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  • Web services, Java EE, Spring, DB integration project ideas - maybe data mining related?

    - by saral jain
    I am a graduate Computer Science student (Data Mining and Machine Learning) and have good exposure to core Java (3 years). I have read up on a bunch of stuff on the following topics: Design patterns, Java EE Web services (SOAP and REST), Spring, and Hibernate Java Concurrency - advanced features like Task and Executors. I would now like to do a project combining this stuff -- over my free time of course -- to get a better understanding of these things and to kind of make an end to end software (to learn the best design principles etc + SVN, maven). Any good project ideas would be really appreciated. I just want to build this stuff to learn, so I don't really mind re-inventing the wheel. Also, anything related to data mining would be an added bonus as it fits with my research but is absolutely not necessary since this project is more to learn to do large scale software development.

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  • DTracing TCP congestion control

    - by user12820842
    In a previous post, I showed how we can use DTrace to probe TCP receive and send window events. TCP receive and send windows are in effect both about flow-controlling how much data can be received - the receive window reflects how much data the local TCP is prepared to receive, while the send window simply reflects the size of the receive window of the peer TCP. Both then represent flow control as imposed by the receiver. However, consider that without the sender imposing flow control, and a slow link to a peer, TCP will simply fill up it's window with sent segments. Dealing with multiple TCP implementations filling their peer TCP's receive windows in this manner, busy intermediate routers may drop some of these segments, leading to timeout and retransmission, which may again lead to drops. This is termed congestion, and TCP has multiple congestion control strategies. We can see that in this example, we need to have some way of adjusting how much data we send depending on how quickly we receive acknowledgement - if we get ACKs quickly, we can safely send more segments, but if acknowledgements come slowly, we should proceed with more caution. More generally, we need to implement flow control on the send side also. Slow Start and Congestion Avoidance From RFC2581, let's examine the relevant variables: "The congestion window (cwnd) is a sender-side limit on the amount of data the sender can transmit into the network before receiving an acknowledgment (ACK). Another state variable, the slow start threshold (ssthresh), is used to determine whether the slow start or congestion avoidance algorithm is used to control data transmission" Slow start is used to probe the network's ability to handle transmission bursts both when a connection is first created and when retransmission timers fire. The latter case is important, as the fact that we have effectively lost TCP data acts as a motivator for re-probing how much data the network can handle from the sending TCP. The congestion window (cwnd) is initialized to a relatively small value, generally a low multiple of the sending maximum segment size. When slow start kicks in, we will only send that number of bytes before waiting for acknowledgement. When acknowledgements are received, the congestion window is increased in size until cwnd reaches the slow start threshold ssthresh value. For most congestion control algorithms the window increases exponentially under slow start, assuming we receive acknowledgements. We send 1 segment, receive an ACK, increase the cwnd by 1 MSS to 2*MSS, send 2 segments, receive 2 ACKs, increase the cwnd by 2*MSS to 4*MSS, send 4 segments etc. When the congestion window exceeds the slow start threshold, congestion avoidance is used instead of slow start. During congestion avoidance, the congestion window is generally updated by one MSS for each round-trip-time as opposed to each ACK, and so cwnd growth is linear instead of exponential (we may receive multiple ACKs within a single RTT). This continues until congestion is detected. If a retransmit timer fires, congestion is assumed and the ssthresh value is reset. It is reset to a fraction of the number of bytes outstanding (unacknowledged) in the network. At the same time the congestion window is reset to a single max segment size. Thus, we initiate slow start until we start receiving acknowledgements again, at which point we can eventually flip over to congestion avoidance when cwnd ssthresh. Congestion control algorithms differ most in how they handle the other indication of congestion - duplicate ACKs. A duplicate ACK is a strong indication that data has been lost, since they often come from a receiver explicitly asking for a retransmission. In some cases, a duplicate ACK may be generated at the receiver as a result of packets arriving out-of-order, so it is sensible to wait for multiple duplicate ACKs before assuming packet loss rather than out-of-order delivery. This is termed fast retransmit (i.e. retransmit without waiting for the retransmission timer to expire). Note that on Oracle Solaris 11, the congestion control method used can be customized. See here for more details. In general, 3 or more duplicate ACKs indicate packet loss and should trigger fast retransmit . It's best not to revert to slow start in this case, as the fact that the receiver knew it was missing data suggests it has received data with a higher sequence number, so we know traffic is still flowing. Falling back to slow start would be excessive therefore, so fast recovery is used instead. Observing slow start and congestion avoidance The following script counts TCP segments sent when under slow start (cwnd ssthresh). #!/usr/sbin/dtrace -s #pragma D option quiet tcp:::connect-request / start[args[1]-cs_cid] == 0/ { start[args[1]-cs_cid] = 1; } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd tcps_cwnd_ssthresh / { @c["Slow start", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } tcp:::send / start[args[1]-cs_cid] == 1 && args[3]-tcps_cwnd args[3]-tcps_cwnd_ssthresh / { @c["Congestion avoidance", args[2]-ip_daddr, args[4]-tcp_dport] = count(); } As we can see the script only works on connections initiated since it is started (using the start[] associative array with the connection ID as index to set whether it's a new connection (start[cid] = 1). From there we simply differentiate send events where cwnd ssthresh (congestion avoidance). Here's the output taken when I accessed a YouTube video (where rport is 80) and from an FTP session where I put a large file onto a remote system. # dtrace -s tcp_slow_start.d ^C ALGORITHM RADDR RPORT #SEG Slow start 10.153.125.222 20 6 Slow start 138.3.237.7 80 14 Slow start 10.153.125.222 21 18 Congestion avoidance 10.153.125.222 20 1164 We see that in the case of the YouTube video, slow start was exclusively used. Most of the segments we sent in that case were likely ACKs. Compare this case - where 14 segments were sent using slow start - to the FTP case, where only 6 segments were sent before we switched to congestion avoidance for 1164 segments. In the case of the FTP session, the FTP data on port 20 was predominantly sent with congestion avoidance in operation, while the FTP session relied exclusively on slow start. For the default congestion control algorithm - "newreno" - on Solaris 11, slow start will increase the cwnd by 1 MSS for every acknowledgement received, and by 1 MSS for each RTT in congestion avoidance mode. Different pluggable congestion control algorithms operate slightly differently. For example "highspeed" will update the slow start cwnd by the number of bytes ACKed rather than the MSS. And to finish, here's a neat oneliner to visually display the distribution of congestion window values for all TCP connections to a given remote port using a quantization. In this example, only port 80 is in use and we see the majority of cwnd values for that port are in the 4096-8191 range. # dtrace -n 'tcp:::send { @q[args[4]-tcp_dport] = quantize(args[3]-tcps_cwnd); }' dtrace: description 'tcp:::send ' matched 10 probes ^C 80 value ------------- Distribution ------------- count -1 | 0 0 |@@@@@@ 5 1 | 0 2 | 0 4 | 0 8 | 0 16 | 0 32 | 0 64 | 0 128 | 0 256 | 0 512 | 0 1024 | 0 2048 |@@@@@@@@@ 8 4096 |@@@@@@@@@@@@@@@@@@@@@@@@@@ 23 8192 | 0

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  • How to recover data from a drive that was erased during the Ubuntu installation?

    - by user110353
    Yesterday I had two NTFS partitions on my drive. One on which Windows 7 was installed (C Drive) and the other contained my data (D Drive). During Ubuntu installation I choose to install Ubuntu and erase my existing OS. When Ubuntu installed, I was shocked to see no partition. All my data was gone. I must have done something wrong in selecting my option during installation. Is there any way I can recover my D Drive? Thanks in advance.

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  • Move Data into the grid for scalable, predictable response times

    - by JuergenKress
    CloudTran is pleased to introduce the availability of the CloudTran Transaction and Persistence Manager for creating scalable, reliable data services on the Oracle Coherence In-Memory Data Grid (IMDG). Use of IMDG architectures has been key to handling today’s web-scale loads because it eliminates database latency by storing important and frequently access data in memory instead of on disk. The CloudTran product lets developers easily use an IMDG for full ACID-compliant transactions without having to be concerned about the location or spread of data. The system has its own implementation of fast, scalable distributed transactions that does NOT depend on XA protocols but still guarantees all ACID properties. Plus, CloudTran asynchronously replicates data going into the IMDG to back-end datastores and back-up data centers, again ensuring ACID properties. CloudTran can be accessed through Java Persistence API (JPA via TopLink Grid) and now, through a new Low-Level API, or LLAPI. This is ideal for use in SOA applications that need data reliability, high availability, performance, and scalability. It is still in its limited beta release, the LLAPI gives developers the ability to use standard put/remove logic available in Coherence and then wrap logic with simple Spring annotations or XML+AspectJ to start transactions. An important feature of LLAPI is the ability to join transactions. This is a common outcome for SOA applications that need to reduce network traffic by aggregating data into single cache entries and then doing SOA service processing in the node holding the data. This results in the need to orchestrate transaction processing across multiple service calls. CloudTran has the capability to handle these “multi-client” transactions at speed with no loss in ACID properties. Developing software around an IMDG like Oracle Coherence is an important choice for today’s web-scale applications and services. But this introduces new architectural considerations to maintain scalability in light of increased network loads and data movement. Without using CloudTran, developers are faced with an incredibly difficult task to ensure data reliability, availability, performance, and scalability when working with an IMDG. Working with highly distributed data that is entirely volatile while stored in memory presents numerous edge cases where failures can result in data loss. The CloudTran product takes care of all of this, leaving developers with the confidence and peace of mind that all data is processed correctly. For those interested in evaluating the CloudTran product and IMDGs, take a look at this link for more information: http://www.CloudTran.com/downloadAPI.ph , or send your questions to [email protected]. 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: CloudTran,data grid,M,SOA Community,Oracle SOA,Oracle BPM,BPM,Community,OPN,Jürgen Kress

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  • Fusion CRM Data Integration and Migration from Conemis (D)

    - by Richard Lefebvre
    Conemis Data Integration Tools edited for Oracle Fusion CRM offers easy-to-use and pre-configured tools for data integration, data quality, and migration of data from Oracle CRM on Demand and third-party applications to Oracle Fusion CRM Conemis solution includes: Pressure Fueling of data for Fusion CRM Migration covered from legacy to Fusion CRM Data Quality in migration and integration Intuitive Data Housekeeping for IT and Sales Backups of Fusion CRM environments Conemis's solution benefits include Fusion CRM integrated out-of-the-box, connection to other applications, ready-made data mapping, instant availability without installation, fully configurable, shared use in integration expert groups, one GUI for several environments/pods, reduced costs & risks in migration projects, etc. Conemis AG, a German-based data integration company founded in 2009, offers Software and services solution and expertize for Oracle CRM products's data migration and integration. For more details, please contact Dr. Daniel Rolli ([email protected]) www.conemis.com.

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  • web services, J2EE, spring, DB integration project ideas- maybe data mining related?

    - by sj88
    Hey guys, I am a graduate CS student (Data mining and machine learning) and have a good exposure to core JAVA (3 years). I have read up a bunch of stuff on Design patterns J2EE Web services( soap and rest) spring and hibernate Java Concurrency - advanced features like Task and Executors. I would now like to do a project combining this stuff (over my free time of corse) to get a better understanding of these things and to kind of make an end to end software (to learn the best design principles etc + svn, maven). Any good project ideas would be really appreciated. I just wanna build this stuff to learn so I dont really mind re-inventing the wheel. Also, anything related to data mining would be an added bonus (fits with my research) but absolutly not necesary (since this project is more to learn to do large scale software developement)

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  • How can I store all my level data in a single file instead of spread out over many files?

    - by Jon
    I am currently generating my level data, and saving to disk to ensure that any modifications done to the level are saved. I am storing "chunks" of 2048x2048 pixels into a file. Whenever the player moves over a section that doesn't have a file associated with the position, a new file is created. This works great, and is very fast. My issue, is that as you are playing the file count gets larger and larger. I'm wondering what are techniques that can be used to alleviate the file count, without taking a performance hit. I am interested in how you would store/seek/update this data in a single file instead of multiple files efficiently.

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  • What is the most complicated data structure you have used in a practical situation?

    - by Fanatic23
    The germ for this question came up from a discussion I was having with couple of fellow developers from the industry. Turns out that in a lot of places project managers are wary about complex data structures, and generally insist on whatever exists out-of-the-box from standard library/packages. The general idea seems to be like use a combination of whats already available unless performance is seriously impeded. This helps keeping the code base simple, which to the non-diplomatic would mean "we have high attrition, and newer ones we hire may not be that good". So no bloom filter or skip-lists or splay trees for you CS junkies. So here's the question (again): Whats the most complicated data structure you did or used in office? Helps get a sense of how good/sophisticated real world software are.

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  • How can I protect my save data from casual hacking?

    - by Danran
    What options are there for saving game data in a secure manner? I'm interested in solutions specifically tailored for C++. I'm looking for something that is fast and easy to use. I'm only concerned about storing simple information such as Which levels are and are not unlocked The user's score for each level I'm curious again to know what's out there to use, any good libraries to use that give me nice, secure game data files that the average player can't mess with. I just found this here which looks very nice, but it would be great to get some opinions on potential other libraries/options out there.

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  • What data-structure/algorithm will allow me to send a list of key/value dictionaries using the least amount of bits?

    - by user12365
    I have server objects that have corresponding client objects. The data to be kept in sync is inside the server object's key/value dictionary. To keep the client objects in sync with the sever objects, I want the server to send the key/value dictionary every frame for each object. What data-structure/algorithm will allow me to send a list of key/value dictionaries using the least amount of bits? Bonus constraint 1: For each type of object, the values of some keys change more often than others. Bonus constraint 2: Memory usage on the server side is relatively expensive.

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  • Data structures for storing finger/stylus movements in drawing application?

    - by mattja?øb
    I have a general question about creating a drawing application, the language could be C++ or ObjectiveC with OpenGL. I would like to hear what are the best methods and practices for storing strokes data. Think of the many iPad apps that allow you to draw with your finger (or a stylus) or any other similar function on a desktop app. To summarize, the data structure must: be highly responsive to the movement store precise values (close in space / time) usable for rendering the strokes with complex textures (textures based on the dynamic of the stroke etc) exportable to a text file for saving/loading

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  • Unlock the Value of Big Data

    - by Mike.Hallett(at)Oracle-BI&EPM
    Partners should read this comprehensive new e-book to get advice from Oracle and industry leaders on how you can use big data to generate new business insights and make better decisions for your customers. “Big data represents an opportunity averaging 14% of current revenue.” —From the Oracle big data e-book, Meeting the Challenge of Big Data You’ll gain instant access to: Straightforward approaches for acquiring, organizing, and analyzing data Architectures and tools needed to integrate new data with your existing investments Survey data revealing how leading companies are using big data, so you can benchmark your progress Expert resources such as white papers, analyst videos, 3-D demos, and more If you want to be ready for the data deluge, Meeting the Challenge of Big Data is a must-read. Register today for the e-book and read it on your computer or Apple iPad.  

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  • Android: Having trouble creating a subclass of application to share data with multiple Activities

    - by Mike
    Hello, I just finished a couple of activities in my game and now I was going to start to wire them both up to use real game data, instead of the test data I was using just to make sure each piece worked. Since multiple Activities will need access to this game data, I started researching the best way to pass this data to my Activities. I know about using putExtra with intents, but my GameData class has quite a bit of data and not just simple key value pairs. Besides quite a few basic data types, it also has large arrays. I didn't really want to try and pass all that, unless I can pass the entire object, instead of just key/data pairs. I read the following post and thought it would be the way to go, but so far, I haven't got it to work. Android: How to declare global variables? I created a simple test app to try this method out, but it keeps crashing and my code seems to look the same as in the post above - except I changed the names. Here is the error I am getting. Can someone help me understand what I am doing wrong? 12-23 00:50:49.762: ERROR/AndroidRuntime(608): Caused by: java.lang.ClassCastException: android.app.Application It crashes on the following statement: GameData newGameData = ((GameData)getApplicationContext()); Here is my code: package mrk.examples.StaticGameData; import android.app.Application; public class GameData extends Application { private int intTest; GameData () { intTest = 0; } public int getIntTest(){ return intTest; } public void setIntTest(int value){ intTest = value; } } // My main activity package mrk.examples.StaticGameData; import android.app.Activity; import android.content.Intent; import android.os.Bundle; import android.util.Log; public class StaticGameData extends Activity { int intStaticTest; /** Called when the activity is first created. */ @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.main); GameData newGameData = ((GameData)getApplicationContext()); newGameData.setIntTest(0); intStaticTest = newGameData.getIntTest(); Log.d("StaticGameData", "Well: IntStaticTest = " + intStaticTest); newGameData.setIntTest(1); Log.d("StaticGameData", "Well: IntStaticTest = " + intStaticTest + " newGameData: " + newGameData.getIntTest()); Intent intentNew = new Intent(this, PassData2Activity.class); startActivity (intentNew); } } // My test Activity to see if it can access the data and its previous state from the last activity package mrk.examples.StaticGameData; import android.app.Activity; import android.os.Bundle; import android.util.Log; public class PassData2Activity extends Activity { @Override public void onCreate(Bundle savedInstanceState) { super.onCreate(savedInstanceState); setContentView(R.layout.main); GameData gamedataPass = ((GameData)getApplicationContext()); Log.d("PassData2Activity", "IntTest = " + gamedataPass.getIntTest()); } } Below is the relevant portion of my manifest: <application android:icon="@drawable/icon" android:label="@string/app_name"> <activity android:name=".StaticGameData" android:label="@string/app_name"> <intent-filter> <action android:name="android.intent.action.MAIN" /> <category android:name="android.intent.category.LAUNCHER" /> </intent-filter> </activity> <activity android:name=".PassData2Activity"></activity> </application> <application android:name=".GameData" android:icon="@drawable/icon" android:label="@string/app_name"> </application> Thanks in advance for helping me understand why this code is crashing. Also, if you think this is just the wrong approach to let multiple activities have access to the same data, please give your suggestion. Please keep in mind that I am talking about quite a few variables and some large arrays.

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  • DVCS and data loss?

    - by David Wolever
    After almost two years of using DVCS, it seems that one inherent "flaw" is accidental data loss: I have lost code which isn't pushed, and I know other people who have as well. I can see a few reasons for this: off-site data duplication (ie, "commits have to go to a remote host") is not built in, the repository lives in the same directory as the code and the notion of "hack 'till you've got something to release" is prevalent... But that's beside the point. I'm curious to know: have you experienced DVCS-related data loss? Or have you been using DVCS without trouble? And, related, apart from "remember to push often", is there anything which can be done to minimize the risk?

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  • Best practice? iphone: sync data

    - by Andy Jacobs
    So i'm working on a project where there is data visualization. My ultimate goal is that i have a set of data shipped with the download of the iphone app. But i want it connected to a backend, that if the iphone has a connection with the internet. it can sync the changes from the backend. The syncing is no problem or the connection between the backend & the iphone. But what should i use as data storage on my iphone? what is the best way. my data is purely text and doesn't have to be secure. But it's main feature should be updating certain parts of data ( adding and deleting are not so important ) so what is the easiest (read: least time consuming development ) or the best way? sqlite? plist? ..?

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  • Explaining persistent data structures in simple terms

    - by Jason Baker
    I'm working on a library for Python that implements some persistent data structures (mainly as a learning exercise). However, I'm beginning to learn that explaining persistent data structures to people unfamiliar with them can be difficult. Can someone help me think of an easy (or at least the least complicated) way to describe persistent data structures to them? I've had a couple of people tell me that the documentation that I have is somewhat confusing. (And before anyone asks, no I don't mean persistent data structures as in persisted to the file system. Google persistent data structures if you're unclear on this.)

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  • Aging Data Structure in C#

    - by thelsdj
    I want a data structure that will allow querying how many items in last X minutes. An item may just be a simple identifier or a more complex data structure, preferably the timestamp of the item will be in the item, rather than stored outside (as a hash or similar, wouldn't want to have problems with multiple items having same timestamp). So far it seems that with LINQ I could easily filter items with timestamp greater than a given time and aggregate a count. Though I'm hesitant to try to work .NET 3.5 specific stuff into my production environment yet. Are there any other suggestions for a similar data structure? The other part that I'm interested in is aging old data out, If I'm only going to be asking for counts of items less than 6 hours ago I would like anything older than that to be removed from my data structure because this may be a long-running program.

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  • Data mining logs to locate a bug

    - by gooli
    I'm working on a data distribution application which receives data from a source and distributes that data to multiple target application. After successfully distributing several messages each second for 8 days, it missed a single message and did not deliver it properly to the clients. As I was looking at the logs I tried to find something there that was special for the time the miss happend - either in the data, its rate or some other condition but couldn't find anything. Is there any data mining technique I can use to identify how that specific event differs from other events?

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  • How to build a data flow?

    - by salvationishere
    I am running Visual Studio 2008, the SSIS Tutorial described on: http://msdn.microsoft.com/en-us/library/ms167106.aspx I finished all of the tasks but am getting following errors: Error 1 Validation error. Extract Sample Currency Data: Extract Sample Currency Data: input column "CurrencyAlternateKey" (123) has lineage ID 55 that was not previously used in the Data Flow task. Lesson 1.dtsx 0 0 Error 2 Validation error. Extract Sample Currency Data SSIS.Pipeline: input column "CurrencyAlternateKey" (123) has lineage ID 55 that was not previously used in the Data Flow task. Lesson 1.dtsx 0 0 Can you tell what I need to do to make this build without errors?

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  • Parsing content-disposion header's filename in multipart/from-data

    - by Artyom
    Hello According to RFC, in multipart/form-data content-disposition header filename field receives as parameter HTTP quoted string - string between quites where character '\' can escape any other ascii character. Problem web browsers don't do it. IE6 sends: Content-Disposition: form-data; name="file"; filename="z:\tmp\test.txt" Instead of expected Content-Disposition: form-data; name="file"; filename="z:\\tmp\\test.txt" Which should be parsed as z:tmptest.txt according to rules instead of z:\tmp\test.txt. Firefox, Konqueror and Chrome don't escape " characters for example: Content-Disposition: form-data; name="file"; filename=""test".txt" Instead of expected Content-Disposition: form-data; name="file"; filename="\"test\".txt" So... how would you suggest to deal with this issue?

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  • Last Observation Carried Forward In a data frame?

    - by Tal Galili
    Hi all, I wish to implement a "Last Observation Carried Forward" for a data set I am working on which has missing values at the end of it. Here is a simple code to do it (question after it): LOCF <- function(x) { # Last Observation Carried Forward (for a left to right series) LOCF <- max(which(!is.na(x))) # the location of the Last Observation to Carry Forward x[LOCF:length(x)] <- x[LOCF] return(x) } # example: LOCF(c(1,2,3,4,NA,NA)) LOCF(c(1,NA,3,4,NA,NA)) Now this works great for simple vectors. But if I where to try and use it on a data frame: a <- data.frame(rep("a",4), 1:4,1:4, c(1,NA,NA,NA)) a t(apply(a, 1, LOCF)) # will make a mess It will turn my data frame into a character matrix. Can you think of a way to do LOCF on a data.frame, without turning it into a matrix? (I could use loops and such to correct the mess, but would love for a more elegant solution) Cheers, Tal

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  • How to preserve data integrity while minimizing the transmission size

    - by user1500578
    we have sensors in the wild that send their data to a server every day via TCP/IP, either through 3G or through satellite for the physical layer. The sensors can automatically switch from one to the other depending on their location and the quality of the signal with the local 3G operator. Given that the 3G and satellite communications are very expensive, we want to minimize the amount of data to send. But also, we want to protect ourselves from lost data. What would be the best strategy to ensure with reasonable certainty that the integrity of our data is preserved, while minimizing the amount of redundancy, i.e the amount of data transmitted ? I've read about the zfec codec, but I'm not sure if we need to transmit all the chunks, or if we need to send a hash code along each chunk.

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  • Merging MySQL Structure and Data

    - by Shahid
    I have a MySQL database running on a deployment machine which also contains data. Then I have another MySQL database which has evolved in terms of STRUCTURE + DATA for some time. I need a way to merge the changes (ONLY) for both structure and data to the DB in deployment machine without disturbing the existing data. Does anyone know of a tool available which can do this safely. I have had a look at a few comparison tools but I need a tool which can automate the merge operation. Note also that most of the data in the tables is in BINARY so I can't use many file comparison tools. Does any one know of a solution to this? thanks

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  • JavaScript data grid for millions of rows

    - by Rudiger
    I need to present millions of rows of data to users in a grid using JavaScript. I don't want the user thinking about viewing finite pieces of data; it should appear that all of the data is available. Rather than downloading all the data at once, small chunks are downloaded as the user comes to them (by scrolling, keying in row numbers, searching). The rows will not be edited through this front end, so read-only answers are acceptable. What JavaScript data grids are best for this kind of seamless paging?

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  • Letting Wcf data service implement another contract

    - by Wasim
    Hi all , I have a wcf data service with the standart configuration . I want to add another functionality to it , so I built a contract interface and let my wcf data service implements it . Now I see in the service the InitializeService method , and the contract interface methods . When I come to connect the service , I get an error , that there is no end point declared to the contract I added . How can do that ? examples ? links ? I choosed to add the contract interface to the wcf data service and not adding another service , because the client application uses the wcf data service generated objects , and I want to use the same obkject to make operations not related to data , for more coplex processing . If I do the methods in another service , then I have types incompatibility . Thanks in advance ...

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