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  • SQL – Migrate Database from SQL Server to NuoDB – A Quick Tutorial

    - by Pinal Dave
    Data is growing exponentially and every organization with growing data is thinking of next big innovation in the world of Big Data. Big data is a indeed a future for every organization at one point of the time. Just like every other next big thing, big data has its own challenges and issues. The biggest challenge associated with the big data is to find the ideal platform which supports the scalability and growth of the data. If you are a regular reader of this blog, you must be familiar with NuoDB. I have been working with NuoDB for a while and their recent release is the best thus far. NuoDB is an elastically scalable SQL database that can run on local host, datacenter and cloud-based resources. A key feature of the product is that it does not require sharding (read more here). Last week, I was able to install NuoDB in less than 90 seconds and have explored their Explorer and Admin sections. You can read about my experiences in these posts: SQL – Step by Step Guide to Download and Install NuoDB – Getting Started with NuoDB SQL – Quick Start with Admin Sections of NuoDB – Manage NuoDB Database SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database Many SQL Authority readers have been following me in my journey to evaluate NuoDB. One of the frequently asked questions I’ve received from you is if there is any way to migrate data from SQL Server to NuoDB. The fact is that there is indeed a way to do so and NuoDB provides a fantastic tool which can help users to do it. NuoDB Migrator is a command line utility that supports the migration of Microsoft SQL Server, MySQL, Oracle, and PostgreSQL schemas and data to NuoDB. The migration to NuoDB is a three-step process: NuoDB Migrator generates a schema for a target NuoDB database It loads data into the target NuoDB database It dumps data from the source database Let’s see how we can migrate our data from SQL Server to NuoDB using a simple three-step approach. But before we do that we will create a sample database in MSSQL and later we will migrate the same database to NuoDB: Setup Step 1: Build a sample data CREATE DATABASE [Test]; CREATE TABLE [Department]( [DepartmentID] [smallint] NOT NULL, [Name] VARCHAR(100) NOT NULL, [GroupName] VARCHAR(100) NOT NULL, [ModifiedDate] [datetime] NOT NULL, CONSTRAINT [PK_Department_DepartmentID] PRIMARY KEY CLUSTERED ( [DepartmentID] ASC ) ) ON [PRIMARY]; INSERT INTO Department SELECT * FROM AdventureWorks2012.HumanResources.Department; Note that I am using the SQL Server AdventureWorks database to build this sample table but you can build this sample table any way you prefer. Setup Step 2: Install Java 64 bit Before you can begin the migration process to NuoDB, make sure you have 64-bit Java installed on your computer. This is due to the fact that the NuoDB Migrator tool is built in Java. You can download 64-bit Java for Windows, Mac OSX, or Linux from the following link: http://java.com/en/download/manual.jsp. One more thing to remember is that you make sure that the path in your environment settings is set to your JAVA_HOME directory or else the tool will not work. Here is how you can do it: Go to My Computer >> Right Click >> Select Properties >> Click on Advanced System Settings >> Click on Environment Variables >> Click on New and enter the following values. Variable Name: JAVA_HOME Variable Value: C:\Program Files\Java\jre7 Make sure you enter your Java installation directory in the Variable Value field. Setup Step 3: Install JDBC driver for SQL Server. There are two JDBC drivers available for SQL Server.  Select the one you prefer to use by following one of the two links below: Microsoft JDBC Driver jTDS JDBC Driver In this example we will be using jTDS JDBC driver. Once you download the driver, move the driver to your NuoDB installation folder. In my case, I have moved the JAR file of the driver into the C:\Program Files\NuoDB\tools\migrator\jar folder as this is my NuoDB installation directory. Now we are all set to start the three-step migration process from SQL Server to NuoDB: Migration Step 1: NuoDB Schema Generation Here is the command I use to generate a schema of my SQL Server Database in NuoDB. First I go to the folder C:\Program Files\NuoDB\tools\migrator\bin and execute the nuodb-migrator.bat file. Note that my database name is ‘test’. Additionally my username and password is also ‘test’. You can see that my SQL Server database is running on my localhost on port 1433. Additionally, the schema of the table is ‘dbo’. nuodb-migrator schema –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.path=/tmp/schema.sql The above script will generate a schema of all my SQL Server tables and will put it in the folder C:\tmp\schema.sql . You can open the schema.sql file and execute this file directly in your NuoDB instance. You can follow the link here to see how you can execute the SQL script in NuoDB. Please note that if you have not yet created the schema in the NuoDB database, you should create it before executing this step. Step 2: Generate the Dump File of the Data Once you have recreated your schema in NuoDB from SQL Server, the next step is very easy. Here we create a CSV format dump file, which will contain all the data from all the tables from the SQL Server database. The command to do so is very similar to the above command. Be aware that this step may take a bit of time based on your database size. nuodb-migrator dump –source.driver=net.sourceforge.jtds.jdbc.Driver –source.url=jdbc:jtds:sqlserver://localhost:1433/ –source.username=test –source.password=test –source.catalog=test –source.schema=dbo –output.type=csv –output.path=/tmp/dump.cat Once the above command is successfully executed you can find your CSV file in the C:\tmp\ folder. However, you do not have to do anything manually. The third and final step will take care of completing the migration process. Migration Step 3: Load the Data into NuoDB After building schema and taking a dump of the data, the very next step is essential and crucial. It will take the CSV file and load it into the NuoDB database. nuodb-migrator load –target.url=jdbc:com.nuodb://localhost:48004/mytest –target.schema=dbo –target.username=test –target.password=test –input.path=/tmp/dump.cat Please note that in the above script we are now targeting the NuoDB database, which we have already created with the name of “MyTest”. If the database does not exist, create it manually before executing the above script. I have kept the username and password as “test”, but please make sure that you create a more secure password for your database for security reasons. Voila!  You’re Done That’s it. You are done. It took 3 setup and 3 migration steps to migrate your SQL Server database to NuoDB.  You can now start exploring the database and build excellent, scale-out applications. In this blog post, I have done my best to come up with simple and easy process, which you can follow to migrate your app from SQL Server to NuoDB. Download NuoDB I strongly encourage you to download NuoDB and go through my 3-step migration tutorial from SQL Server to NuoDB. Additionally here are two very important blog post from NuoDB CTO Seth Proctor. He has written excellent blog posts on the concept of the Administrative Domains. NuoDB has this concept of an Administrative Domain, which is a collection of hosts that can run one or multiple databases.  Each database has its own TEs and SMs, but all are managed within the Admin Console for that particular domain. http://www.nuodb.com/techblog/2013/03/11/getting-started-provisioning-a-domain/ http://www.nuodb.com/techblog/2013/03/14/getting-started-running-a-database/ 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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  • Does it make sense to develop open source python library for database inspection?

    - by gruszczy
    Some time ago I came up with an idea for a library for database inspection. I started developing it and got some very basic functionality, just to check if that's possible. Recently however, I get second thoughts, whether such project would really be useful. I am actually planning to develop following software suite: library for python, that would provide easy interface to inspect database structure, desktop application in PyQt that would use the interface to provide graphical database inspection, web application in Django that would use the interface to provide database inspection through the browser. Do you think such suite would be useful for other developers/database administrators/analysts? I know, that there is pgadmin for PostgreSQL and some tool for sqlite3 and that there is Java tool called DBInspect. Usually I would be against creating new tool and rather join existing project, but I am not Java programmer (and I would rather stick to python or C, which I like) and none of these projects provide a library for database inspection. Anyway I would like to hear some opinions from fellow developers, whether such project make sense or I should try to spend my free time on developing something else.

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  • SQL University: What and why of database testing

    - by Mladen Prajdic
    This is a post for a great idea called SQL University started by Jorge Segarra also famously known as SqlChicken on Twitter. It’s a collection of blog posts on different database related topics contributed by several smart people all over the world. So this week is mine and we’ll be talking about database testing and refactoring. In 3 posts we’ll cover: SQLU part 1 - What and why of database testing SQLU part 2 - What and why of database refactoring SQLU part 2 – Tools of the trade With that out of the way let us sharpen our pencils and get going. Why test a database The sad state of the industry today is that there is very little emphasis on testing in general. Test driven development is still a small niche of the programming world while refactoring is even smaller. The cause of this is the inability of developers to convince themselves and their managers that writing tests is beneficial. At the moment they are mostly viewed as waste of time. This is because the average person (let’s not fool ourselves, we’re all average) is unable to think about lower future costs in relation to little more current work. It’s orders of magnitude easier to know about the current costs in relation to current amount of work. That’s why programmers convince themselves testing is a waste of time. However we have to ask ourselves what tests are really about? Maybe finding bugs? No, not really. If we introduce bugs, we’re likely to write test around those bugs too. But yes we can find some bugs with tests. The main point of tests is to have reproducible repeatability in our systems. By having a code base largely covered by tests we can know with better certainty what a small code change can break in other parts of the system. By having repeatability we can make code changes with confidence, since we know we’ll see what breaks in other tests. And here comes the inability to estimate future costs. By spending just a few more hours writing those tests we’d know instantly what broke where. Imagine we fix a reported bug. We check-in the code, deploy it and the users are happy. Until we get a call 2 weeks later about a certain monthly process has stopped working. What we don’t know is that this process was developed by a long gone coworker and for some reason it relied on that same bug we’ve happily fixed. There’s no way we could’ve known that. We say OK and go in and fix the monthly process. But what we have no clue about is that there’s this ETL job that relied on data from that monthly process. Now that we’ve fixed the process it’s giving unexpected (yet correct since we fixed it) data to the ETL job. So we have to fix that too. But there’s this part of the app we coded that relies on data from that exact ETL job. And just like that we enter the “Loop of maintenance horror”. With the loop eventually comes blame. Here’s a nice tip for all developers and DBAs out there: If you make a mistake man up and admit to it. All of the above is valid for any kind of software development. Keeping this in mind the database is nothing other than just a part of the application. But a big part! One reason why testing a database is even more important than testing an application is that one database is usually accessed from multiple applications and processes. This makes it the central and vital part of the enterprise software infrastructure. Knowing all this can we really afford not to have tests? What to test in a database Now that we’ve decided we’ll dive into this testing thing we have to ask ourselves what needs to be tested? The short answer is: everything. The long answer is: read on! There are 2 main ways of doing tests: Black box and White box testing. Black box testing means we have no idea how the system internals are built and we only have access to it’s inputs and outputs. With it we test that the internal changes to the system haven’t caused the input/output behavior of the system to change. The most important thing to test here are the edge conditions. It’s where most programs break. Having good edge condition tests we can be more confident that the systems changes won’t break. White box testing has the full knowledge of the system internals. With it we test the internal system changes, different states of the application, etc… White and Black box tests should be complementary to each other as they are very much interconnected. Testing database routines includes testing stored procedures, views, user defined functions and anything you use to access the data with. Database routines are your input/output interface to the database system. They count as black box testing. We test then for 2 things: Data and schema. When testing schema we only care about the columns and the data types they’re returning. After all the schema is the contract to the out side systems. If it changes we usually have to change the applications accessing it. One helpful T-SQL command when doing schema tests is SET FMTONLY ON. It tells the SQL Server to return only empty results sets. This speeds up tests because it doesn’t return any data to the client. After we’ve validated the schema we have to test the returned data. There no other way to do this but to have expected data known before the tests executes and comparing that data to the database routine output. Testing Authentication and Authorization helps us validate who has access to the SQL Server box (Authentication) and who has access to certain database objects (Authorization). For desktop applications and windows authentication this works well. But the biggest problem here are web apps. They usually connect to the database as a single user. Please ensure that that user is not SA or an account with admin privileges. That is just bad. Load testing ensures us that our database can handle peak loads. One often overlooked tool for load testing is Microsoft’s OSTRESS tool. It’s part of RML utilities (x86, x64) for SQL Server and can help determine if our database server can handle loads like 100 simultaneous users each doing 10 requests per second. SQL Profiler can also help us here by looking at why certain queries are slow and what to do to fix them.   One particular problem to think about is how to begin testing existing databases. First thing we have to do is to get to know those databases. We can’t test something when we don’t know how it works. To do this we have to talk to the users of the applications accessing the database, run SQL Profiler to see what queries are being run, use existing documentation to decipher all the object relationships, etc… The way to approach this is to choose one part of the database (say a logical grouping of tables that go together) and filter our traces accordingly. Once we’ve done that we move on to the next grouping and so on until we’ve covered the whole database. Then we move on to the next one. Database Testing is a topic that we can spent many hours discussing but let this be a nice intro to the world of database testing. See you in the next post.

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  • Connecting remote mysql database to local mysql databse? [migrated]

    - by Shashank
    I want to write a php code to be embedded in drupal7 module. I want to call a procedure which can copy the newly generated data in local mysql database to the remote mysql database. When data is inserted in tables 'A' of my local data base it should be copied to the specific table 'B' of the remote mysql server's database. Table 'A' is on local host. Table 'B' is on remote server. insert data on 'A' - copied data in 'B' Is this possible? Thanks for the help.

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  • Data Guard - Snapshot Standby Database??

    - by Jian Zhang-Oracle
    ?? -------- ?????,??standby?????mount??????????REDO??,??standby????????????????????,???????read-only???open????,????ACTIVE DATA GUARD,????standby?????????(read-only)??(????????),????standby???????????(read-write)? ?????,?????????????Real Application Testing(RAT)??????????,?????????standby??????snapshot standby?????????,??snapshot standby??????????,???????????(read-write)??????snapshot standby??????????????,?????????,??????????,????????,?????????snapshot standby?????standby???,????????? ?? ---------  1.??standby?????? SQL> Alter system set db_recovery_file_dest_size=500M; System altered. SQL> Alter system set db_recovery_file_dest='/u01/app/oracle/snapshot_standby'; System altered. 2.??standby?????? SQL> alter database recover managed standby database cancel; Database altered. 3.??standby???snapshot standby,??open snapshot standby SQL> alter database convert to snapshot standby; Database altered. SQL> alter database open;    Database altered. ??snapshot standby??????SNAPSHOT STANDBY,open???READ WRITE: SQL> select DATABASE_ROLE,name,OPEN_MODE from v$database; DATABASE_ROLE    NAME      OPEN_MODE ---------------- --------- -------------------- SNAPSHOT STANDBY FSDB      READ WRITE 4.?snapshot standby???????????Real Application Testing(RAT)????????? 5.?????,??snapshot standby???physical standby,?????????? SQL> shutdown immediate; Database closed. Database dismounted. ORACLE instance shut down. SQL> startup mount; ORACLE instance started. Database mounted. SQL> ALTER DATABASE CONVERT TO PHYSICAL STANDBY; Database altered. SQL> shutdown immediate; ORA-01507: database not mounted ORACLE instance shut down. SQL> startup mount; ORACLE instance started. Database mounted. SQL>ALTER DATABASE RECOVER MANAGED STANDBY DATABASE DISCONNECT FROM SESSION; Database altered. 5.?????standby?,???????PHYSICAL STANDBY,open???MOUNTED SQL> select DATABASE_ROLE,name,OPEN_MODE from v$database; DATABASE_ROLE    NAME      OPEN_MODE ---------------- --------- -------------------- PHYSICAL STANDBY FSDB      MOUNTED 6.??????????????? ????: SQL> select ads.dest_id,max(sequence#) "Current Sequence",            max(log_sequence) "Last Archived"        from v$archived_log al, v$archive_dest ad, v$archive_dest_status ads        where ad.dest_id=al.dest_id        and al.dest_id=ads.dest_id        and al.resetlogs_change#=(select max(resetlogs_change#) from v$archived_log )        group by ads.dest_id;    DEST_ID Current Sequence Last Archived ---------- ---------------- -------------      1              361           361      2              361           362 --???? SQL>    select al.thrd "Thread", almax "Last Seq Received", lhmax "Last Seq Applied"       from (select thread# thrd, max(sequence#) almax           from v$archived_log           where resetlogs_change#=(select resetlogs_change# from v$database)           group by thread#) al,          (select thread# thrd, max(sequence#) lhmax           from v$log_history           where resetlogs_change#=(select resetlogs_change# from v$database)           group by thread#) lh      where al.thrd = lh.thrd;     Thread Last Seq Received Last Seq Applied ---------- ----------------- ----------------          1               361              361 ??????????,???blog,???????????,??"??:Data Guard - Snapshot Standby Database??" 

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  • What are some good tips for a developer trying to design a scalable MySQL database?

    - by CFL_Jeff
    As the question states, I am a developer, not a DBA. I have experience with designing good ER schemas and am fairly knowledgeable about normalization and good schema design. I have also worked with data warehouses that use dimensional modeling with fact tables and dim tables. However, all of the database-driven applications I've developed at previous jobs have been internal applications on the company's intranet, never receiving "real-world traffic". Furthermore, at previous jobs, I have always had a DBA or someone who knew much more than me about these things. At this new job I just started, I've been asked to develop a public-facing application with a MySQL backend and the data stored by this application is expected to grow very rapidly. Oh, and we don't have a DBA. Well, I guess I am the DBA. ;) As far as designing a database to be scalable, I don't even know where to start. Does anyone have any good tips or know of any good educational materials for a developer who has been sort of shoved into a DBA/database designer role and has been tasked with designing a scalable database to support an application like this? Have any other developers been through this sort of thing? What did you do to quickly become good at this role? I've found some good slides on the subject here but it's hard to glean details from slides. Wish I could've attended that guy's talk. I also found a good blog entry called 5 Ways to Boost MySQL Scalability which had some good information, though some of it was over my head. tl;dr I just want to make sure the database doesn't have to be completely redesigned when it scales up, and I'm looking for tips to get it right the first time. The answer I'm looking for is a "list of things every developer should know about making a scalable MySQL database so your application doesn't perform like crap when the data gets huge".

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  • WPF: RenderOptions.EdgeMode="Unspecified" vs "Alias" override global setting with local setting

    - by msfanboy
    Hello, in the ressource-tag of my MainWindowView.xaml I have this markup: RenderOptions.EdgeMode="Aliased" to get a general sharp look of my whole application. Using mostly rectangular shapes/controls this works fine. But for my validation error symbols I use a red ellipse with a white cross or "X" in it. The ellipse is using now the global "Aliased" settings what looks not good because I can see the pixelated border of the ellipse. Using now does NOT change anything ??? I always set in wpf local settings override global settings ?

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  • UAC on Win2k8/VIsta x64 - local "Administrator" works but domain account in Administrators group fai

    - by deltanine
    I have come across a strange problem in one of our applications on win2k8/Vista x64 with UAC enabled. It is a process which hosts the UI for our service and runs in the context of the logged on user. When logged in as a domain user who is a member of the "Administrators" group, writing to the registry under HKLM fails due to UAC with access denied. But when logged in as the local "Administrator" account (non-domain) then writing to the registry succeeds. Both accounts are adminstrators - is there a distinction between domain and non-domain accounts with UAC? What gives?

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  • Pointer to local variable

    - by Radek Šimko
    May I have any acces to local variable in different function? If may, how? void replaceNumberAndPrint(int array[3]) { printf("%i\n", array[1]); printf("%i\n", array[1]); } int * getArray() { int myArray[3] = {4, 65, 23}; return myArray; } int main() { replaceNumberAndPrint(getArray()); } The output of the piece of code above: 65 4202656 What am i doing wrong? What the "4202656" means?? Do I have to copy the whole array in the replaceNumberAndPrint() function to be able to access to it more than first times?

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  • changing body class based on user's local time

    - by John
    I'm trying to add a body class of 'day' if it's 6am-5pm and 'night' if "else" based on the user's local time. I tried the following but it didn't work. Any ideas? In the head: <script> function setTimesStyles() { var currentTime = new Date().getHours(); if(currentTime > 5 && currentTime < 17) { document.body.className = 'day'; } else { document.body.className = 'night'; } } </script> In the body: <body onload="setTimeStyles();"> Also, is there a more elegant way to achieve what I need?

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  • split a database web application - good idea or bad idea?

    - by Khou
    Is it a bad idea to split up a application and the database? Application1 uses database1 on ServerX Application2 uses database2 on ServerY Both application communicates over web service API, they are apart of the same application, one application is used to manage user's profile/personal data, while the other application is used to manages user's financial data. Or should just put them together and just use 1 database on the same server?

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  • How to choose between UUIDs, autoincrement/sequence keys and sequence tables for database primary keys?

    - by Tim
    I'm looking at the pros and cons of these three primary methods of coming up with primary keys for database rows. So assuming I am using a database that supports more than one of these methods, is there a simple heuristic to determine what the best option would be for me? How do considerations such a distributed/multiple masters, performance requirements, ORM use, security and testing have on the choice? Any unexpected drawbacks that one might run into?

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you’ll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you’ve read my previous blog posts, you’ll be aware that I’ve been focusing on the database continuous integration theme. In my CI setup I create a “production”-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it’s not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn’t I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn’t an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley’s “Continuous Delivery” teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you’ve been allotted. 2. It’s not just about the storage requirements, it’s also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I’m just not going to get the feedback quickly enough to react. So what’s the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I’m sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server’s point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no ‘duplicate’ storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly “release test” process triggered by my CI tool. RESTORE DATABASE WidgetProduction_Virtual FROM DISK=N'D:\VirtualDatabase\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE WidgetProduction_Virtual WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the ‘virtual’ restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • Google I/O 2012 - Empower Local Shopping Through Google Shopping

    Google I/O 2012 - Empower Local Shopping Through Google Shopping Thomas Kotzmann, Claudia Ciorascu More and more of consumers research online first before going to a local store to purchase a product and we can expect this trend to continue to rise. How can merchants and retailers take advantage of this trend? Local shopping enables merchants to declare product price and availability per local store. In this session, we will show you how to set up and manage local shopping accounts in the Google Merchant Center and how to use the Content API to upload local products and do live inventory updates. For all I/O 2012 sessions, go to developers.google.com From: GoogleDevelopers Views: 100 1 ratings Time: 49:01 More in Science & Technology

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  • How to restore your production database without needing additional storage

    - by David Atkinson
    Production databases can get very large. This in itself is to be expected, but when a copy of the database is needed the database must be restored, requiring additional and costly storage.  For example, if you want to give each developer a full copy of your production server, you'll need n times the storage cost for your n-developer team. The same is true for any test databases that are created during the course of your project lifecycle. If you've read my previous blog posts, you'll be aware that I've been focusing on the database continuous integration theme. In my CI setup I create a "production"-equivalent database directly from its source control representation, and use this to test my upgrade scripts. Despite this being a perfectly valid and practical thing to do as part of a CI setup, it's not the exact equivalent to running the upgrade script on a copy of the actual production database. So why shouldn't I instead simply restore the most recent production backup as part of my CI process? There are two reasons why this would be impractical. 1. My CI environment isn't an exact copy of my production environment. Indeed, this would be the case in a perfect world, and it is strongly recommended as a good practice if you follow Jez Humble and David Farley's "Continuous Delivery" teachings, but in practical terms this might not always be possible, especially where storage is concerned. It may just not be possible to restore a huge production database on the environment you've been allotted. 2. It's not just about the storage requirements, it's also the time it takes to do the restore. The whole point of continuous integration is that you are alerted as early as possible whether the build (yes, the database upgrade script counts!) is broken. If I have to run an hour-long restore each time I commit a change to source control I'm just not going to get the feedback quickly enough to react. So what's the solution? Red Gate has a technology, SQL Virtual Restore, that is able to restore a database without using up additional storage. Although this sounds too good to be true, the explanation is quite simple (although I'm sure the technical implementation details under the hood are quite complex!) Instead of restoring the backup in the conventional sense, SQL Virtual Restore will effectively mount the backup using its HyperBac technology. It creates a data and log file, .vmdf, and .vldf, that becomes the delta between the .bak file and the virtual database. This means that both read and write operations are permitted on a virtual database as from SQL Server's point of view it is no different from a conventional database. Instead of doubling the storage requirements upon a restore, there is no 'duplicate' storage requirements, other than the trivially small virtual log and data files (see illustration below). The benefit is magnified the more databases you mount to the same backup file. This technique could be used to provide a large development team a full development instance of a large production database. It is also incredibly easy to set up. Once SQL Virtual Restore is installed, you simply run a conventional RESTORE command to create the virtual database. This is what I have running as part of a nightly "release test" process triggered by my CI tool. RESTORE DATABASE WidgetProduction_virtual FROM DISK=N'C:\WidgetWF\ProdBackup\WidgetProduction.bak' WITH MOVE N'WidgetProduction' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_WidgetProduction_Virtual.vmdf', MOVE N'WidgetProduction_log' TO N'C:\WidgetWF\ProdBackup\WidgetProduction_log_WidgetProduction_Virtual.vldf', NORECOVERY, STATS=1, REPLACE GO RESTORE DATABASE mydatabase WITH RECOVERY   Note the only change from what you would do normally is the naming of the .vmdf and .vldf files. SQL Virtual Restore intercepts this by monitoring the extension and applies its magic, ensuring the 'virtual' restore happens rather than the conventional storage-heavy restore. My automated release test then applies the upgrade scripts to the virtual production database and runs some validation tests, giving me confidence that were I to run this on production for real, all would go smoothly. For illustration, here is my 8Gb production database: And its corresponding backup file: Here are the .vldf and .vmdf files, which represent the only additional used storage for the new database following the virtual restore.   The beauty of this product is its simplicity. Once it is installed, the interaction with the backup and virtual database is exactly the same as before, as the clever stuff is being done at a lower level. SQL Virtual Restore can be downloaded as a fully functional 14-day trial. Technorati Tags: SQL Server

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  • ROracle support for TimesTen In-Memory Database

    - by Sam Drake
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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  • SQL SERVER – ?Finding Out What Changed in a Deleted Database – Notes from the Field #041

    - by Pinal Dave
    [Note from Pinal]: This is a 41th episode of Notes from the Field series. The real world is full of challenges. When we are reading theory or book, we sometimes do not realize how real world reacts works and that is why we have the series notes from the field, which is extremely popular with developers and DBA. Let us talk about interesting problem of how to figure out what has changed in the DELETED database. Well, you think I am just throwing the words but in reality this kind of problems are making our DBA’s life interesting and in this blog post we have amazing story from Brian Kelley about the same subject. In this episode of the Notes from the Field series database expert Brian Kelley explains a how to find out what has changed in deleted database. Read the experience of Brian in his own words. Sometimes, one of the hardest questions to answer is, “What changed?” A similar question is, “Did anything change other than what we expected to change?” The First Place to Check – Schema Changes History Report: Pinal has recently written on the Schema Changes History report and its requirement for the Default Trace to be enabled. This is always the first place I look when I am trying to answer these questions. There are a couple of obvious limitations with the Schema Changes History report. First, while it reports what changed, when it changed, and who changed it, other than the base DDL operation (CREATE, ALTER, DELETE), it does not present what the changes actually were. This is not something covered by the default trace. Second, the default trace has a fixed size. When it hits that size, the changes begin to overwrite. As a result, if you wait too long, especially on a busy database server, you may find your changes rolled off. But the Database Has Been Deleted! Pinal cited another issue, and that’s the inability to run the Schema Changes History report if the database has been dropped. Thankfully, all is not lost. One thing to remember is that the Schema Changes History report is ultimately driven by the Default Trace. As you may have guess, it’s a trace, like any other database trace. And the Default Trace does write to disk. The trace files are written to the defined LOG directory for that SQL Server instance and have a prefix of log_: Therefore, you can read the trace files like any other. Tip: Copy the files to a working directory. Otherwise, you may occasionally receive a file in use error. With the Default Trace files, if you ask the question early enough, you can see the information for a deleted database just the same as any other database. Testing with a Deleted Database: Here’s a short script that will create a database, create a schema, create an object, and then drop the database. Without the database, you can’t do a standard Schema Changes History report. CREATE DATABASE DeleteMe; GO USE DeleteMe; GO CREATE SCHEMA Test AUTHORIZATION dbo; GO CREATE TABLE Test.Foo (FooID INT); GO USE MASTER; GO DROP DATABASE DeleteMe; GO This sets up the perfect situation where we can’t retrieve the information using the Schema Changes History report but where it’s still available. Finding the Information: I’ve sorted the columns so I can see the Event Subclass, the Start Time, the Database Name, the Object Name, and the Object Type at the front, but otherwise, I’m just looking at the trace files using SQL Profiler. As you can see, the information is definitely there: Therefore, even in the case of a dropped/deleted database, you can still determine who did what and when. You can even determine who dropped the database (loginame is captured). The key is to get the default trace files in a timely manner in order to extract the information. If you want to get started with performance tuning and database security with the help of experts, read more over at Fix Your SQL Server. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: Notes from the Field, PostADay, SQL, SQL Authority, SQL Query, SQL Security, SQL Server, SQL Tips and Tricks, T SQL

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  • ROracle support for TimesTen In-Memory Database

    - by Sherry LaMonica
    Today's guest post comes from Jason Feldhaus, a Consulting Member of Technical Staff in the TimesTen Database organization at Oracle.  He shares with us a sample session using ROracle with the TimesTen In-Memory database.  Beginning in version 1.1-4, ROracle includes support for the Oracle Times Ten In-Memory Database, version 11.2.2. TimesTen is a relational database providing very fast and high throughput through its memory-centric architecture.  TimesTen is designed for low latency, high-volume data, and event and transaction management. A TimesTen database resides entirely in memory, so no disk I/O is required for transactions and query operations. TimesTen is used in applications requiring very fast and predictable response time, such as real-time financial services trading applications and large web applications. TimesTen can be used as the database of record or as a relational cache database to Oracle Database. ROracle provides an interface between R and the database, providing the rich functionality of the R statistical programming environment using the SQL query language. ROracle uses the OCI libraries to handle database connections, providing much better performance than standard ODBC.The latest ROracle enhancements include: Support for Oracle TimesTen In-Memory Database Support for Date-Time using R's POSIXct/POSIXlt data types RAW, BLOB and BFILE data type support Option to specify number of rows per fetch operation Option to prefetch LOB data Break support using Ctrl-C Statement caching support Times Ten 11.2.2 contains enhanced support for analytics workloads and complex queries: Analytic functions: AVG, SUM, COUNT, MAX, MIN, DENSE_RANK, RANK, ROW_NUMBER, FIRST_VALUE and LAST_VALUE Analytic clauses: OVER PARTITION BY and OVER ORDER BY Multidimensional grouping operators: Grouping clauses: GROUP BY CUBE, GROUP BY ROLLUP, GROUP BY GROUPING SETS Grouping functions: GROUP, GROUPING_ID, GROUP_ID WITH clause, which allows repeated references to a named subquery block Aggregate expressions over DISTINCT expressions General expressions that return a character string in the source or a pattern within the LIKE predicate Ability to order nulls first or last in a sort result (NULLS FIRST or NULLS LAST in the ORDER BY clause) Note: Some functionality is only available with Oracle Exalytics, refer to the TimesTen product licensing document for details. Connecting to TimesTen is easy with ROracle. Simply install and load the ROracle package and load the driver. > install.packages("ROracle") > library(ROracle) Loading required package: DBI > drv <- dbDriver("Oracle") Once the ROracle package is installed, create a database connection object and connect to a TimesTen direct driver DSN as the OS user. > conn <- dbConnect(drv, username ="", password="", dbname = "localhost/SampleDb_1122:timesten_direct") You have the option to report the server type - Oracle or TimesTen? > print (paste ("Server type =", dbGetInfo (conn)$serverType)) [1] "Server type = TimesTen IMDB" To create tables in the database using R data frame objects, use the function dbWriteTable. In the following example we write the built-in iris data frame to TimesTen. The iris data set is a small example data set containing 150 rows and 5 columns. We include it here not to highlight performance, but so users can easily run this example in their R session. > dbWriteTable (conn, "IRIS", iris, overwrite=TRUE, ora.number=FALSE) [1] TRUE Verify that the newly created IRIS table is available in the database. To list the available tables and table columns in the database, use dbListTables and dbListFields, respectively. > dbListTables (conn) [1] "IRIS" > dbListFields (conn, "IRIS") [1] "SEPAL.LENGTH" "SEPAL.WIDTH" "PETAL.LENGTH" "PETAL.WIDTH" "SPECIES" To retrieve a summary of the data from the database we need to save the results to a local object. The following call saves the results of the query as a local R object, iris.summary. The ROracle function dbGetQuery is used to execute an arbitrary SQL statement against the database. When connected to TimesTen, the SQL statement is processed completely within main memory for the fastest response time. > iris.summary <- dbGetQuery(conn, 'SELECT SPECIES, AVG ("SEPAL.LENGTH") AS AVG_SLENGTH, AVG ("SEPAL.WIDTH") AS AVG_SWIDTH, AVG ("PETAL.LENGTH") AS AVG_PLENGTH, AVG ("PETAL.WIDTH") AS AVG_PWIDTH FROM IRIS GROUP BY ROLLUP (SPECIES)') > iris.summary SPECIES AVG_SLENGTH AVG_SWIDTH AVG_PLENGTH AVG_PWIDTH 1 setosa 5.006000 3.428000 1.462 0.246000 2 versicolor 5.936000 2.770000 4.260 1.326000 3 virginica 6.588000 2.974000 5.552 2.026000 4 <NA> 5.843333 3.057333 3.758 1.199333 Finally, disconnect from the TimesTen Database. > dbCommit (conn) [1] TRUE > dbDisconnect (conn) [1] TRUE We encourage you download Oracle software for evaluation from the Oracle Technology Network. See these links for our software: Times Ten In-Memory Database,  ROracle.  As always, we welcome comments and questions on the TimesTen and  Oracle R technical forums.

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