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  • Enterprise class storage best practices

    - by churnd
    One thing that has always perplexed me is storage best practices. Filesystems brag about how they can be petabytes or exabytes in size. Yet, I do not know many sysadmins who are willing to let a single volume grow over several terrabytes. I do know the primary reason behind this is how long it would take to rebuild the array should a drive fail. The more drives in a single LUN, the longer this takes and the greater your risk of losing another drive while the rebuild is taking place. Then there's usage reasons. Admins will carve out a LUN based on how much space they think needs to be allocated to the project. It seems more practical to me for the LUN to be one large array and to use quotas. I understand this wouldn't satisfy every requirement (iSCSI), but I see a lot of NAS systems (NFS) managed this way. I also understand that the underlying volumes can be grown/shrunk as needed quite easily, but wouldn't it be less "risky" to use quotas rather than manipulating volumes and bringing possible data loss into the equation? There may be some other reasons I'm missing, so please enlighten me. Can we not expect filesystems to ever be so large? Are we waiting for the hardware to get faster to cut down on rebuild times?

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  • How to diagnose storage system scaling problems?

    - by Unknown
    We are currently testing the maximum sequential read throughput of a storage system (48 disks total behind two HP P2000 arrays) connected to HP DL580 G7 running RHEL 5 with 128 GB of memory. Initial testing has been mainly done by running DD-commands like this: dd if=/dev/mapper/mpath1 of=/dev/null bs=1M count=3000 In parallel for each disk. However, we have been unable to scale the results from one array (maximum throughput of 1.3 GB/s) to two (almost the same throughput). Each array is connected to a dedicated host bust adapter, so they should not be the bottleneck. The disks are currently in JBOD configuration, so each disk can be addressed directly. I have two questions: Is running multiple DD commands in parallel really a good way to test maximum read throughput? We have noticed very high SWAPIN-% numbers in iotop, which I find hard to explain because the target is /dev/null How shoud we proceed in trying to find the reason for the scaling problem? Do you thing the server itself is the bottleneck here, or could there be some linux parameters that we have overlooked?

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  • Big Data – Buzz Words: What is Hadoop – Day 6 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is NoSQL. In this article we will take a quick look at one of the four most important buzz words which goes around Big Data – Hadoop. What is Hadoop? Apache Hadoop is an open-source, free and Java based software framework offers a powerful distributed platform to store and manage Big Data. It is licensed under an Apache V2 license. It runs applications on large clusters of commodity hardware and it processes thousands of terabytes of data on thousands of the nodes. Hadoop is inspired from Google’s MapReduce and Google File System (GFS) papers. The major advantage of Hadoop framework is that it provides reliability and high availability. What are the core components of Hadoop? There are two major components of the Hadoop framework and both fo them does two of the important task for it. Hadoop MapReduce is the method to split a larger data problem into smaller chunk and distribute it to many different commodity servers. Each server have their own set of resources and they have processed them locally. Once the commodity server has processed the data they send it back collectively to main server. This is effectively a process where we process large data effectively and efficiently. (We will understand this in tomorrow’s blog post). Hadoop Distributed File System (HDFS) is a virtual file system. There is a big difference between any other file system and Hadoop. When we move a file on HDFS, it is automatically split into many small pieces. These small chunks of the file are replicated and stored on other servers (usually 3) for the fault tolerance or high availability. (We will understand this in the day after tomorrow’s blog post). Besides above two core components Hadoop project also contains following modules as well. Hadoop Common: Common utilities for the other Hadoop modules Hadoop Yarn: A framework for job scheduling and cluster resource management There are a few other projects (like Pig, Hive) related to above Hadoop as well which we will gradually explore in later blog posts. A Multi-node Hadoop Cluster Architecture Now let us quickly see the architecture of the a multi-node Hadoop cluster. A small Hadoop cluster includes a single master node and multiple worker or slave node. As discussed earlier, the entire cluster contains two layers. One of the layer of MapReduce Layer and another is of HDFC Layer. Each of these layer have its own relevant component. The master node consists of a JobTracker, TaskTracker, NameNode and DataNode. A slave or worker node consists of a DataNode and TaskTracker. It is also possible that slave node or worker node is only data or compute node. The matter of the fact that is the key feature of the Hadoop. In this introductory blog post we will stop here while describing the architecture of Hadoop. In a future blog post of this 31 day series we will explore various components of Hadoop Architecture in Detail. Why Use Hadoop? There are many advantages of using Hadoop. Let me quickly list them over here: Robust and Scalable – We can add new nodes as needed as well modify them. Affordable and Cost Effective – We do not need any special hardware for running Hadoop. We can just use commodity server. Adaptive and Flexible – Hadoop is built keeping in mind that it will handle structured and unstructured data. Highly Available and Fault Tolerant – When a node fails, the Hadoop framework automatically fails over to another node. Why Hadoop is named as Hadoop? In year 2005 Hadoop was created by Doug Cutting and Mike Cafarella while working at Yahoo. Doug Cutting named Hadoop after his son’s toy elephant. Tomorrow In tomorrow’s blog post we will discuss Buzz Word – MapReduce. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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  • Master Data Management for Location Data - Oracle Site Hub

    - by david.butler(at)oracle.com
    Most MDM discussions cover key domains such as customer, supplier, product, service, and reference data. It is usually understood that these domains have complex structures and hundreds if not thousands of attributes that need governing. Location, on the other hand, strikes most people as address data. How hard can that be? But for many industries, locations are complex, and site information is critical to efficient operations and relevant analytics. Retail stores and malls, bank branches, construction sites come to mind. But one of the best industries for illustrating the power of a site mastering application is Oil & Gas.   Oracle's Master Data Management solution for location data is the Oracle Site Hub. It is a location mastering solution that enables organizations to centralize site and location specific information from heterogeneous systems, creating a single view of site information that can be leveraged across all functional departments and analytical systems.   Let's take a look at the location entities the Oracle Site Hub can manage for the Oil & Gas industry: organizations, property, land, buildings, roads, oilfield, service center, inventory site, real estate, facilities, refineries, storage tanks, vendor locations, businesses, assets; project site, area, well, basin, pipelines, critical infrastructure, offshore platform, compressor station, gas station, etc. Any site can be classified into multiple hierarchies, like organizational hierarchy, operational hierarchy, geographic hierarchy, divisional hierarchies and so on. Any site can also be associated to multiple clusters, i.e. collections of sites, and these can be used as a foundation for driving reporting, analysis, organize daily work, etc. Hierarchies can also be used to model entities which are structured or non-structured collections of nodes, like for example routes, pipelines and more. The User Defined Attribute Framework provides the needed infrastructure to add single row attributes groups like well base attributes (well IDs, well type, well structure and key characterizing measures, and more) and well geometry, and multi row attribute groups like well applications, permits, production data, activities, operations, logs, treatments, tests, drills, treatments, and KPIs. Site Hub can also model areas, lands, fields, basins, pools, platforms, eco-zones, and stratigraphic layers as specific sites, tracking their base attributes, aliases, descriptions, subcomponents and more. Midstream entities (pipelines, logistic sites, pump stations) and downstream entities (cylinders, tanks, inventories, meters, partner's sites, routes, facilities, gas stations, and competitor sites) can also be easily modeled, together with their specific attributes and relationships. Site Hub can store any type of unstructured data associated to a site. This could be stored directly or on an external content management solution, like Oracle Universal Content Management. Considering a well, for example, Site Hub can store any relevant associated multimedia file such as: CAD drawings of the well profile, structure and/or parts, engineering documents, contracts, applications, permits, logs, pictures, photos, videos and more. For any site entity, Site Hub can associate all the related assets and equipments at the site, as well as all relationships between sites, between a site and multiple parties, and between a site and any purchasable or sellable item, over time. Items can be equipment, instruments, facilities, services, products, production entities, production facilities (pipelines, batteries, compressor stations, gas plants, meters, separators, etc.), support facilities (rigs, roads, transmission or radio towers, airstrips, etc.), supplier products and services, catalogs, and more. Items can just be associated to sites using standard Site Hub features, or they can be fully mastered by implementing Oracle Product Hub. Site locations (addresses or geographical coordinates) are also managed with out-of-the-box address geo-coding capabilities coupled with Google Maps integration to deliver powerful mapping capabilities and spatial data analysis. Locations can be shared between different sites. Centered on the site location, any site can also have associated areas. Site Hub can master any site location specific information, like for example cadastral, ownership, jurisdictional, geological, seismic and more, and any site-centric area specific information, like for example economical, political, risk, weather, logistic, traffic information and more. Now if anyone ever asks you why locations need MDM, think about how all these Oil & Gas entities and attributes would translate into your business locations. To learn more about Oracle's full MDM solution for the digital oil field, here is a link to Roberto Negro's outstanding whitepaper: Oracle Site Master Data Management for mastering wells and other PPDM entities in a digital oilfield context  

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  • Optimal Data Structure for our own API

    - by vermiculus
    I'm in the early stages of writing an Emacs major mode for the Stack Exchange network; if you use Emacs regularly, this will benefit you in the end. In order to minimize the number of calls made to Stack Exchange's API (capped at 10000 per IP per day) and to just be a generally responsible citizen, I want to cache the information I receive from the network and store it in memory, waiting to be accessed again. I'm really stuck as to what data structure to store this information in. Obviously, it is going to be a list. However, as with any data structure, the choice must be determined by what data is being stored and what how it will be accessed. What, I would like to be able to store all of this information in a single symbol such as stack-api/cache. So, without further ado, stack-api/cache is a list of conses keyed by last update: `(<csite> <csite> <csite>) where <csite> would be (1362501715 . <site>) At this point, all we've done is define a simple association list. Of course, we must go deeper. Each <site> is a list of the API parameter (unique) followed by a list questions: `("codereview" <cquestion> <cquestion> <cquestion>) Each <cquestion> is, you guessed it, a cons of questions with their last update time: `(1362501715 <question>) (1362501720 . <question>) <question> is a cons of a question structure and a list of answers (again, consed with their last update time): `(<question-structure> <canswer> <canswer> <canswer> and ` `(1362501715 . <answer-structure>) This data structure is likely most accurately described as a tree, but I don't know if there's a better way to do this considering the language, Emacs Lisp (which isn't all that different from the Lisp you know and love at all). The explicit conses are likely unnecessary, but it helps my brain wrap around it better. I'm pretty sure a <csite>, for example, would just turn into (<epoch-time> <api-param> <cquestion> <cquestion> ...) Concerns: Does storing data in a potentially huge structure like this have any performance trade-offs for the system? I would like to avoid storing extraneous data, but I've done what I could and I don't think the dataset is that large in the first place (for normal use) since it's all just human-readable text in reasonable proportion. (I'm planning on culling old data using the times at the head of the list; each inherits its last-update time from its children and so-on down the tree. To what extent this cull should take place: I'm not sure.) Does storing data like this have any performance trade-offs for that which must use it? That is, will set and retrieve operations suffer from the size of the list? Do you have any other suggestions as to what a better structure might look like?

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  • How do you handle the fetchxml result data?

    - by Luke Baulch
    I have avoided working with fetchxml as I have been unsure the best way to handle the result data after calling crmService.Fetch(fetchXml). In a couple of situations, I have used an XDocument with LINQ to retrieve the data from this data structure, such as: XDocument resultset = XDocument.Parse(_service.Fetch(fetchXml)); if (resultset.Root == null || !resultset.Root.Elements("result").Any()) { return; } foreach (var displayItem in resultset.Root.Elements("result").Select(item => item.Element(displayAttributeName)).Distinct()) { if (displayItem!= null && displayItem.Value != null) { dropDownList.Items.Add(displayItem.Value); } } What is the best way to handle fetchxml result data, so that it can be easily used. Applications such as passing these records into an ASP.NET datagrid would be quite useful.

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  • Generate Entity Data Model from Data Contract

    - by CSmooth.net
    I would like to find a fast way to convert a Data Contract to a Entity Data Model. Consider the following Data Contract: [DataContract] class PigeonHouse { [DataMember] public string housename; [DataMember] public List<Pigeon> pigeons; } [DataContract] class Pigeon { [DataMember] public string name; [DataMember] public int numberOfWings; [DataMember] public int age; } Is there an easy way to create an ADO.NET Entity Data Model from this code?

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  • Detecting a Lightweight Core Data Migration

    - by hadronzoo
    I'm using Core Data's automatic lightweight migration successfully. However, when a particular entity gets created during a migration, I'd like to populate it with some data. Of course I could check if the entity is empty every time the application starts, but this seems inefficient when Core Data has a migration framework. Is it possible to detect when a lightweight migration occurs (possibly using KVO or notifications), or does this require implementing standard migrations? I've tried using the NSPersistentStoreCoordinatorStoresDidChangeNotification, but it doesn't fire when migrations occur.

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  • Getting started with massive data

    - by Max
    I'm a math guy and occasionally do some statistics/machine learning analysis consulting projects on the side. The data I have access to are usually on the smaller side, at most a couple hundred of megabytes (and almost always far less), but I want to learn more about handling and analyzing data on the gigabyte/terabyte scale. What do I need to know and what are some good resources to learn from? Hadoop/MapReduce is one obvious start. Is there a particular programming language I should pick up? (I primarily work now in Python, Ruby, R, and occasionally Java, but it seems like C and Clojure are often used for large-scale data analysis?) I'm not really familiar with the whole NoSQL movement, except that it's associated with big data. What's a good place to learn about it, and is there a particular implementation (Cassandra, CouchDB, etc.) I should get familiar with? Where can I learn about applying machine learning algorithms to huge amounts of data? My math background is mostly on the theory side, definitely not on the numerical or approximation side, and I'm guessing most of the standard ML algorithms don't really scale. Any other suggestions on things to learn would be great!

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  • what is best way to store long term data in iphone Core Data or SQLLite?

    - by AmitSri
    Hi all, I am working on i-Phone app targeting 3.1.3 and later SDK. I want to know the best way to store user's long term data on i-phone without losing performance, consistency and security. I know, that i can use Core Data, PList and SQL-Lite for storing user specific data in custom formats.But, want to know which one is good to use without compromising app performance and scalability in near future. Thanks

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  • How to view existing data in Core Data?

    - by mshsayem
    Well, may be this question is silly, but I couldn't find a way (except programmatically). I built a project (for iPhone OS 3.0) which uses Core Data. The xcdatamodel file shows the schema description, but I want to see the data in tabular form (like the management studio for mssql server or phpmyadmin for mysql). Is there any way (except coding)? What is that? Also, which file (in disk/device) those data are stored into? [ I built the tutorial (from apple) on Core Data, named Locations. They used this line somewhere in the code: NSURL *storeUrl = [NSURL fileURLWithPath: [[self applicationDocumentsDirectory] stringByAppendingPathComponent: @"Locations.sqlite"]]; But, I did not see any "xxxxx.sqlite" file in project location (nor in the disk).]

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  • Efficient alternatives to merge for larger data.frames R

    - by Etienne Low-Décarie
    I am looking for an efficient (both computer resource wise and learning/implementation wise) method to merge two larger (size1 million / 300 KB RData file) data frames. "merge" in base R and "join" in plyr appear to use up all my memory effectively crashing my system. Example load test data frame and try test.merged<-merge(test, test) or test.merged<-join(test, test, type="all") - The following post provides a list of merge and alternatives: How to join data frames in R (inner, outer, left, right)? The following allows object size inspection: https://heuristically.wordpress.com/2010/01/04/r-memory-usage-statistics-variable/ Data produced by anonym

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  • find the top K most frequent numbers in a data stream

    - by Jin
    This is more of a data structure question rather than a coding question. If I am fetching a data stream, i.e, I keep receiving float numbers once at a time, how should I keep track of the top K frequent numbers? Here my memory is 4G and I prefer to have less communication with hard drive unless necessary. I think heap is good for updating the max and min. How should I design the data structure? Thanks

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  • How to obtain a random sub-datatable from another data table

    - by developerit
    Introduction In this article, I’ll show how to get a random subset of data from a DataTable. This is useful when you already have queries that are filtered correctly but returns all the rows. Analysis I came across this situation when I wanted to display a random tag cloud. I already had the query to get the keywords ordered by number of clicks and I wanted to created a tag cloud. Tags that are the most popular should have more chance to get picked and should be displayed larger than less popular ones. Implementation In this code snippet, there is everything you need. ' Min size, in pixel for the tag Private Const MIN_FONT_SIZE As Integer = 9 ' Max size, in pixel for the tag Private Const MAX_FONT_SIZE As Integer = 14 ' Basic function that retreives Tags from a DataBase Public Shared Function GetTags() As MediasTagsDataTable ' Simple call to the TableAdapter, to get the Tags ordered by number of clicks Dim dt As MediasTagsDataTable = taMediasTags.GetDataValide ' If the query returned no result, return an empty DataTable If dt Is Nothing OrElse dt.Rows.Count < 1 Then Return New MediasTagsDataTable End If ' Set the font-size of the group of data ' We are dividing our results into sub set, according to their number of clicks ' Example: 10 results -> [0,2] will get font size 9, [3,5] will get font size 10, [6,8] wil get 11, ... ' This is the number of elements in one group Dim groupLenth As Integer = CType(Math.Floor(dt.Rows.Count / (MAX_FONT_SIZE - MIN_FONT_SIZE)), Integer) ' Counter of elements in the same group Dim counter As Integer = 0 ' Counter of groups Dim groupCounter As Integer = 0 ' Loop througt the list For Each row As MediasTagsRow In dt ' Set the font-size in a custom column row.c_FontSize = MIN_FONT_SIZE + groupCounter ' Increment the counter counter += 1 ' If the group counter is less than the counter If groupLenth <= counter Then ' Start a new group counter = 0 groupCounter += 1 End If Next ' Return the new DataTable with font-size Return dt End Function ' Function that generate the random sub set Public Shared Function GetRandomSampleTags(ByVal KeyCount As Integer) As MediasTagsDataTable ' Get the data Dim dt As MediasTagsDataTable = GetTags() ' Create a new DataTable that will contains the random set Dim rep As MediasTagsDataTable = New MediasTagsDataTable ' Count the number of row in the new DataTable Dim count As Integer = 0 ' Random number generator Dim rand As New Random() While count < KeyCount Randomize() ' Pick a random row Dim r As Integer = rand.Next(0, dt.Rows.Count - 1) Dim tmpRow As MediasTagsRow = dt(r) ' Import it into the new DataTable rep.ImportRow(tmpRow) ' Remove it from the old one, to be sure not to pick it again dt.Rows.RemoveAt(r) ' Increment the counter count += 1 End While ' Return the new sub set Return rep End Function Pro’s This method is good because it doesn’t require much work to get it work fast. It is a good concept when you are working with small tables, let says less than 100 records. Con’s If you have more than 100 records, out of memory exception may occur since we are coping and duplicating rows. I would consider using a stored procedure instead.

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  • Integrating Data Mining into your BI Solution (Presentation)

    I recently gave a live meeting presentation to the UK User Group on Integrating Data Mining into your BI Solution.  In it I talk about and demo ways of using your data mining models inside Integration Services, Analysis Services and Reporting Services.  This is the first in a series of presentations I will be doing for the UG as I try to get the word out that Data Mining can be for the masses. You can download my deck and my line meeting recording from here.

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  • Inside Sweden’s Nuclear Bunker Turned Data Center

    - by Jason Fitzpatrick
    A data center inside a decommissioned nuclear bunker is interesting enough, but one that looks as futuristic and awesome as the center under Stockholm begs to be seen. A hundred feet under the city of Stockholm is a decommissioned nuclear bunker that the government had previously leased out intermittently for various events, but it was never put to serious or extended use. Not until, that is,  Jon Karlung discovered the location and brought his vision of an ultra-modern, stylish, and secure data center to life. The passage from Wired’s write up of their photo tour that best encapsulates the feel of the bunker is: Most often data centers are built in boxy warehouses, so Bahnhof stands out as perhaps the world’s most stylish. In fact, it inspired Cisco IT Architect Douglas Alger to write a book on the world’s best-looking data centers. ”The idea that people were sitting in a design meeting and said, ‘what we need for our data center is waterfalls,’ that must have been a very fascinating discussion,” Alger says. Hit up the link below for the full photo tour. Deep Inside the James Bond Villain Lair That Actually Exists [Wired] Why Does 64-Bit Windows Need a Separate “Program Files (x86)” Folder? Why Your Android Phone Isn’t Getting Operating System Updates and What You Can Do About It How To Delete, Move, or Rename Locked Files in Windows

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  • Is there a way to track data structure dependencies from the database, through the tiers, all the way out to a web page?

    - by Sean Mickey
    When we design applications, we generally end up with the same tiered sets of data structures: A persistent data structure that is described using DDL and implemented as RDBMS tables and columns. A set of domain objects that consist primarily of data structures, usually combined with business-rule level logic, that are implemented in a programming language such as Java. A set of service layer interfaces that directly support use case implementations (which use the domain data structures as parameters), implemented as EJBs or something equivalent in another programming language. UI screens that allow users to C reate, R etrieve, U pdate, and (maybe) D elete all manner of data structures and graphs of data structures, with numerous screens and with multiple UI widgets, all structured to support the same data structures. But if you want to change the data structures in any of these tiers, it always seems extremely difficult to assess the impact(s) the change will have across the application. UML can help, but tracing through diagram after diagram is not a real solution to this problem. The best I have ever seen was a homespun data tracking spreadsheet document that listed all of the data structures and walked the relationships from tier-to-tier. Is there a tool or accepted approach that makes it easy to identify a data structure in any tier and easily obtain a list of all dependent: database table and column data structures domain object data structures service layer interface methods and parameter data structures screen & UI component data structures

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  • Dokuwiki: Moving Just the data directory on other server

    - by amit
    I have installed dokuwiki on IIS7. As per my teams requirement we have to move just the Data directory to other server location. e.g - IIS7 installed Dokuwiki location: C:\inetpub\wwwroot\dokuwiki\conf - data location on the other server we want: U:\Archive\LP_Archive\SH_Systems\DEV01\dokuwiki So for doing that I followed pointers on dokuwiki install iis7 As per the above link, I tried adding IUSR to data folder permissions but its failing due to my insufficient privileges. And without that IUSR permission set on data folder I am getting an error as "The datadir ('pages') at is not found, isn't accessible or writable". Is there any other way to make it work? Is there any other account than IUSR I can use?

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  • Big Data Accelerator

    - by Jean-Pierre Dijcks
    For everyone who does not regularly listen to earnings calls, Oracle's Q4 call was interesting (as it mostly is). One of the announcements in the call was the Big Data Accelerator from Oracle (Seeking Alpha link here - slightly tweaked for correctness shown below):  "The big data accelerator includes some of the standard open source software, HDFS, the file system and a number of other pieces, but also some Oracle components that we think can dramatically speed up the entire map-reduce process. And will be particularly attractive to Java programmers [...]. There are some interesting applications they do, ETL is one. Log processing is another. We're going to have a lot of those features, functions and pre-built applications in our big data accelerator."  Not much else we can say right now, more on this (and Big Data in general) at Openworld!

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  • Willy Rotstein on Analytics and Social Media in Retail

    - by sarah.taylor(at)oracle.com
    Recently I came across a presentation from Dan Zarrella on "The Science of Retweets. (http://www.slideshare.net/HubSpot/the-science-of-retweets-with-dan-zarrella). It is an insightful, fact-based analysis of how tweets propagate and what makes them successful. The analysis is of course very interesting for those of us interested Tweeting. However, what really caught my attention is how well it illustrates, form a very different angle, some of the issues I am discussing with retailers these days. In particular the opportunities that e-commerce and social media open to those retailers with the appetite and vision to tackle the associated analytical challenges. And these challenges are of course not straightforward.   In his presentation Dan introduces the concept of Observability, I haven't had the opportunity to discuss with Dan his specific definition for the term. However, in practical retail terms, I would say that it means that through social media (and other web channels such as search) we can analyze and track processes by measuring Indicators that were not measurable before. The focus is in identifying patterns across a large number of consumers rather than what a particular individual "Likes".   The potential impact for retailers is huge. It opens the opportunity to monitor changes in consumer preference  and plan the business accordingly. And you can do this almost "real time" rather than through infrequent surveys that provide a "rear view" picture of your consumer behaviour. For instance, you could envision identifying when a particular set of fashion styles are breaking out from the pack, and commit a re-buy. Or you could monitor when the preference for a specific mobile device has declined and hence markdowns should be considered; or how demand for a specific ready-made food typically flows across regions and manage the inventory accordingly. Search, blogging, website and store data may need to be considered in identifying these trends. The data volumes involved are huge (check Andrea Morgan's recent post on "Big Data" in retail) but so are the benefits. As Andrea says, for the first time we can start getting insight into "Why" the business is performing in a certain way rather than just reporting on what is happening. And it is not just about the data volumes. Tackling the challenge also calls for integrated planning systems that can bring data and insight into the context of the Decision Making process Buyers, Merchandisers and Supply Chain managers are following. I strongly believe that only when data and process come together you can move from the anecdotal to systematically improving business performance.   I would love to hear your opinions on these trends and where you think Retail is heading to exploit these topics - please email me: [email protected]

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  • Extracting data from internet

    - by Ankiov Spetsnaz
    I would like to extract data from internet like www.mozenda.com does but I want to write my own program to do that. Specific data I'm looking for is various event data. Based on my research, I think custom web crawler is my answer but I Would like to confirm the answer and see if there are any suggestion to make custom web crawlers if web crawler indeed is an answer. Personally, I would prefer Java and I'm planning on using Glassfish technology if that matters...

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  • What is the best strategy for transforming unicode strings into filenames?

    - by David Cowden
    I have a bunch (thousands) of resources in an RDF/XML file. I am writing a certain subset of the resources to files -- one file for each, and I'm using the resource's title property as the file name. However, the titles are every day article, website, and blog post titles, so they contain characters unsafe for a URI (the necessary step for constructing a valid file path). I know of the Jersey UriBuilder but I can't quite get it to work for my needs as I detailed in a different question on SO. Some possibilities I have considered are: Since each resource should also have an associated URL, I could try to use the name of the file on the server. The down side of this is sometimes people don't name their content logically and I think the title of an article better reflects the content that will be in each text file. Construct a white list of valid characters and parse the string myself defining substitutions for unsafe characters. The downside of this is the result could be just as unreadable as the former solution because presumably the content creators went through a similar process when placing the files on their server. Choose a more generic naming scheme, place the title in the text file along with the other attributes, and tell my boss to live with it. So my question here is, what methods work well for dealing with a scenario where you need to construct file names out of strings with potentially unsafe characters? Is there a solution that better fills out my constraints?

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

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

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