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  • Data recovery on a data HDD (no OS)

    - by aCuria
    I am helping a family member with a dead hard disk. It is a seagate 200Gb 3.5" HDD in one of those old-school external enclosures. The problem was that windows failed to detect the hard disk when plugged in through USB. I removed the hard disk from its enclosure, and plugged it into my desktop PC. The BIOS does detect it upon POST, but unfortunately windows 7 would refuse to boot. It will get stuck on the loading screen with the glowing windows logo. Safe mode doesn't help either. What options do I have before going for some professional data recovery? edit: Someone modified the Title to something completely different from what I was asking, i just changed it back. 1) 2 HDD drives, DiskA(Dead), DiskB(my OS disk) 2) when B is connected to my system, everything works fine 3) when A AND B is connected, failure to boot. POSTs fine, but windows wont load 4) A has NO OS, its PURE data. It came from an EXTERNAL HDD enclosure which doesnt belong to me, and im trying to do data recovery.

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  • Unable to control requests for static files on Google App Engine

    - by dan
    My simple GAE app is not redirecting to the /static directory for requests when url is multiple levels. Dir structure: /app/static/css/main.css App: I have two handlers one for /app and one for /app/new app.yaml: handlers: - url: /static static_dir: static - url: /app/static/(.*) static_dir: static\1 - url: /app/.* script: app.py login: required HTML: Description: When page is loaded from /app HTTP request for main.css is successful GET /static/css/main.css But when page is loaded from /app/new I see the following request: GET /app/static/css/main.cs That's when I tried adding the /app/static/(.*) in the app.yaml but it is not having any effect.

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  • How do I get the application title of a Google AppEngine app from within that app

    - by Noah McIlraith
    Under the application settings page in the Administration console, it is possible to specify a name for the application, AFAIK this is used in the login page when using the users API to login. I would like to be able to use this information within an application, currently, the title is also specified in a separate configuration file, but configuration repetition is something I would like to avoid if at all possible. Is there some way for a GAE application to determine the "Application Title"? Oh, also, I am using python.

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  • Data Governance 2010 Conference in San Diego

    - by Tony Ouk
    The Data Governance Annual Conference is one of the world's most authoritative and vendor neutral event on Data Governance and Data Quality.  The conference will focus on the "how-tos" from starting a data governance and stewardship program to attaining data governance maturity with specific topics on MDM.  This year's event will be hosted June 7 through June 10 in San Diego, California. For more information, including registration details, visit the Data Governance 2010 Conference website.

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  • How to search for newline or linebreak characters in Excel?

    - by Highly Irregular
    I've imported some data into Excel (from a text file) and it contains some sort of newline characters. It looks like this initially: If I hit F2 (to edit) then Enter (to save changes) on each of the cells with a newline (without actually editing anything), Excel automatically changes the layout to look like this: I don't want these newlines characters here, as it messes up data processing further down the track. How can I do a search for these to detect more of them? The usual search function doesn't accept an enter character as a search character.

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  • Oracle Data Integration 12c: Simplified, Future-Ready, High-Performance Solutions

    - by Thanos Terentes Printzios
    In today’s data-driven business environment, organizations need to cost-effectively manage the ever-growing streams of information originating both inside and outside the firewall and address emerging deployment styles like cloud, big data analytics, and real-time replication. Oracle Data Integration delivers pervasive and continuous access to timely and trusted data across heterogeneous systems. Oracle is enhancing its data integration offering announcing the general availability of 12c release for the key data integration products: Oracle Data Integrator 12c and Oracle GoldenGate 12c, delivering Simplified and High-Performance Solutions for Cloud, Big Data Analytics, and Real-Time Replication. The new release delivers extreme performance, increase IT productivity, and simplify deployment, while helping IT organizations to keep pace with new data-oriented technology trends including cloud computing, big data analytics, real-time business intelligence. With the 12c release Oracle becomes the new leader in the data integration and replication technologies as no other vendor offers such a complete set of data integration capabilities for pervasive, continuous access to trusted data across Oracle platforms as well as third-party systems and applications. Oracle Data Integration 12c release addresses data-driven organizations’ critical and evolving data integration requirements under 3 key themes: Future-Ready Solutions : Supporting Current and Emerging Initiatives Extreme Performance : Even higher performance than ever before Fast Time-to-Value : Higher IT Productivity and Simplified Solutions  With the new capabilities in Oracle Data Integrator 12c, customers can benefit from: Superior developer productivity, ease of use, and rapid time-to-market with the new flow-based mapping model, reusable mappings, and step-by-step debugger. Increased performance when executing data integration processes due to improved parallelism. Improved productivity and monitoring via tighter integration with Oracle GoldenGate 12c and Oracle Enterprise Manager 12c. Improved interoperability with Oracle Warehouse Builder which enables faster and easier migration to Oracle Data Integrator’s strategic data integration offering. Faster implementation of business analytics through Oracle Data Integrator pre-integrated with Oracle BI Applications’ latest release. Oracle Data Integrator also integrates simply and easily with Oracle Business Analytics tools, including OBI-EE and Oracle Hyperion. Support for loading and transforming big and fast data, enabled by integration with big data technologies: Hadoop, Hive, HDFS, and Oracle Big Data Appliance. Only Oracle GoldenGate provides the best-of-breed real-time replication of data in heterogeneous data environments. With the new capabilities in Oracle GoldenGate 12c, customers can benefit from: Simplified setup and management of Oracle GoldenGate 12c when using multiple database delivery processes via a new Coordinated Delivery feature for non-Oracle databases. Expanded heterogeneity through added support for the latest versions of major databases such as Sybase ASE v 15.7, MySQL NDB Clusters 7.2, and MySQL 5.6., as well as integration with Oracle Coherence. Enhanced high availability and data protection via integration with Oracle Data Guard and Fast-Start Failover integration. Enhanced security for credentials and encryption keys using Oracle Wallet. Real-time replication for databases hosted on public cloud environments supported by third-party clouds. Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c and other Oracle technologies, such as Oracle Database 12c and Oracle Applications, provides a number of benefits for organizations: Tight integration between Oracle Data Integrator 12c and Oracle GoldenGate 12c enables developers to leverage Oracle GoldenGate’s low overhead, real-time change data capture completely within the Oracle Data Integrator Studio without additional training. Integration with Oracle Database 12c provides a strong foundation for seamless private cloud deployments. Delivers real-time data for reporting, zero downtime migration, and improved performance and availability for Oracle Applications, such as Oracle E-Business Suite and ATG Web Commerce . Oracle’s data integration offering is optimized for Oracle Engineered Systems and is an integral part of Oracle’s fast data, real-time analytics strategy on Oracle Exadata Database Machine and Oracle Exalytics In-Memory Machine. Oracle Data Integrator 12c and Oracle GoldenGate 12c differentiate the new offering on data integration with these many new features. This is just a quick glimpse into Oracle Data Integrator 12c and Oracle GoldenGate 12c. Find out much more about the new release in the video webcast "Introducing 12c for Oracle Data Integration", where customer and partner speakers, including SolarWorld, BT, Rittman Mead will join us in launching the new release. Resource Kits Meet Oracle Data Integration 12c  Discover what's new with Oracle Goldengate 12c  Oracle EMEA DIS (Data Integration Solutions) Partner Community is available for all your questions, while additional partner focused webcasts will be made available through our blog here, so stay connected. For any questions please contact us at partner.imc-AT-beehiveonline.oracle-DOT-com Stay Connected Oracle Newsletters

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Weindows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Building a Data Mart with Pentaho Data Integration Video Review by Diethard Steiner, Packt Publishing

    - by Compudicted
    Originally posted on: http://geekswithblogs.net/Compudicted/archive/2014/06/01/building-a-data-mart-with-pentaho-data-integration-video-review-again.aspx The Building a Data Mart with Pentaho Data Integration Video by Diethard Steiner from Packt Publishing is more than just a course on how to use Pentaho Data Integration, it also implements and uses the principals of the Data Warehousing (and I even heard the name of Ralph Kimball in the video). Indeed, a video watcher should be familiar with its concepts as the Star Schema, Slowly Changing Dimension types, etc. so I suggest prior to watching this course to consider skimming through the Data Warehouse concepts (if unfamiliar) or even better, read the excellent Ralph’s The Data Warehouse Tooolkit. By the way, the author expands beyond using Pentaho along to MySQL and MonetDB which is a real icing on the cake! Indeed, I even suggest the name of the course should be ‘Building a Data Warehouse with Pentaho’. To successfully complete the course one needs to know some Linux (Ubuntu used in the course), the VI editor and the Bash command shell, but it seems that similar requirements would also apply to the Windows OS. Additionally, knowing some basic SQL would not hurt. As I had said, MonetDB is used in this course several times which seems to be not anymore complex than say MySQL, but based on what I read is very well suited for fast querying big volumes of data thanks to having a columnstore (vertical data storage). I don’t see what else can be a barrier, the material is very digestible. On this note, I must add that the author does not cover how to acquire the software, so here is what I found may help: Pentaho: the free Community Edition must be more than anyone needs to learn it. Or even go into a POC. MonetDB can be downloaded (exists for both, Linux and Windows) from http://goo.gl/FYxMy0 (just see the appropriate link on the left). The author seems to be using Eclipse to run SQL code, one can get it from http://goo.gl/5CcuN. To create, or edit database entities and/or schema otherwise one can use a universal tool called SQuirreL, get it from http://squirrel-sql.sourceforge.net.   Next, I must confess Diethard is very knowledgeable in what he does and beyond. However, there will be some accent heard to the user of the course especially if one’s mother tongue language is English, but it I got over it in a few chapters. I liked the rate at which the material is being presented, it makes me feel I paid for every second Eventually, my impressions are: Pentaho is an awesome ETL offering, it is worth learning it very much (I am an ETL fan and a heavy user of SSIS) MonetDB is nice, it tickles my fancy to know it more Data Warehousing, despite all the BigData tool offerings (Hive, Scoop, Pig on Hadoop), using the traditional tools still rocks Chapters 2 to 6 were the most fun to me with chapter 8 being the most difficult.   In terms of closing, I highly recommend this video to anyone who needs to grasp Pentaho concepts quick, likewise, the course is very well suited for any developer on a “supposed to be done yesterday” type of a project. It is for a beginner to intermediate level ETL/DW developer. But one would need to learn more on Data Warehousing and Pentaho, for such I recommend the 5 star Pentaho Data Integration 4 Cookbook. Enjoy it! Disclaimer: I received this video from the publisher for the purpose of a public review.

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  • Internal Mutation of Persistent Data Structures

    - by Greg Ros
    To clarify, when I mean use the terms persistent and immutable on a data structure, I mean that: The state of the data structure remains unchanged for its lifetime. It always holds the same data, and the same operations always produce the same results. The data structure allows Add, Remove, and similar methods that return new objects of its kind, modified as instructed, that may or may not share some of the data of the original object. However, while a data structure may seem to the user as persistent, it may do other things under the hood. To be sure, all data structures are, internally, at least somewhere, based on mutable storage. If I were to base a persistent vector on an array, and copy it whenever Add is invoked, it would still be persistent, as long as I modify only locally created arrays. However, sometimes, you can greatly increase performance by mutating a data structure under the hood. In more, say, insidious, dangerous, and destructive ways. Ways that might leave the abstraction untouched, not letting the user know anything has changed about the data structure, but being critical in the implementation level. For example, let's say that we have a class called ArrayVector implemented using an array. Whenever you invoke Add, you get a ArrayVector build on top of a newly allocated array that has an additional item. A sequence of such updates will involve n array copies and allocations. Here is an illustration: However, let's say we implement a lazy mechanism that stores all sorts of updates -- such as Add, Set, and others in a queue. In this case, each update requires constant time (adding an item to a queue), and no array allocation is involved. When a user tries to get an item in the array, all the queued modifications are applied under the hood, requiring a single array allocation and copy (since we know exactly what data the final array will hold, and how big it will be). Future get operations will be performed on an empty cache, so they will take a single operation. But in order to implement this, we need to 'switch' or mutate the internal array to the new one, and empty the cache -- a very dangerous action. However, considering that in many circumstances (most updates are going to occur in sequence, after all), this can save a lot of time and memory, it might be worth it -- you will need to ensure exclusive access to the internal state, of course. This isn't a question about the efficacy of such a data structure. It's a more general question. Is it ever acceptable to mutate the internal state of a supposedly persistent or immutable object in destructive and dangerous ways? Does performance justify it? Would you still be able to call it immutable? Oh, and could you implement this sort of laziness without mutating the data structure in the specified fashion?

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  • Pro Google App Engine developer interview questions (with answers)

    - by WooYek
    What are good questions to determine if applicant is pro Google App Egine developer? Questions that can distinguish that someone is not an ad-hoc GAE programmer, but is really doing professional GAE development, with all areas concerned (eg. performance, transactions, async/batch data processing). Please provide answers, so an intermediate developer (such as myself :) can interview someone more experienced. Please avoid open questions. If possible please provide a link to a documentation part that's covering a topic in question. Please keep one interview question/answer per response for better reading experience and easier interview preparation.

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  • Sabre Manages Fast Data Growth with Oracle Data Integration Products

    - by Irem Radzik
    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:0in 5.4pt 0in 5.4pt; mso-para-margin-top:0in; mso-para-margin-right:0in; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0in; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin;} Last year at OpenWorld we announced Sabre Holding as a winner of the Fusion Middleware Innovation Awards. The Sabre team did an excellent job at leveraging cutting edge technologies for managing rapid data growth and exponential scalability demands they have experienced in the travel industry. Today we announced the details and specific benefits of Sabre’s new real-time data integration solution in a press release. Please take a look if you haven’t seen it yet. Sabre Holdings Deploys Oracle Data Integrator and Oracle GoldenGate to Support Rapid Customer Growth There are 3 different areas of benefits Sabre achieved by using Oracle Data Integration products: Manages 7X increase in data sources for the enterprise data warehouse Reduced infrastructure complexity Decreased time to market for new products and services by 30 percent. This simply shows that using latest technologies helps the companies to innovate robust solutions against today’s key data management challenges. And the benefit of using a next generation data integration technology is not only seen in the IT operations, but also in the business side. A better data integration solution for the enterprise data warehouse delivered the platform they need to accelerate how they service their customers, improving their competitive advantage. Tomorrow I will give another great example of innovation with next generation data integration from Oracle. We will be discussing the Fusion Middleware Innovation Awards 2012 winners and their results with using Oracle’s data integration products.

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  • Pro Google App Engine developer interview questions (with answers)

    - by WooYek
    What are good questions to determine if applicant is pro Google App Engine developer? Questions that can distinguish that someone is not an ad-hoc GAE programmer, but is really doing professional GAE development, with all areas concerned (eg. performance, transactions, async/batch data processing). Please provide answers, so an intermediate developer (such as myself :) can interview someone more experienced. Please avoid open questions. If possible please provide a link to a documentation part that's covering a topic in question. Please keep one interview question/answer per response for better reading experience and easier interview preparation.

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  • Page for Page Redirect in Google App Engine

    - by clifgray
    I have recently changed domain name for a webapp I run on Google App Engine and I am wondering if there is a simple way to do a page for page redirect from my old website to the new domain. Everything code wise is staying exactly the same but I just want it to go to the new domain. I am using python and the webapp2 framework for the webapp. I know I could go through and for every single handler do: webapp2.redirect('the specific url', permanent=True) But I am hoping for a simpler solution.

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  • Google I/O 2012 - Putting the App Back into Web App - Web Programming with Dart

    Google I/O 2012 - Putting the App Back into Web App - Web Programming with Dart Dan Grove, Vijay Menon Do you want to build blazingly fast applications with beautiful graphics and offline support? Would you like to run those apps anywhere on the open web? Would you like to develop those apps in a language that supports modular large-scale development while keeping the lightweight feel of a scripting language? This session will show you how to use the Dart programming language to develop the next generation of amazing applications for the open web. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 187 4 ratings Time: 57:16 More in Science & Technology

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  • implementing dynamic query handler on historical data

    - by user2390183
    EDIT : Refined question to focus on the core issue Context: I have historical data about property (house) sales collected from various sources in a centralized/cloud data source (assume info collection is handled by a third party) Planning to develop an application to query and retrieve data from this centralized data source Example Queries: Simple : for given XYZ post code, what is average house price for 3 bed room house? Complex: What is estimated price for an house at "DD,Some Street,XYZ Post Code" (worked out from average values of historic data filtered by various characteristics of the house: house post code, no of bed rooms, total area, and other deeper insights like house building type, year of built, features)? In addition to average price, the application should support other property info ** maximum, or minimum price..etc and trend (graph) on a selected property attribute over a period of time**. Hence, the queries should not enforce the search based on a primary key or few fixed fields In other words, queries can be What is the change in 3 Bed Room house price (irrespective of location) over last 30 days? What kind of properties we can get for X price (irrespective of location or house type) The challenge I have is identifying the domain (BI/ Data Analytical or DB Design or DB Query Interface or DW related or something else) this problem (dynamic query on historic data) belong to, so that I can do further exploration My findings so far I could be wrong on the following, so please correct me if you think so I briefly read about BI/Data Analytics - I think it is heavy weight solution for my problem and has scalability issues. DB Design - As I understand RDBMS works well if you know Data model at design time. I am expecting attributes about property or other entity (user) that am going to bring in, would evolve quickly. hence maintenance would be an issue. As I am going to have multiple users executing query at same time, performance would be a bottleneck Other options like Graph DB (http://www.tinkerpop.com/) seems to be bit complex (they are good. but using those tools meant for generic purpose, make me think like assembly programming to solve my problem ) BigData related solution are to analyse data from multiple unrelated domains So, Any suggestion on the space this problem fit in ? (Especially if you have design/implementation experience of back-end for property listing or similar portals)

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  • App Engine charges in November 2011 [closed]

    - by broiyan
    I had a billing enabled test application on Google App Engine left over from early 2011. I have not received a bill in many months because I have not been hitting the URL and according to the activity monitor, nobody has. Then unexpectedly in November 2011, I received 2 bills in as many weeks for quite minimal amounts. Checking the monitor it looks like nobody has been hitting the URL and according to the SQL-like search, there is nothing in the Datastore. I know that GAE has left the "preview" in recent weeks but I am not sure how that would affect what is essentially a dormant application with no Datastore objects. Has GAE started charging for completely unused applications in recent weeks? Edit: Most of my applications were already disabled and I have just disabled the only one that was enabled but unused the past several months. If I get another bill next week that should be informative.

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  • AngularJS dealing with large data sets (Strategy)

    - by Brian
    I am working on developing a personal temperature logging viewer based on my rasppi curl'ing data into my web server's api. Temperatures are taken every 2 seconds and I can have several temperature sensors posting data. Needless to say I will have a lot of data to handle even within the scope of an hour. I have implemented a very simple paging api from the server so the server doesn't timeout and is currently only returning data in 1000 units per call, then paging through the data. I had the idea to intially show say the last 20 minutes of data from a sensor (or all sensors depending on user choices), then allowing the user to select other timeframes from which to show data. The issue comes in when you want to view all sensors or an extended time period (say 24 hours). Is there a best practice of handling this large amount of data? Would it be useful to load those first 20 minutes into the live view and then cache into local storage something like the last 24 hours? I haven't been able to find a decent idea of this in use yet even though there are a lot of ways to take this problem. I am just looking for some suggestions as to what might provide a good balance between good performance and not caching the entire data set on the client side (as beyond a week of data this might not be feasible).

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  • I need some help creating a non-binary tree (or some other data structure that will better solve my problem)

    - by EDO
    I have about ten lists of numbers and some strings. Each list has about <= 30K lines. Each line on a list has a distinct number. I need to build an efficient way of finding all the lines in each list that has the same 'control' number (or key for dB guys) and comparing what is in their string parts. I am writing this in Java. I have thought about using trees but my brain cells are about burnt now. I need some help.

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  • App not showing up in Google Play search on app name [on hold]

    - by William Jockusch
    About 30 hours ago, I released an app on Google Play. I am concerned that if you search on the exact app name, it does not show up in the results, even if you click "show more". https://play.google.com/store/search?q=free+graphing+calculator&c=apps It does show up if you put the name in quotes. But that's awfully low discoverability. https://play.google.com/store/search?q=%22free%20graphing%20calculator%22&c=apps Possibly relevant information: I had an earlier version with a different bundle ID. It was up for just an hour or so, and probably never actually visible to users. How can I fix this?

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  • replacing data.frame element-wise operations with data.table (that used rowname)

    - by Harold
    So lets say I have the following data.frames: df1 <- data.frame(y = 1:10, z = rnorm(10), row.names = letters[1:10]) df2 <- data.frame(y = c(rep(2, 5), rep(5, 5)), z = rnorm(10), row.names = letters[1:10]) And perhaps the "equivalent" data.tables: dt1 <- data.table(x = rownames(df1), df1, key = 'x') dt2 <- data.table(x = rownames(df2), df2, key = 'x') If I want to do element-wise operations between df1 and df2, they look something like dfRes <- df1 / df2 And rownames() is preserved: R> head(dfRes) y z a 0.5 3.1405463 b 1.0 1.2925200 c 1.5 1.4137930 d 2.0 -0.5532855 e 2.5 -0.0998303 f 1.2 -1.6236294 My poor understanding of data.table says the same operation should look like this: dtRes <- dt1[, !'x', with = F] / dt2[, !'x', with = F] dtRes[, x := dt1[,x,]] setkey(dtRes, x) (setkey optional) Is there a more data.table-esque way of doing this? As a slightly related aside, more generally, I would have other columns such as factors in each data.table and I would like to omit those columns while doing the element-wise operations, but still have them in the result. Does this make sense? Thanks!

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  • PHP - post data ends when '&' is in data.

    - by Phil Jackson
    Hi all, im posting data using jquery/ajax and PHP at the backend. Problem being, when I input something like 'Jack & Jill went up the hill' im only recieving 'Jack' when it gets to the backend. I have thrown an error at the frontend before that data is sent which alerts 'Jack & Jill went up the hill'. When I put die(print_r($_POST)); at the very top of my index page im only getting [key] => Jack how can I be loosing the data? I thought It may have been my filter; <?php function filter( $data ) { $data = trim( htmlentities( strip_tags( mb_convert_encoding( $data, 'HTML-ENTITIES', "UTF-8") ) ) ); if ( get_magic_quotes_gpc() ) { $data = stripslashes( $data ); } //$data = mysql_real_escape_string( $data ); return $data; } echo "<xmp>" . filter("you & me") . "</xmp>"; ?> but that returns fine in the test above you &amp; me which is in place after I added die(print_r($_POST));. Can anyone think of how and why this is happening? Any help much appreciated. Regards, Phil.

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  • The Raspberry Pi Now Has Its Own App Store

    - by Jason Fitzpatrick
    Raspberry Pi, the credit-card sized computer with an ARM processor, now has its own appstore where Raspberry Pi hobbyists and developers can share their creations in a one-stop location accessible to all Raspberry Pi users. In today’s press release about the store, the Raspberry Pi Foundation writes: We’ve been amazed by the variety of software that people have written for, or ported to, the Raspberry Pi. Today, together with our friends at IndieCity and Velocix, we’re launching the Pi Store to make it easier for developers of all ages to share their games, applications, tools and tutorials with the rest of the community. The Pi Store will, we hope, become a one-stop shop for all your Raspberry Pi needs; it’s also an easier way into the Raspberry Pi experience for total beginners, who will find everything they need to get going in one place, for free. The store runs as an X application under Raspbian, and allows users to download content, and to upload their own content for moderation and release. At launch, we have 23 free titles in the store, ranging from utilities like LibreOffice and Asterisk to classic games like Freeciv and OpenTTD and Raspberry Pi exclusive Iridium Rising. We also have one piece of commercial content: the excellent Storm in a Teacup from Cobra Mobile. For more information about the store, including how to install the app store on your Pi, check out the full press release here. To get started browsing the store, hit up the link below. Secure Yourself by Using Two-Step Verification on These 16 Web Services How to Fix a Stuck Pixel on an LCD Monitor How to Factory Reset Your Android Phone or Tablet When It Won’t Boot

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  • How to Re-install an App that Shows up in the Appstore as 'Update' Instead of 'Buy App'

    - by Craig Reville
    So long story short: I dropped the wrong app into 'clean my mac' and I hit 'cancel' but it was too late by that point. I rebooted and appstore said it had an update, when I opened appstore it was showing an update for the app I just uninstalled. I tried clicking 'update' but it gives me an error saying it's unable to install after 'downloading'. When I try to go into 'purchased apps' it shows the app as uninstalled so I click 'install' and I get an error saying it's already installed. I'm running Lion OS X, latest version, updated, mac book pro is only a few months old. I tried searching through the entire system to remove all traces of the app, after rebooting appstore no longer shows the app and no longer shows the update but on the apps page it still says 'Update'. I tried reinstalling the app from desktop OUT of the appstore and again says the app is 'already installed'. So after reading more about lion I found an article that spoke about 'BundleID' being the thing that tells appstore what's installed and needing updating however I can't find the location of where the BundleID would be. Any thoughts? I've tried CCleaner, AppCleaner etc and none of them show the app, mainly because it is uninstalled. Update I've spoken to Apple Support who confirmed that there is a file in the system that connects separately to tell the system if there are updates available however they declined to inform me of any further details. Apple also referred me from technical support to iTunes App Store opposed to Mac App Store support and from there I have been referred to AppleCare who are currently 'investigating' this issue. Hopefully there will be a fix that's simple to implement for people having similar issues, this appears to be a more common issue than I previously thought.

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  • Using Google App Engine to Perform World Updates vs an Authoritative Server

    - by Error 454
    I am considering different game server architectures that use GAE. The types of games I am considering are turn-based where the world status would need to be updated about once per minute. I am looking for an answer that persuades me to either perform the world update on the google servers OR an authoritative server that syncs with the datastore. The main goal here would be to minimize GAE daily quotas. For some rough numbers, I am assuming 10,000 entities requiring updates. Each entity update would require: Reading 5 private entity variables (fetched from datastore) Fetching as many as 20 static variables (from datastore or persisted in server memory) Writing 5 entity variables Clients of the game would authenticate and set state directly against GAE as well as pull the latest world state from GAE. Running the update on GAE would consist of a cron job launched every minute. This would update all of the entities and save the results to the datastore. This would be more CPU intensive for GAE. Running the update on an authoritative server would consist of fetching entity data from the GAE datastore, calculating the new entity states and pushing the new state variables back to the datastore. This would be more bandwidth intensive for the datastore.

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