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• SQL SERVER – Select the Most Optimal Backup Methods for Server

  - by pinaldave

  Backup and Restore are very interesting concepts and one should be very much with the concept if you are dealing with production database. One never knows when a natural disaster or user error will surface and the first thing everybody wants is to get back on point in time when things were all fine. Well, in this article I have attempted to answer a few of the common questions related to Backup methodology. How to Select a SQL Server Backup Type In order to select a proper SQL Server backup type, a SQL Server administrator needs to understand the difference between the major backup types clearly. Since a picture is worth a thousand words, let me offer it to you below. Select a Recovery Model First The very first question that you should ask yourself is: Can I afford to lose at least a little (15 min, 1 hour, 1 day) worth of data? Resist the temptation to save it all as it comes with the overhead – majority of businesses outside finances can actually afford to lose a bit of data. If your answer is YES, I can afford to lose some data – select a SIMPLE (default) recovery model in the properties of your database, otherwise you need to select a FULL recovery model. The additional advantage of the Full recovery model is that it allows you to restore the data to a specific point in time vs to only last backup time in the Simple recovery model, but it exceeds the scope of this article Backups in SIMPLE Recovery Model In SIMPLE recovery model you can select to do just Full backups or Full + Differential. Full Backup This is the simplest type of backup that contains all information needed to restore the database and should be your first choice. It is often sufficient for small databases, but note that it makes a big impact on the performance of your database Full + Differential Backup After Full, Differential backup picks up all of the changes since the last Full backup. This means if you made Full, Diff, Diff backup – the last Diff backup contains all of the changes and you don’t need the previous Differential backup. Differential backup is obviously smaller and carries less performance overhead Backups in FULL Recovery Model In FULL recovery model you can select Full + Transaction Log or Full + Differential + Transaction Log backup. You have to create Transaction Log backup, because at that time the log is being truncated. Otherwise your Transaction Log will grow uncontrollably. Full + Transaction Log Backup You would always need to perform a Full backup first. Then a series of Transaction log backup. Note that (in contrast to Differential) you need ALL transactions to log since the last Full of Diff backup to properly restore. Transaction log backups have the smallest performance overhead and can be performed often. Full + Differential + Transaction Log Backup If you want to ease the performance overhead on your server, you can replace some of the Full backup in the previous scenario with Differential. You restore scenario would start from Full, then the Last Differential, then all of the remaining transactions log backups Typical backup Scenarios You may say “Well, it is all nice – give me the examples now”. As you may already know, my favorite SQL backup software is SQLBackupAndFTP. If you go to Advanced Backup Schedule form in this program and click “Load a typical backup plan…” link, it will give you these scenarios that I think are quite common – see the image below. The Simplest Way to Schedule SQL Backups I hate to repeat myself, but backup scheduling in SQL agent leaves a lot to be desired. I do not know the simple way to schedule your SQL server backups than in SQLBackupAndFTP – see the image below. The whole backup scheduling with compression, encryption and upload to a Network Folder / HDD / NAS Drive / FTP / Dropbox / Google Drive / Amazon S3 takes just a few minutes – see my previous post for the review. Final Words This post offered an explanation for major backup types only. For more complicated scenarios or to research other options as usually go to MSDN. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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• Tuning Red Gate: #1 of Many

  - by Grant Fritchey

  Everyone runs into performance issues at some point. Same thing goes for Red Gate software. Some of our internal systems were running into some serious bottlenecks. It just so happens that we have this nice little SQL Server monitoring tool. What if I were to, oh, I don't know, use the monitoring tool to identify the bottlenecks, figure out the causes and then apply a fix (where possible) and then start the whole thing all over again? Just a crazy thought. OK, I was asked to. This is my first time looking through these servers, so here's how I'd go about using SQL Monitor to get a quick health check, sort of like checking the vitals on a patient. First time opening up our internal SQL Monitor instance and I was greeted with this: Oh my. Maybe I need to get our internal guys to read my blog. Anyway, I know that there are two servers where most of the load is. I'll drill down on the first. I'm selecting the server, not the instance, by clicking on the server name. That opens up the Global Overview page for the server. The information here much more applicable to the "oh my gosh, I have a problem now" type of monitoring. But, looking at this, I am seeing something immediately. There are four(4) drives on the system. The C:\ has an average read time of 16.9ms, more than double the others. Is that a problem? Not sure, but it's something I'll look at. It's write time is higher too. I'll keep drilling down, first, to the unclosed alerts on the server. Now things get interesting. SQL Monitor has a number of different types of alerts, some related to error states, others to service status, and then some related to performance. Guess what I'm seeing a bunch of right here: Long running queries and long job durations. If you check the dates, they're all recent, within the last 24 hours. If they had just been old, uncleared alerts, I wouldn't be that concerned. But with all these, all performance related, and all in the last 24 hours, yeah, I'm concerned. At this point, I could just start responding to the Alerts. If I click on one of the the Long-running query alerts, I'll get all kinds of cool data that can help me determine why the query ran long. But, I'm not in a reactive mode here yet. I'm still gathering data, trying to understand how the server works. I have the information that we're generating a lot of performance alerts, let's sock that away for the moment. Instead, I'm going to back up and look at the Global Overview for the SQL Instance. It shows all the databases on the server and their status. Then it shows a number of basic metrics about the SQL Server instance, again for that "what's happening now" view or things. Then, down at the bottom, there is the Top 10 expensive queries list: This is great stuff. And no, not because I can see the top queries for the last 5 minutes, but because I can adjust that out 3 days. Now I can see where some serious pain is occurring over the last few days. Databases have been blocked out to protect the guilty. That's it for the moment. I have enough knowledge of what's going on in the system that I can start to try to figure out why the system is running slowly. But, I want to look a little more at some historical data, to understand better how this server is behaving. More next time.

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• Expanding the Partner Ecosystem with Third-Party Plug-ins

  - by Joe Diemer

  Oracle Enterprise Manager’s extensibility capabilities are designed to allow customers and partners to adapt Enterprise Manager for management of heterogeneous environments with Plug-ins and Connectors.  Third-party developers continue to take advantage of Oracle Enterprise Manager’s Extensibility Development Kit (EDK) to build plug-ins to Enterprise Manager 12c, such as F5’s BIG IP Plug-in and Entuity’s Eye of the Storm Network Management Plug-In.  Partners can also validate their plug-ins through the Oracle Validated Integration (OVI) program, which assures customers that the plug-in has been tested and is functionally and technically sound, is designed in a reliable and standardized manner, and operates and performs as documented.   Two very recent examples of partners which have beta versions of their plug-ins are Blue Medora's VMware vSphere plug-in and the NetApp Storage plug-in.  VMware vSphere Plug-in by Blue Medora Blue Medora, an Oracle Partner Network (OPN) “Gold” member, which just announced that it is now signing up customers to try a beta version of their new VMware vSphere plug-in for Enterprise Manager 12c.  According to Blue Medora, the vSphere plug-in monitors critical VMware metrics (CPU, Memory, Disk, Network, etc) at the Host, VM, Cluster and Resource Pool levels.  It has minimal performance impact via an “agentless” approach that requires no installation directly on VMware servers.  It has discovery capabilities for VMware Datacenters, ESX Hosts, Clusters, Virtual Machines, and Datastores.  It offers integration of native VMware Events into Enterprise Manager, and it provides over 300 VMware-related health, availability, performance, and configuration metrics.  It comes with more than 30 out-of-the-box pre-defined thresholds and can manage VMware via a series of jobs split between cluster, host and VM target types.The company reports that the Enterprise Manager 12c plug-in supports vSphere versions 4.0, 4.5 and 5.0.  Platforms supported include Linux 64-bit, Windows, AIX and Solaris SPARC and x86.  Information about the plug-in, including how to sign up for the beta, is available at their web site at http://bluemedora.com after selecting the "Products" tab. NetApp Storage Plug-in NetApp believes the combination of storage system monitoring with comprehensive management of Oracle systems with Enterprise Manager will help customers reduce the cost and complexity of managing applications that rely on NetApp storage and Oracle technologies.  So, NetApp built a plug-in and reports that it has comprehensive availability and performance information for NetApp storage systems.  Using the plug-in, Oracle Enterprise Manager customers with NetApp storage solutions can track the association between databases and storage components and thereby respond to faults and IO performance bottlenecks quickly. With the latest configuration management capabilities, one can also perform drift analysis to make sure all storage systems are configured as per established gold standards. The company is also now signing up beta customers, which can be done at the NetApp Communities site at https://communities.netapp.com/groups/netapp-storage-system-plug-in-for-oem12c-beta. Learn More about Enterprise Manager Extensibility More plug-ins from other partners are soon to come, which I'll be reporting on them here.  To learn more about Enterprise Manager and how customers and partners can build plug-ins using the EDK to manage a multi-vendor data center, go to http://oracle.com/enterprisemanager in the Heterogeneous Management solution area.  The site also lists the plug-ins available with information on how to obtain them.  More info about the Oracle Validated Integration program can be found at the OPN Enterprise Manager Knowledge Zone in the "Develop" tab.

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• Exalytics and Oracle Business Intelligence Enterprise Edition (OBIEE) Partner Workshop

  - by mseika

  Workshop Description Oracle Fusion Middleware 11g is the #1 application infrastructure foundation. It enables enterprises to create and run agile and intelligent business applications and maximize IT efficiency by exploiting modern hardware and software architectures. Oracle Exalytics Business Intelligence Machine is the world’s first engineered system specifically designed to deliver high performance analysis, modeling and planning. Built using industry-standard hardware, market-leading business intelligence software and in-memory database technology, Oracle Exalytics is an optimized system that delivers unmatched speed, visualizations and scalability for Business Intelligence and Enterprise Performance Management applications. This FREE hands-on, partner workshop highlights both the hardware and software components that are engineered to work together to deliver Oracle Exalytics - an optimized version of the industry-leading Oracle TimesTen In-Memory Database with analytic extensions, a highly scalable Oracle server designed specifically for in-memory business intelligence, and Oracle’s proven Business Intelligence Foundation with enhanced visualization capabilities and performance optimizations. This workshop will provide hands-on experience with Oracle's latest engineered system. Topics covered will include TimesTen In-Memory Database and the new Summary Advisor for Exalytics, the technical details (including mobile features) of the latest release of visualization enhancements for OBI-EE, and technical updates on Essbase. After taking this course, you will be well prepared to architect, build, demo, and implement an end-to-end Exalytics solution. You will also be able to extend your current analytical and enterprise performance management application implementations with numerous Oracle technologies specifically enhanced to take advantage of the compute capacity and in-memory capabilities of Oracle Exalytics.If you are a BI or Data Warehouse Architect, developer or consultant, you don’t want to miss this 3-day workshop. Register Now! Presentations Exalytics Architectural Overview Upgrade and Lifecycle Management Times Ten for Exalytics Summary Advisor Utility Essbase and EPM System on Exalytics Dashboard and Analysis Interactions OBIEE 11.1.1.6 Features and Advanced Topics Lab OutlineThe labs showcase Oracle Exalytics core components and functionality and provide expertise of Oracle Business Intelligence 11.1.1.6 new features and updates from prior releases. The hands-on activities are based on an Oracle VirtualBox image with software and training samples pre-installed. Lab Environment Setup Creating and Working with Oracle TimesTen In-Memory Database Running Summary Advisor Utility Working with Exalytics Visualization Features – Dashboard and Analysis Interactions Audience Oracle Partners BI and EPM Application Developers and Implementers System Integrators and Solution Consultants Data Warehouse Developers Enterprise Architects Prerequisites Experience and understanding of OBIEE 11g is required Previous attendance of Oracle Business Intelligence Foundation Suite Workshop or BIEE 11gIntroduction Workshop is highly recommended Good understanding of data warehousing and data modeling for reporting and analysis purpose Strong experience with database technologies preferred Equipment RequirementsThis workshop requires attendees to provide their own laptops for this class.Attendee laptops must meet the following minimum hardware/software requirements: Hardware Minimum 8GB RAM 60 GB free space (includes staging) USB 2.0 port (at least one available) It is strongly recommended that you bring a mouse. You will be working in a development environment and using the mouse heavily. Software One of the following operating systems: 64-bit Windows host/laptop OS 64-bit host/laptop OS with a Windows VM (XP, Server, or Win 7, BIC2g, etc.) Internet Explorer 7.x/8.x or Firefox 3.5.x WINRAR or 7ziputility to unzip workshop files: Download-able from http://www.win-rar.com/download.html Download-able from http://www.7zip.com/ Oracle VirtualBox 4.0.2 or higher Downloadable from http://www.virtualbox.org/wiki/Downloads CPU virtualization mode needs to be enabled. We will provide guidance on the day of the workshop. Attendees will be given a VirtualBox image containing a pre-installed Oracle Exalytics environment. Schedule This workshop is 3 days. - Times vary by country!9:00am: Sign-in and technical setup 9:30am: Workshop starts 5:00pm: Workshop ends Oracle Exalytics and Business Intelligence (OBIEE) Workshop December 11-13, 2012: Oracle BVP, Birmingham, UK Register Here. Questions? Send email to: [email protected] Oracle Platform Technologies Enablement Services

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• SQL Constraints &ndash; CHECK and NOCHECK

  - by David Turner

  One performance issue i faced at a recent project was with the way that our constraints were being managed, we were using Subsonic as our ORM, and it has a useful tool for generating your ORM code called SubStage – once configured, you can regenerate your DAL code easily based on your database schema, and it can even be integrated into your build as a pre-build event if you want to do this.  SubStage also offers the useful feature of being able to generate DDL scripts for your entire database, and can script your data for you too. The problem came when we decided to use the generate scripts feature to migrate the database onto a test database instance – it turns out that the DDL scripts that it generates include the WITH NOCHECK option, so when we executed them on the test instance, and performed some testing, we found that performance wasn’t as expected. A constraint can be disabled, enabled but not trusted, or enabled and trusted.  When it is disabled, data can be inserted that violates the constraint because it is not being enforced, this is useful for bulk load scenarios where performance is important.  So what does it mean to say that a constraint is trusted or not trusted?  Well this refers to the SQL Server Query Optimizer, and whether it trusts that the constraint is valid.  If it trusts the constraint then it doesn’t check it is valid when executing a query, so the query can be executed much faster. Here is an example base in this article on TechNet, here we create two tables with a Foreign Key constraint between them, and add a single row to each.  We then query the tables: 1 DROP TABLE t2 2 DROP TABLE t1 3 GO 4 5 CREATE TABLE t1(col1 int NOT NULL PRIMARY KEY) 6 CREATE TABLE t2(col1 int NOT NULL) 7 8 ALTER TABLE t2 WITH CHECK ADD CONSTRAINT fk_t2_t1 FOREIGN KEY(col1) 9 REFERENCES t1(col1) 10 11 INSERT INTO t1 VALUES(1) 12 INSERT INTO t2 VALUES(1) 13 GO14 15 SELECT COUNT(*) FROM t2 16 WHERE EXISTS17 (SELECT *18 FROM t1 19 WHERE t1.col1 = t2.col1) This all works fine, and in this scenario the constraint is enabled and trusted.  We can verify this by executing the following SQL to query the ‘is_disabled’ and ‘is_not_trusted’ properties: 1 select name, is_disabled, is_not_trusted from sys.foreign_keys This gives the following result: We can disable the constraint using this SQL: 1 alter table t2 NOCHECK CONSTRAINT fk_t2_t1 And when we query the constraints again, we see that the constraint is disabled and not trusted: So the constraint won’t be enforced and we can insert data into the table t2 that doesn’t match the data in t1, but we don’t want to do this, so we can enable the constraint again using this SQL: 1 alter table t2 CHECK CONSTRAINT fk_t2_t1 But when we query the constraints again, we see that the constraint is enabled, but it is still not trusted: This means that the optimizer will check the constraint each time a query is executed over it, which will impact the performance of the query, and this is definitely not what we want, so we need to make the constraint trusted by the optimizer again.  First we should check that our constraints haven’t been violated, which we can do by running DBCC: 1 DBCC CHECKCONSTRAINTS (t2) Hopefully you see the following message indicating that DBCC completed without finding any violations of your constraint: Having verified that the constraint was not violated while it was disabled, we can simply execute the following SQL:   1 alter table t2 WITH CHECK CHECK CONSTRAINT fk_t2_t1 At first glance this looks like it must be a typo to have the keyword CHECK repeated twice in succession, but it is the correct syntax and when we query the constraints properties, we find that it is now trusted again: To fix our specific problem, we created a script that checked all constraints on our tables, using the following syntax: 1 ALTER TABLE t2 WITH CHECK CHECK CONSTRAINT ALL

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• VirtualBox 3.2 is released! A Red Letter Day?

  - by Fat Bloke

  Big news today! A new release of VirtualBox packed full of innovation and improvements. Over the next few weeks we'll take a closer look at some of these new features in a lot more depth, but today we'll whet your appetite with the headline descriptions. To start with, we should point out that this is the first Oracle-branded version which makes today a real Red-letter day ;-)  Oracle VM VirtualBox 3.2 Version 3.2 moves VirtualBox forward in 3 main areas ( handily, all beginning with "P" ) : performance, power and supported guest operating system platforms.  Let's take a look: Performance New Latest Intel hardware support - Harnessing the latest in chip-level support for virtualization, VirtualBox 3.2 supports new Intel Core i5 and i7 processor and Intel Xeon processor 5600 Series support for Unrestricted Guest Execution bringing faster boot times for everything from Windows to Solaris guests; New Large Page support - Reducing the size and overhead of key system resources, Large Page support delivers increased performance by enabling faster lookups and shorter table creation times. New In-hypervisor Networking - Significant optimization of the networking subsystem has reduced context switching between guests and host, increasing network throughput by up to 25%. New New Storage I/O subsystem - VirtualBox 3.2 offers a completely re-worked virtual disk subsystem which utilizes asynchronous I/O to achieve high-performance whilst maintaining high data integrity; New Remote Video Acceleration - The unique built-in VirtualBox Remote Display Protocol (VRDP), which is primarily used in virtual desktop infrastructure deployments, has been enhanced to deliver video acceleration. This delivers a rich user experience coupled with reduced computational expense, which is vital when servers are running hundreds of virtual machines; Power New Page Fusion - Traditional Page Sharing techniques have suffered from long and expensive cache construction as pages are scrutinized as candidates for de-duplication. Taking a smarter approach, VirtualBox Page Fusion uses intelligence in the guest virtual machine to determine much more rapidly and accurately those pages which can be eliminated thereby increasing the capacity or vm density of the system; New Memory Ballooning- Ballooning provides another method to increase vm density by allowing the memory of one guest to be recouped and made available to others; New Multiple Virtual Monitors - VirtualBox 3.2 now supports multi-headed virtual machines with up to 8 virtual monitors attached to a guest. Each virtual monitor can be a host window, or be mapped to the hosts physical monitors; New Hot-plug CPU's - Modern operating systems such Windows Server 2008 x64 Data Center Edition or the latest Linux server platforms allow CPUs to be dynamically inserted into a system to provide incremental computing power while the system is running. Version 3.2 introduces support for Hot-plug vCPUs, allowing VirtualBox virtual machines to be given more power, with zero-downtime of the guest; New Virtual SAS Controller - VirtualBox 3.2 now offers a virtual SAS controller, enabling it to run the most demanding of high-end guests; New Online Snapshot Merging - Snapshots are powerful but can eat up disk space and need to be pruned from time to time. Historically, machines have needed to be turned off to delete or merge snapshots but with VirtualBox 3.2 this operation can be done whilst the machines are running. This allows sophisticated system management with minimal interruption of operations; New OVF Enhancements - VirtualBox has supported the OVF standard for virtual machine portability for some time. Now with 3.2, VirtualBox specific configuration data is also stored in the standard allowing richer virtual machine definitions without compromising portability; New Guest Automation - The Guest Automation APIs allow host-based logic to drive operations in the guest; Platforms New USB Keyboard and Mouse - Support more guests that require USB input devices; New Oracle Enterprise Linux 5.5 - Support for the latest version of Oracle's flagship Linux platform; New Ubuntu 10.04 ("Lucid Lynx") - Support for both the desktop and server version of the popular Ubuntu Linux distribution; And as a man once said, "just one more thing" ... New Mac OS X (experimental) - On Apple hardware only, support for creating virtual machines run Mac OS X. All in all this is a pretty powerful release packed full of innovation and speedups. So what are you waiting for?  -FB 

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• How Do You Actually Model Data?

  Since the 1970’s Developers, Analysts and DBAs have been able to represent concepts and relations in the form of data through the use of generic symbols.  But what is data modeling?  The first time I actually heard this term I could not understand why anyone would want to display a computer on a fashion show runway. Hey, what do you expect? At that time I was a freshman in community college, and obviously this was a long time ago.  I have since had the chance to learn what data modeling truly is through using it. Data modeling is a process of breaking down information and/or requirements in to common categories called objects. Once objects start being defined then relationships start to form based on dependencies found amongst other existing objects.  Currently, there are several tools on the market that help data designer actually map out objects and their relationships through the use of symbols and lines.  These diagrams allow for designs to be review from several perspectives so that designers can ensure that they have the optimal data design for their project and that the design is flexible enough to allow for potential changes and/or extension in the future. Additionally these basic models can always be further refined to show different levels of details depending on the target audience through the use of three different types of models. Conceptual Data Model(CDM)Conceptual Data Models include all key entities and relationships giving a viewer a high level understanding of attributes. Conceptual data model are created by gathering and analyzing information from various sources pertaining to a project during the typical planning phase of a project. Logical Data Model (LDM)Logical Data Models are conceptual data models that have been expanded to include implementation details pertaining to the data that it will store. Additionally, this model typically represents an origination’s business requirements and business rules by defining various attribute data types and relationships regarding each entity. This additional information can be directly translated to the Physical Data Model which reduces the actual time need to implement it. Physical Data Model(PDMs)Physical Data Model are transformed Logical Data Models that include the necessary tables, columns, relationships, database properties for the creation of a database. This model also allows for considerations regarding performance, indexing and denormalization that are applied through database rules, data integrity. Further expanding on why we actually use models in modern application/database development can be seen in the benefits that data modeling provides for data modelers and projects themselves, Benefits of Data Modeling according to Applied Information Science Abstraction that allows data designers remove concepts and ideas form hard facts in the form of data. This gives the data designers the ability to express general concepts and/or ideas in a generic form through the use of symbols to represent data items and the relationships between the items. Transparency through the use of data models allows complex ideas to be translated in to simple symbols so that the concept can be understood by all viewpoints and limits the amount of confusion and misunderstanding. Effectiveness in regards to tuning a model for acceptable performance while maintaining affordable operational costs. In addition it allows systems to be built on a solid foundation in terms of data. I shudder at the thought of a world without data modeling, think about it? Data is everywhere in our lives. Data modeling allows for optimizing a design for performance and the reduction of duplication. If one was to design a database without data modeling then I would think that the first things to get impacted would be database performance due to poorly designed database and there would be greater chances of unnecessary data duplication that would also play in to the excessive query times because unneeded records would need to be processed. You could say that a data designer designing a database is like a box of chocolates. You will never know what kind of database you will get until after it is built.

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• Best Practices - Core allocation

  - by jsavit

  This post is one of a series of "best practices" notes for Oracle VM Server for SPARC (also called Logical Domains) Introduction SPARC T-series servers currently have up to 4 CPU sockets, each of which has up to 8 or (on SPARC T3) 16 CPU cores, while each CPU core has 8 threads, for a maximum of 512 dispatchable CPUs. The defining feature of Oracle VM Server for SPARC is that each domain is assigned CPU threads or cores for its exclusive use. This avoids the overhead of software-based time-slicing and emulation (or binary rewriting) of system state-changing privileged instructions used in traditional hypervisors. To create a domain, administrators specify either the number of CPU threads or cores that the domain will own, as well as its memory and I/O resources. When CPU resources are assigned at the individual thread level, the logical domains constraint manager attempts to assign threads from the same cores to a domain, and avoid "split core" situations where the same CPU core is used by multiple domains. Sometimes this is unavoidable, especially when domains are allocated and deallocated CPUs in small increments. Why split cores can matter Split core allocations can silenty reduce performance because multiple domains with different address spaces and memory contents are sharing the core's Level 1 cache (L1$). This is called false cache sharing since even identical memory addresses from different domains must point to different locations in RAM. The effect of this is increased contention for the cache, and higher memory latency for each domain using that core. The degree of performance impact can be widely variable. For applications with very small memory working sets, and with I/O bound or low-CPU utilization workloads, it may not matter at all: all machines wait for work at the same speed. If the domains have substantial workloads, or are critical to performance then this can have an important impact: This blog entry was inspired by a customer issue in which one CPU core was split among 3 domains, one of which was the control and service domain. The reported problem was increased I/O latency in guest domains, but the root cause might be higher latency servicing the I/O requests due to the control domain being slowed down. What to do about it Split core situations are easily avoided. In most cases the logical domain constraint manager will avoid it without any administrative action, but it can be entirely prevented by doing one of the several actions: Assign virtual CPUs in multiples of 8 - the number of threads per core. For example: ldm set-vcpu 8 mydomain or ldm add-vcpu 24 mydomain. Each domain will then be allocated on a core boundary. Use the whole core constraint when assigning CPU resources. This allocates CPUs in increments of entire cores instead of virtual CPU threads. The equivalent of the above commands would be ldm set-core 1 mydomain or ldm add-core 3 mydomain. Older syntax does the same thing by adding the -c flag to the add-vcpu, rm-vcpu and set-vcpu commands, but the new syntax is recommended. When whole core allocation is used an attempt to add cores to a domain fails if there aren't enough completely empty cores to satisfy the request. See https://blogs.oracle.com/sharakan/entry/oracle_vm_server_for_sparc4 for an excellent article on this topic by Eric Sharakan. Don't obsess: - if the workloads have minimal CPU requirements and don't need anywhere near a full CPU core, then don't worry about it. If you have low utilization workloads being consolidated from older machines onto a current T-series, then there's no need to worry about this or to assign an entire core to domains that will never use that much capacity. In any case, make sure the most important domains have their own CPU cores, in particular the control domain and any I/O or service domain, and of course any important guests. Summary Split core CPU allocation to domains can potentially have an impact on performance, but the logical domains manager tends to prevent this situation, and it can be completely and simply avoided by allocating virtual CPUs on core boundaries.

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• Organization &amp; Architecture UNISA Studies &ndash; Chap 6

  - by MarkPearl

  Learning Outcomes Discuss the physical characteristics of magnetic disks Describe how data is organized and accessed on a magnetic disk Discuss the parameters that play a role in the performance of magnetic disks Describe different optical memory devices Magnetic Disk The way data is stored on and retried from magnetic disks Data is recorded on and later retrieved form the disk via a conducting coil named the head (in many systems there are two heads) The writ mechanism exploits the fact that electricity flowing through a coil produces a magnetic field. Electric pulses are sent to the write head, and the resulting magnetic patterns are recorded on the surface below with different patterns for positive and negative currents The physical characteristics of a magnetic disk   Summarize from book   The factors that play a role in the performance of a disk Seek time – the time it takes to position the head at the track Rotational delay / latency – the time it takes for the beginning of the sector to reach the head Access time – the sum of the seek time and rotational delay Transfer time – the time it takes to transfer data RAID The rate of improvement in secondary storage performance has been considerably less than the rate for processors and main memory. Thus secondary storage has become a bit of a bottleneck. RAID works on the concept that if one disk can be pushed so far, additional gains in performance are to be had by using multiple parallel components. Points to note about RAID… RAID is a set of physical disk drives viewed by the operating system as a single logical drive Data is distributed across the physical drives of an array in a scheme known as striping Redundant disk capacity is used to store parity information, which guarantees data recoverability in case of a disk failure (not supported by RAID 0 or RAID 1) Interesting to note that the increase in the number of drives, increases the probability of failure. To compensate for this decreased reliability RAID makes use of stored parity information that enables the recovery of data lost due to a disk failure.   The RAID scheme consists of 7 levels…   Category Level Description Disks Required Data Availability Large I/O Data Transfer Capacity Small I/O Request Rate Striping 0 Non Redundant N Lower than single disk Very high Very high for both read and write Mirroring 1 Mirrored 2N Higher than RAID 2 – 5 but lower than RAID 6 Higher than single disk Up to twice that of a signle disk for read Parallel Access 2 Redundant via Hamming Code N + m Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Parallel Access 3 Bit interleaved parity N + 1 Much higher than single disk Highest of all listed alternatives Approximately twice that of a single disk Independent Access 4 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, significantly lower than single disk for write Similar to RAID 0 for read, significantly lower than single disk for write Independent Access 5 Block interleaved parity N + 1 Much higher than single disk Similar to RAID 0 for read, lower than single disk for write Similar to RAID 0 for read, generally  lower than single disk for write Independent Access 6 Block interleaved parity N + 2 Highest of all listed alternatives Similar to RAID 0 for read; lower than RAID 5 for write Similar to RAID 0 for read, significantly lower than RAID 5  for write   Read page 215 – 221 for detailed explanation on RAID levels Optical Memory There are a variety of optical-disk systems available. Read through the table on page 222 – 223 Some of the devices include… CD CD-ROM CD-R CD-RW DVD DVD-R DVD-RW Blue-Ray DVD Magnetic Tape Most modern systems use serial recording – data is lade out as a sequence of bits along each track. The typical recording used in serial is referred to as serpentine recording. In this technique when data is being recorded, the first set of bits is recorded along the whole length of the tape. When the end of the tape is reached the heads are repostioned to record a new track, and the tape is again recorded on its whole length, this time in the opposite direction. That process continued back and forth until the tape is full. To increase speed, the read-write head is capable of reading and writing a number of adjacent tracks simultaneously. Data is still recorded serially along individual tracks, but blocks in sequence are stored on adjacent tracks as suggested. A tape drive is a sequential access device. Magnetic tape was the first kind of secondary memory. It is still widely used as the lowest-cost, slowest speed member of the memory hierarchy.

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• Efficiently separating Read/Compute/Write steps for concurrent processing of entities in Entity/Component systems

  - by TravisG

  Setup I have an entity-component architecture where Entities can have a set of attributes (which are pure data with no behavior) and there exist systems that run the entity logic which act on that data. Essentially, in somewhat pseudo-code: Entity { id; map<id_type, Attribute> attributes; } System { update(); vector<Entity> entities; } A system that just moves along all entities at a constant rate might be MovementSystem extends System { update() { for each entity in entities position = entity.attributes["position"]; position += vec3(1,1,1); } } Essentially, I'm trying to parallelise update() as efficiently as possible. This can be done by running entire systems in parallel, or by giving each update() of one system a couple of components so different threads can execute the update of the same system, but for a different subset of entities registered with that system. Problem In reality, these systems sometimes require that entities interact(/read/write data from/to) each other, sometimes within the same system (e.g. an AI system that reads state from other entities surrounding the current processed entity), but sometimes between different systems that depend on each other (i.e. a movement system that requires data from a system that processes user input). Now, when trying to parallelize the update phases of entity/component systems, the phases in which data (components/attributes) from Entities are read and used to compute something, and the phase where the modified data is written back to entities need to be separated in order to avoid data races. Otherwise the only way (not taking into account just "critical section"ing everything) to avoid them is to serialize parts of the update process that depend on other parts. This seems ugly. To me it would seem more elegant to be able to (ideally) have all processing running in parallel, where a system may read data from all entities as it wishes, but doesn't write modifications to that data back until some later point. The fact that this is even possible is based on the assumption that modification write-backs are usually very small in complexity, and don't require much performance, whereas computations are very expensive (relatively). So the overhead added by a delayed-write phase might be evened out by more efficient updating of entities (by having threads work more % of the time instead of waiting). A concrete example of this might be a system that updates physics. The system needs to both read and write a lot of data to and from entities. Optimally, there would be a system in place where all available threads update a subset of all entities registered with the physics system. In the case of the physics system this isn't trivially possible because of race conditions. So without a workaround, we would have to find other systems to run in parallel (which don't modify the same data as the physics system), other wise the remaining threads are waiting and wasting time. However, that has disadvantages Practically, the L3 cache is pretty much always better utilized when updating a large system with multiple threads, as opposed to multiple systems at once, which all act on different sets of data. Finding and assembling other systems to run in parallel can be extremely time consuming to design well enough to optimize performance. Sometimes, it might even not be possible at all because a system just depends on data that is touched by all other systems. Solution? In my thinking, a possible solution would be a system where reading/updating and writing of data is separated, so that in one expensive phase, systems only read data and compute what they need to compute, and then in a separate, performance-wise cheap, write phase, attributes of entities that needed to be modified are finally written back to the entities. The Question How might such a system be implemented to achieve optimal performance, as well as making programmer life easier? What are the implementation details of such a system and what might have to be changed in the existing EC-architecture to accommodate this solution?

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• Blink-Data vs Instinct?

  - by Samantha.Y. Ma

  In his landmark bestseller Blink, well-known author and journalist Malcolm Gladwell explores how human beings everyday make seemingly instantaneous choices --in the blink of an eye--and how we “think without thinking.”  These situations actually aren’t as simple as they seem, he postulates; and throughout the book, Gladwell seeks answers to questions such as: 1.    What makes some people good at thinking on their feet and making quick spontaneous decisions?2.    Why do some people follow their instincts and win, while others consistently seem to stumble into error?3.    Why are some of the best decisions often those that are difficult to explain to others?In Blink, Gladwell introduces us to the psychologist who has learned to predict whether a marriage will last, based on a few minutes of observing a couple; the tennis coach who knows when a player will double-fault before the racket even makes contact with the ball; the antiquities experts who recognize a fake at a glance. Ultimately, Blink reveals that great decision makers aren't those who spend the most time deliberating or analyzing information, but those who focus on key factors among an overwhelming number of variables-- i.e., those who have perfected the art of "thin-slicing.” In Data vs. Instinct: Perfecting Global Sales Performance, a new report sponsored by Oracle, the Economist Intelligence Unit (EIU) explores the roles data and instinct play in decision-making by sales managers and discusses how sales executives can increase sales performance through more effective  territory planning and incentive/compensation strategies.If you are a sales executive, ask yourself this:  “Do you rely on knowledge (data) when you plan out your sales strategy?  If you rely on data, how do you ensure that your data sources are reliable, up-to-date, and complete?  With the emergence of social media and the proliferation of both structured and unstructured data, how do you know that you are applying your information/data correctly and in-context?  Three key findings in the report are:•    Six out of ten executives say they rely more on data than instinct to drive decisions. •    Nearly one half (48 percent) of incentive compensation plans do not achieve the desired results. •    Senior sales executives rely more on current and historical data than on forecast data. Strikingly similar to what Gladwell concludes in Blink, the report’s authors succinctly sum up their findings: "The best outcome is a combination of timely information, insightful predictions, and support data."Applying this insight is crucial to creating a sound sales plan that drives alignment and results.  In the area of sales performance management, “territory programs and incentive compensation continue to present particularly complex challenges in an increasingly globalized market," say the report’s authors. "It behooves companies to get a better handle on translating that data into actionable and effective plans." To help solve this challenge, CRM Oracle Fusion integrates forecasting, quotas, compensation, and territories into a single system.   For example, Oracle Fusion CRM provides a natural integration between territories, which define the sales targets (e.g., collection of accounts) for the sales force, and quotas, which quantify the sales targets. In fact, territory hierarchy is a core analytic dimension to slice and dice sales results, using sales analytics and alerts to help you identify where problems are occurring. This makes territoriesStart tapping into both data and instinct effectively today with Oracle Fusion CRM.   Here is a short video to provide you with a snapshot of how it can help you optimize your sales performance.  

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• The Best Data Integration for Exadata Comes from Oracle

  - by maria costanzo

  Oracle Data Integrator and Oracle GoldenGate offer unique and optimized data integration solutions for Oracle Exadata. For example, customers that choose to feed their data warehouse or reporting database with near real-time throughout the day, can do so without decreasing  performance or availability of source and target systems. And if you ask why real-time, the short answer is: in today’s fast-paced, always-on world, business decisions need to use more relevant, timely data to be able to act fast and seize opportunities. A longer response to "why real-time" question can be found in a related blog post. If we look at the solution architecture, as shown on the diagram below,  Oracle Data Integrator and Oracle GoldenGate are both uniquely designed to take full advantage of the power of the database and to eliminate unnecessary middle-tier components. Oracle Data Integrator (ODI) is the best bulk data loading solution for Exadata. ODI is the only ETL platform that can leverage the full power of Exadata, integrate directly on the Exadata machine without any additional hardware, and by far provides the simplest setup and fastest overall performance on an Exadata system. We regularly see customers achieving a 5-10 times boost when they move their ETL to ODI on Exadata. For  some companies the performance gain is even much higher. For example a large insurance company did a proof of concept comparing ODI vs a traditional ETL tool (one of the market leaders) on Exadata. The same process that was taking 5hrs and 11 minutes to complete using the competing ETL product took 7 minutes and 20 seconds with ODI. Oracle Data Integrator was 42 times faster than the conventional ETL when running on Exadata.This shows that Oracle's own data integration offering helps you to gain the most out of your Exadata investment with a truly optimized solution. GoldenGate is the best solution for streaming data from heterogeneous sources into Exadata in real time. Oracle GoldenGate can also be used together with Data Integrator for hybrid use cases that also demand non-invasive capture, high-speed real time replication. Oracle GoldenGate enables real-time data feeds from heterogeneous sources non-invasively, and delivers to the staging area on the target Exadata system. ODI runs directly on Exadata to use the database engine power to perform in-database transformations. Enterprise Data Quality is integrated with Oracle Data integrator and enables ODI to load trusted data into the data warehouse tables. Only Oracle can offer all these technical benefits wrapped into a single intelligence data warehouse solution that runs on Exadata. Compared to traditional ETL with add-on CDC this solution offers: §  Non-invasive data capture from heterogeneous sources and avoids any performance impact on source §  No mid-tier; set based transformations use database power §  Mini-batches throughout the day –or- bulk processing nightly which means maximum availability for the DW §  Integrated solution with Enterprise Data Quality enables leveraging trusted data in the data warehouse In addition to Starwood Hotels and Resorts, Morrison Supermarkets, United Kingdom’s fourth-largest food retailer, has seen the power of this solution for their new BI platform and shared their story with us. Morrisons needed to analyze data across a large number of manufacturing, warehousing, retail, and financial applications with the goal to achieve single view into operations for improved customer service. The retailer deployed Oracle GoldenGate and Oracle Data Integrator to bring new data into Oracle Exadata in near real-time and replicate the data into reporting structures within the data warehouse—extending visibility into operations. Using Oracle's data integration offering for Exadata, Morrisons produced financial reports in seconds, rather than minutes, and improved staff productivity and agility. You can read more about Morrison’s success story here and hear from Starwood here. From an Irem Radzik article.

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• JavaOne 2012: Nashorn Edition

  - by $utils.escapeXML($entry.author)

  As with my JavaOne 2012: OpenJDK Edition post a while back (now updated to reflect the schedule of the talks), I find it convenient to have my JavaOne schedule ordered by subjects of interest. Beside OpenJDK in all its flavors, another subject I find very exciting is Nashorn. I blogged about the various material on Nashorn in the past, and we interviewed Jim Laskey, the Project Lead on Project Nashorn in the Java Spotlight podcast. So without further ado, here are the JavaOne 2012 talks and BOFs with Nashorn in their title, or abstract:CON5390 - Nashorn: Optimizing JavaScript and Dynamic Language Execution on the JVM - Monday, Oct 1, 8:30 AM - 9:30 AMThere are many implementations of JavaScript, meant to run either on the JVM or standalone as native code. Both approaches have their respective pros and cons. The Oracle Nashorn JavaScript project is based on the former approach. This presentation goes through the performance work that has gone on in Oracle’s Nashorn JavaScript project to date in order to make JavaScript-to-bytecode generation for execution on the JVM feasible. It shows that the new invoke dynamic bytecode gets us part of the way there but may not quite be enough. What other tricks did the Nashorn project use? The presentation also discusses future directions for increased performance for dynamic languages on the JVM, covering proposed enhancements to both the JVM itself and to the bytecode compiler.CON4082 - Nashorn: JavaScript on the JVM - Monday, Oct 1, 3:00 PM - 4:00 PMThe JavaScript programming language has been experiencing a renaissance of late, driven by the interest in HTML5. Nashorn is a JavaScript engine implemented fully in Java on the JVM. It is based on the Da Vinci Machine (JSR 292) and will be available with JDK 8. This session describes the goals of Project Nashorn, gives a top-level view of how it all works, provides the current status, and demonstrates examples of JavaScript and Java working together.BOF4763 - Meet the Nashorn JavaScript Team - Tuesday, Oct 2, 4:30 PM - 5:15 PMCome to this session to meet the Oracle JavaScript (Project Nashorn) language teamBOF6661 - Nashorn, Node, and Java Persistence - Tuesday, Oct 2, 5:30 PM - 6:15 PMWith Project Nashorn, developers will have a full and modern JavaScript engine available on the JVM. In addition, they will have support for running Node applications with Node.jar. This unique combination of capabilities opens the door for best-of-breed applications combining Node with Java SE and Java EE. In this session, you’ll learn about Node.jar and how it can be combined with Java EE components such as EclipseLink JPA for rich Java persistence. You’ll also hear about all of Node.jar’s mapping, caching, querying, performance, and scaling features.CON10657 - The Polyglot Java VM and Java Middleware - Thursday, Oct 4, 12:30 PM - 1:30 PMIn this session, Red Hat and Oracle discuss the impact of polyglot programming from their own unique perspectives, examining non-Java languages that utilize Oracle’s Java HotSpot VM. You’ll hear a discussion of topics relating to Ruby, Lisp, and Clojure and the intersection of other languages where they may touch upon individual frameworks and projects, and you’ll get perspectives on JavaScript via the Nashorn Project, an upcoming JavaScript engine, developed fully in Java.CON5251 - Putting the Metaobject Protocol to Work: Nashorn’s Java Bindings - Thursday, Oct 4, 2:00 PM - 3:00 PMProject Nashorn is Oracle’s new JavaScript runtime in Java 8. Being a JavaScript runtime running on the JVM, it provides integration with the underlying runtime by enabling JavaScript objects to manipulate Java objects, implement Java interfaces, and extend Java classes. Nashorn is invokedynamic-based, and for its Java integration, it does away with the concept of wrapper objects in favor of direct virtual machine linking to Java objects’ methods provided by a metaobject protocol, providing much higher performance than what could be expected from a scripting runtime. This session looks at the details of the integration, a topic of interest to other language implementers on the JVM and a wider audience of developers who want to understand how Nashorn works.That's 6 sessions tooting the Nashorn this year at JavaOne, up from 2 last year.

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• Wireless connection works but the internet is too slow to use in Ubuntu 11.04

  - by Garrin

  The internet is so slow as to be unusable. And I'm not being picky. Even after minutes I can't get my Google home page to load. I tried installing a package through apt-get and was getting rates between 0 and a few hundred bytes/s. That's bytes, not kilobytes! Mostly 0 however (no exaggeration, it spends large amounts of time stalled). And I would go to a speed test web site of some kind but I can't since nothing will load. Briefly put, the laptop I am using was connected to two wireless networks while using Ubuntu 11.04 without any issues before this. It was also connected to a wired network without any issues. It dual boats Windows 7 which has never had any issues, not even with the current wireless network. Just to be clear, on the current wi-fi network, Windows 7 encounters no issues (speedtest.net puts the network speed at 1mb/s) but my network connection in Ubuntu 11.04 is so slow as to literally be unusable. I am unfamiliar with the router except for the fact that it boasts a Rogers logo (that's a large ISP/cable provider in Canada for those not familiar with the land of igloos and polar bears). I am far from the router and some desktop widget I use tells me the signal strength is at 58% (it seems fairly reliable and this would appear to match up with the filled bars in the network icon). I should also mention I'm just renting a room in this house so I'm not the network administrator and while I can access the 192.168.0.1 router page, the password wasn't set to 'password' so it's not much use to me. Here are a bunch of commands I ran which don't tell me a whole lot but I thought might be more instructive to the wise around here: lspci (just showing my network card): 05:00.0 Network controller: Atheros Communications Inc. AR928X Wireless Network Adapter (PCI-Express) (rev 01) This one is self explanatory. PING www.googele.com (216.65.41.185) 56(84) bytes of data. 64 bytes from nnw.net (216.65.41.185): icmp_req=1 ttl=51 time=267 ms 64 bytes from nnw.net (216.65.41.185): icmp_req=2 ttl=51 time=190 ms 64 bytes from nnw.net (216.65.41.185): icmp_req=3 ttl=51 time=212 ms 64 bytes from nnw.net (216.65.41.185): icmp_req=4 ttl=51 time=207 ms 64 bytes from nnw.net (216.65.41.185): icmp_req=5 ttl=51 time=220 ms --- www.googele.com ping statistics --- 5 packets transmitted, 5 received, 0% packet loss, time 4003ms rtt min/avg/max/mdev = 190.079/219.699/267.963/26.121 ms ifconfig eth0 Link encap:Ethernet HWaddr 20:6a:8a:02:20:da UP BROADCAST MULTICAST MTU:1500 Metric:1 RX packets:0 errors:0 dropped:0 overruns:0 frame:0 TX packets:0 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:0 (0.0 B) TX bytes:0 (0.0 B) Interrupt:42 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:16 errors:0 dropped:0 overruns:0 frame:0 TX packets:16 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:0 RX bytes:960 (960.0 B) TX bytes:960 (960.0 B) wlan0 Link encap:Ethernet HWaddr 20:7c:8f:05:c6:bf inet addr:192.168.0.16 Bcast:192.168.0.255 Mask:255.255.255.0 inet6 addr: fe80::227c:8fff:fe05:c6bf/64 Scope:Link UP BROADCAST RUNNING MULTICAST MTU:1500 Metric:1 RX packets:982 errors:0 dropped:0 overruns:0 frame:0 TX packets:658 errors:0 dropped:0 overruns:0 carrier:0 collisions:0 txqueuelen:1000 RX bytes:497250 (497.2 KB) TX bytes:95076 (95.0 KB) Thank you

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• Drive

  - by erikanollwebb

  Picking up where we left off, let's summarize.  People have both intrinsic motivation and extrinsic motivation, and whether reward works depends a bit on what you are rewarding.  Rewards don't decreased intrinsic motivation provided you know what you are getting and why, and when you reward high performance.  But as anyone who has watched the great animation of Dan Pink's TED talk knows, even that doesn't tell the whole story.  Although people may not be less intrinsically motivated by rewards, the impact of rewards on actual performance is a really odd questions.  Larger rewards don't necessarily lead to better performance and in fact, some times lead to worse performance.  Pink argues that people are driven and engaged when they have autonomy, mastery and purpose.  If they can self-direct and can be good at what they do and have a sense of purpose for what they are doing, they show the highest engagement.   (Personally, I would add progress to the list.  My experience is that if you have autonomy, mastery and a sense of purpose but don't get a feeling that you are making any progress day to day, your level of engagement will drop rapidly.) So Pink is arguing if we could set up work so that people have a sense of purpose in what they do, have some autonomy and the ability to build mastery, you'll have better companies.  And that's probably true in a lot of ways, but there's a problem.  Sometimes, you have things you need to do but maybe you don't really want to do.  Or that you don't really see the point of.  Or that doesn't have a lot of value to you at the end of the day.  Then what does a company do?  Let me give you an example.  I've worked on some customer relationship management (CRM) tools over the years and done user research with sales people to try and understand their world.  And there's a funny thing about sales tools in CRM.  Sometimes what the company wants a sales person to do is at odds with what a sales person thinks is useful to them.  For example, companies would like to know who a sales person talked to at the company and the person level.  They'd like to know what they talked about, when, and whether the deals closed.  Those metrics would help you build a better sales force and understand what works and what does not.  But sales people see that as busy work that doesn't add any value to their ability to sell.  So you have a sales person who has a lot of autonomy, they like to do things that improve their ability to sell and they usually feel a sense of purpose--the group is trying to make a quota!  That quota will help the company succeed!  But then you have tasks that they don't think fit into that equation.  The company would like to know more about what makes them successful and get metrics on what they do and frankly, have a record of what they do in case they leave, but the sales person thinks it's a waste of time to put all that information into a sales application. They have drive, just not for all the things the company would like.   You could punish them for not entering the information, or you could try to reward them for doing it, but you still have an imperfect model of engagement.  Ideally, you'd like them to want to do it.  If they want to do it, if they are motivated to do it, then the company wins.  If *something* about it is rewarding to them, then they are more engaged and more likely to do it.  So the question becomes, how do you create that interest to do something?

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• Challenges in Corporate Reporting - New Independent Research

  - by ndwyouell

  Earlier this year, Oracle and Accenture sponsored a global study on trends in financial close and reporting. We surveyed 1,123 finance professionals in large organizations in 12 countries around the world during February and March. Financial Consolidation and Reporting is the most mature aspect of Enterprise Performance Management with mainstream solutions having been around for over 30 years. But of course over this time there have been many changes and very significant increases in regulation. So just what is the current state is Financial Consolidation and Reporting in our major corporations across the world? We commissioned this independent research to find out. Highlights of the result are: •          Seeking change: Businesses recognize they need to invest in financial reporting to address the challenges they currently face. 47 percent of companies have made substantial investments over the last year to the financial close, filing, and reporting processes. •          Ineffective investments: Despite these investments, spreadsheets (72 percent) and e-mails (68 percent) are still being used daily to track and manage reporting, suggesting that new investments are falling short of expectations. •          Increased costs and uncertainty: The situation is so opaque that managers across the finance function are unable to fully understand the financial impact or cost implications of reporting, with 60 percent of respondents admitting they did not know the total cost of managing and publicizing their financial results. •          Persistent challenges: 68 percent of respondents admitted that they have inadequate visibility into reporting processes, while 84 percent of finance managers surveyed said they find it difficult to control the quality of financial data across the entire reporting process. •          Decreased effectiveness: 71 percent of finance managers feel their effectiveness is limited in some way by data-analysis–related issues, while 39 percent of C-level or VP-level respondents say their effectiveness is impaired by limited visibility. •          Missed deadlines: Due to late changes to the chart of accounts, 15 percent of global businesses have missed statutory filings, putting their companies at risk of financial penalties and potentially impacting share value. The report makes it clear that investments made to date by these large organizations around the world have been uneven across the close, reporting, and filing processes, which has led to the challenges these organizations currently face in the overall process. Regardless of whether companies are using a variety of solutions or a single solution, the report shows they continue to witness increased costs, ineffectual data management, and missed reporting, which—in extreme circumstances—can impact a company’s corporate image and share value. The good news is that businesses realize that these problems persist and 86 percent of companies are likely to make a significant investment during the next five years to address these issues. While they should invest, it is critical that they direct investments correctly to address the key issues this research identified: •          Improving data integrity •          Optimizing processes •          Integrating the extended financial close process By addressing these issues and with clear guidance on how to implement the correct business processes, infrastructure, and software solutions, finance teams will find that their reporting processes are much more effective, cost-efficient, and aligned with their performance expectations. To get a copy of the full report: http://www.oracle.com/webapps/dialogue/ns/dlgwelcome.jsp?p_ext=Y&p_dlg_id=11747758&src=7300117&Act=92 To replay a webcast discussing the findings: http://www.cfo.com/webcast.cfm?webcast=14639438&pcode=ORA061912_ORA

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• Concurrent Affairs

  - by Tony Davis

  I once wrote an editorial, multi-core mania, on the conundrum of ever-increasing numbers of processor cores, but without the concurrent programming techniques to get anywhere near exploiting their performance potential. I came to the.controversial.conclusion that, while the problem loomed for all procedural languages, it was not a big issue for the vast majority of programmers. Two years later, I still think most programmers don't concern themselves overly with this issue, but I do think that's a bigger problem than I originally implied. Firstly, is the performance boost from writing code that can fully exploit all available cores worth the cost of the additional programming complexity? Right now, with quad-core processors that, at best, can make our programs four times faster, the answer is still no for many applications. But what happens in a few years, as the number of cores grows to 100 or even 1000? At this point, it becomes very hard to ignore the potential gains from exploiting concurrency. Possibly, I was optimistic to assume that, by the time we have 100-core processors, and most applications really needed to exploit them, some technology would be around to allow us to do so with relative ease. The ideal solution would be one that allows programmers to forget about the problem, in much the same way that garbage collection removed the need to worry too much about memory allocation. From all I can find on the topic, though, there is only a remote likelihood that we'll ever have a compiler that takes a program written in a single-threaded style and "auto-magically" converts it into an efficient, correct, multi-threaded program. At the same time, it seems clear that what is currently the most common solution, multi-threaded programming with shared memory, is unsustainable. As soon as a piece of state can be changed by a different thread of execution, the potential number of execution paths through your program grows exponentially with the number of threads. If you have two threads, each executing n instructions, then there are 2^n possible "interleavings" of those instructions. Of course, many of those interleavings will have identical behavior, but several won't. Not only does this make understanding how a program works an order of magnitude harder, but it will also result in irreproducible, non-deterministic, bugs. And of course, the problem will be many times worse when you have a hundred or a thousand threads. So what is the answer? All of the possible alternatives require a change in the way we write programs and, currently, seem to be plagued by performance issues. Software transactional memory (STM) applies the ideas of database transactions, and optimistic concurrency control, to memory. However, working out how to break down your program into sufficiently small transactions, so as to avoid contention issues, isn't easy. Another approach is concurrency with actors, where instead of having threads share memory, each thread runs in complete isolation, and communicates with others by passing messages. It simplifies concurrent programs but still has performance issues, if the threads need to operate on the same large piece of data. There are doubtless other possible solutions that I haven't mentioned, and I would love to know to what extent you, as a developer, are considering the problem of multi-core concurrency, what solution you currently favor, and why. Cheers, Tony.

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• Problems with jQuery getJSON using local files in Chrome

  - by Tauren

  I have a very simple test page that uses XHR requests with jQuery's $.getJSON and $.ajax methods. The same page works in some situations and not in others. Specificially, it doesn't work in Chrome on Ubuntu. I'm testing on Ubuntu 9.10 with Chrome 5.0.342.7 beta and Mac OSX 10.6.2 with Chrome 5.0.307.9 beta. It works correctly when files are installed on a web server from both Ubuntu/Chrome and Mac/Chrome (try it out here). It works correctly when files are installed on local hard drive in Mac/Chrome (accessed with file:///...). It FAILS when files are installed on local hard drive in Ubuntu/Chrome (access with file:///...). The small set of 3 files can be downloaded in a tar/gzip file from here: http://issues.tauren.com/testjson/testjson.tgz When it works, the Chrome console will say: XHR finished loading: "http://issues.tauren.com/testjson/data.json". index.html:16Using getJSON index.html:21 Object result: "success" __proto__: Object index.html:22success XHR finished loading: "http://issues.tauren.com/testjson/data.json". index.html:29Using ajax with json dataType index.html:34 Object result: "success" __proto__: Object index.html:35success XHR finished loading: "http://issues.tauren.com/testjson/data.json". index.html:46Using ajax with text dataType index.html:51{"result":"success"} index.html:52undefined When it doesn't work, the Chrome console will show this: index.html:16Using getJSON index.html:21null index.html:22Uncaught TypeError: Cannot read property 'result' of null index.html:29Using ajax with json dataType index.html:34null index.html:35Uncaught TypeError: Cannot read property 'result' of null index.html:46Using ajax with text dataType index.html:51 index.html:52undefined Notice that it doesn't even show the XHR requests, although the success handler is run. I swear this was working previously in Ubuntu/Chrome, and am worried something got messed up. I already uninstalled and reinstalled Chrome, but that didn't help. Can someone try it out locally on your Ubuntu system and tell me if you have any troubles? Note that it seems to be working fine in Firefox.

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• ASP.NET MVC Concurrency with RowVersion in Edit Action

  - by Jorin

  I'm wanting to do a simple edit form for our Issue Tracking app. For simplicity, the HttpGet Edit action looks something like this: // Issues/Edit/12 public ActionResult Edit(int id) { var thisIssue = edmx.Issues.First(i => i.IssueID == id); return View(thisIssue); } and then the HttpPost action looks something like this: [HttpPost] public ActionResult Edit(int id, FormCollection form) { // this is the dumb part where I grab the object before I update it. // concurrency is sidestepped here. var thisIssue = edmx.Issues.Single(c => c.IssueID == id); TryUpdateModel(thisIssue); if (ModelState.IsValid) { edmx.SaveChanges(); TempData["message"] = string.Format("Issue #{0} successfully modified.", id); return RedirectToAction("Index"); } return View(thisIssue); } Which works wonderfully. However, the concurrency check doesn't work because in the Post, I'm re-retreiving the current entity right before I attempt to update it. However, with EF, I don't know how to use the fanciness of SaveChanges() but attach my thisIssue to the context. I tried to call edmx.Issues.Attach(thisIssue) but I get The object cannot be attached because it is already in the object context. An object can only be reattached when it is in an unchanged state. How do I handle concurrency in MVC with EF and/or how do I properly Attach my edited object to the context? Thanks in advance

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• Applications on the Web/Cloud the way to go? over Desktop apps?

  - by jiewmeng

  i am currently a mainly web developer, but is quite attracted to the performance and great integration with the OS (eg. Windows 7, Jump Lists, Taskbar Thumbnails, etc) something like WPF/C# can provide to the user, improving workflow and productivity. privacy and performance seems like a major downside of web/cloud apps compared to desktop apps. applications on the cloud/web work on the go, increased popularity of smartphones/netbooks majority of users may not benefit as much from increased performance of desktop apps, eg. internet surfing, word processing, probably benefit more from decreased startup times, lower costs and data on the cloud desktop applications increased performance benefits power users like 3D rendering, HD video/photo editing, gamers (i wonder if such processing maybe offset to cloud processing) integration with OS increases productivity (maybe such features can be adapted to a web version? maybe with a local desktop app to work with Web App API) more control over privacy (maybe fixed by encryption?) local data access (esp. large files) guaranteed and fast (YouTube HD fast enough most of the time) work not affected by intermittent/slow/availability internet connections (i know this is changing tho) what do you think?

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• Surprising results with .NET multi-theading algorithm

  - by Myles J

  Hi, I've recently wrote a C# console time tabling algorithm that is based on a combination of a genetic algorithm with a few brute force routines thrown in. The initial results were promising but I figured I could improve the performance by splitting the brute force routines up to run in parallel on multi processor architectures. To do this I used the well documented Producer/Consumer model (as documented in this fantastic article http://www.albahari.com/threading/part2.aspx#_ProducerConsumerQWaitHandle). I changed my code to create one thread per logical processor during the brute force routines. The performance gains on my work station were very pleasing. I am running Windows XP on the following hardware: Intel Core 2 Quad CPU 2.33 GHz 3.49 GB RAM Initial tests indicated average performance gains of approx 40% when using 4 threads. The next step was to deploy the new multi-threading version of the algorithm to our higher spec UAT server. Here is the spec of our UAT server: Windows 2003 Server R2 Enterprise x64 8 cpu (Quad-Core) AMD Opteron 2.70 GHz 255 GB RAM After running the first round of tests we were all extremely surprised to find that the algorithm actually runs slower on the high spec W2003 server than on my local XP work station! In fact the tests seem to indicate that it doesn't matter how many threads are generated (tests were ran with the app spawning between 2 to 32 threads). The algorithm always runs significantly slower on the UAT W2003 server? How could this be? Surely the app should run faster on a 8 cpu (Quad-Core) than my 2 Quad work station? Why are we seeing no performance gains with the multi-threading on the W2003 server whilst the XP workstation tests show gains of up to 40%? Any help or pointers would be appreciated. Regards Myles

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• How to simply a foreach iteration using reflection

  - by Priya

  Consider that I have to get the overall performance of X. X has Y elements and Y in turn has Z elements which inturn has some N elements. To get the performance of X I do this: List<double> XQ = new List<double>(); foreach (Elem Y in X.Y){ List<double> YQ = new List<double>(); foreach (Elem Z in Y.Z){ List<double> ZQ = new List<double>(); foreach (Elem N in Z.N){ ZQ.Add(GetPerformance(N)); } YQ.Add(AVG(ZQ)); } XQ.Add(AVG(YQ)); } AVG of XQ list gives the performance of X. The performance can be calculated for either X or Y or for Z. X, Y and Z share the same base class. So depending on the item given the foreach loop has to be executed. Currently I have a switch case to determine each item (X or Y or Z) and the foreach loop is repeated in the code pertaining to the item (eg. If Y foreach starts from Y.Z). Is is possible to convert this whole code generic using reflection instead of having to repeat it in each switch case? Thanks

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• LaTeX printing only first two pages of a document

  - by Peter Flom

  I am working in LaTeX, and when I create a pdf file (using LaTeX button or pdfLaTeX button or using yap) the pdf has only the first two pages. No errors. It just stops. If I make the first page longer by adding text, it still stops at end of 2nd page. Any ideas? OK, responding to first comment, here is the code \documentclass{article} \title{Outline of Book} \author{Peter L. Flom} \begin{document} \maketitle \section*{Preface} \subsection*{Audience} \subsection*{What makes this book different?} \subsection*{Necessary background} \subsection*{How to read this book} \section{Introduction} \subsection{The purpose of logistic regression} \subsection{The need for logistic regression} \subsection{Types of logistic regression} \section{General issues in logistic regression} \subsection{Transforming independent and dependent variables} \subsection{Interactions} \subsection{Model selection} \subsection{Parameter estimates, confidence intervals, p values} \subsection{Summary and further reading} \section{Dichotomous logistic regression} \subsection{Introduction, theory, examples} \subsection{Exploratory plots and analysis} \subsection{Basic model fitting} \subsection{Advanced and special issues in model fitting} \subsection{Diagnostic and descriptive plots and analysis} \subsection{Traps and gotchas} \subsection{Power analysis} \subsection{Summary and further reading} \subsection{Exercises} \section{Ordinal logistic regression} \subsection{Introduction, theory, examples} \subsubsection{Introduction - what are ordinal variables?} \subsubsection{Theory of the model} \subsubsection{Examples for this chapter} \subsection{Exploratory plots and analysis} \subsection{Basic model fitting} \subsection{Advanced and special issues in model fitting} \subsection{Diagnostic and descriptive plots and analysis} \subsection{Traps and gotchas} \subsection{Power analysis} \subsection{Summary and further reading} \subsection{Exercises} \section{Multinomial logistic regression} \subsection{Introduction, theory, examples} \subsection{Exploratory plots and analysis} \subsection{Basic model fitting} \subsection{Advanced and special issues in model fitting} \subsection{Diagnostic and descriptive plots and analysis} \subsection{Traps and gotchas} \subsection{Power analysis} \subsection{Summary and further reading} \subsection{Exercises} \section{Choosing a model} \subsection{NOIR and its problems} \subsection{Linear vs. ordinal} \subsection{Ordinal vs. multinomial} \subsection{Summary and further reading} \subsection{Exercises} \section{Extensions and related models} \subsection{Other logistic models} \subsection{Multilevel models - PROC NLMIXED and GLIMMIX} \subsection{Loglinear models - PROC CATMOD} \section{Summary} \end{document} thanks Peter

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• Slow Python HTTP server on localhost

  - by Abiel

  I am experiencing some performance problems when creating a very simple Python HTTP server. The key issue is that performance is varying depending on which client I use to access it, where the server and all clients are being run on the local machine. For instance, a GET request issued from a Python script (urllib2.urlopen('http://localhost/').read()) takes just over a second to complete, which seems slow considering that the server is under no load. Running the GET request from Excel using MSXML2.ServerXMLHTTP also feels slow. However, requesting the data Google Chrome or from RCurl, the curl add-in for R, yields an essentially instantaneous response, which is what I would expect. Adding further to my confusion is that I do not experience any performance problems for any client when I am on my computer at work (the performance problems are on my home computer). Both systems run Python 2.6, although the work computer runs Windows XP instead of 7. Below is my very simple server example, which simply returns 'Hello world' for any get request. from BaseHTTPServer import BaseHTTPRequestHandler, HTTPServer class MyHandler(BaseHTTPRequestHandler): def do_GET(self): print("Just received a GET request") self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write('Hello world') return def log_request(self, code=None, size=None): print('Request') def log_message(self, format, *args): print('Message') if __name__ == "__main__": try: server = HTTPServer(('localhost', 80), MyHandler) print('Started http server') server.serve_forever() except KeyboardInterrupt: print('^C received, shutting down server') server.socket.close() Note that in MyHandler I override the log_request() and log_message() functions. The reason is that I read that a fully-qualified domain name lookup performed by one of these functions might be a reason for a slow server. Unfortunately setting them to just print a static message did not solve my problem. Also, notice that I have put in a print() statement as the first line of the do_GET() routine in MyHandler. The slowness occurs prior to this message being printed, meaning that none of the stuff that comes after it is causing a delay.

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• duplicate rows in join table with has_many => through and accepts_nested_attributes_for

  - by shalako

  An event has many artists, and an artist has many events. The join of an artist and an event is called a performance. I want to add artists to an event. This works except that I'm getting duplicate entries into my join table when creating a new event. This causes problems elsewhere. event.rb has_many :performances, :dependent => :destroy has_many :artists, :through => :performances accepts_nested_attributes_for :artists, :reject_if => proc {|a| a['name'].blank?} accepts_nested_attributes_for :performances, :reject_if => proc { |a| a['artist_id'].blank? }, :allow_destroy => true artist.rb has_many :performances, :dependent => :destroy has_many :artists, :through => :performances performance.rb belongs_to :artist belongs_to :event events_controller.rb def new @event = Event.new @event.artists.build respond_to do |format| format.html # new.html.erb format.xml { render :xml => @event } end end def create @event = Event.new(params[:event]) respond_to do |format| if @event.save flash[:notice] = 'Event was successfully created.' format.html { redirect_to(admin_events_url) } format.xml { render :xml => @event, :status => :created, :location => @event } else format.html { render :action => "new" } format.xml { render :xml => @event.errors, :status => :unprocessable_entity } end end end output Performance Create (0.2ms) INSERT INTO `performances` (`event_id`, `artist_id`) VALUES(7, 19) Performance Create (0.1ms) INSERT INTO `performances` (`event_id`, `artist_id`) VALUES(7, 19)

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