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  • Query Level 2 Caching throwing ClassCastException

    - by Sameer Malhotra
    Hi, I am using JPA and Hibernate for the database. I have configured (EHCacache) second level cache and query level cache, but just to make sure that caching is working I was trying to get the statistics which is throwing class cast exception.Any help will be highly appreciated. My main goal is to see all the objects which have been cached to make sure that the caching is working properly. Here is the code: public List<CodeValue> findByCodetype(String propertyName) { try { final String queryString = "select model from CodeValue model where model.codetype" + "= :propertyValue" + " order by model.code"; Query query = em.createQuery(queryString); query.setHint("org.hibernate.cacheable", true); query.setHint("org.hibernate.cacheRegion", "query.findByCodetype"); query.setParameter("propertyValue", propertyName); List resultList = query.getResultList(); org.hibernate.Session session = (Session) em.getDelegate(); SessionFactory sessionFactory = session.getSessionFactory(); Map cacheEntries = sessionFactory.getStatistics() .getSecondLevelCacheStatistics("query.findByCodetype") .getEntries(); logger.info("The statistics are: " + cacheEntries); return resultList; } catch (RuntimeException re) { logger.error("findByCodetype failed in trauma patient", re); throw re; } } The error is existing right when I am trying to print the statistics. Below is exception: [6/7/10 19:23:17:059 GMT] 00000034 SystemOut O java.lang.ClassCastException: org.hibernate.cache.QueryKey incompatible with org.hibernate.cache.CacheKey at org.hibernate.stat.SecondLevelCacheStatistics.getEntries(SecondLevelCacheStatistics.java:51) at com.idph.trauma.registry.service.TraumaPatientDAO.findByCodetype(TraumaPatientDAO.java:439) at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:64) at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) at java.lang.reflect.Method.invoke(Method.java:615) at org.springframework.aop.support.AopUtils.invokeJoinpointUsingReflection(AopUtils.java:307) at org.springframework.aop.framework.ReflectiveMethodInvocation.invokeJoinpoint(ReflectiveMethodInvocation.java:182) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:149) at org.springframework.transaction.interceptor.TransactionInterceptor.invoke(TransactionInterceptor.java:106) at org.springframework.aop.framework.ReflectiveMethodInvocation.proceed(ReflectiveMethodInvocation.java:171) at org.springframework.aop.framework.JdkDynamicAopProxy.invoke(JdkDynamicAopProxy.java:204) at $Proxy209.findByCodetype(Unknown Source) Do you know what's going on?

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  • MySQL Gurus: How to pull a complex grid of data from MySQL database with one query?

    - by iopener
    Hopefully this is less complex than I think. I have one table of companies, and another table of jobs, and a third table with that contains a single entry for each employee in each job from each company. NOTE: Some companies won't have employees in some jobs, and some companies will have more than one employee in some jobs. The company table has a companyid and companyname field, the job table has a jobid and jobtitle field, and the employee table has employeeid, companyid, jobid and employeename fields. I want to build a table like this: +-----------+-----------+-----------+ | Company A | Company B | Company C | ------+-----------+-----------+-----------+ Job A | Emp 1 | Emp 2 | | ------+-----------+-----------+-----------+ Job B | Emp 3 | | Emp 4 | | | | Emp 5 | ------+-----------+-----------+-----------+ Job C | | Emp 6 | | | | Emp 7 | | | | Emp 8 | | ------+-----------+-----------+-----------+ I had previously been looping through a result set of jobs, and for each job, looping through a result set of each company, and for each company, looping through each employee and printing it in a table (gross, but performance was not supposed to be a consideration). The app has grown in popularity, and now we have 100 companies and hundreds of jobs, and the server is crapping out (all the id fields are indexed). Any suggestions on how to write a single query to get this data? I don't need the company names or job titles (obviously), but I do need some way to identify where each row from the result should be printed. I'm imagining a result set that just contained a long list of joined employees, and I could write a loop to use the companyid and employeeid values to tell me when to create a new cell or table row. This works as long as there aren't ZERO employees; I would need a NULL employee name for that I think? Am I completely on the wrong track? Thanks in advance for any ideas!

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  • How can i get rid of 'ORA-01489: result of string concatenation is too long' in this query?

    - by core_pro
    this query gets the dominating sets in a network. so for example given a network A<----->B B<----->C B<----->D C<----->E D<----->C D<----->E F<----->E it returns B,E B,F A,E but it doesn't work for large data because i'm using string methods in my result. i have been trying to remove the string methods and return a view or something but to no avail With t as (select 'A' as per1, 'B' as per2 from dual union all select 'B','C' from dual union all select 'B','D' from dual union all select 'C','B' from dual union all select 'C','E' from dual union all select 'D','C' from dual union all select 'D','E' from dual union all select 'E','C' from dual union all select 'E','D' from dual union all select 'F','E' from dual) ,t2 as (select distinct least(per1, per2) as per1, greatest(per1, per2) as per2 from t union select distinct greatest(per1, per2) as per1, least(per1, per2) as per1 from t) ,t3 as (select per1, per2, row_number() over (partition by per1 order by per2) as rn from t2) ,people as (select per, row_number() over (order by per) rn from (select distinct per1 as per from t union select distinct per2 from t) ) ,comb as (select sys_connect_by_path(per,',')||',' as p from people connect by rn > prior rn ) ,find as (select p, per2, count(*) over (partition by p) as cnt from ( select distinct comb.p, t3.per2 from comb, t3 where instr(comb.p, ','||t3.per1||',') > 0 or instr(comb.p, ','||t3.per2||',') > 0 ) ) ,rnk as (select p, rank() over (order by length(p)) as rnk from find where cnt = (select count(*) from people) order by rnk ) select distinct trim(',' from p) as p from rnk where rnk.rnk = 1`

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  • World's Most Challening MySQL SQL Query (least I think so...)

    - by keruilin
    Whoever answers this question can claim credit for solving the world's most challenging SQL query, according to yours truly. Working with 3 tables: users, badges, awards. Relationships: user has many awards; award belongs to user; badge has many awards; award belongs to badge. So badge_id and user_id are foreign keys in the awards table. The business logic at work here is that every time a user wins a badge, he/she receives it as an award. A user can be awarded the same badge multiple times. Each badge is assigned a designated point value (point_value is a field in the badges table). For example, BadgeA can be worth 500 Points, BadgeB 1000 Points, and so on. As further example, let's say UserX won BadgeA 10 times and BadgeB 5 times. BadgeA being worth 500 Points, and BadgeB being worth 1000 Points, UserX has accumulated a total of 10,000 Points ((10 x 500) + (5 x 1000)). The end game here is to return a list of top 50 users who have accumulated the most badge points. Can you do it?

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  • How does C#'s DateTime.Now affect query plan caching in SQL Server?

    - by Bill Paetzke
    Given: Let's say we have a stored procedure. It reports data back to a user on a webpage. The user can set a date range. If the user sets today's date as the "end date," which includes today's data, the web app passes DateTime.Now to the sql proc. Let's say that one user runs a report--5/1/2010 to now--over and over several times. On the webpage, the user sees "5/1/2010" to "5/4/2010." But the web app passes DateTime.Now to the sql proc as the end date. So, the end date in the proc will always be different, although the user is querying a similar date range. Assume the number of records in the table and number of users are large. So any performance gains matter. Hence the importance of the question. Question: Does passing DateTime.Now as a parameter to a proc prevent SQL Server from caching the query plan? If so, then is the web app missing out on huge performance gains? Possible Solution: I thought DateTime.Today.AddDays(1) would be a possible solution. It would allow the user to get the latest data and always pass the same end date to the sql proc--"5/5/2010" in this case. Please speak to this as well. Sample proc and execution (if that helps to understand): CREATE PROCEDURE GetFooData @StartDate datetime @EndDate datetime AS SELECT * FROM Foo WHERE LogDate >= @StartDate AND LogDate < @EndDate Here's a sample execution using DateTime.Now: EXEC GetFooData '2010-05-01', '2010-05-04 15:41:27' -- passed in DateTime.Now Here's a sample execution using DateTime.Today.AddDays(1) EXEC GetFooData '2010-05-01', '2010-05-05' -- passed in DateTime.Today.AddDays(1) The same data is returned for both procs, since the current time is: 2010-05-04 15:41:27.

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  • Delaying LINQ to SQL Select Query Execution

    - by Maxim Z.
    I'm building an ASP.NET MVC site that uses LINQ to SQL. In my search method that has some required and some optional parameters, I want to build a LINQ query while testing for the existence of those optional parameters. Here's what I'm currently thinking: using(var db = new DBDataContext()) { IQueryable<Listing> query = null; //Handle required parameter query = db.Listings.Where(l => l.Lat >= form.bounds.extent1.latitude && l.Lat <= form.bounds.extent2.latitude); //Handle optional parameter if (numStars != null) query = query.Where(l => l.Stars == (int)numStars); //Other parameters... //Execute query (does this happen here?) var result = query.ToList(); //Process query... Will this implementation "bundle" the where clauses and then execute the bundled query? If not, how should I implement this feature? Also, is there anything else that I can improve? Thanks in advance.

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  • How does DateTime.Now affect query plan caching in SQL Server?

    - by Bill Paetzke
    Question: Does passing DateTime.Now as a parameter to a proc prevent SQL Server from caching the query plan? If so, then is the web app missing out on huge performance gains? Possible Solution: I thought DateTime.Today.AddDays(1) would be a possible solution. It would pass the same end-date to the sql proc (per day). And the user would still get the latest data. Please speak to this as well. Given Example: Let's say we have a stored procedure. It reports data back to a user on a webpage. The user can set a date range. If the user sets today's date as the "end date," which includes today's data, the web app passes DateTime.Now to the sql proc. Let's say that one user runs a report--5/1/2010 to now--over and over several times. On the webpage, the user sees 5/1/2010 to 5/4/2010. But the web app passes DateTime.Now to the sql proc as the end date. So, the end date in the proc will always be different, although the user is querying a similar date range. Assume the number of records in the table and number of users are large. So any performance gains matter. Hence the importance of the question. Example proc and execution (if that helps to understand): CREATE PROCEDURE GetFooData @StartDate datetime @EndDate datetime AS SELECT * FROM Foo WHERE LogDate >= @StartDate AND LogDate < @EndDate Here's a sample execution using DateTime.Now: EXEC GetFooData '2010-05-01', '2010-05-04 15:41:27' -- passed in DateTime.Now Here's a sample execution using DateTime.Today.AddDays(1) EXEC GetFooData '2010-05-01', '2010-05-05' -- passed in DateTime.Today.AddDays(1) The same data is returned for both procs, since the current time is: 2010-05-04 15:41:27.

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  • query structure - ignoring entries for the same event from multiple users?

    - by Andrew Heath
    One table in my MySQL database tracks game plays. It has the following structure: SCENARIO_VICTORIES [ID] [scenario_id] [game] [timestamp] [user_id] [winning_side] [play_date] ID is the autoincremented primary key. timestamp records the moment of submission for the record. winning_side has one of three possible values: 1, 2, or 0 (meaning a draw) One of the queries done on this table calculates the victory percentage for each scenario, when that scenario's page is viewed. The output is expressed as: Side 1 win % Side 2 win % Draw % and queried with: SELECT winning_side, COUNT(scenario_id) FROM scenario_victories WHERE scenario_id='$scenID' GROUP BY winning_side ORDER BY winning_side ASC and then processed into the percentages and such. Sorry for the long setup. My problem is this: several of my users play each other, and record their mutual results. So these battles are being doubly represented in the victory percentages and result counts. Though this happens infrequently, the userbase isn't large and the double entries do have a noticeable effect on the data. Given the table and query above - does anyone have any suggestions for how I can "collapse" records that have the same play_date & game & scenario_id & winning_side so that they're only counted once?

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  • How should I name my SQL query files? Should I use some methodology?

    - by Mehper C. Palavuzlar
    We have an Oracle 10g database (a huge one) in our company, and I provide employees with data upon their requests. My problem is, I save almost every SQL query I wrote, and now my list has grown too much. I want to organize and rename these .sql files so that I can find the one I want easily. At the moment, I'm using some folders named as Sales Dept, Field Team, Planning Dept, Special etc. and under those folders there are .sql files like Delivery_sales_1, Delivery_sales_2, ... Sent_sold_lostsales_endpoints, ... Sales_provinces_period, Returnrates_regions_bymonths, ... Jack_1, Steve_1, Steve_2, ... I try to name the files regarding their content but this makes file names longer and does not completely meet my needs. Sometimes someone comes and demands a special report, and I give the file his name, but this is also not so good. I know duplicates or very similar files are growing in time but I don't have control over them. Can you show me the right direction to rename all these files and folders and organize my queries for easy and better control? TIA.

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  • Why can't you return a List from a Compiled Query?

    - by Andrew
    I was speeding up my app by using compiled queries for queries which were getting hit over and over. I tried to implement it like this: Function Select(ByVal fk_id As Integer) As List(SomeEntity) Using db As New DataContext() db.ObjectTrackingEnabled = False Return CompiledSelect(db, fk_id) End Using End Function Shared CompiledSelect As Func(Of DataContext, Integer, List(Of SomeEntity)) = _ CompiledQuery.Compile(Function(db As DataContext, fk_id As Integer) _ (From u In db.SomeEntities _ Where u.SomeLinkedEntity.ID = fk_id _ Select u).ToList()) This did not work and I got this error message: Type : System.ArgumentNullException, mscorlib, Version=2.0.0.0, Culture=neutral, PublicKeyToken=b77a5c561934e089 Message : Value cannot be null. Parameter name: value However, when I changed my compiled query to return IQueryable instead of List like so: Function Select(ByVal fk_id As Integer) As List(SomeEntity) Using db As New DataContext() db.ObjectTrackingEnabled = False Return CompiledSelect(db, fk_id).ToList() End Using End Function Shared CompiledSelect As Func(Of DataContext, Integer, IQueryable(Of SomeEntity)) = _ CompiledQuery.Compile(Function(db As DataContext, fk_id As Integer) _ From u In db.SomeEntities _ Where u.SomeLinkedEntity.ID = fk_id _ Select u) It worked fine. Can anyone shed any light as to why this is? BTW, compiled queries rock! They sped up my app by a factor of 2.

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  • Using a variable in a mysql query, in a C++ MFC program.

    - by D.Gaughan
    Hi, after extensive trawling of the internet I still havent found any solution for this problem. I`m writing a small C++ app that connects to an online database and outputs the data in a listbox. I need to enable a search function using an edit box, but I cant get the query to work while using a variable. My code is: res = mysql_perform_query (conn, "select distinct artist from Artists"); //res = mysql_perform_query (conn, "select album from Artists where artist = ' ' "); while((row = mysql_fetch_row(res)) != NULL){ CString str; UpdateData(); str = ("%s\n", row[0]); UpdateData(FALSE); m_list_control.AddString(str); } the first "res = " line is working fine, but I need the second one to work. I have a member variable m_search_edit set up for the edit box, but any way I try to include it in the sql statement causes errors. eg. res = mysql_perform_query (conn, "select album from Artists where artist = '"+m_search_edit+" ' "); causes this error: error C2664: 'mysql_perform_query' : cannot convert parameter 2 from 'class CString' to 'char *' No user-defined-conversion operator available that can perform this conversion, or the operator cannot be called" And when I convert m_search_edit to a char* it gives me a " Cannot add 2 pointers" error. Any way around this???

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  • In sync query calls, one query causing other query to run slower. Why?

    - by Irchi
    Sorry for the long question, but I think this is an interesting situation and I couldn't find any explanations for it: I was involved in optimization of an application that performed a large number of sequential SELECT and INSERT statements on a single dedicated SQL Server database. The process needs to INSERT a large number of records into a table, but for each of them there should be some value mappings, which performed using SELECT statements on another table in the same database. For a specific execution, it took 90 minutes to run. I used a profiler (JProfiler - the application is Java-based) to determine how much time does each part of the application take. It yields that 60% of the time was spent on INSERT method calls, and almost 20% on SELECT calls (the rest distributed in other parts). After some trials, I came to this situation: I commented out the INSERT query that took 60% of the time. I was expecting for the total run time to be around 35 minutes, as I have removed 60% of the 90 minutes. But the whole process took the same 90 minutes (doing only SELECTs and nothing else), but each SELECT took longer this time! Everything was running sync, there were no async calls. And there was only one single thread of execution. SELECT and INSERT queries are very simple, and don't have anything special, and they are on different tables, but on the same DB. I tested with both the DB on the application machine, and on a remote network machine. I can't think of any explanation for this, as the Profiler (Application profiler, not SQL Profiler) reported the changes in the method call times, and by removing INSERT statements SELECT statements took longer to run. Can anyone give me some kind of explanation of what could have happened? (there can't be cache / query optimization stuff, because the queries were run in sync, and in a single thread, and it was far from affecting the cache this much) I should note that the bottleneck of the speed was in SQL server, using most of the CPU time.

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  • SQL SERVER – Developer Training Resources and Summary Roundup

    - by pinaldave
    It is always pleasure for any author when other renowned authors in the industry write about you. Earlier I wrote a five part blog series on Developer Training and I have received a phenomenal response to the series. I have received plenty of comments, questions and feedback. I thought it would be nice to sum up the whole series as well answer a few of the questions received. Quick Recap Developer Training - Importance and Significance - Part 1 In this part we discussed the importance of training in the real world. The most important and valuable resource any company is its employee. Employees who have been well-trained will be better at their jobs and produce a better product.  An employee who is well trained obviously knows more about their job and all the technical aspects. I have a very high opinion about training employees and it is the most important task. Developer Training – Employee Morals and Ethics – Part 2 In this part we discussed the most crucial components of training. Often employees are expecting the company to pay for their training and the company expresses no interest in training the employee. Quite often training expenses are the real issue for both the employee and employer. There are companies that pay for 100% of the expenses and there are employees who opt for training on their own expense during their personal time. Training is often looked at as vacation by employee and employers and we need to change this mind-set. One of the ways is to report back the learning to your manager and implement newly learned knowledge in day-to-day work. Developer Training – Difficult Questions and Alternative Perspective - Part 3 This part was the most difficult to write as I tried to address a few difficult questions and answers. Training is such a sensitive issue that many developers when not receiving chance for training think about leaving the organization. The manager often feels pressure to accommodate every single employee for training even though his training budget is limited. It is indeed the responsibility of the developer to get maximum advantage from the training. Training immediately helps organizations but stays as a part of an employee’s knowledge forever. Developer Training – Various Options for Developer Training – Part 4 In this part I tried to explore a few methods and options for training. The generic feedback I received on this blog post was short and I should have explored each of the subject of the training in details. I believe there are two big buckets of training 1) Instructor Lead Training and 2) Self Lead Training. The common element between both the methods is “learning material”. Learning material can be of any format – videos, books, paper notes or just a plain black board. Instructor-led training is a very effective mode but not possible every single time. During the course of the developer’s career, one has to learn lots of new technology and it is almost impossible to have a quality trainer available on that subject at that time. Books are most effective and proven methods, however, it always helps if someone explains the concepts of the book with a demonstration. In recent times I have started to believe in online trainings which leads to a hybrid experience. Online trainings take the best part of the books and the best part of the instructor-led training and gives effective training in a matter of hours. Developer Training – A Conclusive Summary- Part 5 In this part, I shared what I was continuously thinking about developer training. There is no better teacher than oneself. There is no better motivation than a personal desire to learn new technology. Honestly there is nothing more personal learning. That “change is the only constant” and “adapt & overcome” are the essential lessons of life. One cannot stop the learning and resist the change. In the IT industry “ego of knowing all” and the “resistance to change” are the most challenging issues. Once someone overcomes them, life is much easier. I believe that proper and appropriate high quality training can help to address the burning issues. Opinion of Friends I invited a few of my friends to express their opinion about developer training and here are their opinions. I am listing them here in the order of the blog post publishing date. Nakul Vachhrajani - Developer Trainings-Importance, Benefits, Tips and follow-up Nakul’s sums of many of the concepts which are complementary to my blog posts. Nakul addresses the burning question of developer training with different angles. I am personally very impressed by his following statement - “Being skilled does not mean having just a stack of certifications, but it also means having an understanding about the internals of the products that you are working on – and using that knowledge to improve the efficiency & productivity at the workplace in turn resulting in better products, better consulting abilities and a happier self.” Nakul also suggests the online training options of Pluralsight. Vinod Kumar - Training–a necessity or bonus Vinod Kumar comes up with excellent follow up on developer training. Vinod is known for his inspirational writing about SQL Server. Vinod starts with a story of a student who is extremely eager to learn the wisdom of life from a monk but the monk does not accept him as a disciple for a long time. The conversation between student and monk is indeed an essence of all learning. We all want to learn quickly and be successful but the most important thing in life is to have the right attitude towards learning and more so towards life. The blog post end with a very important thought about how to avoid the famous excuse – “I don’t have enough time.” Ritesh Shah - Training – useful or useless? Ritesh brings up very important concept related to training. Ritesh in his meticulous style explains why training is an important and lifelong process. Training must not stop at any age but should continue forever. The moment training stops, progress stops along with. Paras Doshi - Professional Development Resource Paras is known for his to–the-point writing, and has summarized the five part series very precisely. He read the five part series and created a digest summary of the blog post. If you are in a rush and have no time to read my five series – I suggest you read his blog post. Training Resources I am often asked what the best resources for learning new technology are. This is the most difficult question EVER. There are plenty of good training resources available. When it is about training our needs are different, our preference of learning is different and we all have an opinion. Additionally, we all are located in different geographic locations worldwide and there is no way one solution will fit all. However, let me list a few of the training resources which I have built so far and you can consume them if you find it relevant to your need. SQL Server Books SQL Server Interview Questions and Answers SQL Wait Stats SQL Programming Joes 2 Pros SQL Server Video Tutorials SQL Server Questions and Answers SQL Server Performance: Indexing Basics SQL Server Performance: Introduction to Query Tuning SQL in Sixty Seconds Series of Sixty Seconds Learning Video on YouTube Trust me worldwide web is very big and there are plenty of high quality learning materials available worldwide – trainer-led as well online. I suggest you explore various options and make the best choice for yourself. Remember, training is your personal journey and it should never stop. Are you ready? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Developer Training, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Developer’s Life – Disaster Lessons – Notes from the Field #039

    - by Pinal Dave
    [Note from Pinal]: This is a 39th episode of Notes from the Field series. What is the best solution do you have when you encounter a disaster in your organization. Now many of you would answer that in this scenario you would have another standby machine or alternative which you will plug in. Now let me ask second question – What would you do if you as an individual faces disaster?  In this episode of the Notes from the Field series database expert Mike Walsh explains a very crucial issue we face in our career, which is not technical but more to relate to human nature. Read on this may be the best blog post you might read in recent times. Howdy! When it was my turn to share the Notes from the Field last time, I took a departure from my normal technical content to talk about Attitude and Communication.(http://blog.sqlauthority.com/2014/05/08/developers-life-attitude-and-communication-they-can-cause-problems-notes-from-the-field-027/) Pinal said it was a popular topic so I hope he won’t mind if I stick with Professional Development for another of my turns at sharing some information here. Like I said last time, the “soft skills” of the IT world are often just as important – sometimes more important – than the technical skills. As a consultant with Linchpin People – I see so many situations where the professional skills I’ve gained and use are more valuable to clients than knowing the best way to tune a query. Today I want to continue talking about professional development and tell you about the way I almost got myself hit by a train – and why that matters in our day jobs. Sometimes we can learn a lot from disasters. Whether we caused them or someone else did. If you are interested in learning about some of my observations in these lessons you can see more where I talk about lessons from disasters on my blog. For now, though, onto how I almost got my vehicle hit by a train… The Train Crash That Almost Was…. My family and I own a little schoolhouse building about a 10 mile drive away from our house. We use it as a free resource for families in the area that homeschool their children – so they can have some class space. I go up there a lot to check in on the property, to take care of the trash and to do work on the property. On the way there, there is a very small Stop Sign controlled railroad intersection. There is only two small freight trains a day passing there. Actually the same train, making a journey south and then back North. That’s it. This road is a small rural road, barely ever a second car driving in the neighborhood there when I am. The stop sign is pretty much there only for the train crossing. When we first bought the building, I was up there a lot doing renovations on the property. Being familiar with the area, I am also familiar with the train schedule and know the tracks are normally free of trains. So I developed a bad habit. You see, I’d approach the stop sign and slow down as I roll through it. Sometimes I’d do a quick look and come to an “almost” stop there but keep on going. I let my impatience and complacency take over. And that is because most of the time I was going there long after the train was done for the day or in between the runs. This habit became pretty well established after a couple years of driving the route. The behavior reinforced a bit by the success ratio. I saw others doing it as well from the neighborhood when I would happen to be there around the time another car was there. Well. You already know where this ends up by the title and backstory here. A few months ago I came to that little crossing, and I started to do the normal routine. I’d pretty much stopped looking in some respects because of the pattern I’d gotten into.  For some reason I looked and heard and saw the train slowly approaching and slammed on my brakes and stopped. It was an abrupt stop, and it was close. I probably would have made it okay, but I sat there thinking about lessons for IT professionals from the situation once I started breathing again and watched the cars loaded with sand and propane slowly labored down the tracks… Here are Those Lessons… It’s easy to get stuck into a routine – That isn’t always bad. Except when it’s a bad routine. Momentum and inertia are powerful. Once you have a habit and a routine developed – it’s really hard to break that. Make sure you are setting the right routines and habits TODAY. What almost dangerous things are you doing today? How are you almost messing up your production environment today? Stop doing that. Be Deliberate – (Even when you are the only one) – Like I said – a lot of people roll through that stop sign. Perhaps the neighbors or other drivers think “why is he fully stopping and looking… The train only comes two times a day!” – they can think that all they want. Through deliberate actions and forcing myself to pay attention, I will avoid that oops again. Slow down. Take a deep breath. Be Deliberate in your job. Pay attention to the small stuff and go out of your way to be careful. It will save you later. Be Observant – Keep your eyes open. By looking around, observing the situation and understanding what your servers, databases, users and vendors are doing – you’ll notice when something is out of place. But if you don’t know what is normal, if you don’t look to make sure nothing has changed – that train will come and get you. Where can you be more observant? What warning signs are you ignoring in your environment today? In the IT world – trains are everywhere. Projects move fast. Decisions happen fast. Problems turn from a warning sign to a disaster quickly. If you get stuck in a complacent pattern of “Everything is okay, it always has been and always will be” – that’s the time that you will most likely get stuck in a bad situation. Don’t let yourself get complacent, don’t let your team get complacent. That will lead to being proactive. And a proactive environment spends less money on consultants for troubleshooting problems you should have seen ahead of time. You can spend your money and IT budget on improving for your customers. If you want to get started with performance analytics and triage of virtualized SQL Servers 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 Server, SQL Tips and Tricks, T SQL

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  • SQL SERVER – Guest Post – Architecting Data Warehouse – Niraj Bhatt

    - by pinaldave
    Niraj Bhatt works as an Enterprise Architect for a Fortune 500 company and has an innate passion for building / studying software systems. He is a top rated speaker at various technical forums including Tech·Ed, MCT Summit, Developer Summit, and Virtual Tech Days, among others. Having run a successful startup for four years Niraj enjoys working on – IT innovations that can impact an enterprise bottom line, streamlining IT budgets through IT consolidation, architecture and integration of systems, performance tuning, and review of enterprise applications. He has received Microsoft MVP award for ASP.NET, Connected Systems and most recently on Windows Azure. When he is away from his laptop, you will find him taking deep dives in automobiles, pottery, rafting, photography, cooking and financial statements though not necessarily in that order. He is also a manager/speaker at BDOTNET, Asia’s largest .NET user group. Here is the guest post by Niraj Bhatt. As data in your applications grows it’s the database that usually becomes a bottleneck. It’s hard to scale a relational DB and the preferred approach for large scale applications is to create separate databases for writes and reads. These databases are referred as transactional database and reporting database. Though there are tools / techniques which can allow you to create snapshot of your transactional database for reporting purpose, sometimes they don’t quite fit the reporting requirements of an enterprise. These requirements typically are data analytics, effective schema (for an Information worker to self-service herself), historical data, better performance (flat data, no joins) etc. This is where a need for data warehouse or an OLAP system arises. A Key point to remember is a data warehouse is mostly a relational database. It’s built on top of same concepts like Tables, Rows, Columns, Primary keys, Foreign Keys, etc. Before we talk about how data warehouses are typically structured let’s understand key components that can create a data flow between OLTP systems and OLAP systems. There are 3 major areas to it: a) OLTP system should be capable of tracking its changes as all these changes should go back to data warehouse for historical recording. For e.g. if an OLTP transaction moves a customer from silver to gold category, OLTP system needs to ensure that this change is tracked and send to data warehouse for reporting purpose. A report in context could be how many customers divided by geographies moved from sliver to gold category. In data warehouse terminology this process is called Change Data Capture. There are quite a few systems that leverage database triggers to move these changes to corresponding tracking tables. There are also out of box features provided by some databases e.g. SQL Server 2008 offers Change Data Capture and Change Tracking for addressing such requirements. b) After we make the OLTP system capable of tracking its changes we need to provision a batch process that can run periodically and takes these changes from OLTP system and dump them into data warehouse. There are many tools out there that can help you fill this gap – SQL Server Integration Services happens to be one of them. c) So we have an OLTP system that knows how to track its changes, we have jobs that run periodically to move these changes to warehouse. The question though remains is how warehouse will record these changes? This structural change in data warehouse arena is often covered under something called Slowly Changing Dimension (SCD). While we will talk about dimensions in a while, SCD can be applied to pure relational tables too. SCD enables a database structure to capture historical data. This would create multiple records for a given entity in relational database and data warehouses prefer having their own primary key, often known as surrogate key. As I mentioned a data warehouse is just a relational database but industry often attributes a specific schema style to data warehouses. These styles are Star Schema or Snowflake Schema. The motivation behind these styles is to create a flat database structure (as opposed to normalized one), which is easy to understand / use, easy to query and easy to slice / dice. Star schema is a database structure made up of dimensions and facts. Facts are generally the numbers (sales, quantity, etc.) that you want to slice and dice. Fact tables have these numbers and have references (foreign keys) to set of tables that provide context around those facts. E.g. if you have recorded 10,000 USD as sales that number would go in a sales fact table and could have foreign keys attached to it that refers to the sales agent responsible for sale and to time table which contains the dates between which that sale was made. These agent and time tables are called dimensions which provide context to the numbers stored in fact tables. This schema structure of fact being at center surrounded by dimensions is called Star schema. A similar structure with difference of dimension tables being normalized is called a Snowflake schema. This relational structure of facts and dimensions serves as an input for another analysis structure called Cube. Though physically Cube is a special structure supported by commercial databases like SQL Server Analysis Services, logically it’s a multidimensional structure where dimensions define the sides of cube and facts define the content. Facts are often called as Measures inside a cube. Dimensions often tend to form a hierarchy. E.g. Product may be broken into categories and categories in turn to individual items. Category and Items are often referred as Levels and their constituents as Members with their overall structure called as Hierarchy. Measures are rolled up as per dimensional hierarchy. These rolled up measures are called Aggregates. Now this may seem like an overwhelming vocabulary to deal with but don’t worry it will sink in as you start working with Cubes and others. Let’s see few other terms that we would run into while talking about data warehouses. ODS or an Operational Data Store is a frequently misused term. There would be few users in your organization that want to report on most current data and can’t afford to miss a single transaction for their report. Then there is another set of users that typically don’t care how current the data is. Mostly senior level executives who are interesting in trending, mining, forecasting, strategizing, etc. don’t care for that one specific transaction. This is where an ODS can come in handy. ODS can use the same star schema and the OLAP cubes we saw earlier. The only difference is that the data inside an ODS would be short lived, i.e. for few months and ODS would sync with OLTP system every few minutes. Data warehouse can periodically sync with ODS either daily or weekly depending on business drivers. Data marts are another frequently talked about topic in data warehousing. They are subject-specific data warehouse. Data warehouses that try to span over an enterprise are normally too big to scope, build, manage, track, etc. Hence they are often scaled down to something called Data mart that supports a specific segment of business like sales, marketing, or support. Data marts too, are often designed using star schema model discussed earlier. Industry is divided when it comes to use of data marts. Some experts prefer having data marts along with a central data warehouse. Data warehouse here acts as information staging and distribution hub with spokes being data marts connected via data feeds serving summarized data. Others eliminate the need for a centralized data warehouse citing that most users want to report on detailed data. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Best Practices, Business Intelligence, Data Warehousing, Database, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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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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  • SQL SERVER – A Quick Look at Logging and Ideas around Logging

    - by pinaldave
    This blog post is written in response to the T-SQL Tuesday post on Logging. When someone talks about logging, personally I get lots of ideas about it. I have seen logging as a very generic term. Let me ask you this question first before I continue writing about logging. What is the first thing comes to your mind when you hear word “Logging”? Now ask the same question to the guy standing next to you. I am pretty confident that you will get  a different answer from different people. I decided to do this activity and asked 5 SQL Server person the same question. Question: What is the first thing comes to your mind when you hear the word “Logging”? Strange enough I got a different answer every single time. Let me just list what answer I got from my friends. Let us go over them one by one. Output Clause The very first person replied output clause. Pretty interesting answer to start with. I see what exactly he was thinking. SQL Server 2005 has introduced a new OUTPUT clause. OUTPUT clause has access to inserted and deleted tables (virtual tables) just like triggers. OUTPUT clause can be used to return values to client clause. OUTPUT clause can be used with INSERT, UPDATE, or DELETE to identify the actual rows affected by these statements. Here are some references for Output Clause: OUTPUT Clause Example and Explanation with INSERT, UPDATE, DELETE Reasons for Using Output Clause – Quiz Tips from the SQL Joes 2 Pros Development Series – Output Clause in Simple Examples Error Logs I was expecting someone to mention Error logs when it is about logging. The error log is the most looked place when there is any error either with the application or there is an error with the operating system. I have kept the policy to check my server’s error log every day. The reason is simple – enough time in my career I have figured out that when I am looking at error logs I find something which I was not expecting. There are cases, when I noticed errors in the error log and I fixed them before end user notices it. Other common practices I always tell my DBA friends to do is that when any error happens they should find relevant entries in the error logs and document the same. It is quite possible that they will see the same error in the error log  and able to fix the error based on the knowledge base which they have created. There can be many different kinds of error log files exists in SQL Server as well – 1) SQL Server Error Logs 2) Windows Event Log 3) SQL Server Agent Log 4) SQL Server Profile Log 5) SQL Server Setup Log etc. Here are some references for Error Logs: Recycle Error Log – Create New Log file without Server Restart SQL Error Messages Change Data Capture I got surprised with this answer. I think more than the answer I was surprised by the person who had answered me this one. I always thought he was expert in HTML, JavaScript but I guess, one should never assume about others. Indeed one of the cool logging feature is Change Data Capture. Change Data Capture records INSERTs, UPDATEs, and DELETEs applied to SQL Server tables, and makes a record available of what changed, where, and when, in simple relational ‘change tables’ rather than in an esoteric chopped salad of XML. These change tables contain columns that reflect the column structure of the source table you have chosen to track, along with the metadata needed to understand the changes that have been made. Here are some references for Change Data Capture: Introduction to Change Data Capture (CDC) in SQL Server 2008 Tuning the Performance of Change Data Capture in SQL Server 2008 Download Script of Change Data Capture (CDC) CDC and TRUNCATE – Cannot truncate table because it is published for replication or enabled for Change Data Capture Dynamic Management View (DMV) I like this answer. If asked I would have not come up with DMV right away but in the spirit of the original question, I think DMV does log the data. DMV logs or stores or records the various data and activity on the SQL Server. Dynamic management views return server state information that can be used to monitor the health of a server instance, diagnose problems, and tune performance. One can get plethero of information from DMVs – High Availability Status, Query Executions Details, SQL Server Resources Status etc. Here are some references for Dynamic Management View (DMV): SQL SERVER – Denali – DMV Enhancement – sys.dm_exec_query_stats – New Columns DMV – sys.dm_os_windows_info – Information about Operating System DMV – sys.dm_os_wait_stats Explanation – Wait Type – Day 3 of 28 DMV sys.dm_exec_describe_first_result_set_for_object – Describes the First Result Metadata for the Module Transaction Log Impact Detection Using DMV – dm_tran_database_transactions Log Files I almost flipped with this final answer from my friend. This should be probably the first answer. Yes, indeed log file logs the SQL Server activities. One can write infinite things about log file. SQL Server uses log file with the extension .ldf to manage transactions and maintain database integrity. Log file ensures that valid data is written out to database and system is in a consistent state. Log files are extremely useful in case of the database failures as with the help of full backup file database can be brought in the desired state (point in time recovery is also possible). SQL Server database has three recovery models – 1) Simple, 2) Full and 3) Bulk Logged. Each of the model uses the .ldf file for performing various activities. It is very important to take the backup of the log files (along with full backup) as one never knows when backup of the log file come into the action and save the day! How to Stop Growing Log File Too Big Reduce the Virtual Log Files (VLFs) from LDF file Log File Growing for Model Database – model Database Log File Grew Too Big master Database Log File Grew Too Big SHRINKFILE and TRUNCATE Log File in SQL Server 2008 Can I just say I loved this month’s T-SQL Tuesday Question. It really provoked very interesting conversation around me. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Optimization, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – SSMS: Disk Usage Report

    - by Pinal Dave
    Let us start with humor!  I think we the series on various reports, we come to a logical point. We covered all the reports at server level. This means the reports we saw were targeted towards activities that are related to instance level operations. These are mostly like how a doctor diagnoses a patient. At this point I am reminded of a dialog which I read somewhere: Patient: Doc, It hurts when I touch my head. Doc: Ok, go on. What else have you experienced? Patient: It hurts even when I touch my eye, it hurts when I touch my arms, it even hurts when I touch my feet, etc. Doc: Hmmm … Patient: I feel it hurts when I touch anywhere in my body. Doc: Ahh … now I get it. You need a plaster to your finger John. Sometimes the server level gives an indicator to what is happening in the system, but we need to get to the root cause for a specific database. So, this is the first blog in series where we would start discussing about database level reports. To launch database level reports, expand selected server in Object Explorer, expand the Databases folder, and then right-click any database for which we want to look at reports. From the menu, select Reports, then Standard Reports, and then any of database level reports. In this blog, we would talk about four “disk” reports because they are similar: Disk Usage Disk Usage by Top Tables Disk Usage by Table Disk Usage by Partition Disk Usage This report shows multiple information about the database. Let us discuss them one by one.  We have divided the output into 5 different sections. Section 1 shows the high level summary of the database. It shows the space used by database files (mdf and ldf). Under the hood, the report uses, various DMVs and DBCC Commands, it is using sys.data_spaces and DBCC SHOWFILESTATS. Section 2 and 3 are pie charts. One for data file allocation and another for the transaction log file. Pie chart for “Data Files Space Usage (%)” shows space consumed data, indexes, allocated to the SQL Server database, and unallocated space which is allocated to the SQL Server database but not yet filled with anything. “Transaction Log Space Usage (%)” used DBCC SQLPERF (LOGSPACE) and shows how much empty space we have in the physical transaction log file. Section 4 shows the data from Default Trace and looks at Event IDs 92, 93, 94, 95 which are for “Data File Auto Grow”, “Log File Auto Grow”, “Data File Auto Shrink” and “Log File Auto Shrink” respectively. Here is an expanded view for that section. If default trace is not enabled, then this section would be replaced by the message “Trace Log is disabled” as highlighted below. Section 5 of the report uses DBCC SHOWFILESTATS to get information. Here is the enhanced version of that section. This shows the physical layout of the file. In case you have In-Memory Objects in the database (from SQL Server 2014), then report would show information about those as well. Here is the screenshot taken for a different database, which has In-Memory table. I have highlighted new things which are only shown for in-memory database. The new sections which are highlighted above are using sys.dm_db_xtp_checkpoint_files, sys.database_files and sys.data_spaces. The new type for in-memory OLTP is ‘FX’ in sys.data_space. The next set of reports is targeted to get information about a table and its storage. These reports can answer questions like: Which is the biggest table in the database? How many rows we have in table? Is there any table which has a lot of reserved space but its unused? Which partition of the table is having more data? Disk Usage by Top Tables This report provides detailed data on the utilization of disk space by top 1000 tables within the Database. The report does not provide data for memory optimized tables. Disk Usage by Table This report is same as earlier report with few difference. First Report shows only 1000 rows First Report does order by values in DMV sys.dm_db_partition_stats whereas second one does it based on name of the table. Both of the reports have interactive sort facility. We can click on any column header and change the sorting order of data. Disk Usage by Partition This report shows the distribution of the data in table based on partition in the table. This is so similar to previous output with the partition details now. Here is the query taken from profiler. SELECT row_number() OVER (ORDER BY a1.used_page_count DESC, a1.index_id) AS row_number ,      (dense_rank() OVER (ORDER BY a5.name, a2.name))%2 AS l1 ,      a1.OBJECT_ID ,      a5.name AS [schema] ,       a2.name ,       a1.index_id ,       a3.name AS index_name ,       a3.type_desc ,       a1.partition_number ,       a1.used_page_count * 8 AS total_used_pages ,       a1.reserved_page_count * 8 AS total_reserved_pages ,       a1.row_count FROM sys.dm_db_partition_stats a1 INNER JOIN sys.all_objects a2  ON ( a1.OBJECT_ID = a2.OBJECT_ID) AND a1.OBJECT_ID NOT IN (SELECT OBJECT_ID FROM sys.tables WHERE is_memory_optimized = 1) INNER JOIN sys.schemas a5 ON (a5.schema_id = a2.schema_id) LEFT OUTER JOIN  sys.indexes a3  ON ( (a1.OBJECT_ID = a3.OBJECT_ID) AND (a1.index_id = a3.index_id) ) WHERE (SELECT MAX(DISTINCT partition_number) FROM sys.dm_db_partition_stats a4 WHERE (a4.OBJECT_ID = a1.OBJECT_ID)) >= 1 AND a2.TYPE <> N'S' AND  a2.TYPE <> N'IT' ORDER BY a5.name ASC, a2.name ASC, a1.index_id, a1.used_page_count DESC, a1.partition_number Using all of the above reports, you should be able to get the usage of database files and also space used by tables. I think this is too much disk information for a single blog and I hope you have used them in the past to get data. Do let me know if you found anything interesting using these reports in your environments. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • SQL SERVER – Core Concepts – Elasticity, Scalability and ACID Properties – Exploring NuoDB an Elastically Scalable Database System

    - by pinaldave
    I have been recently exploring Elasticity and Scalability attributes of databases. You can see that in my earlier blog posts about NuoDB where I wanted to look at Elasticity and Scalability concepts. The concepts are very interesting, and intriguing as well. I have discussed these concepts with my friend Joyti M and together we have come up with this interesting read. The goal of this article is to answer following simple questions What is Elasticity? What is Scalability? How ACID properties vary from NOSQL Concepts? What are the prevailing problems in the current database system architectures? Why is NuoDB  an innovative and welcome change in database paradigm? Elasticity This word’s original form is used in many different ways and honestly it does do a decent job in holding things together over the years as a person grows and contracts. Within the tech world, and specifically related to software systems (database, application servers), it has come to mean a few things - allow stretching of resources without reaching the breaking point (on demand). What are resources in this context? Resources are the usual suspects – RAM/CPU/IO/Bandwidth in the form of a container (a process or bunch of processes combined as modules). When it is about increasing resources the simplest idea which comes to mind is the addition of another container. Another container means adding a brand new physical node. When it is about adding a new node there are two questions which comes to mind. 1) Can we add another node to our software system? 2) If yes, does adding new node cause downtime for the system? Let us assume we have added new node, let us see what the new needs of the system are when a new node is added. Balancing incoming requests to multiple nodes Synchronization of a shared state across multiple nodes Identification of “downstate” and resolution action to bring it to “upstate” Well, adding a new node has its advantages as well. Here are few of the positive points Throughput can increase nearly horizontally across the node throughout the system Response times of application will increase as in-between layer interactions will be improved Now, Let us put the above concepts in the perspective of a Database. When we mention the term “running out of resources” or “application is bound to resources” the resources can be CPU, Memory or Bandwidth. The regular approach to “gain scalability” in the database is to look around for bottlenecks and increase the bottlenecked resource. When we have memory as a bottleneck we look at the data buffers, locks, query plans or indexes. After a point even this is not enough as there needs to be an efficient way of managing such large workload on a “single machine” across memory and CPU bound (right kind of scheduling)  workload. We next move on to either read/write separation of the workload or functionality-based sharing so that we still have control of the individual. But this requires lots of planning and change in client systems in terms of knowing where to go/update/read and for reporting applications to “aggregate the data” in an intelligent way. What we ideally need is an intelligent layer which allows us to do these things without us getting into managing, monitoring and distributing the workload. Scalability In the context of database/applications, scalability means three main things Ability to handle normal loads without pressure E.g. X users at the Y utilization of resources (CPU, Memory, Bandwidth) on the Z kind of hardware (4 processor, 32 GB machine with 15000 RPM SATA drives and 1 GHz Network switch) with T throughput Ability to scale up to expected peak load which is greater than normal load with acceptable response times Ability to provide acceptable response times across the system E.g. Response time in S milliseconds (or agreed upon unit of measure) – 90% of the time The Issue – Need of Scale In normal cases one can plan for the load testing to test out normal, peak, and stress scenarios to ensure specific hardware meets the needs. With help from Hardware and Software partners and best practices, bottlenecks can be identified and requisite resources added to the system. Unfortunately this vertical scale is expensive and difficult to achieve and most of the operational people need the ability to scale horizontally. This helps in getting better throughput as there are physical limits in terms of adding resources (Memory, CPU, Bandwidth and Storage) indefinitely. Today we have different options to achieve scalability: Read & Write Separation The idea here is to do actual writes to one store and configure slaves receiving the latest data with acceptable delays. Slaves can be used for balancing out reads. We can also explore functional separation or sharing as well. We can separate data operations by a specific identifier (e.g. region, year, month) and consolidate it for reporting purposes. For functional separation the major disadvantage is when schema changes or workload pattern changes. As the requirement grows one still needs to deal with scale need in manual ways by providing an abstraction in the middle tier code. Using NOSQL solutions The idea is to flatten out the structures in general to keep all values which are retrieved together at the same store and provide flexible schema. The issue with the stores is that they are compromising on mostly consistency (no ACID guarantees) and one has to use NON-SQL dialect to work with the store. The other major issue is about education with NOSQL solutions. Would one really want to make these compromises on the ability to connect and retrieve in simple SQL manner and learn other skill sets? Or for that matter give up on ACID guarantee and start dealing with consistency issues? Hybrid Deployment – Mac, Linux, Cloud, and Windows One of the challenges today that we see across On-premise vs Cloud infrastructure is a difference in abilities. Take for example SQL Azure – it is wonderful in its concepts of throttling (as it is shared deployment) of resources and ability to scale using federation. However, the same abilities are not available on premise. This is not a mistake, mind you – but a compromise of the sweet spot of workloads, customer requirements and operational SLAs which can be supported by the team. In today’s world it is imperative that databases are available across operating systems – which are a commodity and used by developers of all hues. An Ideal Database Ability List A system which allows a linear scale of the system (increase in throughput with reasonable response time) with the addition of resources A system which does not compromise on the ACID guarantees and require developers to learn new paradigms A system which does not force fit a new way interacting with database by learning Non-SQL dialect A system which does not force fit its mechanisms for providing availability across its various modules. Well NuoDB is the first database which has all of the above abilities and much more. In future articles I will cover my hands-on experience with it. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology Tagged: NuoDB

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  • SQL SERVER – Weekly Series – Memory Lane – #032

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Complete Series of Database Coding Standards and Guidelines SQL SERVER Database Coding Standards and Guidelines – Introduction SQL SERVER – Database Coding Standards and Guidelines – Part 1 SQL SERVER – Database Coding Standards and Guidelines – Part 2 SQL SERVER Database Coding Standards and Guidelines Complete List Download Explanation and Example – SELF JOIN When all of the data you require is contained within a single table, but data needed to extract is related to each other in the table itself. Examples of this type of data relate to Employee information, where the table may have both an Employee’s ID number for each record and also a field that displays the ID number of an Employee’s supervisor or manager. To retrieve the data tables are required to relate/join to itself. Insert Multiple Records Using One Insert Statement – Use of UNION ALL This is very interesting question I have received from new developer. How can I insert multiple values in table using only one insert? Now this is interesting question. When there are multiple records are to be inserted in the table following is the common way using T-SQL. Function to Display Current Week Date and Day – Weekly Calendar Straight blog post with script to find current week date and day based on the parameters passed in the function.  2008 In my beginning years, I have almost same confusion as many of the developer had in their earlier years. Here are two of the interesting question which I have attempted to answer in my early year. Even if you are experienced developer may be you will still like to read following two questions: Order Of Column In Index Order of Conditions in WHERE Clauses Example of DISTINCT in Aggregate Functions Have you ever used DISTINCT with the Aggregation Function? Here is a simple example about how users can do it. Create a Comma Delimited List Using SELECT Clause From Table Column Straight to script example where I explained how to do something easy and quickly. Compound Assignment Operators SQL SERVER 2008 has introduced new concept of Compound Assignment Operators. Compound Assignment Operators are available in many other programming languages for quite some time. Compound Assignment Operators is operator where variables are operated upon and assigned on the same line. PIVOT and UNPIVOT Table Examples Here is a very interesting question – the answer to the question can be YES or NO both. “If we PIVOT any table and UNPIVOT that table do we get our original table?” Read the blog post to get the explanation of the question above. 2009 What is Interim Table – Simple Definition of Interim Table The interim table is a table that is generated by joining two tables and not the final result table. In other words, when two tables are joined they create an interim table as resultset but the resultset is not final yet. It may be possible that more tables are about to join on the interim table, and more operations are still to be applied on that table (e.g. Order By, Having etc). Besides, it may be possible that there is no interim table; sometimes final table is what is generated when the query is run. 2010 Stored Procedure and Transactions If Stored Procedure is transactional then, it should roll back complete transactions when it encounters any errors. Well, that does not happen in this case, which proves that Stored Procedure does not only provide just the transactional feature to a batch of T-SQL. Generate Database Script for SQL Azure When talking about SQL Azure the most common complaint I hear is that the script generated from stand-along SQL Server database is not compatible with SQL Azure. This was true for some time for sure but not any more. If you have SQL Server 2008 R2 installed you can follow the guideline below to generate a script which is compatible with SQL Azure. Convert IN to EXISTS – Performance Talk It is NOT necessary that every time when IN is replaced by EXISTS it gives better performance. However, in our case listed above it does for sure give better performance. You can read about this subject in the associated blog post. Subquery or Join – Various Options – SQL Server Engine Knows the Best Every single time whenever there is a performance tuning exercise, I hear the conversation from developer where some prefer subquery and some prefer join. In this two part blog post, I explain the same in the detail with examples. Part 1 | Part 2 Merge Operations – Insert, Update, Delete in Single Execution MERGE is a new feature that provides an efficient way to do multiple DML operations. In earlier versions of SQL Server, we had to write separate statements to INSERT, UPDATE, or DELETE data based on certain conditions; however, at present, by using the MERGE statement, we can include the logic of such data changes in one statement that even checks when the data is matched and then just update it, and similarly, when the data is unmatched, it is inserted. 2011 Puzzle – Statistics are not updated but are Created Once Here is the quick scenario about my setup. Create Table Insert 1000 Records Check the Statistics Now insert 10 times more 10,000 indexes Check the Statistics – it will be NOT updated – WHY? Question to You – When to use Function and When to use Stored Procedure Personally, I believe that they are both different things - they cannot be compared. I can say, it will be like comparing apples and oranges. Each has its own unique use. However, they can be used interchangeably at many times and in real life (i.e., production environment). I have personally seen both of these being used interchangeably many times. This is the precise reason for asking this question. 2012 In year 2012 I had two interesting series ran on the blog. If there is no fun in learning, the learning becomes a burden. For the same reason, I had decided to build a three part quiz around SEQUENCE. The quiz was to identify the next value of the sequence. I encourage all of you to take part in this fun quiz. Guess the Next Value – Puzzle 1 Guess the Next Value – Puzzle 2 Guess the Next Value – Puzzle 3 Guess the Next Value – Puzzle 4 Simple Example to Configure Resource Governor – Introduction to Resource Governor Resource Governor is a feature which can manage SQL Server Workload and System Resource Consumption. We can limit the amount of CPU and memory consumption by limiting /governing /throttling on the SQL Server. If there are different workloads running on SQL Server and each of the workload needs different resources or when workloads are competing for resources with each other and affecting the performance of the whole server resource governor is a very important task. Tricks to Replace SELECT * with Column Names – SQL in Sixty Seconds #017 – Video  Retrieves unnecessary columns and increases network traffic When a new columns are added views needs to be refreshed manually Leads to usage of sub-optimal execution plan Uses clustered index in most of the cases instead of using optimal index It is difficult to debug SQL SERVER – Load Generator – Free Tool From CodePlex The best part of this SQL Server Load Generator is that users can run multiple simultaneous queries again SQL Server using different login account and different application name. The interface of the tool is extremely easy to use and very intuitive as well. A Puzzle – Swap Value of Column Without Case Statement Let us assume there is a single column in the table called Gender. The challenge is to write a single update statement which will flip or swap the value in the column. For example if the value in the gender column is ‘male’ swap it with ‘female’ and if the value is ‘female’ swap it with ‘male’. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – Weekly Series – Memory Lane – #031

    - by Pinal Dave
    Here is the list of selected articles of SQLAuthority.com across all these years. Instead of just listing all the articles I have selected a few of my most favorite articles and have listed them here with additional notes below it. Let me know which one of the following is your favorite article from memory lane. 2007 Find Table without Clustered Index – Find Table with no Primary Key Clustered index is very important concept for any table. They impact the performance very heavily. Here is a quick script to find tables without a clustered index. Replace TEXT with VARCHAR(MAX) – Stop using TEXT, NTEXT, IMAGE Data Types Question: “Is VARCHAR (MAX) big enough to store the TEXT field?” Answer: “Yes, VARCHAR(MAX) is big enough to accommodate TEXT field. TEXT, NTEXT and IMAGE data types of SQL Server 2000 will be deprecated in a future version of SQL Server, SQL Server 2005 provides backward compatibility to data types but it is recommended to use new data types which are VARHCAR (MAX), NVARCHAR (MAX) and VARBINARY (MAX).” Limiting Result Sets by Using TABLESAMPLE – Examples Introduced in SQL Server 2005, TABLESAMPLE allows you to extract a sampling of rows from a table in the FROM clause. The rows retrieved are random and they are are not in any order. This sampling can be based on a percentage of number of rows. You can use TABLESAMPLE when only a sampling of rows is necessary for the application instead of a full result set. User Defined Functions (UDF) Limitations UDF have its own advantage and usage but in this article we will see the limitation of UDF. Things UDF can not do and why Stored Procedure are considered as more flexible then UDFs. Stored Procedure are more flexibility then User Defined Functions(UDF). However, this blog post is a good read to know what are the limitations of UDF. Change Database Compatible Level – Backward Compatibility For a long time SQL Server stayed on the compatibility level of 80 which is of SQL Server 2000. However, as soon as SQL Server 2005 introduced the issue of compatibility was quite a major issue. Since that time MS has been releasing the versions at every 2-3 years, changing compatibility is a ever popular topic. In this blog post, we learn how we can do the same using T-SQL. We can also do the same using SSMS and here is the blog post for the same: Change Database Compatible Level – Backward Compatibility – Part 2 – Management Studio. Constraint on VARCHAR(MAX) Field To Limit It Certain Length How can I limit the VARCHAR(MAX) field with maximum length of 12500 characters only. His Question was valid as our application was allowed 12500 characters. First of all – this requirement is bit strange but if someone wants to do the same, they can do it as described in this blog post. 2008 UNPIVOT Table Example Understanding UNPIVOT can be very complicated at times. In this blog post, I have attempted to explain the same concept in very simple words. Create Default Constraint Over Table Column A simple straight to script blog post – I still use this blog quite many times for my own reference. UDF – Get the Day of the Week Function It took me 4 iteration to find this very simple function which can immediately get the day of the week in a single line. 2009 Find Hostname and Current Logged In User Name There are two tricks listed in this blog post where users can find out the hostname and current logged user name immediately and very easily. Interesting Observation of Logon Trigger On All Servers When I was doing a project, I made an interesting observation of executing a logon trigger multiple times. It was absolutely unexpected for me! As I was logging only once, naturally, I was expecting the entry only once. However, it did it multiple times on different threads – indeed an eccentric phenomenon at first sight! Difference Between Candidate Keys and Primary Key One needs to be very careful in selecting the Primary Key as an incorrect selection can adversely impact the database architect and future normalization. For a Candidate Key to qualify as a Primary Key, it should be Non-NULL and unique in any domain. I have observed quite often that Primary Keys are seldom changed. I would like to have your feedback on not changing a Primary Key. Create Multiple Filegroup For Single Database Why should one create multiple file group for any database and what are the advantages of the same. In this blog post, I explain the same in detail. List All Objects Created on All Filegroups in Database In this blog post we discuss the essential question – “How can I find which object belongs to which filegroup. Is there any way to know this?” 2010 DATE and TIME in SQL Server 2008 When DATE is converted to DATETIME it adds the of midnight. When TIME is converted to DATETIME it adds the date of 1900 and it is something one wants to consider if you are going to run scripts from SQL Server 2008 to earlier version with CONVERT. Disabled Index and Update Statistics If you do not need a nonclustered index, I suggest you to drop it as keeping them disabled is an overhead on your system. This is because every time the statistics are updated for system all the statistics for disabled indexes are also updated. Precision of SMALLDATETIME – A 1 Minute Precision The precision of the datatype SMALLDATETIME is 1 minute. It discards the seconds by rounding up or rounding down any seconds greater than zero. 2011 Getting Columns Headers without Result Data – SET FMTONLY ON SET FMTONLY ON returns only metadata to the client. It can be used to test the format of the response without actually running the query. When this setting is ON the resultset only have headers of the results but no data. Copy Database from Instance to Another Instance – Copy Paste in SQL Server SQL Server has a feature which copy database from one database to another database and it can be automated as well using SSIS. Make sure you have SQL Server Agent Turned on as this feature will create a job. Puzzle – SELECT * vs SELECT COUNT(*) If you have ever wondered SELECT * gives error when executed alone but SELECT COUNT(*) does not. Why? in that case, you should read this blog post. Creating All New Database with Full Recovery Model This blog post is very based on very interesting story where the user wants to do something by default for every single new database created. Model database is a secret weapon which should be used very carefully and with proper evalution. If used carefully this can be a very much beneficiary when we need a newly created database behave in certain fashion. 2012 In year 2012 I had two interesting series ran on the blog. If there is no fun in learning, the learning becomes a burden. For the same reason, I had decided to build a three part quiz around SEQUENCE. The quiz was to identify the next value of the sequence. I encourage all of you to take part in this fun quiz. Guess the Next Value – Puzzle 1 Guess the Next Value – Puzzle 2 Guess the Next Value – Puzzle 3 Can anyone remember their final day of schooling?  This is probably a silly question because – of course you can!  Many people mark this as the most exciting, happiest day of their life.  It marks the end of testing, the end of following rules set by teachers, and the beginning of finally being able to earn money and work in your chosen field. Read five part series on developer training subject Developer Training - Importance and Significance - Part 1 Developer Training – Employee Morals and Ethics – Part 2 Developer Training – Difficult Questions and Alternative Perspective - Part 3 Developer Training – Various Options for Developer Training – Part 4 Developer Training – A Conclusive Summary- Part 5 Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Memory Lane, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – 2011 – Wait Type – Day 25 of 28

    - by pinaldave
    Since the beginning of the series, I have been getting the following question again and again: “What are the changes in SQL Server 2011 – Denali with respect to Wait Types?” SQL Server 2011 – Denali is yet to be released, and making statements on the subject will be inappropriate. Denali CTP1 has been released so I suggest that all of you download the same and experiment on it. I quickly compared the wait stats of SQL Server 2008 R2 and Denali (CTP1) and found the following changes: Wait Types Exists in SQL Server 2008 R2 and Not Exists in SQL Server 2011 “Denali” SOS_RESERVEDMEMBLOCKLIST SOS_LOCALALLOCATORLIST QUERY_WAIT_ERRHDL_SERVICE QUERY_ERRHDL_SERVICE_DONE XE_PACKAGE_LOCK_BACKOFF Wait Types Exists in SQL Server 2011 and Not Exists in SQL Server 2008 SLEEP_MASTERMDREADY SOS_MEMORY_TOPLEVELBLOCKALLOCATOR SOS_PHYS_PAGE_CACHE FILESTREAM_WORKITEM_QUEUE FILESTREAM_FILE_OBJECT FILESTREAM_FCB FILESTREAM_CACHE XE_CALLBACK_LIST PWAIT_MD_RELATION_CACHE PWAIT_MD_SERVER_CACHE PWAIT_MD_LOGIN_STATS DISPATCHER_PRIORITY_QUEUE_SEMAPHORE FT_PROPERTYLIST_CACHE SECURITY_KEYRING_RWLOCK BROKER_TRANSMISSION_WORK BROKER_TRANSMISSION_OBJECT BROKER_TRANSMISSION_TABLE BROKER_DISPATCHER BROKER_FORWARDER UCS_MANAGER UCS_TRANSPORT UCS_MEMORY_NOTIFICATION UCS_ENDPOINT_CHANGE UCS_TRANSPORT_STREAM_CHANGE QUERY_TASK_ENQUEUE_MUTEX DBCC_SCALE_OUT_EXPR_CACHE PWAIT_ALL_COMPONENTS_INITIALIZED PREEMPTIVE_SP_SERVER_DIAGNOSTICS SP_SERVER_DIAGNOSTICS_SLEEP SP_SERVER_DIAGNOSTICS_INIT_MUTEX AM_INDBUILD_ALLOCATION QRY_PARALLEL_THREAD_MUTEX FT_MASTER_MERGE_COORDINATOR PWAIT_RESOURCE_SEMAPHORE_FT_PARALLEL_QUERY_SYNC REDO_THREAD_PENDING_WORK REDO_THREAD_SYNC COUNTRECOVERYMGR HADR_DB_COMMAND HADR_TRANSPORT_SESSION HADR_CLUSAPI_CALL PWAIT_HADR_CHANGE_NOTIFIER_TERMINATION_SYNC PWAIT_HADR_ACTION_COMPLETED PWAIT_HADR_OFFLINE_COMPLETED PWAIT_HADR_ONLINE_COMPLETED PWAIT_HADR_FORCEFAILOVER_COMPLETED PWAIT_HADR_WORKITEM_COMPLETED HADR_WORK_POOL HADR_WORK_QUEUE HADR_LOGCAPTURE_SYNC LOGPOOL_CACHESIZE LOGPOOL_FREEPOOLS LOGPOOL_REPLACEMENTSET LOGPOOL_CONSUMERSET LOGPOOL_MGRSET LOGPOOL_CONSUMER LOGPOOLREFCOUNTEDOBJECT_REFDONE HADR_SYNC_COMMIT HADR_AG_MUTEX PWAIT_SECURITY_CACHE_INVALIDATION PWAIT_HADR_SERVER_READY_CONNECTIONS HADR_FILESTREAM_MANAGER HADR_FILESTREAM_BLOCK_FLUSH HADR_FILESTREAM_IOMGR XDES_HISTORY XDES_SNAPSHOT HADR_FILESTREAM_IOMGR_IOCOMPLETION UCS_SESSION_REGISTRATION ENABLE_EMPTY_VERSIONING HADR_DB_OP_START_SYNC HADR_DB_OP_COMPLETION_SYNC HADR_LOGPROGRESS_SYNC HADR_TRANSPORT_DBRLIST HADR_FAILOVER_PARTNER XDESTSVERMGR GHOSTCLEANUPSYNCMGR HADR_AR_UNLOAD_COMPLETED HADR_PARTNER_SYNC HADR_DBSTATECHANGE_SYNC We already know that Wait Types and Wait Stats are going to be the next big thing in the next version of SQL Server. So now I am eagerly waiting to dig deeper in the wait stats. Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – Generate Report for Index Physical Statistics – SSMS

    - by pinaldave
    Few days ago, I wrote about SQL SERVER – Out of the Box – Activity and Performance Reports from SSSMS (Link). A user asked me a question regarding if we can use similar reports to get the detail about Indexes. Yes, it is possible to do the same. There are similar type of reports are available at Database level, just like those available at the Server Instance level. You can right click on Database name and click Reports. Under Standard Reports, you will find following reports. Disk Usage Disk Usage by Top Tables Disk Usage by Table Disk Usage by Partition Backup and Restore Events All Transactions All Blocking Transactions Top Transactions by Age Top Transactions by Blocked Transactions Count Top Transactions by Locks Count Resource Locking Statistics by Objects Object Execute Statistics Database Consistency history Index Usage Statistics Index Physical Statistics Schema Change history User Statistics Select the Reports with name Index Physical Statistics. Once click, a report containing all the index names along with other information related to index will be visible, e.g. Index Type and number of partitions. One column that caught my interest was Operation Recommended. In some place, it suggested that index needs to be rebuilt. It is also possible to click and expand the column of partitions and see additional details about index as well. DBA and Developers who just want to have idea about how your index is and its physical statistics can use this tool. Click to Enlarge Note: Please note that I will rebuild my indexes just because this report is recommending it. There are many other parameters you need to consider before rebuilding indexes. However, this tool gives you the accurate stats of your index and it can be right away exported to Excel or PDF writing by clicking on the report. Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Index, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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  • SQL SERVER – Concat Strings in SQL Server using T-SQL – SQL in Sixty Seconds #035 – Video

    - by pinaldave
    Concatenating  string is one of the most common tasks in SQL Server and every developer has to come across it. We have to concat the string when we have to see the display full name of the person by first name and last name. In this video we will see various methods to concatenate the strings. SQL Server 2012 has introduced new function CONCAT which concatenates the strings much efficiently. When we concat values with ‘+’ in SQL Server we have to make sure that values are in string format. However, when we attempt to concat integer we have to convert the integers to a string or else it will throw an error. However, with the newly introduce the function of CONCAT in SQL Server 2012 we do not have to worry about this kind of issue. It concatenates strings and integers without casting or converting them. You can specify various values as a parameter to CONCAT functions and it concatenates them together. Let us see how to concat the values in Sixty Seconds: Here is the script which is used in the video. -- Method 1: Concatenating two strings SELECT 'FirstName' + ' ' + 'LastName' AS FullName -- Method 2: Concatenating two Numbers SELECT CAST(1 AS VARCHAR(10)) + ' ' + CAST(2 AS VARCHAR(10)) -- Method 3: Concatenating values of table columns SELECT FirstName + ' ' + LastName AS FullName FROM AdventureWorks2012.Person.Person -- Method 4: SQL Server 2012 CONCAT function SELECT CONCAT('FirstName' , ' ' , 'LastName') AS FullName -- Method 5: SQL Server 2012 CONCAT function SELECT CONCAT('FirstName' , ' ' , 1) AS FullName Related Tips in SQL in Sixty Seconds: SQL SERVER – Concat Function in SQL Server – SQL Concatenation String Function – CONCAT() – A Quick Introduction 2012 Functions – FORMAT() and CONCAT() – An Interesting Usage A Quick Trick about SQL Server 2012 CONCAT Function – PRINT A Quick Trick about SQL Server 2012 CONCAT function What would you like to see in the next SQL in Sixty Seconds video? Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: Database, Pinal Dave, PostADay, SQL, SQL Authority, SQL in Sixty Seconds, SQL Query, SQL Scripts, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL, Technology, Video Tagged: Excel

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  • SQL SERVER – Shrinking NDF and MDF Files – Readers’ Opinion

    - by pinaldave
    Previously, I had written a blog post about SQL SERVER – Shrinking NDF and MDF Files – A Safe Operation. After that, I have written the following blog post that talks about the advantage and disadvantage of Shrinking and why one should not be Shrinking a file SQL SERVER – SHRINKFILE and TRUNCATE Log File in SQL Server 2008. On this subject, SQL Server Expert Imran Mohammed left an excellent comment. I just feel that his comment is worth a big article itself. For everybody to read his wonderful explanation, I am posting this blog post here. Thanks Imran! Shrinking Database always creates performance degradation and increases fragmentation in the database. I suggest that you keep that in mind before you start reading the following comment. If you are going to say Shrinking Database is bad and evil, here I am saying it first and loud. Now, the comment of Imran is written while keeping in mind only the process showing how the Shrinking Database Operation works. Imran has already explained his understanding and requests further explanation. I have removed the Best Practices section from Imran’s comments, as there are a few corrections. Comments from Imran - Before I explain to you the concept of Shrink Database, let us understand the concept of Database Files. When we create a new database inside the SQL Server, it is typical that SQl Server creates two physical files in the Operating System: one with .MDF Extension, and another with .LDF Extension. .MDF is called as Primary Data File. .LDF is called as Transactional Log file. If you add one or more data files to a database, the physical file that will be created in the Operating System will have an extension of .NDF, which is called as Secondary Data File; whereas, when you add one or more log files to a database, the physical file that will be created in the Operating System will have the same extension as .LDF. The questions now are, “Why does a new data file have a different extension (.NDF)?”, “Why is it called as a secondary data file?” and, “Why is .MDF file called as a primary data file?” Answers: Note: The following explanation is based on my limited knowledge of SQL Server, so experts please do comment. A data file with a .MDF extension is called a Primary Data File, and the reason behind it is that it contains Database Catalogs. Catalogs mean Meta Data. Meta Data is “Data about Data”. An example for Meta Data includes system objects that store information about other objects, except the data stored by the users. sysobjects stores information about all objects in that database. sysindexes stores information about all indexes and rows of every table in that database. syscolumns stores information about all columns that each table has in that database. sysusers stores how many users that database has. Although Meta Data stores information about other objects, it is not the transactional data that a user enters; rather, it’s a system data about the data. Because Primary Data File (.MDF) contains important information about the database, it is treated as a special file. It is given the name Primary Data file because it contains the Database Catalogs. This file is present in the Primary File Group. You can always create additional objects (Tables, indexes etc.) in the Primary data file (This file is present in the Primary File group), by mentioning that you want to create this object under the Primary File Group. Any additional data file that you add to the database will have only transactional data but no Meta Data, so that’s why it is called as the Secondary Data File. It is given the extension name .NDF so that the user can easily identify whether a specific data file is a Primary Data File or a Secondary Data File(s). There are many advantages of storing data in different files that are under different file groups. You can put your read only in the tables in one file (file group) and read-write tables in another file (file group) and take a backup of only the file group that has read the write data, so that you can avoid taking the backup of a read-only data that cannot be altered. Creating additional files in different physical hard disks also improves I/O performance. A real-time scenario where we use Files could be this one: Let’s say you have created a database called MYDB in the D-Drive which has a 50 GB space. You also have 1 Database File (.MDF) and 1 Log File on D-Drive and suppose that all of that 50 GB space has been used up and you do not have any free space left but you still want to add an additional space to the database. One easy option would be to add one more physical hard disk to the server, add new data file to MYDB database and create this new data file in a new hard disk then move some of the objects from one file to another, and put the file group under which you added new file as default File group, so that any new object that is created gets into the new files, unless specified. Now that we got a basic idea of what data files are, what type of data they store and why they are named the way they are, let’s move on to the next topic, Shrinking. First of all, I disagree with the Microsoft terminology for naming this feature as “Shrinking”. Shrinking, in regular terms, means to reduce the size of a file by means of compressing it. BUT in SQL Server, Shrinking DOES NOT mean compressing. Shrinking in SQL Server means to remove an empty space from database files and release the empty space either to the Operating System or to SQL Server. Let’s examine this through an example. Let’s say you have a database “MYDB” with a size of 50 GB that has a free space of about 20 GB, which means 30GB in the database is filled with data and the 20 GB of space is free in the database because it is not currently utilized by the SQL Server (Database); it is reserved and not yet in use. If you choose to shrink the database and to release an empty space to Operating System, and MIND YOU, you can only shrink the database size to 30 GB (in our example). You cannot shrink the database to a size less than what is filled with data. So, if you have a database that is full and has no empty space in the data file and log file (you don’t have an extra disk space to set Auto growth option ON), YOU CANNOT issue the SHRINK Database/File command, because of two reasons: There is no empty space to be released because the Shrink command does not compress the database; it only removes the empty space from the database files and there is no empty space. Remember, the Shrink command is a logged operation. When we perform the Shrink operation, this information is logged in the log file. If there is no empty space in the log file, SQL Server cannot write to the log file and you cannot shrink a database. Now answering your questions: (1) Q: What are the USEDPAGES & ESTIMATEDPAGES that appear on the Results Pane after using the DBCC SHRINKDATABASE (NorthWind, 10) ? A: According to Books Online (For SQL Server 2000): UsedPages: the number of 8-KB pages currently used by the file. EstimatedPages: the number of 8-KB pages that SQL Server estimates the file could be shrunk down to. Important Note: Before asking any question, make sure you go through Books Online or search on the Google once. The reasons for doing so have many advantages: 1. If someone else already has had this question before, chances that it is already answered are more than 50 %. 2. This reduces your waiting time for the answer. (2) Q: What is the difference between Shrinking the Database using DBCC command like the one above & shrinking it from the Enterprise Manager Console by Right-Clicking the database, going to TASKS & then selecting SHRINK Option, on a SQL Server 2000 environment? A: As far as my knowledge goes, there is no difference, both will work the same way, one advantage of using this command from query analyzer is, your console won’t be freezed. You can do perform your regular activities using Enterprise Manager. (3) Q: What is this .NDF file that is discussed above? I have never heard of it. What is it used for? Is it used by end-users, DBAs or the SERVER/SYSTEM itself? A: .NDF File is a secondary data file. You never heard of it because when database is created, SQL Server creates database by default with only 1 data file (.MDF) and 1 log file (.LDF) or however your model database has been setup, because a model database is a template used every time you create a new database using the CREATE DATABASE Command. Unless you have added an extra data file, you will not see it. This file is used by the SQL Server to store data which are saved by the users. Hope this information helps. I would like to as the experts to please comment if what I understand is not what the Microsoft guys meant. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Readers Contribution, Readers Question, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, T SQL, Technology

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