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  • My Oracle Suport?????

    - by Dongwei Wang
    ????????????????,??????MOS???????(????),????????????????????????????:Note 62143.1 - Troubleshooting: Tuning the Shared Pool and Tuning Library Cache Latch ContentionNote 376442.1 - * How To Collect 10046 Trace (SQL_TRACE) Diagnostics for Performance IssuesNote 749227.1 - * How to Gather Optimizer Statistics on 11gNote 1359094.1 - FAQ: How to Use AWR reports to Diagnose Database Performance IssuesNote 1320966.1 - Things to Consider Before Upgrading to 11.2.0.2 to Avoid Poor Performance or Wrong ResultsNote 1392633.1 - Things to Consider Before Upgrading to 11.2.0.3 to Avoid Poor Performance or Wrong Results????????????????”??“???,?????????????????(PDF??)???????????????”Rate this document“????

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  • What's special in July 26th and why is it used in examples for Expires header so often?

    - by zerkms
    I've noticed that July 26th (my birthday) is used really often in various examples related to preventing http caching using Expires header, like: http://stackoverflow.com/questions/12398714/cache-issue-with-private-networking-stream http://stackoverflow.com/questions/2833305/how-to-expire-page-in-php-when-user-logout http://expressionengine.com/archived_forums/viewthread/81945/ What's special in that date? PS: couldn't add conspiracy tag to the tags because of lack of rep points

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  • PMDB Block Size Choice

    - by Brian Diehl
    Choosing a block size for the P6 PMDB database is not a difficult task. In fact, taking the default of 8k is going to be just fine. Block size is one of those things that is always hotly debated. Everyone has their personal preference and can sight plenty of good reasons for their choice. To add to the confusion, Oracle supports multiple block sizes withing the same instance. So how to decide and what is the justification? Like most OLTP systems, Oracle Primavera P6 has a wide variety of data. A typical table's average row size may be less than 50 bytes or upwards of 500 bytes. There are also several tables with BLOB types but the LOB data tends not to be very large. It is likely that no single block size would be perfect for every table. So how to choose? My preference is for the 8k (8192 bytes) block size. It is a good compromise that is not too small for the wider rows, yet not to big for the thin rows. It is also important to remember that database blocks are the smallest unit of change and caching. I prefer to have more, individual "working units" in my database. For an instance with 4gb of buffer cache, an 8k block will provide 524,288 blocks of cache. The following SQL*Plus script returns the average, median, min, and max rows per block. column "AVG(CNT)" format 999.99 set verify off select avg(cnt), median(cnt), min(cnt), max(cnt), count(*) from ( select dbms_rowid.ROWID_RELATIVE_FNO(rowid) , dbms_rowid.ROWID_BLOCK_NUMBER(rowid) , count(*) cnt from &tab group by dbms_rowid.ROWID_RELATIVE_FNO(rowid) , dbms_rowid.ROWID_BLOCK_NUMBER(rowid) ) Running this for the TASK table, I get this result on a database with an 8k block size. Each activity, on average, has about 19 rows per block. Enter value for tab: task AVG(CNT) MEDIAN(CNT) MIN(CNT) MAX(CNT) COUNT(*) -------- ----------- ---------- ---------- ---------- 18.72 19 3 28 415917 I recommend an 8k block size for the P6 transactional database. All of our internal performance and scalability test are done with this block size. This does not mean that other block sizes will not work. Instead, like many other parameters, this is the safest choice.

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  • How can I get rid of just the untracked files in git?

    - by dukeofgaming
    In Mercurial I can do this with the bundled Purge Extension and executing the following command: hg purge Also good to get rid of ignored files: hg purge --all I'm curious about the most practical/used equivalent solution in git. Edit: I want to just get rid of the untracked files, not reset everything (e.g. suppose I have a program generating cache files or generated code and I want to delete them with git's help)

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  • A quick look at: sys.dm_os_buffer_descriptors

    - by fatherjack
    SQL Server places data into cache as it reads it from disk so as to speed up future queries. This dmv lets you see how much data is cached at any given time and knowing how this changes over time can help you ensure your servers run smoothly and are adequately resourced to run your systems. This dmv gives the number of cached pages in the buffer pool along with the database id that they relate to: USE [tempdb] GO SELECT COUNT(*) AS cached_pages_count , CASE database_id ...(read more)

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  • where are apt-get files stored?

    - by loolooyyyy
    i have an ubuntu with three virtual machines running inside running ubuntu also i update the host using apt-get update but i can update VM's, it takes a long time + uses a lot of bandwith which i'm running out of,i want to transfer the updated files by apt-get to VMs, could you please tell me where are they? i'm not talking about the packages themselves stored in /var/cache/apt/archives, i want the file that stores list of available packages on mirror i have selected, thanks lot ps: i know this question has been asked somewhere but i cant find it!

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  • Lancement proche d'une API Google+ pour les photos et vidéos annoncée par erreur, les pages s'ouvrent aux solutions tierces d'entreprise

    Lancement proche d'une API Google+ pour les photos et vidéos Annoncée prématurément par erreur, les pages s'ouvrent aux solutions d'entreprises tierces Mise à jour du 16 novembre 2011 par Idelways Avec la publication par erreur d'un billet de blog et son retrait rapide trahi par le cache de Google et les différents flux, l'entreprise a anticipé l'annonce d'une nouvelle API permettant d'accéder aux albums photo et vidéo postés sur le réseau social Google+. L'ingénieur Yongzhu Li a expliqué sur le blog officiel de la plateforme Google+ (exemple de code à l'appui) que la nouvelle API donnera accès aux contenus multimédias d...

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  • Upgrade from 12.04 to 12.10 Failed due to network troubles

    - by user99100
    Every time I try and upgrade from 12.04 to 12.10 it keeps telling me that there are network problems. Is this a problem on "the other" side? My upgrade got through downloading half the packages last night but then went into sleep and then failed. Could it have something to do with that? Would I need to open a terminal and clear a "cache" (no idea what I'm talking about here) Thanks (Solved now, tried it again through out the day and it downloaded and installed fine)

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  • Disallowed images in the robots.txt of my Joomla site can't be displayed when shared in Facebook

    - by opk
    I have noticed that since I have disallowed images using the robots.txt in my Joomla site, when sharing an article in Facebook, the image will not be displayed. Why is that? Is it indeed related? My robots.txt file: User-agent: * Disallow: /administrator/ Disallow: /cache/ Disallow: /cli/ Disallow: /components/ Disallow: /images/ Disallow: /includes/ Disallow: /installation/ Disallow: /language/ Disallow: /libraries/ Disallow: /logs/ Disallow: /media/ Disallow: /modules/ Disallow: /plugins/ Disallow: /templates/ Disallow: /tmp/

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  • Can I turn off global menu only in Nautilus?

    - by Syzygy
    According to post #15 of this Ubuntu Forums thread about Nautilus being slow, turning off global menu speeds Nautilus up significantly. This is certainly true for me, as running Nautilus as root makes it a few times (!) faster (with no gnome-scripts installed, cache cleared, Dropbox turned off). Now, I like the global menu--but I also want Nautilus to be fast! Is there a way to turn off the global menu only for Nautilus?

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  • A quick look at: sys.dm_os_buffer_descriptors

    - by fatherjack
    SQL Server places data into cache as it reads it from disk so as to speed up future queries. This dmv lets you see how much data is cached at any given time and knowing how this changes over time can help you ensure your servers run smoothly and are adequately resourced to run your systems. This dmv gives the number of cached pages in the buffer pool along with the database id that they relate to: USE [tempdb] GO SELECT COUNT(*) AS cached_pages_count , CASE database_id ...(read more)

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  • Oracle présente sa solution « in-memory » pour concurrencer SAP et Microsoft, l'option sera disponible avec Oracle Database 12c dans un mois

    Oracle présente sa solution « in-memory » pour concurrencer SAP et Microsoft l'option sera disponible avec Oracle Database 12c dans un moisDans le secteur des bases de données, la tendance est à la course aux performances avec la nouvelle option « in-Memory », un concept qui consiste à mettre en cache les données traitées par les applications plutôt que, par exemple, de faire des appels à un serveur.SAP a été le pionnier des solutions in-memory avec sa solution « SAP in-memory » incluse dans la...

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  • Unable to access “430 GB Volume”

    - by user170924
    Error mounting /dev/sda3 at /media/fehr/D42CAFD92CAFB4C0: Command-line `mount -t "ntfs" -o "uhelper=udisks2,nodev,nosuid,uid=1000,gid=1000,dmask=0077,fmask=0177" "/dev/sda3" "/media/fehr/D42CAFD92CAFB4C0"' exited with non-zero exit status 14: The disk contains an unclean file system (0, 0). Metadata kept in Windows cache, refused to mount. Failed to mount '/dev/sda3': Operation not permitted The NTFS partition is in an unsafe state. Please resume and shutdown Windows fully (no hibernation or fast restarting), or mount the volume read-only with the 'ro' mount option.

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  • Markus Zirn, "Big Data with CEP and SOA" @ SOA, Cloud &amp; Service Technology Symposium 2012

    - by JuergenKress
    ORACLE PROMOTIONAL DISCOUNT FOR EXCLUSIVE ORACLE DISCOUNT, ENTER PROMO CODE: DJMXZ370 Early-Bird Registration is Now Open with Special Pricing! Register before July 1, 2012 to qualify for discounts. Visit the Registration page for details. The International SOA, Cloud + Service Technology Symposium is a yearly event that features the top experts and authors from around the world, providing a series of keynotes, talks, demonstrations, and panels, as well as training and certification workshops - all dedicated to empowering IT professionals to realize modern service technologies and practices in the real world. Click here for a two-page printable conference overview (PDF). Big Data with CEP and SOA - September 25, 2012 - 14:15 Speaker: Markus Zirn, Oracle and Baz Kuthi, Avocent The "Big Data" trend is driving new kinds of IT projects that process machine-generated data. Such projects store and mine using Hadoop/ Map Reduce, but they also analyze streaming data via event-driven patterns, which can be called "Fast Data" complementary to "Big Data". This session highlights how "Big Data" and "Fast Data" design patterns can be combined with SOA design principles into modern, event-driven architectures. We will describe specific architectures that combines CEP, Distributed Caching, Event-driven Network, SOA Composites, Application Development Framework, as well as Hadoop. Architecture patterns include pre-processing and filtering event streams as close as possible to the event source, in memory master data for event pattern matching, event-driven user interfaces as well as distributed event processing. Focus is on how "Fast Data" requirements are elegantly integrated into a traditional SOA architecture. Markus Zirn is Vice President of Product Management covering Oracle SOA Suite, SOA Governance, Application Integration Architecture, BPM, BPM Solutions, Complex Event Processing and UPK, an end user learning solution. He is the author of “The BPEL Cookbook” (rated best book on Services Oriented Architecture in 2007) as well as “Fusion Middleware Patterns”. Previously, he was a management consultant with Booz Allen & Hamilton’s High Tech practice in Duesseldorf as well as San Francisco and Vice President of Product Marketing at QUIQ. Mr. Zirn holds a Masters of Electrical Engineering from the University of Karlsruhe and is an alumnus of the Tripartite program, a joint European degree from the University of Karlsruhe, Germany, the University of Southampton, UK, and ESIEE, France. KEYNOTES & SPEAKERS More than 80 international subject matter experts will be speaking at the Symposium. Below are confirmed keynotes and speakers so far. Over 50% of the agenda has not yet been finalized. Many more speakers to come. View the partial program calendars on the Conference Agenda page. CONFERENCE THEMES & TRACKS Cloud Computing Architecture & Patterns New SOA & Service-Orientation Practices & Models Emerging Service Technology Innovation Service Modeling & Analysis Techniques Service Infrastructure & Virtualization Cloud-based Enterprise Architecture Business Planning for Cloud Computing Projects Real World Case Studies Semantic Web Technologies (with & without the Cloud) Governance Frameworks for SOA and/or Cloud Computing Projects Service Engineering & Service Programming Techniques Interactive Services & the Human Factor New REST & Web Services Tools & Techniques Oracle Specialized SOA & BPM Partners Oracle Specialized partners have proven their skills by certifications and customer references. To find a local Specialized partner please visit http://solutions.oracle.com SOA & BPM Partner Community For regular information on Oracle SOA Suite become a member in the SOA & BPM Partner Community for registration please visit  www.oracle.com/goto/emea/soa (OPN account required) If you need support with your account please contact the Oracle Partner Business Center. Blog Twitter LinkedIn Mix Forum Technorati Tags: Markus Zirn,SOA Symposium,Thomas Erl,SOA Community,Oracle SOA,Oracle BPM,BPM Community,OPN,Jürgen Kress

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  • Windows Azure Use Case: Web Applications

    - by BuckWoody
    This is one in a series of posts on when and where to use a distributed architecture design in your organization's computing needs. You can find the main post here: http://blogs.msdn.com/b/buckwoody/archive/2011/01/18/windows-azure-and-sql-azure-use-cases.aspx  Description: Many applications have a requirement to be located outside of the organization’s internal infrastructure control. For instance, the company website for a brick-and-mortar retail company may want to post not only static but interactive content to be available to their external customers, and not want the customers to have access inside the organization’s firewall. There are also cases of pure web applications used for a great many of the internal functions of the business. This allows for remote workers, shared customer/employee workloads and data and other advantages. Some firms choose to host these web servers internally, others choose to contract out the infrastructure to an “ASP” (Application Service Provider) or an Infrastructure as a Service (IaaS) company. In any case, the design of these applications often resembles the following: In this design, a server (or perhaps more than one) hosts the presentation function (http or https) access to the application, and this same system may hold the computational aspects of the program. Authorization and Access is controlled programmatically, or is more open if this is a customer-facing application. Storage is either placed on the same or other servers, hosted within an RDBMS or NoSQL database, or a combination of the options, all coded into the application. High-Availability within this scenario is often the responsibility of the architects of the application, and by purchasing more hosting resources which must be built, licensed and configured, and manually added as demand requires, although some IaaS providers have a partially automatic method to add nodes for scale-out, if the architecture of the application supports it. Disaster Recovery is the responsibility of the system architect as well. Implementation: In a Windows Azure Platform as a Service (PaaS) environment, many of these architectural considerations are designed into the system. The Azure “Fabric” (not to be confused with the Azure implementation of Application Fabric - more on that in a moment) is designed to provide scalability. Compute resources can be added and removed programmatically based on any number of factors. Balancers at the request-level of the Fabric automatically route http and https requests. The fabric also provides High-Availability for storage and other components. Disaster recovery is a shared responsibility between the facilities (which have the ability to restore in case of catastrophic failure) and your code, which should build in recovery. In a Windows Azure-based web application, you have the ability to separate out the various functions and components. Presentation can be coded for multiple platforms like smart phones, tablets and PC’s, while the computation can be a single entity shared between them. This makes the applications more resilient and more object-oriented, and lends itself to a SOA or Distributed Computing architecture. It is true that you could code up a similar set of functionality in a traditional web-farm, but the difference here is that the components are built into the very design of the architecture. The API’s and DLL’s you call in a Windows Azure code base contains components as first-class citizens. For instance, if you need storage, it is simply called within the application as an object.  Computation has multiple options and the ability to scale linearly. You also gain another component that you would either have to write or bolt-in to a typical web-farm: the Application Fabric. This Windows Azure component provides communication between applications or even to on-premise systems. It provides authorization in either person-based or claims-based perspectives. SQL Azure provides relational storage as another option, and can also be used or accessed from on-premise systems. It should be noted that you can use all or some of these components individually. Resources: Design Strategies for Scalable Active Server Applications - http://msdn.microsoft.com/en-us/library/ms972349.aspx  Physical Tiers and Deployment  - http://msdn.microsoft.com/en-us/library/ee658120.aspx

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  • Oracle Big Data Software Downloads

    - by Mike.Hallett(at)Oracle-BI&EPM
    Companies have been making business decisions for decades based on transactional data stored in relational databases. Beyond that critical data, is a potential treasure trove of less structured data: weblogs, social media, email, sensors, and photographs that can be mined for useful information. Oracle offers a broad integrated portfolio of products to help you acquire and organize these diverse data sources and analyze them alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data Connectors Downloads here, includes: Oracle SQL Connector for Hadoop Distributed File System Release 2.1.0 Oracle Loader for Hadoop Release 2.1.0 Oracle Data Integrator Companion 11g Oracle R Connector for Hadoop v 2.1 Oracle Big Data Documentation The Oracle Big Data solution offers an integrated portfolio of products to help you organize and analyze your diverse data sources alongside your existing data to find new insights and capitalize on hidden relationships. Oracle Big Data, Release 2.2.0 - E41604_01 zip (27.4 MB) Integrated Software and Big Data Connectors User's Guide HTML PDF Oracle Data Integrator (ODI) Application Adapter for Hadoop Apache Hadoop is designed to handle and process data that is typically from data sources that are non-relational and data volumes that are beyond what is handled by relational databases. Typical processing in Hadoop includes data validation and transformations that are programmed as MapReduce jobs. Designing and implementing a MapReduce job usually requires expert programming knowledge. However, when you use Oracle Data Integrator with the Application Adapter for Hadoop, you do not need to write MapReduce jobs. Oracle Data Integrator uses Hive and the Hive Query Language (HiveQL), a SQL-like language for implementing MapReduce jobs. Employing familiar and easy-to-use tools and pre-configured knowledge modules (KMs), the application adapter provides the following capabilities: Loading data into Hadoop from the local file system and HDFS Performing validation and transformation of data within Hadoop Loading processed data from Hadoop to an Oracle database for further processing and generating reports Oracle Database Loader for Hadoop Oracle Loader for Hadoop is an efficient and high-performance loader for fast movement of data from a Hadoop cluster into a table in an Oracle database. It pre-partitions the data if necessary and transforms it into a database-ready format. Oracle Loader for Hadoop is a Java MapReduce application that balances the data across reducers to help maximize performance. Oracle R Connector for Hadoop Oracle R Connector for Hadoop is a collection of R packages that provide: Interfaces to work with Hive tables, the Apache Hadoop compute infrastructure, the local R environment, and Oracle database tables Predictive analytic techniques, written in R or Java as Hadoop MapReduce jobs, that can be applied to data in HDFS files You install and load this package as you would any other R package. Using simple R functions, you can perform tasks such as: Access and transform HDFS data using a Hive-enabled transparency layer Use the R language for writing mappers and reducers Copy data between R memory, the local file system, HDFS, Hive, and Oracle databases Schedule R programs to execute as Hadoop MapReduce jobs and return the results to any of those locations Oracle SQL Connector for Hadoop Distributed File System Using Oracle SQL Connector for HDFS, you can use an Oracle Database to access and analyze data residing in Hadoop in these formats: Data Pump files in HDFS Delimited text files in HDFS Hive tables For other file formats, such as JSON files, you can stage the input in Hive tables before using Oracle SQL Connector for HDFS. Oracle SQL Connector for HDFS uses external tables to provide Oracle Database with read access to Hive tables, and to delimited text files and Data Pump files in HDFS. Related Documentation Cloudera's Distribution Including Apache Hadoop Library HTML Oracle R Enterprise HTML Oracle NoSQL Database HTML Recent Blog Posts Big Data Appliance vs. DIY Price Comparison Big Data: Architecture Overview Big Data: Achieve the Impossible in Real-Time Big Data: Vertical Behavioral Analytics Big Data: In-Memory MapReduce Flume and Hive for Log Analytics Building Workflows in Oozie

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  • MySQL Cluster 7.3: On-Demand Webinar and Q&A Available

    - by Mat Keep
    The on-demand webinar for the MySQL Cluster 7.3 Development Release is now available. You can learn more about the design, implementation and getting started with all of the new MySQL Cluster 7.3 features from the comfort and convenience of your own device, including: - Foreign Key constraints in MySQL Cluster - Node.js NoSQL API  - Auto-installation of higher performance distributed, clusters We received some great questions over the course of the webinar, and I wanted to share those for the benefit of a broader audience. Q. What Foreign Key actions are supported: A. The core referential actions defined in the SQL:2003 standard are implemented: CASCADE RESTRICT NO ACTION SET NULL Q. Where are Foreign Keys implemented, ie data nodes or SQL nodes? A. They are implemented in the data nodes, therefore can be enforced for both the SQL and NoSQL APIs Q. Are they compatible with the InnoDB Foreign Key implementation? A. Yes, with the following exceptions: - InnoDB doesn’t support “No Action” constraints, MySQL Cluster does - You can choose to suspend FK constraint enforcement with InnoDB using the FOREIGN_KEY_CHECKS parameter; at the moment, MySQL Cluster ignores that parameter. - You cannot set up FKs between 2 tables where one is stored using MySQL Cluster and the other InnoDB. - You cannot change primary keys through the NDB API which means that the MySQL Server actually has to simulate such operations by deleting and re-adding the row. If the PK in the parent table has a FK constraint on it then this causes non-ideal behaviour. With Restrict or No Action constraints, the change will result in an error. With Cascaded constraints, you’d want the rows in the child table to be updated with the new FK value but, the implicit delete of the row from the parent table would remove the associated rows from the child table and the subsequent implicit insert into the parent wouldn’t reinstate the child rows. For this reason, an attempt to add an ON UPDATE CASCADE where the parent column is a primary key will be rejected. Q. Does adding or dropping Foreign Keys cause downtime due to a schema change? A. Nope, this is an online operation. MySQL Cluster supports a number of on-line schema changes, ie adding and dropping indexes, adding columns, etc. Q. Where can I see an example of node.js with MySQL Cluster? A. Check out the tutorial and download the code from GitHub Q. Can I use the auto-installer to support remote deployments? How about setting up MySQL Cluster 7.2? A. Yes to both! Q. Can I get a demo Check out the tutorial. You can download the code from http://labs.mysql.com/ Go to Select Build drop-down box Q. What is be minimum internet speen required for Geo distributed cluster with synchronous replication? A. if you're splitting you cluster between sites then we recommend a network latency of 20ms or less. Alternatively, use MySQL asynchronous replication where the latency of your WAN doesn't impact the latency of your reads/writes. Q. Where you can one learn more about the PayPal project with MySQL Cluster? A. Take a look at the following - you'll find press coverage, a video and slides from their keynote presentation  So, if you want to learn more, listen to the new MySQL Cluster 7.3 on-demand webinar  MySQL Cluster 7.3 is still in the development phase, so it would be great to get your feedback on these new features, and things you want to see!

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  • Orchestrating the Virtual Enterprise, Part II

    - by Kathryn Perry
    A guest post by Jon Chorley, Oracle's CSO & Vice President, SCM Product Strategy Almost everyone has ordered from Amazon.com at one time or another. Our orders are as likely to be fulfilled by third parties as they are by Amazon itself. To deliver the order promptly and efficiently, Amazon has to send it to the right fulfillment location and know the availability in that location. It needs to be able to track status of the fulfillment and deal with exceptions. As a virtual enterprise, Amazon's operations, using thousands of trading partners, requires a very different approach to fulfillment than the traditional 'take an order and ship it from your own warehouse' model. Amazon had no choice but to develop a complex, expensive and custom solution to tackle this problem as there used to be no product solution available. Now, other companies who want to follow similar models have a better off-the-shelf choice -- Oracle Distributed Order Orchestration (DOO).  Consider how another of our customers is using our distributed orchestration solution. This major airplane manufacturer has a highly complex business and interacts regularly with the U.S. Government and major airlines. It sits in the middle of an intricate supply chain and needed to improve visibility across its many different entities. Oracle Fusion DOO gives the company an orchestration mechanism so it could improve quality, speed, flexibility, and consistency without requiring an organ transplant of these highly complex legacy systems. Many retailers face the challenge of dealing with brick and mortar, Web, and reseller channels. They all need to be knitted together into a virtual enterprise experience that is consistent for their customers. When a large U.K. grocer with a strong brick and mortar retail operation added an online business, they turned to Oracle Fusion DOO to bring these entities together. Disturbing the Peace with Acquisitions Quite often a company's ERP system is disrupted when it acquires a new company. An acquisition can inject a new set of processes and systems -- or even introduce an entirely new business like Sun's hardware did at Oracle. This challenge has been a driver for some of our DOO customers. A large power management company is using Oracle Fusion DOO to provide the flexibility to rapidly integrate additional products and services into its central fulfillment operation. The Flip Side of Fulfillment Meanwhile, we haven't ignored similar challenges on the supply side of the equation. Specifically, how to manage complex supply in a flexible way when there are multiple trading parties involved? How to manage the supply to suppliers? How to manage critical components that need to merge in a tier two or tier three supply chain? By investing in supply orchestration solutions for the virtual enterprise, we plan to give users better visibility into their network of suppliers to help them drive down costs. We also think this technology and full orchestration process can be applied to the financial side of organizations. An example is transactions that flow through complex internal structures to minimize tax exposure. We can help companies manage those transactions effectively by thinking about the internal organization as a virtual enterprise and bringing the same solution set to this internal challenge.  The Clear Front Runner No other company is investing in solving the virtual enterprise supply chain issues like Oracle is. Oracle is in a unique position to become the gold standard in this market space. We have the infrastructure of Oracle technology. We already have an Oracle Fusion DOO application which embraces the best of what's required in this area. And we're absolutely committed to extending our Fusion solution to other use cases and delivering even more business value. Jon ChorleyChief Sustainability Officer & Vice President, SCM Product StrategyOracle Corporation

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  • Blueprints for Oracle NoSQL Database

    - by dan.mcclary
    I think that some of the most interesting analytic problems are graph problems.  I'm always interested in new ways to store and access graphs.  As such, I really like the work being done by Tinkerpop to create Open Source Software to make property graphs more accessible over a wide variety of datastores.  Since key-value stores like Oracle NoSQL Database are well-suited to storing property graphs, I decided to extend the Blueprints API to work with it.  Below I'll discuss some of the implementation details, but you can check out the finished product here: http://github.com/dwmclary/blueprints-oracle-nosqldb.  What's in a Property Graph?  In the most general sense, a graph is just a collection of vertices and edges.  Vertices and edges can have properties: weights, names, or any number of other traits.  In an undirected graph, edges connect vertices without direction.  A directed graph specifies that all edges have a head and a tail --- a direction.  A multi-graph allows multiple edges to connect two vertices.  A "property graph" encompasses all of these traits. Key-Value Stores for Property Graphs Key-Value stores like Oracle NoSQL Database tend to be ideal for implementing property graphs.  First, if any vertex or edge can have any number of traits, we can treat it as a hash map.  For example: Vertex["name"] = "Mary" Vertex["age"] = 28 Vertex["ID"] = 12345  and so on.  This is a natural key-value relationship: the key "name" maps to the value "Mary."  Moreover if we maintain two hash maps, one for vertex objects and one for edge objects, we've essentially captured the graph.  As such, any scalable key-value store is fertile ground for planting graphs. Oracle NoSQL Database as a Scalable Graph Database While Oracle NoSQL Database offers useful features like tunable consistency, what lends it to storing property graphs is the storage guarantees around its key structure.  Keys in Oracle NoSQL Database are divided into two parts: a major key and a minor key.  The storage guarantee is simple.  Major keys will be distributed across storage nodes, which could encompass a large number of servers.  However, all minor keys which are children of a given major key are guaranteed to be stored on the same storage node.  For example, the vertices: /Personnel/Vertex/1  and /Personnel/Vertex/2 May be stored on different servers, but /Personnel/Vertex/1-/name and  /Personnel/Vertex/1-/age will always be on the same server.  This means that we can structure our graph database such that retrieving all the properties for a vertex or edge requires I/O from only a single storage node.  Moreover, Oracle NoSQL Database provides a storeIterator which allows us to store a huge number of vertices and edges in a scalable fashion.  By storing the vertices and edges as major keys, we guarantee that they are distributed evenly across all storage nodes.  At the same time we can use a partial major key to iterate over all the vertices or edges (e.g. we search over /Personnel/Vertex to iterate over all vertices). Fork It! The Blueprints API and Oracle NoSQL Database present a great way to get started using a scalable key-value database to store and access graph data.  However, a graph store isn't useful without a good graph to work on.  I encourage you to fork or pull the repository, store some data, and try using Gremlin or any other language to explore.

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  • My Dog, Cross-Channel Shopping, and Fusion SCM

    - by Kathryn Perry
    A guest post by Mark Carson, Director, Oracle Fusion Supply Chain Management I was walking my dog Max in an open space behind my house. As we tromped through the tall weeds I remembered it is tick season and that I should get Max some protection. While he sniffed merrily in the tick infested brush, I started shopping in the middle of an open field on my phone. I thought it would be convenient to pick up the tick medicine from a pet store on the way home. Searching the pet store website I saw that they had the medicine, but there was no information on whether the store had any in stock and there were no options for shipping it to the store for pickup. I could return it, but not pick it up which seamed kind of odd. I really didn't feel like making calls to the local stores to find out if they had it. Since the product is popular, I tried one of the large 'everything' stores. Browsing its website I could see that it could be shipped to me, shipped to the store for free, and that the store nearest to me had it in stock. Needless to say, this store became a better option. This experience is a small example of why retailers, distributors, and manufactures have placed a high priority on enabling 'cross-channel commerce.' Shoppers like you and me expect to be able to search, compare, buy and return products on-line and over the phone using a variety of devices including PDAs, tablets and in-store kiosks. The pet store lost my business because its web channel had limited information about its stores. I have spoken with many customers and prospects about cross-channel commerce. They all realize the business implications and urgency behind cross-channel commerce but recognize there are challenges to enable it. New and existing applications must be integrated together globally through a consistent cross-channel business process. Integration is required between applications that provide the initial shopping experience and delivery applications associated with warehouses, stores, and partners. The enablement must be accomplished in a flexible way to react to fast-changing product portfolios and new acquisitions, while at the same time minimizing costs through reuse of existing systems. Meanwhile, the business must continue to grow and decision makers need to balance new capability with peak seasons. The challenges above are not unique to retail. Any customer in any industry who has multiple points for capturing orders and multiple points for fulfilling orders will face these challenges. With this in mind, we had a unique opportunity in Fusion SCM to re-think how to build a set of modular and flexible applications in the order management space that would make these challenges easier to conquer. The results are Fusion Distributed Order Orchestration and Global Order Promising. These applications can help companies, such as the pet store, enable true cross-channel commerce. The apps provide highly adaptable and flexible business processes to automate order orchestration across multiple cross-channel systems. They also show a global view of supply across warehouses, stores, and partners for real-time availability and more accurate order promising. Additional capability includes a standards-based integration framework for seamless execution and the ability to reuse existing systems for faster and lower cost implementations. OK, that was a mouthful of features and benefits. As Max waited to cross the street (he can do basic math too), I wondered if he could relate. He does not care about leash laws, pick-up courtesy, where he can/can't walk, what time of day it is, or even ticks. He does not care about how all these things could make walking complicated. He just wants to walk. Similarly, customers just want to shop and companies just want to make it easier to sell and deliver. You can learn more about Distributed Order Orchestration and Global Order Promising in cross-channel here.

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  • New R Interface to Oracle Data Mining Available for Download

    - by charlie.berger
      The R Interface to Oracle Data Mining ( R-ODM) allows R users to access the power of Oracle Data Mining's in-database functions using the familiar R syntax. R-ODM provides a powerful environment for prototyping data analysis and data mining methodologies. R-ODM is especially useful for: Quick prototyping of vertical or domain-based applications where the Oracle Database supports the application Scripting of "production" data mining methodologies Customizing graphics of ODM data mining results (examples: classification, regression, anomaly detection) The R-ODM interface allows R users to mine data using Oracle Data Mining from the R programming environment. It consists of a set of function wrappers written in source R language that pass data and parameters from the R environment to the Oracle RDBMS enterprise edition as standard user PL/SQL queries via an ODBC interface. The R-ODM interface code is a thin layer of logic and SQL that calls through an ODBC interface. R-ODM does not use or expose any Oracle product code as it is completely an external interface and not part of any Oracle product. R-ODM is similar to the example scripts (e.g., the PL/SQL demo code) that illustrates the use of Oracle Data Mining, for example, how to create Data Mining models, pass arguments, retrieve results etc. R-ODM is packaged as a standard R source package and is distributed freely as part of the R environment's Comprehensive R Archive Network (CRAN). For information about the R environment, R packages and CRAN, see www.r-project.org. R-ODM is particularly intended for data analysts and statisticians familiar with R but not necessarily familiar with the Oracle database environment or PL/SQL. It is a convenient environment to rapidly experiment and prototype Data Mining models and applications. Data Mining models prototyped in the R environment can easily be deployed in their final form in the database environment, just like any other standard Oracle Data Mining model. What is R? R is a system for statistical computation and graphics. It consists of a language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files. The design of R has been heavily influenced by two existing languages: Becker, Chambers & Wilks' S and Sussman's Scheme. Whereas the resulting language is very similar in appearance to S, the underlying implementation and semantics are derived from Scheme. R was initially written by Ross Ihaka and Robert Gentleman at the Department of Statistics of the University of Auckland in Auckland, New Zealand. Since mid-1997 there has been a core group (the "R Core Team") who can modify the R source code archive. Besides this core group many R users have contributed application code as represented in the near 1,500 publicly-available packages in the CRAN archive (which has shown exponential growth since 2001; R News Volume 8/2, October 2008). Today the R community is a vibrant and growing group of dozens of thousands of users worldwide. It is free software distributed under a GNU-style copyleft, and an official part of the GNU project ("GNU S"). Resources: R website / CRAN R-ODM

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  • Application Logging needs work

    Application Logging Application logging is the act of logging events that occur within an application much like how a court report documents what happens in court case. Application logs can be useful for several reasons, but the most common use for logs is to recreate steps to find the root cause of applications errors. Other uses can include the detection of Fraud, verification of user activity, or provide audits on user/data interactions. “Logs can contain different kinds of data. The selection of the data used is normally affected by the motivation leading to the logging. “ (OWASP, 2009) OWASP also stats that logging include applicable debugging information like the event date time, responsible process, and a description of the event. “There are many reasons why a logging system is a necessary part of delivering a distributed application. One of the most important is the ability to track exactly how many users are using the application during different time periods.” (Hatton, 2000) Hatton also states that application logging helps system designers determine whether parts of an application aren't being used as designed. He implies that low usage can be used to identify if users like or do not like aspects of a system based on user usage of the application. This enables application designers to extract why users don't like aspects of an application so that changes can be made to increase its usefulness and effectiveness. “Logging memory usage can also assist you in tuning up the internals of your application. If you're experiencing a randomly occurring problem, being able to match activities performed with the memory status at the time may enable you to discover the cause of the problem. It also gives you a good indication of the health of the distributed server machine at the time any activity is performed. “ (Hatton, 2000) Commonly Logged Application Events (Defined by OWASP) Access of Data Creation of Data Modification of Data in any form Administrative Functions  Configuration Changes Debugging Information(Application Events)  Authorization Attempts  Data Deletion Network Communication  Authentication Events  Errors/Exceptions Application Error Logging The functionality associated with application error logging is actually the combination of proper error handling and applications logging.  If we look back at Figure 4 and Figure 5, these code examples allow developers to handle various types of errors that occur within the life cycle of an application’s execution. Application logging can be applied within the Catch section of the TryCatch statement allowing for the errors to be logged when they occur. By placing the logging within the Catch section specific error details can be accessed that help identify the source of the error, the path to the error, what caused the error and definition of the error that occurred. This can then be logged and reviewed at a later date in order recreate the error that was received based data found in the application log. By allowing applications to log errors developers IT staff can use them to recreate errors that are encountered by end-users or other dependent systems.

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  • Webcast On-Demand: Building Java EE Apps That Scale

    - by jeckels
    With some awesome work by one of our architects, Randy Stafford, we recently completed a webcast on scaling Java EE apps efficiently. Did you miss it? No problem. We have a replay available on-demand for you. Just hit the '+' sign drop-down for access.Topics include: Domain object caching Service response caching Session state caching JSR-107 HotCache and more! Further, we had several interesting questions asked by our audience, and we thought we'd share a sampling of those here for you - just in case you had the same queries yourself. Enjoy! What is the largest Coherence deployment out there? We have seen deployments with over 500 JVMs in the Coherence cluster, and deployments with over 1000 JVMs using the Coherence jar file, in one system. On the management side there is an ecosystem of monitoring tools from Oracle and third parties with dashboards graphing values from Coherence's JMX instrumentation. For lifecycle management we have seen a lot of custom scripting over the years, but we've also integrated closely with WebLogic to leverage its management ecosystem for deploying Coherence-based applications and managing process life cycles. That integration introduces a new Java EE archive type, the Grid Archive or GAR, which embeds in an EAR and can be seen by a WAR in WebLogic. That integration also doesn't require any extra WebLogic licensing if Coherence is licensed. How is Coherence different from a NoSQL Database like MongoDB? Coherence can be considered a NoSQL technology. It pre-dates the NoSQL movement, having been first released in 2001 whereas the term "NoSQL" was coined in 2009. Coherence has a key-value data model primarily but can also be used for document data models. Coherence manages data in memory currently, though disk persistence is in a future release currently in beta testing. Where the data is managed yields a few differences from the most well-known NoSQL products: access latency is faster with Coherence, though well-known NoSQL databases can manage more data. Coherence also has features that well-known NoSQL database lack, such as grid computing, eventing, and data source integration. Finally Coherence has had 15 years of maturation and hardening from usage in mission-critical systems across a variety of industries, particularly financial services. Can I use Coherence for local caching? Yes, you get additional features beyond just a java.util.Map: you get expiration capabilities, size-limitation capabilities, eventing capabilites, etc. Are there APIs available for GoldenGate HotCache? It's mostly a black box. You configure it, and it just puts objects into your caches. However you can treat it as a glass box, and use Coherence event interceptors to enhance its behavior - and there are use cases for that. Are Coherence caches updated transactionally? Coherence provides several mechanisms for concurrency control. If a project insists on full-blown JTA / XA distributed transactions, Coherence caches can participate as resources. But nobody does that because it's a performance and scalability anti-pattern. At finer granularity, Coherence guarantees strict ordering of all operations (reads and writes) against a single cache key if the operations are done using Coherence's "EntryProcessor" feature. And Coherence has a unique feature called "partition-level transactions" which guarantees atomic writes of multiple cache entries (even in different caches) without requiring JTA / XA distributed transaction semantics.

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  • TransactionScope won't work with DB2 provider

    - by Florin
    Hi Everyone, I've been trying to use TransactionScope with a DB2 database (using DB2 .Net provider v 9.0.0.2 and c# 2.0) which SHOULD be supported according to IBM. I have tried all the advice i could find on the IBM forums (such as here) to no avail. I have enabled XA transactions on my XP Sp2 machine, tried also from a Win 2003 Server machine but i consistently get the infamous error: ERROR [58005] [IBM][DB2/NT] SQL0998N Error occurred during transaction or heuristic processing. Reason Code = "16". Subcode = "2-80004005". SQLSTATE=58005 The windows event log says: The XA Transaction Manager attempted to load the XA resource manager DLL. The call to LOADLIBRARY for the XA resource manager DLL failed: DLL=C:\APPS\IBM\DB2v95fp2\SQLLIB\BIN\DB2APP.DLL File=d:\comxp_sp2\com\com1x\dtc\dtc\xatm\src\xarmconn.cpp Line=2467. Also, granted the NETWORK SERVICE user full rights to the folder and dll. Here's the MSDTC startup message MS DTC started with the following settings: Security Configuration (OFF = 0 and ON = 1): Network Administration of Transactions = 0, Network Clients = 0, Inbound Distributed Transactions using Native MSDTC Protocol = 0, Outbound Distributed Transactions using Native MSDTC Protocol = 0, Transaction Internet Protocol (TIP) = 0, XA Transactions = 1 Any help would be much appreciated! Thanks, Florin

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