220 server with the onboard LSI card and two disks that were in a RAID 1 mirror. The data is not important right now but we had a failed disk and are trying to understand how to do this for real if we had to recover from a failure. The initial situation looked like this: # raidctl -l c1t0d0 Volume Size Stripe Status Cache RAID Sub Size Level Disk ---------------------------------------------------------------- c1t0d0 136.6G N/A DEGRADED OFF RAID1 0.1.0 136.6G GOOD N/A 136.6G FAILED Green light on the 0.0.0 disk. Find / lights up the 0.1.0 disk. So I know I have a bad drive and which one it is. Server still boots obviously. First, we tried putting a new disk in. This disk came from an unknown source. Format would not see it, cfgadm -al would not see it so raidctl -l would not see it. I figure it's bad. We tried another disk from another spare server: # raidctl -c c1t1d0 c1t0d0 (where t1 is my good disk - 0.1.0) Disk has occupied space. Also the different syntax options don't change anything: # raidctl -C "0.1.0 0.0.0" -r 1 1 Disk has occupied space. # raidctl -C "0.1.0 0.0.0" 1 Disk has occupied space. Ok. Maybe this is because the disk from the spare server had a RAID 1 on it already. Aha, I can see another volume in raidctl: # raidctl -l Controller: 1 Volume:c1t1d0 (this is my server's root mirror) Volume:c1t132d0 (this is the foreign root mirror) Disk: 0.0.0 Disk: 0.1.0 ... No problem. I don't care about the data, I'll just delete the foreign mirror. # raidctl -d c1t132d0 (warning about data deletion but it works) At this point, /usr/bin/ binaries freak out. By that I mean, ls -l /usr/bin/which shows 1.4k but cat /usr/bin/which gives me a newline. Great, I just blew away the binaries (ie: binaries in mem still work)? I bounce the box. It all comes back fine. WTF. Anyway, back to recreating my mirror. # raidctl -l Controller: 1 Volume:c1t1d0 (this is my server's root mirror) Disk: 0.0.0 Disk: 0.1.0 ... Man says that you can delete a mirror and it will split it. Ok, I'll delete the root mirror. # raidctl -d c1t0d0 Array in use. (this might not be the exact error) I googled this and found of course you can't do this (even with -f) while booted off the mirror. Ok. I boot cdrom -s and deleted the volume. Now I have one disk that has a type of "LSI-Logical-Volume" on c1t1d0 (where my data is) and a brand new "Hitachi 146GB" on c1t0d0 (what I'm trying to mirror to): (booted off the CD) # raidctl -c c1t1d0 c1t0d0 (man says it's source destination for mirroring) Illegal Array Layout. # raidctl -C "0.1.0 0.0.0" -r 1 1 (alt syntax per man) Illegal Array Layout. # raidctl -C "0.1.0 0.0.0" 1 (assumes raid1, no help) Illegal Array Layout. Same size disks, same manufacturer but I did delete the volume instead of throwing in a blank disk and waiting for it to resync. Maybe this was a critical error. I tried selecting the type in format for my good disk to be a plain 146gb disk but it resets the partition table which I'm pretty sure would wipe the data (bad if this was production). Am I boned? Anyone have experience with breaking and resyncing a mirror? There's nothing on Google about "Illegal Array Layout" so here's my contrib to the search gods.

  Read the article

• Determining cause of high NFS/IO utilization without iotop

  - by Matt

  I have a server that is doing an NFSv4 export for user's home directories. There are roughly 25 users (mostly developers/analysts) and about 40 servers mounting the home directory export. Performance is miserable, with users often seeing multi-second lags for simple commands (like ls, or writing a small text file). Sometimes the home directory mount completely hangs for minutes, with users getting "permission denied" errors. The hardware is a Dell R510 with dual E5620 CPUs and 8 GB RAM. There are eight 15k 2.5” 600 GB drives (Seagate ST3600057SS) configured in hardware RAID-6 with a single hot spare. RAID controller is a Dell PERC H700 w/512MB cache (Linux sees this as a LSI MegaSAS 9260). OS is CentOS 5.6, home directory partition is ext3, with options “rw,data=journal,usrquota”. I have the HW RAID configured to present two virtual disks to the OS: /dev/sda for the OS (boot, root and swap partitions), and /dev/sdb for the home directories. What I find curious, and suspicious, is that the sda device often has very high utilization, even though it only contains the OS. I would expect this virtual drive to be idle almost all the time. The system is not swapping, according to "free" and "vmstat". Why would there be major load on this device? Here is a 30-second snapshot from iostat: Time: 09:37:28 AM Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 44.09 0.03 107.76 0.13 607.40 11.27 0.89 8.27 7.27 78.35 sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.00 44.09 0.03 107.76 0.13 607.40 11.27 0.89 8.27 7.27 78.35 sdb 0.00 2616.53 0.67 157.88 2.80 11098.83 140.04 8.57 54.08 4.21 66.68 sdb1 0.00 2616.53 0.67 157.88 2.80 11098.83 140.04 8.57 54.08 4.21 66.68 dm-0 0.00 0.00 0.03 151.82 0.13 607.26 8.00 1.25 8.23 5.16 78.35 dm-1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-2 0.00 0.00 0.67 2774.84 2.80 11099.37 8.00 474.30 170.89 0.24 66.84 dm-3 0.00 0.00 0.67 2774.84 2.80 11099.37 8.00 474.30 170.89 0.24 66.84 Looks like iotop is the ideal tool to use to sniff out these kinds of issues. But I'm on CentOS 5.6, which doesn't have a new enough kernel to support that program. I looked at Determining which process is causing heavy disk I/O?, and besides iotop, one of the suggestions said to do a "echo 1 /proc/sys/vm/block_dump". I did that (after directing kernel messages to tempfs). In about 13 minutes I had about 700k reads or writes, roughly half from kjournald and the other half from nfsd: # egrep " kernel: .*(READ|WRITE)" messages | wc -l 768439 # egrep " kernel: kjournald.*(READ|WRITE)" messages | wc -l 403615 # egrep " kernel: nfsd.*(READ|WRITE)" messages | wc -l 314028 For what it's worth, for the last hour, utilization has constantly been over 90% for the home directory drive. My 30-second iostat keeps showing output like this: Time: 09:36:30 PM Device: rrqm/s wrqm/s r/s w/s rkB/s wkB/s avgrq-sz avgqu-sz await svctm %util sda 0.00 6.46 0.20 11.33 0.80 71.71 12.58 0.24 20.53 14.37 16.56 sda1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 sda2 0.00 6.46 0.20 11.33 0.80 71.71 12.58 0.24 20.53 14.37 16.56 sdb 137.29 7.00 549.92 3.80 22817.19 43.19 82.57 3.02 5.45 1.74 96.32 sdb1 137.29 7.00 549.92 3.80 22817.19 43.19 82.57 3.02 5.45 1.74 96.32 dm-0 0.00 0.00 0.20 17.76 0.80 71.04 8.00 0.38 21.21 9.22 16.57 dm-1 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 dm-2 0.00 0.00 687.47 10.80 22817.19 43.19 65.48 4.62 6.61 1.43 99.81 dm-3 0.00 0.00 687.47 10.80 22817.19 43.19 65.48 4.62 6.61 1.43 99.82

  Read the article

• Windows 7 .NET 3.5.1 - 2.0 Slightly Corrupted, How to Repair?

  - by Quinxy von Besiex

  My Windows 7 included .NET installation (3.5 to 2.0) appears very slightly and particularly corrupted and I am trying to fix it without reinstalling Windows or trying to revert to backups. Everything was working and then my hard drive started corrupting a few files and checkdisk found bad clusters so I imaged the drive to a new one. As soon as I booted on the new drive everything worked except programs which call the System.Net.NetworkInformation methods within .NET 3.5 to 2.0 (like Ping() and IsNetworkAvailable()), which immediately crash the app in which the calls are (those calls in .NET 4.0 works fine). Those methods are found inside System.dll, and I assume call native methods which I believe are inside winnsi.dll or iphlpapi.dll or something else (I've not found this yet); I assume it calls native methods because the exception which causes the crash is Fatal Execution Engine Error which people mention is usually related to calling native methods and marshaling data between them. A huge clue about the culprit is likely found in the fact that when I launch the exact same crashing application through a code profiler (which executes the exe and captures stats on which methods took the longest) the app works fine, no crash at all! How could running it within the profiler work and running it outside not work? That seems the key to the mystery. I've used procmon to catch all the registry, filesystem, and network events from the crashing execution and the profiler-run successful execution and compared the two outputs but didn't learn much (I see the moment at which the non-profiled app crashes, but up until then they behave the same, loaded the same modules, ). The only big difference seems to be that at the moment before the app crash the profiler-executed code creates 4-6 new threads and the directly executed code only creates 1-2. I have diffed the files/directories which seemed most relevant (the .NET stuff under Windows and Program Files) pre- and post- disk trouble and seen no changes where I didn't expect any (no obvious file corruption). I have diffed the software and system registry hives pre- and post- disk trouble and seen no changes which seemed relevant. I have created a new user account and cleaned up any environment variables in case environment was related. No change. I did "sfc /scannow" and it found no integrity problems. I tried "ngen update" to regenerate pre-compiled code in case I missed something that might be damaged and nothing changed. I assume I need to repair my .NET installation but because Windows 7 included .NET 3.5 - 2.0 you can't just re-run a .NET installer to redo it. I do not have access to the Windows disks to try to re-install Windows over itself (the computer has a recovery partition but it is unusable); also the drive uses a whole-disk encryption solution and re-installing would be difficult. I absolutely do not want to start from scratch here and install a fresh Windows, reinstall dozens of software packages, try and remember dozens of development-related customizations/etc. Given all that... does anyone have any helpful advice? I need .NET 3.5 - 2.0 working as I am a developer and need to build and test against it. Thanks! Quinxy

  Read the article

< Previous Page | 166 167 168 169 170 171 172 173 174  | Next Page >