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  • Livre blanc gratuit : « L'Environnement Personnalisable dans Windows Embedded 7 », l'OS embarqué fondé sur Windows 7

    Livre Blanc : l'environnement personnalisable dans Windows Embedded 7 Le système embarqué de Microsoft fondé sur Windows 7 L'utilisation des systèmes embarqués se distingue de celle des PC à maints égards. L'une des différences tient à la personnalisation et à l'usage de marques. Un système embarqué n'indique généralement aucune autre marque que celle de l'OEM, une exigence qui pose souvent problème au client. Dans sa dernière version, Windows Embedded Standard 7 tente de résoudre ces problèmes en proposant de nouvelles fonctionnalités pour faciliter l'intégration de marques et le blocage des messages. Pour présenter ces nouveautés (écrans de démarrage sans le marqu...

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  • Convert ddply {plyr} to Oracle R Enterprise, or use with Embedded R Execution

    - by Mark Hornick
    The plyr package contains a set of tools for partitioning a problem into smaller sub-problems that can be more easily processed. One function within {plyr} is ddply, which allows you to specify subsets of a data.frame and then apply a function to each subset. The result is gathered into a single data.frame. Such a capability is very convenient. The function ddply also has a parallel option that if TRUE, will apply the function in parallel, using the backend provided by foreach. This type of functionality is available through Oracle R Enterprise using the ore.groupApply function. In this blog post, we show a few examples from Sean Anderson's "A quick introduction to plyr" to illustrate the correpsonding functionality using ore.groupApply. To get started, we'll create a demo data set and load the plyr package. set.seed(1) d <- data.frame(year = rep(2000:2014, each = 3),         count = round(runif(45, 0, 20))) dim(d) library(plyr) This first example takes the data frame, partitions it by year, and calculates the coefficient of variation of the count, returning a data frame. # Example 1 res <- ddply(d, "year", function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(cv.count = cv)   }) To illustrate the equivalent functionality in Oracle R Enterprise, using embedded R execution, we use the ore.groupApply function on the same data, but pushed to the database, creating an ore.frame. The function ore.push creates a temporary table in the database, returning a proxy object, the ore.frame. D <- ore.push(d) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   sd.count <- sd(x$count)   cv <- sd.count/mean.count   data.frame(year=x$year[1], cv.count = cv)   }, FUN.VALUE=data.frame(year=1, cv.count=1)) You'll notice the similarities in the first three arguments. With ore.groupApply, we augment the function to return the specific data.frame we want. We also specify the argument FUN.VALUE, which describes the resulting data.frame. From our previous blog posts, you may recall that by default, ore.groupApply returns an ore.list containing the results of each function invocation. To get a data.frame, we specify the structure of the result. The results in both cases are the same, however the ore.groupApply result is an ore.frame. In this case the data stays in the database until it's actually required. This can result in significant memory and time savings whe data is large. R> class(res) [1] "ore.frame" attr(,"package") [1] "OREbase" R> head(res)    year cv.count 1 2000 0.3984848 2 2001 0.6062178 3 2002 0.2309401 4 2003 0.5773503 5 2004 0.3069680 6 2005 0.3431743 To make the ore.groupApply execute in parallel, you can specify the argument parallel with either TRUE, to use default database parallelism, or to a specific number, which serves as a hint to the database as to how many parallel R engines should be used. The next ddply example uses the summarise function, which creates a new data.frame. In ore.groupApply, the year column is passed in with the data. Since no automatic creation of columns takes place, we explicitly set the year column in the data.frame result to the value of the first row, since all rows received by the function have the same year. # Example 2 ddply(d, "year", summarise, mean.count = mean(count)) res <- ore.groupApply (D, D$year, function(x) {   mean.count <- mean(x$count)   data.frame(year=x$year[1], mean.count = mean.count)   }, FUN.VALUE=data.frame(year=1, mean.count=1)) R> head(res)    year mean.count 1 2000 7.666667 2 2001 13.333333 3 2002 15.000000 4 2003 3.000000 5 2004 12.333333 6 2005 14.666667 Example 3 uses the transform function with ddply, which modifies the existing data.frame. With ore.groupApply, we again construct the data.frame explicilty, which is returned as an ore.frame. # Example 3 ddply(d, "year", transform, total.count = sum(count)) res <- ore.groupApply (D, D$year, function(x) {   total.count <- sum(x$count)   data.frame(year=x$year[1], count=x$count, total.count = total.count)   }, FUN.VALUE=data.frame(year=1, count=1, total.count=1)) > head(res)    year count total.count 1 2000 5 23 2 2000 7 23 3 2000 11 23 4 2001 18 40 5 2001 4 40 6 2001 18 40 In Example 4, the mutate function with ddply enables you to define new columns that build on columns just defined. Since the construction of the data.frame using ore.groupApply is explicit, you always have complete control over when and how to use columns. # Example 4 ddply(d, "year", mutate, mu = mean(count), sigma = sd(count),       cv = sigma/mu) res <- ore.groupApply (D, D$year, function(x) {   mu <- mean(x$count)   sigma <- sd(x$count)   cv <- sigma/mu   data.frame(year=x$year[1], count=x$count, mu=mu, sigma=sigma, cv=cv)   }, FUN.VALUE=data.frame(year=1, count=1, mu=1,sigma=1,cv=1)) R> head(res)    year count mu sigma cv 1 2000 5 7.666667 3.055050 0.3984848 2 2000 7 7.666667 3.055050 0.3984848 3 2000 11 7.666667 3.055050 0.3984848 4 2001 18 13.333333 8.082904 0.6062178 5 2001 4 13.333333 8.082904 0.6062178 6 2001 18 13.333333 8.082904 0.6062178 In Example 5, ddply is used to partition data on multiple columns before constructing the result. Realizing this with ore.groupApply involves creating an index column out of the concatenation of the columns used for partitioning. This example also allows us to illustrate using the ORE transparency layer to subset the data. # Example 5 baseball.dat <- subset(baseball, year > 2000) # data from the plyr package x <- ddply(baseball.dat, c("year", "team"), summarize,            homeruns = sum(hr)) We first push the data set to the database to get an ore.frame. We then add the composite column and perform the subset, using the transparency layer. Since the results from database execution are unordered, we will explicitly sort these results and view the first 6 rows. BB.DAT <- ore.push(baseball) BB.DAT$index <- with(BB.DAT, paste(year, team, sep="+")) BB.DAT2 <- subset(BB.DAT, year > 2000) X <- ore.groupApply (BB.DAT2, BB.DAT2$index, function(x) {   data.frame(year=x$year[1], team=x$team[1], homeruns=sum(x$hr))   }, FUN.VALUE=data.frame(year=1, team="A", homeruns=1), parallel=FALSE) res <- ore.sort(X, by=c("year","team")) R> head(res)    year team homeruns 1 2001 ANA 4 2 2001 ARI 155 3 2001 ATL 63 4 2001 BAL 58 5 2001 BOS 77 6 2001 CHA 63 Our next example is derived from the ggplot function documentation. This illustrates the use of ddply within using the ggplot2 package. We first create a data.frame with demo data and use ddply to create some statistics for each group (gp). We then use ggplot to produce the graph. We can take this same code, push the data.frame df to the database and invoke this on the database server. The graph will be returned to the client window, as depicted below. # Example 6 with ggplot2 library(ggplot2) df <- data.frame(gp = factor(rep(letters[1:3], each = 10)),                  y = rnorm(30)) # Compute sample mean and standard deviation in each group library(plyr) ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y)) # Set up a skeleton ggplot object and add layers: ggplot() +   geom_point(data = df, aes(x = gp, y = y)) +   geom_point(data = ds, aes(x = gp, y = mean),              colour = 'red', size = 3) +   geom_errorbar(data = ds, aes(x = gp, y = mean,                                ymin = mean - sd, ymax = mean + sd),              colour = 'red', width = 0.4) DF <- ore.push(df) ore.tableApply(DF, function(df) {   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4) }) But let's take this one step further. Suppose we wanted to produce multiple graphs, partitioned on some index column. We replicate the data three times and add some noise to the y values, just to make the graphs a little different. We also create an index column to form our three partitions. Note that we've also specified that this should be executed in parallel, allowing Oracle Database to control and manage the server-side R engines. The result of ore.groupApply is an ore.list that contains the three graphs. Each graph can be viewed by printing the list element. df2 <- rbind(df,df,df) df2$y <- df2$y + rnorm(nrow(df2)) df2$index <- c(rep(1,300), rep(2,300), rep(3,300)) DF2 <- ore.push(df2) res <- ore.groupApply(DF2, DF2$index, function(df) {   df <- df[,1:2]   library(ggplot2)   library(plyr)   ds <- ddply(df, .(gp), summarise, mean = mean(y), sd = sd(y))   ggplot() +     geom_point(data = df, aes(x = gp, y = y)) +     geom_point(data = ds, aes(x = gp, y = mean),                colour = 'red', size = 3) +     geom_errorbar(data = ds, aes(x = gp, y = mean,                                  ymin = mean - sd, ymax = mean + sd),                   colour = 'red', width = 0.4)   }, parallel=TRUE) res[[1]] res[[2]] res[[3]] To recap, we've illustrated how various uses of ddply from the plyr package can be realized in ore.groupApply, which affords the user explicit control over the contents of the data.frame result in a straightforward manner. We've also highlighted how ddply can be used within an ore.groupApply call.

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  • Case Study: Polystar Improves Telecom Networks Performance with Embedded MySQL

    - by Bertrand Matthelié
    Polystar delivers and supports systems that increase the quality, revenue and customer satisfaction of telecommunication services. Headquarted in Sweden, Polystar helps operators worldwide including Telia, Tele2, Telekom Malysia and T-Mobile to monitor their network performance and improve service levels. Challenges Deliver complete turnkey solutions to customers integrating a database ensuring high performance at scale, while being very easy to use, manage and optimize. Enable the implementation of distributed architectures including one database per server while maintaining a low Total Cost of Ownership (TCO). Avoid growing database complexity as the volume of mobile data to monitor and analyze drastically increases. Solution Evaluation of several databases and selection of MySQL based on its high performance, manageability, and low TCO. The MySQL databases implemented within the Polystar solutions handle on average 3,000 to 5,000 transactions per second. Up to 50 million records are inserted every day in each database. Typical installations include between 50 and 100 MySQL databases, up to 300 for the largest ones. Data is then periodically aggregated, with the original records being overwritten, as the need for detailed information becomes unnecessary to operators after a few weeks. The exponential growth in mobile data traffic driven by the proliferation of smartphones and usage of social media requires ever more powerful solutions to monitor, analyze and turn network data into actionable business intelligence. With MySQL, Polystar can deliver powerful, yet easy to manage, solutions to its customers. MySQL-based Polystar solutions enable operators to monitor, manage and improve the service levels of their telecom networks in over a dozen countries from a single location. The new and innovative MySQL features constantly delivered by Oracle help ensure Polystar that it will be able to meet its customer’s needs as they evolve. “MySQL has been a great embedded database choice for us. It delivers the high performance we need while remaining very easy to use, manage and tune. Power and simplicity at its best.” Mats Söderlindh, COO at Polystar.

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  • Advice on designing a robust program to handle a large library of meta-information & programs

    - by Sam Bryant
    So this might be overly vague, but here it is anyway I'm not really looking for a specific answer, but rather general design principles or direction towards resources that deal with problems like this. It's one of my first large-scale applications, and I would like to do it right. Brief Explanation My basic problem is that I have to write an application that handles a large library of meta-data, can easily modify the meta-data on-the-fly, is robust with respect to crashing, and is very efficient. (Sorta like the design parameters of iTunes, although sometimes iTunes performs more poorly than I would like). If you don't want to read the details, you can skip the rest Long Explanation Specifically I am writing a program that creates a library of image files and meta-data about these files. There is a list of tags that may or may not apply to each image. The program needs to be able to add new images, new tags, assign tags to images, and detect duplicate images, all while operating. The program contains an image Viewer which has tagging operations. The idea is that if a given image A is viewed while the library has tags T1, T2, and T3, then that image will have boolean flags for each of those tags (depending on whether the user tagged that image while it was open in the Viewer). However, prior to being viewed in the Viewer, image A would have no value for tags T1, T2, and T3. Instead it would have a "dirty" flag indicating that it is unknown whether or not A has these tags or not. The program can introduce new tags at any time (which would automatically set all images to "dirty" with respect to this new tag) This program must be fast. It must be easily able to pull up a list of images with or without a certain tag as well as images which are "dirty" with respect to a tag. It has to be crash-safe, in that if it suddenly crashes, all of the tagging information done in that session is not lost (though perhaps it's okay to loose some of it) Finally, it has to work with a lot of images (10,000) I am a fairly experienced programmer, but I have never tried to write a program with such demanding needs and I have never worked with databases. With respect to the meta-data storage, there seem to be a few design choices: Choice 1: Invidual meta-data vs centralized meta-data Individual Meta-Data: have a separate meta-data file for each image. This way, as soon as you change the meta-data for an image, it can be written to the hard disk, without having to rewrite the information for all of the other images. Centralized Meta-Data: Have a single file to hold the meta-data for every file. This would probably require meta-data writes in intervals as opposed to after every change. The benefit here is that you could keep a centralized list of all images with a given tag, ect, making the task of pulling up all images with a given tag very efficient

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  • Installation of MS SQL Database 2005 on Windows XP Home Sp3 fails with no specific error

    - by PiotrK
    I am trying to install MS SQL Database 2005 on Windows XP Home SP3. It fails giving no reason ("Database failed to install"), then exits. I had already installed MS SQL Database Express Edition 2008 during 2005 setup. But when I removed 2008 one and tried to install 2005 afterwards it still failed with same error. The error happens when I am trying to install Dragon Age Toolset or Visual 2008 Pro edition. I do not known which else informations may be valuable as I never before encountered problems with installing MS database

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  • Opening an oracle database crashes the service

    - by tundal45
    I am experiencing a weird issue with Oracle where the service started fine after a crash. The database mount went fine as well. However, when I issue alter database open; command, the database does not open, gives a generic cannot connect to the database error & crashes the service. Oracle support has not seen this issue before so it's pretty scary. The fact that there are no logs that give any leads as to what could be causing this is also scary. I was wondering if good folks over at Server Fault had seen something like this or have some insights on things that I could try. It's Oracle 10g running on Windows Server 2003. Thanks, Ashish

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  • JavaOne - Java SE Embedded Booth - Freescale Technologies

    - by David Clack
    Hi All, I've been working with Freescale this year on both the Power Architecture (PPC) and ARM solutions to test Java SE Embedded we will have a special Freescale demo case I had built, in the booth at JavaOne is the Freescale i.MX28, i.MX53 and i.MX6 demos plus the P1025 Tower Power Architecture demo. Freescale i.MX ARM Freescale Power Architecture This year we became a sponsor at the Freescale Technology Forum shows in San Antonio, TX, Beijing, China and Bangalore, India, FTF Japan is at the end of October in Tokyo. It's really exciting to get to see what is being developed in the M2M and IoT space on the Freescale technologies, lots of products use the Freescale chips with Java that we don't even really know about like the original Amazon Kindle. If you are registered at JavaOne you can come over to the Java Embedded @ JavaOne for $100 Come see us in booth 5605 See you there Dave

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  • problem with crating table on phpMyAdmin database

    - by tombull89
    Hello all, I'm running a phpMyAdmin Database on my web package on a 1and1-hosted server. I've managed to set up a database in the control panel, have uploaded all to root/phpmyadmin and changed the config.ini.php file to point at 1and1's database server (because that's the way they do it). I can go to the web interface and get to the main page, but all it shows is the database name and I can't find how to create any tables. I know it's a long shot but I'm almost out of ideas. Also, 1and1 have their own phpmyadmin panel, which is pretty annoying to use, and a 1and1 webdatabase which I have barely looked at. Help and suggestions much appriciated.

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  • How to implement Comet in database side?

    - by Morgan Cheng
    I have been searched for this question for a long time. How to implement Comet in database side? To support Comet, we'd better have a web server stack that supports asynchronous operation. So, Apache is not a option. There are some open source web server such as tornado can do asynchronous http handling. This is in web server level. In database level, how to make web server know that some event happens in database? There should be a asynchronous way to let web server know that something updated in database. Polling is not a option. Is there any example available?

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  • Should all foreign table references use foreign key constraints

    - by TecBrat
    Closely related to: Foreign key restrictions -> yes or no? I asked a question on SO and it led me to ask this here. If I'm faced with a choice of having a circular reference or just not enforcing the restraint, which is the better choice? In my particular case I have customers and addresses. I want an address to have a reference to a customer and I want each customer to have a default billing address id and a default shipping address id. I might query for all addresses that have a certain customer ID or I might query for the address with the ID that matches the default shipping or billing address ids. I'm not sure yet how the constraints (or lack of) will effect the system as my application and it's data age.

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  • Video conference/chat tool that can be embedded in own website needed

    - by Olaf
    We are looking for a means (a tool, a commercial service) to enable a closed user group to start a live video conference in a browser, as part of the company website. Something like Skype, but embedded and available for everybody that has access to the page into which the tool is embedded. Most services require registration and the creation of a chat room on their website, or, as Skype or similar solutions, the installation of an extra software. What we need is a solution with some kind of a "hidden login", performed by the site's client script (which knows who the user is and forwards the credentials to the service). Any suggestion?

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  • Is there a good, free, online database application?

    - by andygrunt
    Google docs doesn't have a database app (yet) but can anyone point me to a good, free, online substitute? It'll be for simple things like a database of my DVD collection and I'd want to be able to import/export using standard file formats and add/edit fields of existing databses. By the way, I'm not interested in using a spreadsheet as a database.

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  • Relationships in a Chen ERD

    - by Nibroc A Rehpotsirhc
    I am working on a Chen ERD to model our organizations merchandise. Our central entity is a Style. We have supplemental entities of Color and Season. I am defining our assortment as the relationship between these three entities, and this relationship itself will have attributes and is defined by the three entities which participate in the mandatory relationship. The rules are; Many Styles can be offered in a Season, and a Style can be offered in many Seasons. Within a Season, a Style can be offered in Many Colors. I then have 2 other entities, one of which I believe is a weak entity, Climate, and the other may be weak, but I am not sure, this being Transaction Channel. I am thinking of these as relationships off of a relationship? Meaning, for a given Style/Color combination offered in a Season, it can be available through 1 or more Transaction Channels. Additionally, within a season, a given Style/Color combination can be intended for 1 or more Climates. Is it valid to have relationships off of relationships? Or does this requirement dictate that I should think of this Style/Color/Season relationship as an entity itself, and define the relationships to Climate and Transaction Channel off of this entity?

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  • DHCP server with database backend

    - by Cory J
    I have been looking around for something to replace my (ancient) ISC-DHCPd server. A DHCP server with a database backend sounds like a great idea to me, as I could then have a nice, friendly web interface to my server. Surprisingly, I can't any major open-source projects that offer this. Does anyone know of one? I have also read about modifying ISC to use a database backend...can anyone tell me if this solution is stable enough for a busy production server? Or is using a database a Bad Idea™ all together? PS - http://stackoverflow.com/questions/893887/dchp-with-database-backend looks like SO couldn't answer this old, similar question. EDIT: I am looking for something on a free OS platform, Linux or BSD. If there is something absolutely great that is Windows-only though, still interested.

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  • Why many designs ignore normalization in RDBMS?

    - by Yosi
    I got to see many designs that normalization wasn't the first consideration in decision making phase. In many cases those designs included more than 30 columns, and the main approach was "to put everything in the same place" According to what I remember normalization is one of the first, most important things, so why is it dropped so easily sometimes? Edit: Is it true that good architects and experts choose a denormalized design while non-experienced developers choose the opposite? What are the arguments against starting your design with normalization in mind?

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  • Memory Management/Embedded Management in C

    - by Sauron
    Im wondering if there is a set or a few good books/Tutorials/Etc.. that go into Memory Management/Allocation Specifically (or at least have a good dedicated section to it) when it comes to C. This is more for me learning Embedded and trying to keep Size down. I've read and Learned C fine, and the "standard" Learning books. However most of the books don't spend a huge amount of time (Understandably since C is pretty huge in general) going into the Finer details about whats going on Down Under. I saw a few on Amazon: http://www.amazon.com/C-Pointers-Dynamic-Memory-Management/dp/0471561525 http://www.amazon.com/Understanding-Pointers-C-Yashavant-Kanetkar/dp/8176563587/ref=pd_sim_b_1 (Not sure how relevant this would be) A specific Book for Embedded that has to do with this would be nice. But Code Samples or...Heck tutorials or anything about this topic would be helpful!

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  • Problem with creating table on phpMyAdmin database

    - by tombull89
    Hello all, I'm running a phpMyAdmin Database on my web package on a 1and1-hosted server. I've managed to set up a database in the control panel, have uploaded all to root/phpmyadmin and changed the config.ini.php file to point at 1and1's database server (because that's the way they do it). I can go to the web interface and get to the main page, but all it shows is the database name and I can't find how to create any tables. I know it's a long shot but I'm almost out of ideas. Also, 1and1 have their own phpmyadmin panel, which is pretty annoying to use, and a 1and1 webdatabase which I have barely looked at. Help and suggestions much appriciated.

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  • Keep user and user profile in different tables?

    - by Andrey
    I have seen in a couple of projects that developers prefer to keep essential user info in one table (email/login, password hash, screen name) and rest of the non essential user profile in another (creation date, country, etc). By non-essential I mean that this data is needed only occasionally. Obvious benefit is that if you are using ORM querying less fields is obviously good. But then you can have two entities mapped to same table and this will save you from querying stuff you don't need (while being more convenient). Does anybody know any other advantage of keeping these things in two tables?

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  • How can you predict the time it will take for two processes in two different machines in a cluster to communicate?

    - by Dokkat
    I am trying to develop a computing application which needs a lot of memory (500gb). Buying a single machine for that is overly expensive. I can, though, buy ~100 small instances on Digital Ocean or similar, divide the memory in blocks and use TCP to emulate shared memory between the instances. Now, my question is: how can I measure/predict the time it will take for two processes in two different machines like that to share information, in comparison to IPC and shared memory? Are there rules of thumb? I don't want exact values, but knowing more or less how much faster one is would be very helpful in visualising the feasibility of this approach.

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  • Best approach for saving highlighted areas on geographical map.

    - by Mohsen
    I am designing an application that allow users to highlight areas of a geographical map using a tool that is like brush or a pen. The tool basically draw a circle with a single click and continue drawing those circles with move move. Here is an example of drawing made by moving the tool. It is pretty much same as Microsoft Paint. Regardless of programming language what is best approach (most inexpensive approach) for saving this kind of data?

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  • Disk full, how to move mysql database files?

    - by kopeklan
    my database files located in /var/lib/mysql which located in partition /dev/sda5 this partition is full (refer here for details) so I'm going to move the location of database files from /var/lib/mysql to /home/lib/mysql What is the right way to move this database files? Im going to do this steps: Stop http server and PHP Change datadir=/var/lib/mysql to become datadir=/home/lib/mysql in /etc/my.cnf move all database files to the new location run killall -9 mysql, then /etc/init.d/mysqld start Start http server and PHP Is this right? Correct me if I'm wrong added: currently, mysql won't stop. refer here: mysql wont stop, mysqld_safe appeared in top

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  • Handling deleted users - separate or same table?

    - by Alan Beats
    The scenario is that I've got an expanding set of users, and as time goes by, users will cancel their accounts which we currently mark as 'deleted' (with a flag) in the same table. If users with the same email address (that's how users log in) wish to create a new account, they can signup again, but a NEW account is created. (We have unique ids for every account, so email addresses can be duplicated amongst live and deleted ones). What I've noticed is that all across our system, in the normal course of things we constantly query the users table checking the user is not deleted, whereas what I'm thinking is that we dont need to do that at all...! [Clarification1: by 'constantly querying', I meant that we have queries which are like: '... FROM users WHERE isdeleted="0" AND ...'. For example, we may need to fetch all users registered for all meetings on a particular date, so in THAT query, we also have FROM users WHERE isdeleted="0" - does this make my point clearer?] (1) continue keeping deleted users in the 'main' users table (2) keep deleted users in a separate table (mostly required for historical book-keeping) What are the pros and cons of either approach?

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  • Opening an oracle database crashes the service [SOLVED]

    - by tundal45
    I am experiencing a weird issue with Oracle where the service started fine after a crash. The database mount went fine as well. However, when I issue alter database open; command, the database does not open, gives a generic cannot connect to the database error & crashes the service. Oracle support has not seen this issue before so it's pretty scary. The fact that there are no logs that give any leads as to what could be causing this is also scary. I was wondering if good folks over at Server Fault had seen something like this or have some insights on things that I could try. It's Oracle 10g running on Windows Server 2003. Thanks, Ashish

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  • MTD mtd3ro backup returns BCH decoding failed

    - by saeed144
    While doing a kernel backup of an mtd (Memory Technology Device) from /dev/mtd/mtd3ro of a TI board gives many "BCH decoding failed", Here are system info #cat /proc/mtd dev: size erasesize name mtd0: 00080000 00020000 "X-Loader" mtd1: 00140000 00020000 "U-Boot" mtd2: 000c0000 00020000 "U-Boot Env" mtd3: 00500000 00020000 "Kernel" mtd4: 1f880000 00020000 "File System" here is the method used, dd if=/dev/mtd/mtd3ro of=/data/local/tmp/mtd3.bin doing a cat also returns the same error, and here is the error, BCH decoding failed BCH decoding failed yes, the destination has enough space ;) tell me what do you think? Thanks

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