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• What about the Sql transaction log

  - by Michel

  Hi, i always thought that the sql transaction log keeps track of all the transactions done in the database so it could help recovering the database file in case of a unexpected power down or something like that So then, in normal usage, when the data is committed and written to disk, it is cleared because all the data is nice and safe in the mdf file. Seeing the ldf file grow and reading some i understand that that is not the case, and it will keep growing, until: you shrink the log. Only at that point all the commited transactions are cleared and the log file is shrinked. I found some sp's who should do this, but also found the theory that you first have to backup the database? That last step doesn't make sense to me, so can anyone tell me of that is correct and if so, why that is?

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• rails data aggregation

  - by ash34

  Hi, I have to create a hash of the form h[:bill] = ["Billy", "NA", 20, "PROJ_A"] by login where 20 is the cumulative number of hours reported by the login for all task transactions returned by the query where each login has multiple reported transactions. Did I do this in a bad way or this seems alright. h = Hash.new Task.find_each(:include => [:user], :joins => :user, :conditions => ["from_date >= ? AND from_date <= ? AND category = ?", Date.today - 30, Date.today + 30, 'PROJ1']) do |t| h[t.login.intern] = [t.user.name, 'NA', h[t.login.intern].nil? ? (t.hrs_per_day * t.num_days) : h[t.login.intern][2] + (t.hrs_day * t.workdays), t.category] end Also if I have to aggregate this data not just by login but login and category how do I accomplish this? thanks, ash

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• Does it make sense to use BOTH mongodb and mysql in the same rails application?

  - by Brian Armstrong

  I have a good reason to use mongodb for part of my app. But people generally describe it as not a good fit for "transactional" applications like a bank where transactions have to be exact/consistent, etc. Does it make sense to split the models up in Rails and have some of them use MySql and others mongo? Or will this generally cause more problems than it's worth? I'm not building a banking app or anything, but was thinking it might make sense for my users table or or transactions table (recording revenue) to do that part in MySql.

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• Why are mainframes still around?

  - by ThaDon

  It's a question you've probably asked or been asked several times. What's so great about Mainframes? The answer you've probably been given is "they are fast" "normal computers can't process as many 'transactions' per second as they do". Jeese, I mean it's not like Google is running a bunch of Mainframes and look how many transactions/sec they do! The question here really is "why?". When I ask this question to the mainframe devs I know, they can't answer, they simply restate "It's fast". With the advent of Cloud Computing, I can't imagine mainframes being able to compete both cost-wise and mindshare-wise (aren't all the Cobol devs going to retire at some point, or will offshore just pickup the slack?). And yet, I know a few companies that still pump out net-new Cobol/Mainframe apps, even for things we could do easily in say .NET and Java. Anyone have a real good answer as to why "The Mainframe is faster", or can point me to some good articles relating to the topic?

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• Who owes who money optimisation problem

  - by Francis

  Say you have n people, each who owe each other money. In general it should be possible to reduce the amount of transactions that need to take place. i.e. if X owes Y £4 and Y owes X £8, then Y only needs to pay X £4 (1 transaction instead of 2). This becomes harder when X owes Y, but Y owes Z who owes X as well. I can see that you can easily calculate one particular cycle. It helps for me when I think of it as a fully connected graph, with the nodes being the amount each person owes. Problem seems to be NP-complete, but what kind of optimisation algorithm could I make, nevertheless, to reduce the total amount of transactions? Doesn't have to be that efficient, as N is quite small for me.

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• Average of a Sum in Mysql query

  - by chupeman

  I am having some problems creating a query that gives me the average of a sum. I read a few examples here in stackoverflow and couldn't do it. Can anyone help me to understand how to do this please? This is the data I have: Basically I need the average transaction value by cashier. I can't run a basic avg because it will take all rows but each transaction can have multiple rows. At the end I want to have: Cashier| Average| 131 | 44.31 |(Which comes from the sum divided by 3 transactions not 5 rows) 130 | 33.15 | etc. This is the query I have to SUM the transactions but don't know how or where to include the AVG function. SELECT `products`.`Transaction_x0020_Number`, Sum(`products`.`Sales_x0020_Value`) AS `SUM of Sales_x0020_Value`, `products`.`Cashier` FROM `products` GROUP BY `products`.`Transaction_x0020_Number`, `products`.`Date`, `products`.`Cashier` HAVING (`products`.`Date` ={d'2010-06-04'}) Any help is appreciated.

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• How should flushing be handled in a doctrine EntityManager instance shared across different services in symfony2?

  - by Jbm

  I have defined several services in symfony 2 which persist changes to the database. These services have the doctrine instance as one of their dependencies: a.given.service: class: Acme\TestBundle\Service\AGivenService arguments: [@doctrine] If I have two different services and both of them persist objects through the EntityManager, which is obtained like this from the doctrine instance: $em = $doctrine->getEntityManager(); Would all services always share the same EntityManager? If so, how should I handle flushing if I wanted to handle all the changes in a single transaction? I have checked this: http://docs.doctrine-project.org/projects/doctrine-orm/en/2.0.x/reference/transactions-and-concurrency.html and it explains how to handle different transactions in a request, but I want to achieve the opposite, which is having different changes in different services handled as a single transaction. Is there a better approach to handle multiple changes in different services? For now my best bet is having a front-end service in charge of calling the other services and doing the flushing afterwards. Backend services would persist objects but would not do any flushing.

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• Homework - C# - Creating an object instance with a button click

  - by Erica

  I'm new to learning Windows Programming with C#. My current assignment is to create a very simple bank account program: The user enters the accountholder name, account number and beginning balance, then presses a "Continue" button to work with that account by making deposits and withdrawals. I wrote a separate "BankAccount" class with the required data members and methods. I've put the code for the creation of the BankAccount object in the Continue button click event BankAccount currentAccount = new BankAccount(acctName, acctNum, beginningBalance); But that seems to make it local to that method only, and currentAccount is not recognized when I'm programming the click event for the "Record Transactions" (deposits and withdrawals) button. How and where should the creation of the BankAccount object be coded in order for it to be created when the "Continue" button is clicked and also recognized in the "Record Transactions" button click event? Please let me know if any clarification is needed, or if you need to see part or all of my code.

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• Consolidating separate Loan, Purchase & Sales tables into one transaction table.

  - by Frank Computer

  INFORMIX-SE with ISQL 7.3: I have separate tables for Loan, Purchase & Sales transactions. Each tables rows are joined to their respective customer rows by: customer.id [serial] = loan.foreign_id [integer]; = purchase.foreign_id [integer]; = sale.foreign_id [integer]; I would like to consolidate the three tables into one table called "transaction", where a column "transaction.trx_type" [char(1)] {L=Loan, P=Purchase, S=Sale} identifies the transaction type. Is this a good idea or is it better to keep them in separate tables? Storage space is not a concern, I think it would be easier programming & user=wise to have all types of transactions under one table.

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• Customers and suppliers database design issue

  - by hectorsq

  I am developing a web application in which I will have customers and suppliers. Initially I thought on using a Customers table and a Suppliers table. Then when I was thinking on bank transactions, I noticed that each transaction needs to refer to a customer or a supplier, so I thought on using a single table named Business in which I will save both customers and suppliers. If I use Customers and Suppliers tables when I want to list the bank transactions I will have to search in both tables to get the company name. If I use a Businesses table I will have to use a business type column, and have the union of possible fields for all businesses types. Any suggestions on the design?

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• MySQL count/sum fields

  - by Conor H

  Hi There, What I am trying to achieve is a report on daily financial transactions. With my SQL query I would like to count the total number of cash transactions, the total cash value and the same for checks. I only want to do this for a specified date. Here is a snippet of the query that I am having trouble with. These sum and count commands are processing all the data in the table and not for the selected date. (SELECT SUM(amount) FROM TRANSACTION WHERE payment_type.name = 'cash') AS total_cash, (SELECT COUNT(*) FROM TRANSACTION WHERE payment_type.name = 'cash') AS total_cash_transactions Sorry if I havent posted enough detail as I haven't time. If you need more info just ask.. Cheers.

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• TSQL - create a stored proc inside a transaction statement

  - by Chris L

  I have a sql script that is set to roll to production. I've wrapped the various projects into separate transactions. In each of the transactions we created stored procedures. I'm getting error messages Msg 156, Level 15, State 1, Line 4 Incorrect syntax near the keyword 'procedure'. I created this example script to illustrate Begin Try Begin Transaction -- do a bunch of add/alter tables here -- do a bunch of data manipulation/population here -- create a stored proc create procedure dbo.test as begin select * from some_table end Commit End Try Begin Catch Rollback Declare @Msg nvarchar(max) Select @Msg=Error_Message(); RaisError('Error Occured: %s', 20, 101,@Msg) With Log; End Catch The error seems to imply that I can't create stored procs inside of transaction, but I'm not finding any docs that say otherwise(maybe google isn't being freindly today).

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• SqlCE Flush Interval - Will the default setting lead to corruption?

  - by NormD

  SqlCE has a parameter set on the Connect String called Flush Interval. It is defined as: The interval time (in seconds) before all committed transactions are flushed to disk. If not specified, the default value is 10. I thought that a committed transaction, by definition, is a transaction that has been flushed to disk, specifically the database file. If a transaction is only stored in RAM then cannot the transaction be easily lost? I thought that transactions were first written to a log file and then applied to the database file itself, so perhaps this parameter could mean the time to wait until the transaction log is applied to the database file? I would have thought that this parameter should be 0.

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• JMX Based Monitoring - Part Four - Business App Server Monitoring

  - by Anthony Shorten

  In the last blog entry I talked about the Oracle Utilities Application Framework V4 feature for monitoring and managing aspects of the Web Application Server using JMX. In this blog entry I am going to discuss a similar new feature that allows JMX to be used for management and monitoring the Oracle Utilities business application server component. This feature is primarily focussed on performance tracking of the product. In first release of Oracle Utilities Customer Care And Billing (V1.x I am talking about), we used to use Oracle Tuxedo as part of the architecture. In Oracle Utilities Application Framework V2.0 and above, we removed Tuxedo from the architecture. One of the features that some customers used within Tuxedo was the performance tracking ability. The idea was that you enabled performance logging on the individual Tuxedo servers and then used a utility named txrpt to produce a performance report. This report would list every service called, the number of times it was called and the average response time. When I worked a performance consultant, I used this report to identify badly performing services and also gauge the overall performance characteristics of a site. When Tuxedo was removed from the architecture this information was also lost. While you can get some information from access.log and some Mbeans supplied by the Web Application Server it was not at the same granularity as txrpt or as useful. I am happy to say we have not only reintroduced this facility in Oracle Utilities Application Framework but it is now accessible via JMX and also we have added more detail into the performance tracking. Most of this new design was working with customers around the world to make sure we introduced a new feature that not only satisfied their performance tracking needs but allowed for finer grained performance analysis. As with the Web Application Server, the Business Application Server JMX monitoring is enabled by specifying a JMX port number in RMI Port number for JMX Business and initial credentials in the JMX Enablement System User ID and JMX Enablement System Password configuration options. These options are available using the configureEnv[.sh] -a utility. These credentials are shared across the Web Application Server and Business Application Server for authorization purposes. Once this is information is supplied a number of configuration files are built (by the initialSetup[.sh] utility) to configure the facility: spl.properties - contains the JMX URL, the security configuration and the mbeans that are enabled. For example, on my demonstration machine: spl.runtime.management.rmi.port=6750 spl.runtime.management.connector.url.default=service:jmx:rmi:///jndi/rmi://localhost:6750/oracle/ouaf/ejbAppConnector jmx.remote.x.password.file=scripts/ouaf.jmx.password.file jmx.remote.x.access.file=scripts/ouaf.jmx.access.file ouaf.jmx.com.splwg.ejb.service.management.PerformanceStatistics=enabled ouaf.jmx.* files - contain the userid and password. The default configuration uses the JMX default configuration. You can use additional security features by altering the spl.properties file manually or using a custom template. For more security options see JMX Security for more details. Once it has been configured and the changes reflected in the product using the initialSetup[.sh] utility the JMX facility can be used. For illustrative purposes I will use jconsole but any JSR160 complaint browser or client can be used (with the appropriate configuration). Once you start jconsole (ensure that splenviron[.sh] is executed prior to execution to set the environment variables or for remote connection, ensure java is in your path and jconsole.jar in your classpath) you specify the URL in the spl.runtime.management.connnector.url.default entry. For example: You are then able to track performance of the product using the PerformanceStatistics Mbean. The attributes of the PerformanceStatistics Mbean are counts of each object type. This is where this facility differs from txrpt. The information that is collected includes the following: The Service Type is captured so you can filter the results in terms of the type of service. For maintenance type services you can even see the transaction type (ADD, CHANGE etc) so you can see the performance of updates against read transactions. The Minimum and Maximum are also collected to give you an idea of the spread of performance. The last call is recorded. The date, time and user of the last call are recorded to give you an idea of the timeliness of the data. The Mbean maintains a set of counters per Service Type to give you a summary of the types of transactions being executed. This gives you an overall picture of the types of transactions and volumes at your site. There are a number of interesting operations that can also be performed: reset - This resets the statistics back to zero. This is an important operation. For example, txrpt is restricted to collecting statistics per hour, which is ok for most people. But what if you wanted to be more granular? This operation allows to set the collection period to anything you wish. The statistics collected will represent values since the last restart or last reset. completeExecutionDump - This is the operation that produces a CSV in memory to allow extraction of the data. All the statistics are extracted (see the Server Administration Guide for a full list). This can be then loaded into a database, a tool or simply into your favourite spreadsheet for analysis. Here is an extract of an execution dump from my demonstration environment to give you an idea of the format: ServiceName, ServiceType, MinTime, MaxTime, Avg Time, # of Calls, Latest Time, Latest Date, Latest User ... CFLZLOUL, EXECUTE_LIST, 15.0, 64.0, 22.2, 10, 16.0, 2009-12-16::11-25-36-932, ASHORTEN CILBBLLP, READ, 106.0, 1184.0, 466.3333333333333, 6, 106.0, 2009-12-16::11-39-01-645, BOBAMA CILBBLLP, DELETE, 70.0, 146.0, 108.0, 2, 70.0, 2009-12-15::12-53-58-280, BPAYS CILBBLLP, ADD, 860.0, 4903.0, 2243.5, 8, 860.0, 2009-12-16::17-54-23-862, LELLISON CILBBLLP, CHANGE, 112.0, 3410.0, 815.1666666666666, 12, 112.0, 2009-12-16::11-40-01-103, ASHORTEN CILBCBAL, EXECUTE_LIST, 8.0, 84.0, 26.0, 22, 23.0, 2009-12-16::17-54-01-643, LJACKMAN InitializeUserInfoService, READ_SYSTEM, 49.0, 962.0, 70.83777777777777, 450, 63.0, 2010-02-25::11-21-21-667, ASHORTEN InitializeUserService, READ_SYSTEM, 130.0, 2835.0, 234.85777777777778, 450, 216.0, 2010-02-25::11-21-21-446, ASHORTEN MenuLoginService, READ_SYSTEM, 530.0, 1186.0, 703.3333333333334, 9, 530.0, 2009-12-16::16-39-31-172, ASHORTEN NavigationOptionDescriptionService, READ_SYSTEM, 2.0, 7.0, 4.0, 8, 2.0, 2009-12-21::09-46-46-892, ASHORTEN ... There are other operations and attributes available. Refer to the Server Administration Guide provided with your product to understand the full et of operations and attributes. This is one of the many features I am proud that we implemented as it allows flexible monitoring of the performance of the product.

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• Four Emerging Payment Stories

  - by David Dorf

  The world of alternate payments has been moving fast of late.  Innovation in this area will help both consumers and retailers, but probably hurt the banks (at least that's the plan).  Here are four recent news items in this area: Dwolla, a start-up in Iowa, is trying to make credit cards obsolete.  Twelve guys in Des Moines are using $1.3M they raised to allow businesses to skip the credit card networks and avoid the fees.  Today they move about $1M a day across their network with an average transaction size of $500. Instead of charging merchants 2.9% plus $.30 per transaction, Dwolla charges a quarter -- yep, that coin featuring George Washington. Dwolla (Web + Dollar = Dwolla) avoids the credit networks and connects directly to bank accounts using the bank's ACH network.  They are signing up banks and merchants targeting both B2B and C2B as well as P2P payments.  They leverage social networks to notify people they have a money transfer, and also have a mobile app that uses GPS location. However, all is not rosy.  There have been complaints about unexpected chargebacks and with debit fees being reduced by the big banks, the need is not as pronounced.  The big banks are working on their own network called clearXchange that could provide stiff competition. VeriFone just bought European payment processor Point for around $1B.  By itself this would not have caught my attention except for the fact that VeriFone also announced the acquisition of GlobalBay earlier this month.  In addition to their core business of selling stand-beside payment terminals, with GlobalBay they get employee-operated mobile selling tools and with Point they get a very big payment processing platform. MasterCard and Intel announced a partnership around payments, starting with PayPass, MasterCard's new payment technology.  Intel will lend its expertise to add additional levels of security, which seems to be the biggest barrier for consumer adoption.  Everyone is scrambling to get their piece of cash transactions, which still represents 85% of all transactions. Apple was awarded another mobile payment patent further cementing the rumors that the iPhone 5 will support NFC payments.  As usual, Apple is upsetting the apple cart (sorry) by moving control of key data from the carriers to Apple.  With Apple's vast number of iTunes accounts, they have a ready-made customer base to use the payment infrastructure, which I bet will slowly transition people away from credit cards and toward cheaper ACH.  Gary Schwartz explains the three step process Apple is taking to become a payment processor. Below is a picture I drew representing payments in the retail industry. There's certainly a lot of innovation happening.

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• Need to Know

  - by Tony Davis

  Sometimes, I wonder whether writers of documentation, tutorials and articles stop to ask themselves one very important question: Does the reader really need to know this? I recently took on the task of writing a concise series of articles about the transaction log, what is it, how it works and why it's important. It was an enjoyable task; rather like peering inside a giant, complex clock mechanism. Initially, one sees only the basic components, which work to guarantee the integrity of database transactions, and preserve these transactions so that data can be restored to a previous point in time. On closer inspection, one notices all of small, arcane mechanisms that are necessary to make this happen; LSNs, virtual log files, log chains, database checkpoints, and so on. It was engrossing, escapist, stuff; what I'd written looked weighty and steeped in mysterious significance. Suddenly, however, I jolted myself back to reality with the awful thought "does anyone really need to know all this?" The driver of a car needs only to be dimly aware of what goes on under the hood, however exciting the mechanism is to the engineer. Similarly, while everyone who uses SQL Server ought to be aware of the transaction log, its role in guaranteeing the ACID properties, and how to control its growth, the intricate mechanisms ticking away under its clock face are a world away from the daily work of the harassed developer. The DBA needs to know more, such as the correct rituals for ensuring optimal performance and data integrity, setting the appropriate growth characteristics, backup routines, restore procedures, and so on. However, even then, the average DBA only needs to understand enough about the arcane processes to spot problems and react appropriately, or to know how to Google for the best way of dealing with it. The art of technical writing is tied up in intimate knowledge of your audience and what they need to know at any point. It means serving up just enough at each point to help the reader in a practical way, but not to overcook it, or stuff the reader with information that does them no good. When I think of the books and articles that have helped me the most, they have been full of brief, practical, and well-informed guidance, based on experience. This seems far-removed from the 900-page "beginner's guides" that one now sees everywhere. The more I write and edit, the more I become convinced that the real art of technical communication lies in knowing what to leave out. In what areas do the SQL Server technical materials suffer from "information overload"? Where else does it seem that concise, practical advice is drowned out by endless discussion of the "clock mechanisms"? Cheers, Tony.

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• MySQL – Scalability on Amazon RDS: Scale out to multiple RDS instances

  - by Pinal Dave

  Today, I’d like to discuss getting better MySQL scalability on Amazon RDS. The question of the day: “What can you do when a MySQL database needs to scale write-intensive workloads beyond the capabilities of the largest available machine on Amazon RDS?” Let’s take a look. In a typical EC2/RDS set-up, users connect to app servers from their mobile devices and tablets, computers, browsers, etc.  Then app servers connect to an RDS instance (web/cloud services) and in some cases they might leverage some read-only replicas.   Figure 1. A typical RDS instance is a single-instance database, with read replicas.  This is not very good at handling high write-based throughput. As your application becomes more popular you can expect an increasing number of users, more transactions, and more accumulated data.  User interactions can become more challenging as the application adds more sophisticated capabilities. The result of all this positive activity: your MySQL database will inevitably begin to experience scalability pressures. What can you do? Broadly speaking, there are four options available to improve MySQL scalability on RDS. 1. Larger RDS Instances – If you’re not already using the maximum available RDS instance, you can always scale up – to larger hardware.  Bigger CPUs, more compute power, more memory et cetera. But the largest available RDS instance is still limited.  And they get expensive. “High-Memory Quadruple Extra Large DB Instance”: 68 GB of memory 26 ECUs (8 virtual cores with 3.25 ECUs each) 64-bit platform High I/O Capacity Provisioned IOPS Optimized: 1000Mbps 2. Provisioned IOPs – You can get provisioned IOPs and higher throughput on the I/O level. However, there is a hard limit with a maximum instance size and maximum number of provisioned IOPs you can buy from Amazon and you simply cannot scale beyond these hardware specifications. 3. Leverage Read Replicas – If your application permits, you can leverage read replicas to offload some reads from the master databases. But there are a limited number of replicas you can utilize and Amazon generally requires some modifications to your existing application. And read-replicas don’t help with write-intensive applications. 4. Multiple Database Instances – Amazon offers a fourth option: “You can implement partitioning,thereby spreading your data across multiple database Instances” (Link) However, Amazon does not offer any guidance or facilities to help you with this. “Multiple database instances” is not an RDS feature.  And Amazon doesn’t explain how to implement this idea. In fact, when asked, this is the response on an Amazon forum: Q: Is there any documents that describe the partition DB across multiple RDS? I need to use DB with more 1TB but exist a limitation during the create process, but I read in the any FAQ that you need to partition database, but I don’t find any documents that describe it. A: “DB partitioning/sharding is not an official feature of Amazon RDS or MySQL, but a technique to scale out database by using multiple database instances. The appropriate way to split data depends on the characteristics of the application or data set. Therefore, there is no concrete and specific guidance.” So now what? The answer is to scale out with ScaleBase. Amazon RDS with ScaleBase: What you get – MySQL Scalability! ScaleBase is specifically designed to scale out a single MySQL RDS instance into multiple MySQL instances. Critically, this is accomplished with no changes to your application code.  Your application continues to “see” one database.   ScaleBase does all the work of managing and enforcing an optimized data distribution policy to create multiple MySQL instances. With ScaleBase, data distribution, transactions, concurrency control, and two-phase commit are all 100% transparent and 100% ACID-compliant, so applications, services and tooling continue to interact with your distributed RDS as if it were a single MySQL instance. The result: now you can cost-effectively leverage multiple MySQL RDS instance to scale out write-intensive workloads to an unlimited number of users, transactions, and data. Amazon RDS with ScaleBase: What you keep – Everything! And how does this change your Amazon environment? 1. Keep your application, unchanged – There is no change your application development life-cycle at all.  You still use your existing development tools, frameworks and libraries.  Application quality assurance and testing cycles stay the same. And, critically, you stay with an ACID-compliant MySQL environment. 2. Keep your RDS value-added services – The value-added services that you rely on are all still available. Amazon will continue to handle database maintenance and updates for you. You can still leverage High Availability via Multi A-Z.  And, if it benefits youra application throughput, you can still use read replicas. 3. Keep your RDS administration – Finally the RDS monitoring and provisioning tools you rely on still work as they did before. With your one large MySQL instance, now split into multiple instances, you can actually use less expensive, smallersmaller available RDS hardware and continue to see better database performance. Conclusion Amazon RDS is a tremendous service, but it doesn’t offer solutions to scale beyond a single MySQL instance. Larger RDS instances get more expensive.  And when you max-out on the available hardware, you’re stuck.  Amazon recommends scaling out your single instance into multiple instances for transaction-intensive apps, but offers no services or guidance to help you. This is where ScaleBase comes in to save the day. It gives you a simple and effective way to create multiple MySQL RDS instances, while removing all the complexities typically caused by “DIY” sharding andwith no changes to your applications . With ScaleBase you continue to leverage the AWS/RDS ecosystem: commodity hardware and value added services like read replicas, multi A-Z, maintenance/updates and administration with monitoring tools and provisioning. SCALEBASE ON AMAZON If you’re curious to try ScaleBase on Amazon, it can be found here – Download NOW. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: MySQL, PostADay, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL

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• An Introduction to Cash Till

  Cash till is a machine that can tabulate the amount of sales transactions and usually prints receipt for the customers. It can also make a permanent and cumulative record of the day’s sales. Al... [Author: Alan Wisdom - Computers and Internet - April 05, 2010]

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• SQL SERVER Find Largest Supported DML Operation Question to You

  SQL Server is very big and it is not possible to know everything in SQL Server but we all keep learning. Recently I was going over the best practices of transactions log and I come across following statement. The log size must be at least twice the size of largest supported DML operation (using uncompressed [...]...Did you know that DotNetSlackers also publishes .net articles written by top known .net Authors? We already have over 80 articles in several categories including Silverlight. Take a look: here.

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• Don’t miss the Receiving Webcast on November 20th

  - by user793553

  This one-hour session is recommended for technical and functional users who are interested to know about the Receiving transactions and its debugging techniques. TOPICS WILL INCLUDE: Using generic diagnostic scripts. How to read debug logs in receiving. Data flow for various document types (PO, RMA, ISO, IOT) to help debug issues Receiving Transaction processor Generic datafixes.  See DocID 1456150.1 to sign up now!

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• Minimal set of critical database operations

  - by Juan Carlos Coto

  In designing the data layer code for an application, I'm trying to determine if there is a minimal set of database operations (both single and combined) that are essential for proper application function (i.e. the database is left in an expected state after every data access call). Is there a way to determine the minimal set of database operations (functions, transactions, etc.) that are critical for an application to function correctly? How do I find it? Thanks very much!

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• Exam 71-513: TS: Windows Communication Foundation Development with Microsoft .NET Framework 4

  - by Ricardo Peres

  Just took the 70-513 exam. Here are some thoughts: 84 questions 240 minutes total time Lots of questions on transactions Lots of questions on sessions and callbacks Some questions on scripting (jQuery) Some questions on throttling Absolutely no questions on interception As for the other exams, I still don't know the result, but I think I may have passed...

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• Incremental Statistics Maintenance – what statistics will be gathered after DML occurs on the table?

  - by Maria Colgan

  Incremental statistics maintenance was introduced in Oracle Database 11g to improve the performance of gathering statistics on large partitioned table. When incremental statistics maintenance is enabled for a partitioned table, oracle accurately generated global level  statistics by aggregating partition level statistics. As more people begin to adopt this functionality we have gotten more questions around how they expected incremental statistics to behave in a given scenario. For example, last week we got a question around what partitions should have statistics gathered on them after DML has occurred on the table? The person who asked the question assumed that statistics would only be gathered on partitions that had stale statistics (10% of the rows in the partition had changed). However, what they actually saw when they did a DBMS_STATS.GATHER_TABLE_STATS was all of the partitions that had been affected by the DML had statistics re-gathered on them. This is the expected behavior, incremental statistics maintenance is suppose to yield the same statistics as gathering table statistics from scratch, just faster. This means incremental statistics maintenance needs to gather statistics on any partition that will change the global or table level statistics. For instance, the min or max value for a column could change after just one row is inserted or updated in the table. It might easier to demonstrate this using an example. Let’s take the ORDERS2 table, which is partitioned by month on order_date.  We will begin by enabling incremental statistics for the table and gathering statistics on the table. After the statistics gather the last_analyzed date for the table and all of the partitions now show 13-Mar-12. And we now have the following column statistics for the ORDERS2 table. We can also confirm that we really did use incremental statistics by querying the dictionary table sys.HIST_HEAD$, which should have an entry for each column in the ORDERS2 table. So, now that we have established a good baseline, let’s move on to the DML. Information is loaded into the latest partition of the ORDERS2 table once a month. Existing orders maybe also be update to reflect changes in their status. Let’s assume the following transactions take place on the ORDERS2 table this month. After these transactions have occurred we need to re-gather statistic since the partition ORDERS_MAR_2012 now has rows in it and the number of distinct values and the maximum value for the STATUS column have also changed. Now if we look at the last_analyzed date for the table and the partitions, we will see that the global statistics and the statistics on the partitions where rows have changed due to the update (ORDERS_FEB_2012) and the data load (ORDERS_MAR_2012) have been updated. The column statistics also reflect the changes with the number of distinct values in the status column increase to reflect the update. So, incremental statistics maintenance will gather statistics on any partition, whose data has changed and that change will impact the global level statistics.

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• Don’t Miss The Top Exastack ISV Headlines – Week Of May 26

  - by Roxana Babiciu

  Calypso Technology announced that Calypso version 14 has achieved Oracle Exadata Optimized status through OPN. In simulations of data-intensive straight through-processing tasks, Calypso achieved performance gains of up to 500% using Exadata hardware – Read more Infosys achieves Oracle SuperCluster Optimized status with Finacle, a core banking solution. Finacle can process 6x the volume of transactions currently processed by the entire US banking system – Read more

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• SQL SERVER – Move Database Files MDF and LDF to Another Location

  - by pinaldave

  When a novice DBA or Developer create a database they use SQL Server Management Studio to create new database. Additionally, the T-SQL script to create a database is very easy as well. You can just write CREATE DATABASE DatabaseName and it will create new database for you. The point to remember here is that it will create the database at the default location specified for SQL Server Instance (this default instance can be changed and we will see that in future blog posts). Now, once the database goes in production it will start to grow. It is not common to keep the Database on the same location where OS is installed. Usually Database files are on SAN, Separate Disk Array or on SSDs. This is done usually for performance reason and manageability perspective. Now the challenges comes up when database which was installed at not preferred default location and needs to move to a different location. Here is the quick tutorial how you can do it. Let us assume we have two folders loc1 and loc2. We want to move database files from loc1 to loc2. USE MASTER; GO -- Take database in single user mode -- if you are facing errors -- This may terminate your active transactions for database ALTER DATABASE TestDB SET SINGLE_USER WITH ROLLBACK IMMEDIATE; GO -- Detach DB EXEC MASTER.dbo.sp_detach_db @dbname = N'TestDB' GO Now move the files from loc1 to loc2. You can now reattach the files with new locations. -- Move MDF File from Loc1 to Loc 2 -- Re-Attached DB CREATE DATABASE [TestDB] ON ( FILENAME = N'F:\loc2\TestDB.mdf' ), ( FILENAME = N'F:\loc2\TestDB_log.ldf' ) FOR ATTACH GO Well, we are done. There is little warning here for you: If you do ROLLBACK IMMEDIATE you may terminate your active transactions so do not use it randomly. Do it if you are confident that they are not needed or due to any reason there is a connection to the database which you are not able to kill manually after review. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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