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  • Creating a view linking three different node types with two node references

    - by mikesir87
    I have the following content types: Camp - the top level type Registration Information - contains node reference to Camp called Camp Medical Release Form - contains node reference to registration information called Camper I would like to create a View that takes the nid for the Camp, and pulls out all the fields for the Registration Info and Medical Release Form. I'm having trouble figuring out how to set up the various arguments/relationships. I haven't done something that's referenced more than two types. I know it would be smart/best to just combine the Registration Info and Medical Release Form, since it's a 1:1 mapping, but we can't. So... any help would be appreciated!

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  • Are there any frameworks for data subscription and update?

    - by Timothy Pratley
    There is one server with multiple clients. The clients are viewing subsets of the servers entire data. If the data that a client is viewing changes, the client should be informed of the changes so that it displays the current data. Example: Two clients are viewing a list of users in an administration screen. One client adds a new user to the list and modifies the permissions of another user. The other client sees the changes propagated to their view.

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  • Best way to migrate servers without losing any data and with no downtime(?)

    - by ina
    This is a methodology question from a freelancer, with a corollary on MySQL.. Is there a way to migrate from an old dedicated server to a new one without losing any data in-between - and with no downtime? In the past, I've had to lose MySQL data between the time when the new server goes up (i.e., all files transferred, system up and ready), and when I take the old server down (data still transferred to old until new one takes over). There is also a short period where both are down for DNS, etc., to refresh. Is there a way for MySQL/root to easily transfer all data that was updated/inserted between a certain time frame?

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  • Is there an difference between transient properties defined in the data model, or in the custom subc

    - by mystify
    I was reading that setting the value of a transient property always results in marking the managed object as "dirty". However, what I don't get is this: If I make a subclass of NSManagedObject and use some extra properties which I don't need to be persistet, how does Core Data know about them and how can it mark the object as dirty when I access these? Again, they're not defined in the data model, so Core Data has no really good hint that they are there. Or does Core Data use some kind of introspection to analyze my custom class and figure out what properties I have in there?

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  • Changing colour of types for VB.net in VS

    - by vdh_ant
    I am currently working on a VB.NET project and the hardest thing that I am having trouble with is that everything is black and blue. Having worked a lot with C#, I really like the way that types are colored differently. I have tried going in and having a look at the "Tools > Options > Fonts and Colors" and the various "User Types" under "Display Items" is set to a different colour but its not reflecting that colour in the text editor. Any assistance would be appreciated.

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  • Widget_Controller for different types of data (MVC)

    - by steve-o
    Hello, I have a few widgets I need to show on a site - they are all relating to different types of data (e.g user, house). Each type of data and its relations is represented in specific models, but as far as a controller or helper is concerned, is it an ok plan to have a generic Widget controller/helper which generates the necessary widgets, even though each widget is dealing with distinct data? I don't really want to generate these widgets within the User and House controllers, as these controllers are dealing with different types of functionality. I'd imagine that the Widget_Controller could just contain static methods for generating these widgets, e.g: Widget_Controller::user_panel(); Does that make sense? Cheers!

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  • Mass data store with SQL SERVER

    - by Leo
    We need management 10,000 GPS devices, each GPS device upload a GPS data every 30 seconds, these data need to store in the database(MS SQL Server 2005). Each GPS device daily data quantity is: 24 * 60 * 2 = 2,880 10 000 10,000 GPS devices daily data quantity is: 10000 * 2880 = 28,800,000 Each GPS data approximately 160Byte, the amount of data per day is: 28,800,000 * 160 = 4.29GB We need hold at least 3 months of GPS data in the database, My question is: 1, whether SQL Server 2005 can support such a large amount of data store? 2, How to plan data table? (all GPS data storage in one table? Daily table? Each GPS device with a GPS data table?) The GPS data: GPSID varchar(21), RecvTime datetime, GPSTime datetime, IsValid bit, IsNavi bit, Lng float, Lat float, Alt float, Spd smallint, Head smallint, PulseValue bigint, Oil float, TSW1 bigint, TSW1Mask bigint, TSW2 bigint, TSW2Mask, BSW bigint, StateText varchar(200), PosText varchar(200), UploadType tinyint

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  • R: How to write out a data.frame so that I can paste it into SO for others to read?

    - by John
    I have a large data.frame displaying some weird properties when plotted. I'd like to ask a question about it on Stackoverflow, to do that I'd like to write the data.frame out in a form that I can paste it into SO and somebody else can easily run it and have it back into a data.frame object again. Is there an easy way to accomplish this? Also, if it is really long, should I use paste bin instead of directly paste it here?

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  • C# or windows equivalent of OS X's Core Data?

    - by Nektarios
    I'm late to the boat and have only just now started using Core Data in OS X / Cocoa - it's incredible and is really changing the way I look at things. Is there an equivalent technology in C# or the modern Windows frameworks? i.e. having managed data types where you get saving, data management, deleting, searching all for free? Also wondering if there's anything like this on Linux.

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  • What is the most efficient way to use Core Data?

    - by Eric
    I'm developing an iPad application using Core Data, and was hoping someone could clarify something about Core Data. Right now, I populate my table by making a fetch request for all of my data in viewDidLoad. I'd rather make individual fetch requests in my tableView:cellForRowAtIndexPath:. Can anyone tell me which is more efficient, and why? In other words, is it much less efficient to make lots of small requests as opposed to one big request?

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  • What happens if a user jumps over 10 versions before updating, and every version had a new data mode

    - by dontWatchMyProfile
    Example: User installs app v.1.0, adds data. Then the dev submits 10 updates in 10 weeks. After 11 weeks, the user wants v.11.0 and grabs a copy from the app store. Assuming that the app has got 11 .xcdatamodel versions inside, where ***11.xcdatamodel is the current one, what would happen now since the persistent store of the user is ages old? would the migration happen 10 times, step-by-step through every migration iteration? Or does the actual migration of data (lets assume gigabytes of data) happen exactly once, after Core Data (or the persistent store coordinator) has figured out precisely what to do to go from v.1.0 to v.11.0?

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  • Iterating over a large data set in long running Python process - memory issues?

    - by user1094786
    I am working on a long running Python program (a part of it is a Flask API, and the other realtime data fetcher). Both my long running processes iterate, quite often (the API one might even do so hundreds of times a second) over large data sets (second by second observations of certain economic series, for example 1-5MB worth of data or even more). They also interpolate, compare and do calculations between series etc. What techniques, for the sake of keeping my processes alive, can I practice when iterating / passing as parameters / processing these large data sets? For instance, should I use the gc module and collect manually? Any advice would be appreciated. Thanks!

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  • Metrics - A little knowledge can be a dangerous thing (or 'Why you're not clever enough to interpret metrics data')

    - by Jason Crease
    At RedGate Software, I work on a .NET obfuscator  called SmartAssembly.  Various features of it use a database to store various things (exception reports, name-mappings, etc.) The user is given the option of using either a SQL-Server database (which requires them to have Microsoft SQL Server), or a Microsoft Access MDB file (which requires nothing). MDB is the default option, but power-users soon switch to using a SQL Server database because it offers better performance and data-sharing. In the fashionable spirit of optimization and metrics, an obvious product-management question is 'Which is the most popular? SQL Server or MDB?' We've collected data about this fact, using our 'Feature-Usage-Reporting' technology (available as part of SmartAssembly) and more recently our 'Application Metrics' technology: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 28 19.0 8115 8115 MDB 114 77.6 1449 1449 (As a disclaimer, please note than SmartAssembly has far more than 132 users . This data is just a selection of one build) So, it would appear that SQL-Server is used by fewer users, but more often. Great. But here's why these numbers are useless to me: Only the original developers understand the data What does a single 'usage' of 'MDB' mean? Does this happen once per run? Once per option change? On clicking the 'Obfuscate Now' button? When running the command-line version or just from the UI version? Each question could skew the data 10-fold either way, and the answers only known by the developer that instrumented the application in the first place. In other words, only the original developer can interpret the data - product-managers cannot interpret the data unaided. Most of the data is from uninterested users About half of people who download and run a free-trial from the internet quit it almost immediately. Only a small fraction use it sufficiently to make informed choices. Since the MDB option is the default one, we don't know how many of those 114 were people CHOOSING to use the MDB, or how many were JUST HAPPENING to use this MDB default for their 20-second trial. This is a problem we see across all our metrics: Are people are using X because it's the default or are they using X because they want to use X? We need to segment the data further - asking what percentage of each percentage meet our criteria for an 'established user' or 'informed user'. You end up spending hours writing sophisticated and dubious SQL queries to segment the data further. Not fun. You can't find out why they used this feature Metrics can answer the when and what, but not the why. Why did people use feature X? If you're anything like me, you often click on random buttons in unfamiliar applications just to explore the feature-set. If we listened uncritically to metrics at RedGate, we would eliminate the most-important and more-complex features which people actually buy the software for, leaving just big buttons on the main page and the About-Box. "Ah, that's interesting!" rather than "Ah, that's actionable!" People do love data. Did you know you eat 1201 chickens in a lifetime? But just 4 cows? Interesting, but useless. Often metrics give you a nice number: '5.8% of users have 3 or more monitors' . But unless the statistic is both SUPRISING and ACTIONABLE, it's useless. Most metrics are collected, reviewed with lots of cooing. and then forgotten. Unless a piece-of-data could change things, it's useless collecting it. People get obsessed with significance levels The first things that lots of people do with this data is do a t-test to get a significance level ("Hey! We know with 99.64% confidence that people prefer SQL Server to MDBs!") Believe me: other causes of error/misinterpretation in your data are FAR more significant than your t-test could ever comprehend. Confirmation bias prevents objectivity If the data appears to match our instinct, we feel satisfied and move on. If it doesn't, we suspect the data and dig deeper, plummeting down a rabbit-hole of segmentation and filtering until we give-up and move-on. Data is only useful if it can change our preconceptions. Do you trust this dodgy data more than your own understanding, knowledge and intelligence?  I don't. There's always multiple plausible ways to interpret/action any data Let's say we segment the above data, and get this data: Post-trial users (i.e. those using a paid version after the 14-day free-trial is over): Parameter Number of users % of total users Number of sessions Number of usages SQL Server 13 9.0 1115 1115 MDB 5 4.2 449 449 Trial users: Parameter Number of users % of total users Number of sessions Number of usages SQL Server 15 10.0 7000 7000 MDB 114 77.6 1000 1000 How do you interpret this data? It's one of: Mostly SQL Server users buy our software. People who can't afford SQL Server tend to be unable to afford or unwilling to buy our software. Therefore, ditch MDB-support. Our MDB support is so poor and buggy that our massive MDB user-base doesn't buy it.  Therefore, spend loads of money improving it, and think about ditching SQL-Server support. People 'graduate' naturally from MDB to SQL Server as they use the software more. Things are fine the way they are. We're marketing the tool wrong. The large number of MDB users represent uninformed downloaders. Tell marketing to aggressively target SQL Server users. To choose an interpretation you need to segment again. And again. And again, and again. Opting-out is correlated with feature-usage Metrics tends to be opt-in. This skews the data even further. Between 5% and 30% of people choose to opt-in to metrics (often called 'customer improvement program' or something like that). Casual trial-users who are uninterested in your product or company are less likely to opt-in. This group is probably also likely to be MDB users. How much does this skew your data by? Who knows? It's not all doom and gloom. There are some things metrics can answer well. Environment facts. How many people have 3 monitors? Have Windows 7? Have .NET 4 installed? Have Japanese Windows? Minor optimizations.  Is the text-box big enough for average user-input? Performance data. How long does our app take to start? How many databases does the average user have on their server? As you can see, questions about who-the-user-is rather than what-the-user-does are easier to answer and action. Conclusion Use SmartAssembly. If not for the metrics (called 'Feature-Usage-Reporting'), then at least for the obfuscation/error-reporting. Data raises more questions than it answers. Questions about environment are the easiest to answer.

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  • Data management in unexpected places

    - by Ashok_Ora
    Normal 0 false false false EN-US X-NONE X-NONE Data management in unexpected places When you think of network switches, routers, firewall appliances, etc., it may not be obvious that at the heart of these kinds of solutions is an engine that can manage huge amounts of data at very high throughput with low latencies and high availability. Consider a network router that is processing tens (or hundreds) of thousands of network packets per second. So what really happens inside a router? Packets are streaming in at the rate of tens of thousands per second. Each packet has multiple attributes, for example, a destination, associated SLAs etc. For each packet, the router has to determine the address of the next “hop” to the destination; it has to determine how to prioritize this packet. If it’s a high priority packet, then it has to be sent on its way before lower priority packets. As a consequence of prioritizing high priority packets, lower priority data packets may need to be temporarily stored (held back), but addressed fairly. If there are security or privacy requirements associated with the data packet, those have to be enforced. You probably need to keep track of statistics related to the packets processed (someone’s sure to ask). You have to do all this (and more) while preserving high availability i.e. if one of the processors in the router goes down, you have to have a way to continue processing without interruption (the customer won’t be happy with a “choppy” VoIP conversation, right?). And all this has to be achieved without ANY intervention from a human operator – the router is most likely to be in a remote location – it must JUST CONTINUE TO WORK CORRECTLY, even when bad things happen. How is this implemented? As soon as a packet arrives, it is interpreted by the receiving software. The software decodes the packet headers in order to determine the destination, kind of packet (e.g. voice vs. data), SLAs associated with the “owner” of the packet etc. It looks up the internal database of “rules” of how to process this packet and handles the packet accordingly. The software might choose to hold on to the packet safely for some period of time, if it’s a low priority packet. Ah – this sounds very much like a database problem. For each packet, you have to minimally · Look up the most efficient next “hop” towards the destination. The “most efficient” next hop can change, depending on latency, availability etc. · Look up the SLA and determine the priority of this packet (e.g. voice calls get priority over data ftp) · Look up security information associated with this data packet. It may be necessary to retrieve the context for this network packet since a network packet is a small “slice” of a session. The context for the “header” packet needs to be stored in the router, in order to make this work. · If the priority of the packet is low, then “store” the packet temporarily in the router until it is time to forward the packet to the next hop. · Update various statistics about the packet. In most cases, you have to do all this in the context of a single transaction. For example, you want to look up the forwarding address and perform the “send” in a single transaction so that the forwarding address doesn’t change while you’re sending the packet. So, how do you do all this? Berkeley DB is a proven, reliable, high performance, highly available embeddable database, designed for exactly these kinds of usage scenarios. Berkeley DB is a robust, reliable, proven solution that is currently being used in these scenarios. First and foremost, Berkeley DB (or BDB for short) is very very fast. It can process tens or hundreds of thousands of transactions per second. It can be used as a pure in-memory database, or as a disk-persistent database. BDB provides high availability – if one board in the router fails, the system can automatically failover to another board – no manual intervention required. BDB is self-administering – there’s no need for manual intervention in order to maintain a BDB application. No need to send a technician to a remote site in the middle of nowhere on a freezing winter day to perform maintenance operations. BDB is used in over 200 million deployments worldwide for the past two decades for mission-critical applications such as the one described here. You have a choice of spending valuable resources to implement similar functionality, or, you could simply embed BDB in your application and off you go! I know what I’d do – choose BDB, so I can focus on my business problem. What will you do? /* 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;}

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  • Data Source Connection Pool Sizing

    - by Steve Felts
    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:0in; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:10.0pt; font-family:"Times New Roman","serif";} One of the most time-consuming procedures of a database application is establishing a connection. The connection pooling of the data source can be used to minimize this overhead.  That argues for using the data source instead of accessing the database driver directly. Configuring the size of the pool in the data source is somewhere between an art and science – this article will try to move it closer to science.  From the beginning, WLS data source has had an initial capacity and a maximum capacity configuration values.  When the system starts up and when it shrinks, initial capacity is used.  The pool can grow to maximum capacity.  Customers found that they might want to set the initial capacity to 0 (more on that later) but didn’t want the pool to shrink to 0.  In WLS 10.3.6, we added minimum capacity to specify the lower limit to which a pool will shrink.  If minimum capacity is not set, it defaults to the initial capacity for upward compatibility.   We also did some work on the shrinking in release 10.3.4 to reduce thrashing; the algorithm that used to shrink to the maximum of the currently used connections or the initial capacity (basically the unused connections were all released) was changed to shrink by half of the unused connections. The simple approach to sizing the pool is to set the initial/minimum capacity to the maximum capacity.  Doing this creates all connections at startup, avoiding creating connections on demand and the pool is stable.  However, there are a number of reasons not to take this simple approach. When WLS is booted, the deployment of the data source includes synchronously creating the connections.  The more connections that are configured in initial capacity, the longer the boot time for WLS (there have been several projects for parallel boot in WLS but none that are available).  Related to creating a lot of connections at boot time is the problem of logon storms (the database gets too much work at one time).   WLS has a solution for that by setting the login delay seconds on the pool but that also increases the boot time. There are a number of cases where it is desirable to set the initial capacity to 0.  By doing that, the overhead of creating connections is deferred out of the boot and the database doesn’t need to be available.  An application may not want WLS to automatically connect to the database until it is actually needed, such as for some code/warm failover configurations. There are a number of cases where minimum capacity should be less than maximum capacity.  Connections are generally expensive to keep around.  They cause state to be kept on both the client and the server, and the state on the backend may be heavy (for example, a process).  Depending on the vendor, connection usage may cost money.  If work load is not constant, then database connections can be freed up by shrinking the pool when connections are not in use.  When using Active GridLink, connections can be created as needed according to runtime load balancing (RLB) percentages instead of by connection load balancing (CLB) during data source deployment. Shrinking is an effective technique for clearing the pool when connections are not in use.  In addition to the obvious reason that there times where the workload is lighter,  there are some configurations where the database and/or firewall conspire to make long-unused or too-old connections no longer viable.  There are also some data source features where the connection has state and cannot be used again unless the state matches the request.  Examples of this are identity based pooling where the connection has a particular owner and XA affinity where the connection is associated with a particular RAC node.  At this point, WLS does not re-purpose (discard/replace) connections and shrinking is a way to get rid of the unused existing connection and get a new one with the correct state when needed. So far, the discussion has focused on the relationship of initial, minimum, and maximum capacity.  Computing the maximum size requires some knowledge about the application and the current number of simultaneously active users, web sessions, batch programs, or whatever access patterns are common.  The applications should be written to only reserve and close connections as needed but multiple statements, if needed, should be done in one reservation (don’t get/close more often than necessary).  This means that the size of the pool is likely to be significantly smaller then the number of users.   If possible, you can pick a size and see how it performs under simulated or real load.  There is a high-water mark statistic (ActiveConnectionsHighCount) that tracks the maximum connections concurrently used.  In general, you want the size to be big enough so that you never run out of connections but no bigger.   It will need to deal with spikes in usage, which is where shrinking after the spike is important.  Of course, the database capacity also has a big influence on the decision since it’s important not to overload the database machine.  Planning also needs to happen if you are running in a Multi-Data Source or Active GridLink configuration and expect that the remaining nodes will take over the connections when one of the nodes in the cluster goes down.  For XA affinity, additional headroom is also recommended.  In summary, setting initial and maximum capacity to be the same may be simple but there are many other factors that may be important in making the decision about sizing.

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  • Data Source Security Part 4

    - by Steve Felts
    So far, I have covered Client Identity and Oracle Proxy Session features, with WLS or database credentials.  This article will cover one more feature, Identify-based pooling.  Then, there is one more topic to cover - how these options play with transactions.Identity-based Connection Pooling An identity based pool creates a heterogeneous pool of connections.  This allows applications to use a JDBC connection with a specific DBMS credential by pooling physical connections with different DBMS credentials.  The DBMS credential is based on either the WebLogic user mapped to a database user or the database user directly, based on the “use database credentials” setting as described earlier. Using this feature enabled with “use database credentials” enabled seems to be what is proposed in the JDBC standard, basically a heterogeneous pool with users specified by getConnection(user, password). The allocation of connections is more complex if Enable Identity Based Connection Pooling attribute is enabled on the data source.  When an application requests a database connection, the WebLogic Server instance selects an existing physical connection or creates a new physical connection with requested DBMS identity. The following section provides information on how heterogeneous connections are created:1. At connection pool initialization, the physical JDBC connections based on the configured or default “initial capacity” are created with the configured default DBMS credential of the data source.2. An application tries to get a connection from a data source.3a. If “use database credentials” is not enabled, the user specified in getConnection is mapped to a DBMS credential, as described earlier.  If the credential map doesn’t have a matching user, the default DBMS credential is used from the datasource descriptor.3b. If “use database credentials” is enabled, the user and password specified in getConnection are used directly.4. The connection pool is searched for a connection with a matching DBMS credential.5. If a match is found, the connection is reserved and returned to the application.6. If no match is found, a connection is created or reused based on the maximum capacity of the pool: - If the maximum capacity has not been reached, a new connection is created with the DBMS credential, reserved, and returned to the application.- If the pool has reached maximum capacity, based on the least recently used (LRU) algorithm, a physical connection is selected from the pool and destroyed. A new connection is created with the DBMS credential, reserved, and returned to the application. It should be clear that finding a matching connection is more expensive than a homogeneous pool.  Destroying a connection and getting a new one is very expensive.  If you can use a normal homogeneous pool or one of the light-weight options (client identity or an Oracle proxy connection), those should be used instead of identity based pooling. Regardless of how physical connections are created, each physical connection in the pool has its own DBMS credential information maintained by the pool. Once a physical connection is reserved by the pool, it does not change its DBMS credential even if the current thread changes its WebLogic user credential and continues to use the same connection. To configure this feature, select Enable Identity Based Connection Pooling.  See http://docs.oracle.com/cd/E24329_01/apirefs.1211/e24401/taskhelp/jdbc/jdbc_datasources/EnableIdentityBasedConnectionPooling.html  "Enable identity-based connection pooling for a JDBC data source" in Oracle WebLogic Server Administration Console Help. You must make the following changes to use Logging Last Resource (LLR) transaction optimization with Identity-based Pooling to get around the problem that multiple users will be accessing the associated transaction table.- You must configure a custom schema for LLR using a fully qualified LLR table name. All LLR connections will then use the named schema rather than the default schema when accessing the LLR transaction table.  - Use database specific administration tools to grant permission to access the named LLR table to all users that could access this table via a global transaction. By default, the LLR table is created during boot by the user configured for the connection in the data source. In most cases, the database will only allow access to this user and not allow access to mapped users. Connections within Transactions Now that we have covered the behavior of all of these various options, it’s time to discuss the exception to all of the rules.  When you get a connection within a transaction, it is associated with the transaction context on a particular WLS instance. When getting a connection with a data source configured with non-XA LLR or 1PC (using the JTS driver) with global transactions, the first connection obtained within the transaction is returned on subsequent connection requests regardless of the values of username/password specified and independent of the associated proxy user session, if any. The connection must be shared among all users of the connection when using LLR or 1PC. For XA data sources, the first connection obtained within the global transaction is returned on subsequent connection requests within the application server, regardless of the values of username/password specified and independent of the associated proxy user session, if any.  The connection must be shared among all users of the connection within a global transaction within the application server/JVM.

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  • SQL SERVER – Disable Clustered Index and Data Insert

    - by pinaldave
    Earlier today I received following email. “Dear Pinal, [Removed unrelated content] We looked at your script and found out that in your script of disabling indexes, you have only included non-clustered index during the bulk insert and missed to disabled all the clustered index. Our DBA[name removed] has changed your script a bit and included all the clustered indexes. Since our application is not working. When DBA [name removed] tried to enable clustered indexes again he is facing error incorrect syntax error. We are in deep problem [word replaced] [Removed Identity of organization and few unrelated stuff ]“ I have replied to my client and helped them fixed the problem. What really came to my attention is the concept of disabling clustered index. Let us try to learn a lesson from this experience. In this case, there was no need to disable clustered index at all. I had done necessary work when I was called in to work on tuning project. I had removed unused indexes, created few optimal indexes and wrote a script to disable few selected high cost indexes when bulk insert (and similar) operations are performed. There was another script which rebuild all the indexes as well. The solution worked till they included clustered index in disabling the script. Clustered indexes are in fact original table (or heap) physically ordered (any more things – not scope of this article) according to one or more keys(columns). When clustered index is disabled data rows of the disabled clustered index cannot be accessed. This means there will be no insert possible. When non clustered indexes are disabled all the data related to physically deleted but the definition of the index is kept in the system. Due to the same reason even reorganization of the index is not possible till the clustered index (which was disabled) is rebuild. Now let us come to the second part of the question, regarding receiving the error when clustered index is ‘enabled’. This is very common question I receive on the blog. (The following statement is written keeping the syntax of T-SQL in mind) Clustered indexes can be disabled but can not be enabled, they have to rebuild. It is intuitive to think that something which we have ‘disabled’ can be ‘enabled’ but the syntax for the same is ‘rebuild’. This issue has been explained here: SQL SERVER – How to Enable Index – How to Disable Index – Incorrect syntax near ‘ENABLE’. Let us go over this example where inserting the data is not possible when clustered index is disabled. USE AdventureWorks GO -- Create Table CREATE TABLE [dbo].[TableName]( [ID] [int] NOT NULL, [FirstCol] [varchar](50) NULL, CONSTRAINT [PK_TableName] PRIMARY KEY CLUSTERED ([ID] ASC) ) GO -- Create Nonclustered Index CREATE UNIQUE NONCLUSTERED INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] ([FirstCol] ASC) GO -- Populate Table INSERT INTO [dbo].[TableName] SELECT 1, 'First' UNION ALL SELECT 2, 'Second' UNION ALL SELECT 3, 'Third' GO -- Disable Nonclustered Index ALTER INDEX [IX_NonClustered_TableName] ON [dbo].[TableName] DISABLE GO -- Insert Data should work fine INSERT INTO [dbo].[TableName] SELECT 4, 'Fourth' UNION ALL SELECT 5, 'Fifth' GO -- Disable Clustered Index ALTER INDEX [PK_TableName] ON [dbo].[TableName] DISABLE GO -- Insert Data will fail INSERT INTO [dbo].[TableName] SELECT 6, 'Sixth' UNION ALL SELECT 7, 'Seventh' GO /* Error: Msg 8655, Level 16, State 1, Line 1 The query processor is unable to produce a plan because the index 'PK_TableName' on table or view 'TableName' is disabled. */ -- Reorganizing Index will also throw an error ALTER INDEX [PK_TableName] ON [dbo].[TableName] REORGANIZE GO /* Error: Msg 1973, Level 16, State 1, Line 1 Cannot perform the specified operation on disabled index 'PK_TableName' on table 'dbo.TableName'. */ -- Rebuliding should work fine ALTER INDEX [PK_TableName] ON [dbo].[TableName] REBUILD GO -- Insert Data should work fine INSERT INTO [dbo].[TableName] SELECT 6, 'Sixth' UNION ALL SELECT 7, 'Seventh' GO -- Clean Up DROP TABLE [dbo].[TableName] GO I hope this example is clear enough. There were few additional posts I had written years ago, I am listing them here. SQL SERVER – Enable and Disable Index Non Clustered Indexes Using T-SQL SQL SERVER – Enabling Clustered and Non-Clustered Indexes – Interesting Fact Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Constraint and Keys, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Recover Lost Form Data in Firefox

    - by Asian Angel
    Have you ever filled in a text area or form in a webpage and something happens before you can finish it? If you like the idea of recovering that lost data then you will want to have a look at the Lazarus: Form Recovery extension for Firefox. Lazarus: Form Recovery in Action For our first example we chose the comment text box area for one of the articles here at the website. As you can see we were not finished typing in the whole comment yet… Notice the “Lazarus Icon” in the lower right corner. Note: We simulated accidental tab closures for our two examples. After getting our webpage opened up again all of our text was gone. Right clicking within the text area showed two options available…”Recover Text & Recover Form”. Notice that our lost text was listed as a “sub menu”…this could be extremely useful in matching up the appropriate text to the correct webpage if you had multiple tabs open before something happened. Click on the correct text listing to insert it. So easy to finish writing our comment without having to start from zero again. In our second example we chose the sign-up form page for the website. As before we were not finished filling in the form… Getting the webpage opened back up showed the same problem as before…all the entered text was lost. This time we right clicked in the browser window area and there was that wonderful “Recover Form Command” waiting to be used. One click and… All of our lost form data was back and we were able to finish filling in the form. For those who may be interested you can disable Lazarus: Form Recovery on individual websites using the “Context Menu” for the “Status Bar Icon” Options There are three sections in the options and you should take a quick look through them to make any desired modifications in how Lazarus: Form Recovery functions. The first “Options Area” focuses on display/access for the extension. The second “Options Area” allows you to expand the type of data retained, enable removal of data within a given time frame, set up a password, disable search indexing, and enable form data retention while in “Private Browsing Mode”. The third “Options Area” focuses on the Lazarus database itself. Conclusion If you have ever lost text area or form data before then you know how much time could be lost in starting over. Lazarus: Form Recovery helps provide a nice backup solution to get you up and running once again with a minimum of effort. Links Download the Lazarus: Form Recovery extension (Mozilla Add-ons) Download the Lazarus: Form Recovery extension (Extension Homepage) Similar Articles Productive Geek Tips Quick Tip: Resize Any Textbox or Textarea in FirefoxWhy Doesn’t AutoComplete Always Work in Firefox?Pass Variables between Windows Forms Windows without ShowDialog()Using Secure Login in FirefoxAdd Search Forms to the Firefox Search Bar TouchFreeze Alternative in AutoHotkey The Icy Undertow Desktop Windows Home Server – Backup to LAN The Clear & Clean Desktop Use This Bookmarklet to Easily Get Albums Use AutoHotkey to Assign a Hotkey to a Specific Window Latest Software Reviews Tinyhacker Random Tips DVDFab 6 Revo Uninstaller Pro Registry Mechanic 9 for Windows PC Tools Internet Security Suite 2010 Looking for Good Windows Media Player 12 Plug-ins? Find Out the Celebrity You Resemble With FaceDouble Whoa ! Use Printflush to Solve Printing Problems Icelandic Volcano Webcams Open Multiple Links At One Go

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  • SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB

    - by Pinal Dave
    Let us take a look at the application you own at your business. If you pay attention to the underlying database for that application you will be amazed. Every successful business these days processes way more data than they used to process before. The number of transactions and the amount of data is growing at an exponential rate. Every single day there is way more data to process than before. Big data is no longer a concept; it is now turning into reality. If you look around there are so many different big data solutions and it can be a quite difficult task to figure out where to begin. Personally, I have been experimenting with a lot of different solutions which allow my database to scale immediately without much hassle while maintaining optimal database performance.  There are for sure some solutions out there, but for many I even have to learn their specific language and there is a lot of new exploration to do. Honestly, what I prefer is a product, which works with the language I know (SQL) and follows all the RDBMS concepts which I am familiar with (ACID etc.). NuoDB is one such solution.  It is an operational NewSQL database built on a patented emergent architecture with full support for SQL and ACID guarantees. In this blog post, I will explore how one can download and install NuoDB database. Step 1: Follow me and go to the NuoDB download page. Simply fill out the form, accept the online license agreement, and you will be taken directly to a page where you can select any platform you prefer to install NuoDB. In my example below, I select the Windows 64-bit platform as it is one of the most popular NuoDB platforms. (You can also run NuoDB on Amazon Web Services but I prefer to install it on my local machine for the purposes of this blog). Step 2: Once you have downloaded the NuoDB installer, double click on it to install it on the Windows platform. Here is the enlarged the icon of the installer. Step 3: Follow the wizard installation, as it is pretty straight forward and easy to do so. I have selected all the options to install as the overall installation is very simple and it does not take up much space. I have installed it on my C drive but you can select your preferred drive. It is quite possible that if you do not have 64 bit Java, it will throw following error. If you face following error, I suggest you to download 64-bit Java from here. Make sure that you download 64-bit Java from following link: http://java.com/en/download/manual.jsp If already have Java 64-bit installed, you can continue with the installation as described in following image. Otherwise, install Java and start from with Step 1. As in my case, I already have 64-bit Java installed – and you won’t believe me when I say that the entire installation of NuoDB only took me around 90 seconds. Click on Finish to end to exit the installation. Step 4: Once the installation is successful, NuoDB will automatically open the following two tabs – Console and DevCenter — in your preferred browser. On the Console tab you can explore various components of the NuoDB solution, e.g. QuickStart, Admin, Explorer, Storefront and Samples. We will see various components and their usage in future blog posts. If you follow these steps in this post, which I have followed to install NuoDB, you will agree that the installation of NuoDB is extremely smooth and it was indeed a pleasure to install a database product with such ease. If you have installed other database products in the past, you will absolutely agree with me. So download NuoDB and install it today, and in tomorrow’s blog post I will take the installation to the next level. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Big Data, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • Using the Script Component as a Conditional Split

    This is a quick walk through on how you can use the Script Component to perform Conditional Split like behaviour, splitting your data across multiple outputs. We will use C# code to decide what does flows to which output, rather than the expression syntax of the Conditional Split transformation. Start by setting up the source. For my example the source is a list of SQL objects from sys.objects, just a quick way to get some data: SELECT type, name FROM sys.objects type name S syssoftobjrefs F FK_Message_Page U Conference IT queue_messages_23007163 Shown above is a small sample of the data you could expect to see. Once you have setup your source, add the Script Component, selecting Transformation when prompted for the type, and connect it up to the source. Now open the component, but don’t dive into the script just yet. First we need to select some columns. Select the Input Columns page and then select the columns we want to uses as part of our filter logic. You don’t need to choose columns that you may want later, this is just the columns used in the script itself. Next we need to add our outputs. Select the Inputs and Outputs page.You get one by default, but we need to add some more, it wouldn’t be much of a split otherwise. For this example we’ll add just one more. Click the Add Output button, and you’ll see a new output is added. Now we need to set some properties, so make sure our new Output 1 is selected. In the properties grid change the SynchronousInputID property to be our input Input 0, and  change the ExclusionGroup property to 1. Now select Ouput 0 and change the ExclusionGroup property to 2. This value itself isn’t important, provided each output has a different value other than zero. By setting this property on both outputs it allows us to split the data down one or the other, making each exclusive. If we left it to 0, that output would get all the rows. It can be a useful feature allowing you to copy selected rows to one output whilst retraining the full set of data in the other. Now we can go back to the Script page and start writing some code. For the example we will do a very simple test, if the value of the type column is U, for user table, then it goes down the first output, otherwise it ends up in the other. This mimics the exclusive behaviour of the conditional split transformation. public override void Input0_ProcessInputRow(Input0Buffer Row) { // Filter all user tables to the first output, // the remaining objects down the other if (Row.type.Trim() == "U") { Row.DirectRowToOutput0(); } else { Row.DirectRowToOutput1(); } } The code itself is very simple, a basic if clause that determines which of the DirectRowToOutput methods we call, there is one for each output. Of course you could write a lot more code to implement some very complex logic, but the final direction is still just a method call. If we now close the script component, we can hook up the outputs and test the package. Your numbers will vary depending on the sample database but as you can see we have clearly split out input data into two outputs. As a final tip, when adding the outputs I would normally rename them, changing the Name in the Properties grid. This means the generated methods follow the pattern as do the path label shown on the design surface, making everything that much easier to recognise.

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  • Problems with 3D Array for Voxel Data

    - by Sean M.
    I'm trying to implement a voxel engine in C++ using OpenGL, and I've been working on the rendering of the world. In order to render, I have a 3D array of uint16's that hold that id of the block at the point. I also have a 3D array of uint8's that I am using to store the visibility data for that point, where each bit represents if a face is visible. I have it so the blocks render and all of the proper faces are hidden if needed, but all of the blocks are offset by a power of 2 from where they are stored in the array. So the block at [0][0][0] is rendered at (0, 0, 0), and the block at 11 is rendered at (1, 1, 1), but the block at [2][2][2] is rendered at (4, 4, 4) and the block at [3][3][3] is rendered at (8, 8, 8), and so on and so forth. This is the result of drawing the above situation: I'm still a little new to the more advanced concepts of C++, like triple pointers, which I'm using for the 3D array, so I think the error is somewhere in there. This is the code for creating the arrays: uint16*** _blockData; //Contains a 3D array of uint16s that are the ids of the blocks in the region uint8*** _visibilityData; //Contains a 3D array of bytes that hold the visibility data for the faces //Allocate memory for the world data _blockData = new uint16**[REGION_DIM]; for (int i = 0; i < REGION_DIM; i++) { _blockData[i] = new uint16*[REGION_DIM]; for (int j = 0; j < REGION_DIM; j++) _blockData[i][j] = new uint16[REGION_DIM]; } //Allocate memory for the visibility _visibilityData = new uint8**[REGION_DIM]; for (int i = 0; i < REGION_DIM; i++) { _visibilityData[i] = new uint8*[REGION_DIM]; for (int j = 0; j < REGION_DIM; j++) _visibilityData[i][j] = new uint8[REGION_DIM]; } Here is the code used to create the block mesh for the region: //Check if the positive x face is visible, this happens for every face //Block::VERT_X_POS is just an array of non-transformed cube verts for one face //These checks are in a triple loop, which goes over every place in the array if (_visibilityData[x][y][z] & 0x01 > 0) { _vertexData->AddData(&(translateVertices(Block::VERT_X_POS, x, y, z)[0]), sizeof(Block::VERT_X_POS)); } //This is a seperate method, not in the loop glm::vec3* translateVertices(const glm::vec3 data[], uint16 x, uint16 y, uint16 z) { glm::vec3* copy = new glm::vec3[6]; memcpy(&copy, &data, sizeof(data)); for(int i = 0; i < 6; i++) copy[i] += glm::vec3(x, -y, z); //Make +y go down instead return copy; } I cannot see where the blocks may be getting offset by more than they should be, and certainly not why the offsets are a power of 2. Any help is greatly appreciated. Thanks.

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  • Hadoop growing pains

    - by Piotr Rodak
    This post is not going to be about SQL Server. I have been reading recently more and more about “Big Data” – very catchy term that describes untamed increase of the data that mankind is producing each day and the struggle to capture the meaning of these data. Ten years ago, and perhaps even three years ago this need was not so recognized. Increasing number of smartphones and discernable trend of mainstream Internet traffic moving to the smartphone generated one means that there is bigger and bigger stream of information that has to be stored, transformed, analysed and perhaps monetized. The nature of this traffic makes if very difficult to wrap it into boundaries of relational database engines. The amount of data makes it near to impossible to process them in relational databases within reasonable time. This is where ‘cloud’ technologies come to play. I just read a good article about the growing pains of Hadoop, which became one of the leading players on distributed processing arena within last year or two. Toby Baer concludes in it that lack of enterprise ready toolsets hinders Hadoop’s apprehension in the enterprise world. While this is true, something else drew my attention. According to the article there are already about half of a dozen of commercially supported distributions of Hadoop. For me, who has not been involved into intricacies of open-source world, this is quite interesting observation. On one hand, it is good that there is competition as it is beneficial in the end to the customer. On the other hand, the customer is faced with difficulty of choosing the right distribution. In future, when Hadoop distributions fork even more, this choice will be even harder. The distributions will have overlapping sets of features, yet will be quite incompatible with each other. I suppose it will take a few years until leaders emerge and the market will begin to resemble what we see in Linux world. There are myriads of distributions, but only few are acknowledged by the industry as enterprise standard. Others are honed by bearded individuals with too much time to spend. In any way, the third fact I can’t help but notice about the proliferation of distributions of Hadoop is that IT professionals will have jobs.   BuzzNet Tags: Hadoop,Big Data,Enterprise IT

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