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  • Big Data – Interacting with Hadoop – What is Sqoop? – What is Zookeeper? – Day 17 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the Pig and Pig Latin in Big Data Story. In this article we will understand what is Sqoop and Zookeeper in Big Data Story. There are two most important components one should learn when learning about interacting with Hadoop – Sqoop and Zookper. What is Sqoop? Most of the business stores their data in RDBMS as well as other data warehouse solutions. They need a way to move data to the Hadoop system to do various processing and return it back to RDBMS from Hadoop system. The data movement can happen in real time or at various intervals in bulk. We need a tool which can help us move this data from SQL to Hadoop and from Hadoop to SQL. Sqoop (SQL to Hadoop) is such a tool which extract data from non-Hadoop data sources and transform them into the format which Hadoop can use it and later it loads them into HDFS. Essentially it is ETL tool where it Extracts, Transform and Load from SQL to Hadoop. The best part is that it also does extract data from Hadoop and loads them to Non-SQL (or RDBMS) data stores. Essentially, Sqoop is a command line tool which does SQL to Hadoop and Hadoop to SQL. It is a command line interpreter. It creates MapReduce job behinds the scene to import data from an external database to HDFS. It is very effective and easy to learn tool for nonprogrammers. What is Zookeeper? ZooKeeper is a centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. In other words Zookeeper is a replicated synchronization service with eventual consistency. In simpler words – in Hadoop cluster there are many different nodes and one node is master. Let us assume that master node fails due to any reason. In this case, the role of the master node has to be transferred to a different node. The main role of the master node is managing the writers as that task requires persistence in order of writing. In this kind of scenario Zookeeper will assign new master node and make sure that Hadoop cluster performs without any glitch. Zookeeper is the Hadoop’s method of coordinating all the elements of these distributed systems. Here are few of the tasks which Zookeepr is responsible for. Zookeeper manages the entire workflow of starting and stopping various nodes in the Hadoop’s cluster. In Hadoop cluster when any processes need certain configuration to complete the task. Zookeeper makes sure that certain node gets necessary configuration consistently. In case of the master node fails, Zookeepr can assign new master node and make sure cluster works as expected. There many other tasks Zookeeper performance when it is about Hadoop cluster and communication. Basically without the help of Zookeeper it is not possible to design any new fault tolerant distributed application. Tomorrow In tomorrow’s blog post we will discuss about very important components of the Big Data Ecosystem – Big Data Analytics. 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

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  • SQL Authority News – Secret Tool Box of Successful Bloggers: 52 Tips to Build a High Traffic Top Ranking Blog

    - by Pinal Dave
    When I started this blog, it was meant as a bookmark for myself for helpful tips and tricks.  Gradually, it grew into a blog that others were reading and commenting on.  While SQL and databases are my first love and the reason I started this blog, the side effect was that I discovered I loved writing.  I discovered a secret goal I didn’t even know I wanted – I wanted to become an author.  For a long time, writing this blog satisfied that urge.  Gradually, though, I wanted to see my name in print. 12th Book Over the past few years I have authored and co-authored a number of books – they are all based on my knowledge of SQL Server, and were meant to spread my years of experience into the world, to share what I have learned with my community.  I currently have elevan of these “manuals” available for sale.  As exciting as it was to see my name in print, I still felt that there was more I could do as an author. That is when I realized that I am more than just a SQL expert.  I have been writing this blog now for more than 10 years, and it grew from a personal bookmark to a thriving website with over 2 million views per month.  I thought to myself “I could write a book about how to create a successful blog!”  And that is exactly what I did.  I am extremely excited to share with all of you my new book – “Secret Toolbox of Successful Bloggers.” A Labor of Love This project has been a labor of love for me.  It started out as a series for this blog – I would post one article a week until I felt the topic had been covered.  I found that as I wrote, new topics kept popping up in my mind, and eventually this small blog series grew into a full book.  The blog series was large enough to last a whole year, so I definitely thought that it could be a full book.  Ideas on how to become a successful blogger were so frequent that, I will admit, I feel like there is so much I left out of this book.  I had a lot more to say than I originally thought! I am so excited to be sharing this book with all of you.  I am so passionate about this topic, and I feel like there are so many people who can benefit from this book.  I know that when I started this blog, I did not know what I was doing, and I would have loved a “helping hand” to tell what to do and what not to do.  If this book can act that way to any of my readers, I feel it is a success. Rules of Thumb If you are interested in the topic of becoming a blogger, as you read this book, keep in mind that it is suggestions only.  Blogging is so new to the world that while there are “rules of thumb” about what to do and what not to do, a map of steps (“first, do x, then do y”) is not going to work for every single blogger.  This book is meant to encourage new bloggers to put their content out there in the world, to be brave and create a community like the one I have here at SQL Authority.  I have gained so much from this community, I wanted to give something back, and this book is just one small part. I hope that everyone who reads this books finds at least one helpful tip, and that everyone can experience the joy of blogging.  That is the whole reason I wrote this book, and what I hope everyone takes away from it. Where Can You Get It? You can get the book from following URL: Kindle eBook | Print Book Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: About Me, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, T SQL

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  • SQL Authority News – FalafelCON 2014: 2 days with the Best Developers in the World

    - by Pinal Dave
    I love presenting at various forums on various technologies. I am extremely excited that I got invited to speak at Falafel Conference 2014 in San Francisco. I will present two technology sessions on SQL Server. If you are into web development or if you just want to attend a conference with the best of the industry speakers, this may be the right conference for you. What set apart this conference from other conference is technology presented as well as speakers. Usually one has to attend very expensive and high scale event when they have to hear good speakers. At this conference, you will find quite a many industry legends are available to present on the bleeding edge technology. Here are few of the reasons why I believe you should attend this conference: Choose from four tracks covering Web, Mobile development and testing, Sitefinity, and Automated Testing, or attend sessions from all four! Learn from the best developers and testers in the business in an intimate setting. Surround yourself with your peers and the opportunity to network Learn about the latest platforms and technologies including Kendo UI, AngularJS, ASP.NET MVC, WebAPI, and more! Here are the details for the sessions which I am going to present at Falafel Conference. Secrets of SQL Server: Database Worst Practices Abstract: Chances are you have heard, or even uttered, this expression. This demo-oriented session will show many examples where database professionals were dumbfounded by their own mistakes, and could even bring back memories of your own early DBA days. The goal of this session is to expose the small details that can be dangerous to the production environment and SQL Server as a whole, as well as talk about worst practices and how to avoid them. Shedding light on some of these perils and the tricks to avoid them may even save your current job. After attending this session, Developers will only need 60 seconds to improve performance of their database server in their SharePoint implementation. We will have a quiz during the session to keep the conversation alive. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. Additionally, all attendees of the session will have access to learning material presented in the session. The Unsung Hero Abstract: Slow Running Queries are the most common problem that developers face while working with SQL Server. While it is easy to blame the SQL Server for unsatisfactory performance, however the issue often persists with the way queries have been written, and how Indexes has been set up. The session will focus on the ways of identifying problems that slow down SQL Server, and Indexing tricks to fix them. Developers will walk out with scripts and knowledge that can be applied to their servers, immediately post the session. Register Now! I have learned from the Falafel Team that they are running out of tickets and soon they will close the registration.  For next 10 days the price for the registration is only USD 149. Trust me, you can’t get such a world class training and networking opportunity at such a low price. Click to Register Here! Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority News, T SQL

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  • SQL SERVER – How to Get SQL Server Restart Notification?

    - by Pinal Dave
    Few days back my friend called me to know if there is any tool which can be used to get restart notification about SQL in their environment. I told that SQL Server can do it by itself with some configurations. He was happy and surprised to know that he need not spend any extra money. In SQL Server, we can configure stored procedure(s) to run at start-up of SQL Server. This blog would give steps to achieve how to achieve it. There are many situations where this feature can be used. Below are few. Logging SQL Server startup timings Modify data in some table during startup (i.e. table in tempdb) Sending notification about SQL start. Step 1 – Enable ‘scan for startup procs’ This can be done either using T-SQL or User Interface of Management Studio. EXEC sys.sp_configure N'Show Advanced Options', N'1' GO RECONFIGURE WITH OVERRIDE GO EXEC sys.sp_configure N'scan for startup procs', N'1' GO RECONFIGURE WITH OVERRIDE GO Below is the interface to change the setting. We need to go to “Server” > “Properties” and use “Advanced” tab. “Scan for Startup Procs” is the parameter under “Miscellaneous” section as shown below. We need to make value as “True” and hit OK. Step 2 – Create stored procedure It’s important to note that the procedure is executed after recovery is finished for ALL databases. Here is a sample stored procedure. You can use your own logic in the procedure. CREATE PROCEDURE SQLStartupProc AS BEGIN CREATE TABLE ##ThisTableShouldAlwaysExists (AnyColumn INT) END Step 3 – Set Procedure to run at startup We need to use sp_procoption to mark the procedure to run at startup. Here is the code to let SQL know that this is startup proc. sp_procoption 'SQLStartupProc', 'startup', 'true' This can be used only for procedures in master database. Msg 15398, Level 11, State 1, Procedure sp_procoption, Line 89 Only objects in the master database owned by dbo can have the startup setting changed. We also need to remember that such procedure should not have any input/output parameter. Here is the error which would be raised. Msg 15399, Level 11, State 1, Procedure sp_procoption, Line 107 Could not change startup option because this option is restricted to objects that have no parameters. Verification Here is the query to find which procedures is marked as startup procedures. SELECT name FROM sys.objects WHERE OBJECTPROPERTY(OBJECT_ID, 'ExecIsStartup') = 1 Once this is done, I have restarted SQL instance and here is what we would see in SQL ERRORLOG Launched startup procedure 'SQLStartupProc'. This confirms that stored procedure is executed. You can also notice that this is done after all databases are recovered. Recovery is complete. This is an informational message only. No user action is required. After few days my friend again called me and asked – I want to turn this OFF? Use comments section and post the answer for him.  Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL

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  • Big Data – ClustrixDB – Extreme Scale SQL Database with Real-time Analytics, Releases Software Download – NewSQL

    - by Pinal Dave
    There are so many things to learn and there is so little time we all have. As we have little time we need to be selective to learn whatever we learn. I believe I know quite a lot of things in SQL but I still do not know what is around SQL. I have started to learn about NewSQL recently. If you wonder what is NewSQL I encourage all of you to read my blog post about NewSQL over here Big Data – Buzz Words: What is NewSQL – Day 10 of 21. NewSQL databases are quickly becoming popular – providing the scale of NoSQL with the SQL features and transactions. As a part of learning NewSQL database, I have recently started to learn about ClustrixDB. ClustrixDB has been the most mature NewSQL database used by some of the largest internet sites in the world for over 3 years, with extensive SQL support. In addition to scale, it provides fast real-time analytics by bringing massively parallel processing (MPP), available only in warehousing databases, to the transactional database. The reason I am more intrigued about learning ClustrixDB is their recent announcement on Oct 31. ClustrixDB was only available as an appliance, but now with their software release on Oct 31, everyone can use it. It is now available as forever free for up to 12 cores with community support, and there is a 45 day trial for unlimited cluster sizes. With the forever free world, I am indeed interested in ClustrixDB now. I know that few of the leading eCommerce sites in the world uses them for their transactional database. Here are few of the details I have quickly noted for ClustrixDB. ClustrixDB allows user to: Scale by simply adding nodes to the cluster with a single command Run billions of transactions a day Run fast real-time analytics Achieve high-availability with recovery from node failure Manages itself Easily migrate from MySQL as it is nearly plug-and-play compatible, use MySQL drivers, tools and replication. While I was going through the documentation I realized that ClustrixDB also has extensive support for SQL features including complex queries involving joins on a dozen or more tables, aggregates, sorts, sub-queries. It also supports stored procedures, triggers, foreign keys, partitioned and temporary tables, and fully online schema changes. It is indeed a very matured product and SQL solution. Indeed Clusterix sound very promising solution, I decided to dig a bit deeper to understand who are current customers of the Clustrix as they exist in the industry for quite a few years. Their client list is indeed very interesting and here is my quick research about them. Twoo.com – Europe’s largest social discovery (dating) site runs 4.4 Billion Transactions a day with table sizes over a Terabyte, on a 168 core cluster. EngageBDR – Top 3 in the online advertising category uses ClustrixDB to serve 6.9 billion ads a day through real-time bidding platform. Their reports went from 4 hours to 15 seconds. NoMoreRack – Top 2 fastest growing e-commerce company in US used ClustrixDB for high availability and fast growth through Amazon cloud. MakeMyTrip – India’s leading travel site runs on ClustrixDB with two clusters running as multi-master in Chennai and Bangalore. Many enterprises such as AOL, CSC, Rakuten, Symantec use ClustrixDB when their applications need scale. I must accept that I am impressed with the information I have learned so far and now is the time to do some hand’s on experience with their product. I want to learn this technology so in future when it is about NewSQL, I know what I am talking about. Read more why Clustrix explains why you ClustrixDB might be the right database for you. Download ClustrixDB with me today and install it on your machine so in future when we discuss the technical aspects of it, we all are on the same page. The software can be downloaded here. Reference : Pinal Dave (http://blog.SQLAuthority.com)Filed under: Big Data, MySQL, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Clustrix

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  • Developer’s Life – Summary of Superhero Articles

    - by Pinal Dave
    Earlier this year, I wrote an article series where I talked about developer’s life and compared it with Superhero. I have got amazing response to this series and I have been receiving quite a lots of email suggesting that I should write more blog post about them. Currently I am not planning to write more blog post but I will soon continue another series. In this blog post, I have summarized the entire series. Let me know if you want me to write about any superhero. I will see what I can do about that hero. Developer’s Life – Every Developer is a Captain America Captain America was first created as a comic book character in the 1940’s as a way to boost morale during World War II.  Aimed at a children’s audience, his legacy faded away when the war ended.  However, he has recently has a major reboot to become a popular movie character that deals with modern issues. Developer’s Life – Every Developer is the Incredible Hulk The Incredible Hulk is possibly one of the scariest superheroes out there.  All superheroes are meant to be “out of this world” and awe-inspiring, but I think most people will agree with I say The Hulk takes this to the next level.  He is the result of an industrial accident, which is scary enough in it’s own right.  Plus, when mild-mannered Bruce Banner is angered, he goes completely out-of-control and transforms into a destructive monster that he cannot control and has no memories of. Developer’s Life – Every Developer is a Wonder Woman We have focused a lot lately on this “superhero series.”  I love fantasy books and movies, and I feel like there is a lot to be learned from them.  As I am writing this series, though, I have noticed that every super hero I write about is a man.  So today, I would like to talk about the major female super hero – Wonder Woman. Developer’s Life – Every Developer is a Harry Potter Harry Potter might not be a superhero in the traditional sense, but I believe he still has a lot to teach us and show us about life as a developer.  If you have been living under a rock for the last 17 years, you might not know that Harry Potter is the main character in an extremely popular series of books and movies documenting the education and tribulation of a young wizard (and his friends). Developer’s Life – Every Developer is Like Transformers Transformers may not be superheroes – they don’t wear capes, they don’t have amazing powers outside of their size and folding ability, they’re not even human (technically).  Part of their enduring popularity is that while we are enjoying over-the-top movies, we are learning about good leadership and strong personal skills. Developer’s Life – Every Developer is a Iron Man Iron Man is another superhero who is not naturally “super,” but relies on his brain (and money) to turn him into a fighting machine.  While traditional superheroes are still popular, a three-movie franchise and incorporation into the new Avengers series shows that Iron Man is popular enough on his own. Developer’s Life – Every Developer is a Sherlock Holmes I have been thinking a lot about how developers are like super heroes, and I have written two blog posts now comparing them to Spiderman and Superman.  I have a lot of love and respect for developers, and I hope that they are enjoying these articles, and others are learning a little bit about the profession.  There is another fictional character who, while not technically asuper hero, is very powerful, and I also think stands as a good example of a developer. That character is Sherlock Holmes.  Sherlock Holmes is a British detective, first made popular at the turn of the 19thcentury by author Sir Arthur Conan Doyle.  The original Sherlock Holmes was a brilliant detective who could solve the most mind-boggling crime through simple observations and deduction. Developer’s Life – Every Developer is a Chhota Bheem Chhota Bheem is a cartoon character that is extremely popular where I live.  He is my daughter’s favorite characters.  I like to say that children love Chhota Bheem more than their parents – it is lucky for us he is not real!  Children love Chhota Bheem because he is the absolute “good guy.”  He is smart, loyal, and strong.  He and his friends live in Dholakpur and fight off their many enemies – and always win – in every episode.  In each episode, they learn something about friendship, bravery, and being kind to others.  Chhota Bheem is a good role model for children, and I think that he is a good role model for developers are well. Developer’s Life – Every Developer is a Batman Batman is one of the darkest superheroes in the fantasy canon.  He does not come to his powers through any sort of magical coincidence or radioactive insect, but through a lot of psychological scarring caused by witnessing the death of his parents.  Despite his dark back story, he possesses a lot of admirable abilities that I feel bear comparison to developers. Developer’s Life – Every Developer is a Superman I enjoyed comparing developers to Spiderman so much, that I have decided to continue the trend and encourage some of my favorite people (developers) with another favorite superhero – Superman.  Superman is probably the most famous superhero – and one of the most inspiring. Developer’s Life – Every Developer is a Spiderman I have to admit, Spiderman is my favorite superhero.  The most recent movie recently was released in theaters, so it has been at the front of my mind for some time. Spiderman was my favorite superhero even before the latest movie came out, but of course I took my whole family to see the movie as soon as I could!  Every one of us loved it, including my daughter.  We all left the movie thinking how great it would be to be Spiderman.  So, with that in mind, I started thinking about how we are like Spiderman in our everyday lives, especially developers. I would like to know which Superhero is your favorite hero! Reference: Pinal Dave (http://blog.SQLAuthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: Developer, Superhero

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  • SQLAuthority News – Don’t Be Afraid To Fool The World – Video by John Sonmez

    - by Pinal Dave
    Sometime some words and statements grabs your attention and it is hard to stop thinking about that after a while. Something similar happened a few days ago when I read the twitter statement of my friend and Pluralsight author John Sonmez. He twitted few days ago very interesting statement. “I don’t know a single successful person, who doesn’t deep down think that have the world fooled. #fooltheworld” by John Sonmez. When I read it, I was extremely intrigued by this statement. I read it many times, I shared with my family and I just could not stop interpreting this statement. It was indeed fun to read it again and again and there are so many different meanings one can take away from the statement. I know John very well, he is a  wonderful person and have very positive energy for the life. I just had to request him to build a video around it. Right after 5 days of my request, John created a wonderful video around this subject. I watched it multiple times as it was a wonderful video. I am not going to write about what was in the video much as I suggest you to watch the video itself. Here is one of the personal stories I want to share which is absolutely relevant to this video. I think my story 100% resonant the story of John. A Real Story from My Past Three years ago, I submitted a session in one of the SharePoint conference as a SQL Server session. My session was accepted and I prepared it very well. I put more than 2 month’s time to prepare for the session and I was very excited to present the session. I reached to the event place traveling thousands of the miles and I was very much excited to present the session. However, there was a little mixed up in the session. There were multiple session which were similar to my session title. One of the other speakers also had proposed a database related session and was selected. When the material went to print the printing team got confused and by mistake swapped the sessions. The other speaker got Performance with SQL Server session and I had received Performance with SharePoint session. IT was indeed a big mixed up but now that is how it was in the event guide and it was marketed the same way everything in the event. A Big Mix Up I had to talk with the event organizer and we come to the conclusion that we all had good intention but things just got mixed up and now was the time when “The show must go on“. I had a great amount of hesitation to go and present the session as I had personally never worked with Sharepoint so close in my life and my session abstracted talked about SharePoint tricks in depth. Two hours before the session I took the help of one of my friend and installed the SharePoint on my box. He showed me a few things here and there but it was never a good enough time to learn everything which I wanted to learn. The Moments of Confidence I was very scared and nervous to go on the stage as a SharePoint was not something I felt comfortable. However, I decided to go on stage with confidence as a SharePoint expert. Though I did not know SharePoint at the best, I had confidence that whatever I know is correct and I will not misguide people. I had no intention to fool people but I had no intention to accept that I am a fool and you all wasted your time and money to dedicate your time to attend my session. I decided to be honest but at the same time decided to take the session beyond my expertise. The sixty minutes of the session went very fine and I was able to manage all the difficult question at a satisfactory level. When the session was over my feeling was that I would have not presented or talked any different if I had more knowledge of the SharePoint at that time. I think it was one of my best sessions and it was reflected in the session feedback as well. I was the best speaker across all the track and my session had highest ranking. I was delighted and I learned a very valuable lesson. I must go beyond my limits and knowledge. I must aim higher and work harder. I should not lie but I should have confidence that I have a good heart and I put 100% in my efforts.  Lessions Learned Since this incident I have learned a lot about SharePoint and I am now a regular speaker at various SharePoint conferences along with SQL Server sessions. I am motivated and I am not afraid. I know people have lots of expectation from me but I have learned not to judge myself before I do my best. I leave the judgement of my efforts to my audience. I do not take the burden of the feedback on me, even though I know my audience have expected from me. I know what I know and I put my best. I must go out, if I fail, I learn from my mistake but I must keep my progress trajectory very high. As John said in the video, sometime success is not something we can achieve 100% but we can keep on going near to it. As long as we do not lose our focus from our goal and do not deviate from our progress path, we are doing things right. Reference: Pinal Dave (http://blog.sqlauthority.com)  Filed under: About Me, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL SERVER – SSMS: Memory Usage By Memory Optimized Objects Report

    - by Pinal Dave
    At conferences and at speaking engagements at the local UG, there is one question that keeps on coming which I wish were never asked. The question around, “Why is SQL Server using up all the memory and not releasing even when idle?” Well, the answer can be long and with the release of SQL Server 2014, this got even more complicated. This release of SQL Server 2014 has the option of introducing In-Memory OLTP which is completely new concept and our dependency on memory has increased multifold. In reality, nothing much changes but we have memory optimized objects (Tables and Stored Procedures) additional which are residing completely in memory and improving performance. As a DBA, it is humanly impossible to get a hang of all the innovations and the new features introduced in the next version. So today’s blog is around the report added to SSMS which gives a high level view of this new feature addition. This reports is available only from SQL Server 2014 onwards because the feature was introduced in SQL Server 2014. Earlier versions of SQL Server Management Studio would not show the report in the list. If we try to launch the report on the database which is not having In-Memory File group defined, then we would see the message in report. To demonstrate, I have created new fresh database called MemoryOptimizedDB with no special file group. Here is the query used to identify whether a database has memory-optimized file group or not. SELECT TOP(1) 1 FROM sys.filegroups FG WHERE FG.[type] = 'FX' Once we add filegroup using below command, we would see different version of report. USE [master] GO ALTER DATABASE [MemoryOptimizedDB] ADD FILEGROUP [IMO_FG] CONTAINS MEMORY_OPTIMIZED_DATA GO The report is still empty because we have not defined any Memory Optimized table in the database.  Total allocated size is shown as 0 MB. Now, let’s add the folder location into the filegroup and also created few in-memory tables. We have used the nomenclature of IMO to denote “InMemory Optimized” objects. USE [master] GO ALTER DATABASE [MemoryOptimizedDB] ADD FILE ( NAME = N'MemoryOptimizedDB_IMO', FILENAME = N'E:\Program Files\Microsoft SQL Server\MSSQL12.SQL2014\MSSQL\DATA\MemoryOptimizedDB_IMO') TO FILEGROUP [IMO_FG] GO You may have to change the path based on your SQL Server configuration. Below is the script to create the table. USE MemoryOptimizedDB GO --Drop table if it already exists. IF OBJECT_ID('dbo.SQLAuthority','U') IS NOT NULL DROP TABLE dbo.SQLAuthority GO CREATE TABLE dbo.SQLAuthority ( ID INT IDENTITY NOT NULL, Name CHAR(500)  COLLATE Latin1_General_100_BIN2 NOT NULL DEFAULT 'Pinal', CONSTRAINT PK_SQLAuthority_ID PRIMARY KEY NONCLUSTERED (ID), INDEX hash_index_sample_memoryoptimizedtable_c2 HASH (Name) WITH (BUCKET_COUNT = 131072) ) WITH (MEMORY_OPTIMIZED = ON, DURABILITY = SCHEMA_AND_DATA) GO As soon as above script is executed, table and index both are created. If we run the report again, we would see something like below. Notice that table memory is zero but index is using memory. This is due to the fact that hash index needs memory to manage the buckets created. So even if table is empty, index would consume memory. More about the internals of how In-Memory indexes and tables work will be reserved for future posts. Now, use below script to populate the table with 10000 rows INSERT INTO SQLAuthority VALUES (DEFAULT) GO 10000 Here is the same report after inserting 1000 rows into our InMemory table.    There are total three sections in the whole report. Total Memory consumed by In-Memory Objects Pie chart showing memory distribution based on type of consumer – table, index and system. Details of memory usage by each table. The information about all three is taken from one single DMV, sys.dm_db_xtp_table_memory_stats This DMV contains memory usage statistics for both user and system In-Memory tables. If we query the DMV and look at data, we can easily notice that the system tables have negative object IDs.  So, to look at user table memory usage, below is the over-simplified version of query. USE MemoryOptimizedDB GO SELECT OBJECT_NAME(OBJECT_ID), * FROM sys.dm_db_xtp_table_memory_stats WHERE OBJECT_ID > 0 GO This report would help DBA to identify which in-memory object taking lot of memory which can be used as a pointer for designing solution. I am sure in future we will discuss at lengths the whole concept of In-Memory tables in detail over this blog. To read more about In-Memory OLTP, have a look at In-Memory OLTP Series at Balmukund’s Blog. 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 Memory, SQL Reports

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  • SQL SERVER – SSMS: Backup and Restore Events Report

    - by Pinal Dave
    A DBA wears multiple hats and in fact does more than what an eye can see. One of the core task of a DBA is to take backups. This looks so trivial that most developers shrug this off as the only activity a DBA might be doing. I have huge respect for DBA’s all around the world because even if they seem cool with all the scripting, automation, maintenance works round the clock to keep the business working almost 365 days 24×7, their worth is knowing that one day when the systems / HDD crashes and you have an important delivery to make. So these backup tasks / maintenance jobs that have been done come handy and are no more trivial as they might seem to be as considered by many. So the important question like: “When was the last backup taken?”, “How much time did the last backup take?”, “What type of backup was taken last?” etc are tricky questions and this report lands answers to the same in a jiffy. So the SSMS report, we are talking can be used to find backups and restore operation done for the selected database. Whenever we perform any backup or restore operation, the information is stored in the msdb database. This report can utilize that information and provide information about the size, time taken and also the file location for those operations. Here is how this report can be launched.   Once we launch this report, we can see 4 major sections shown as listed below. Average Time Taken For Backup Operations Successful Backup Operations Backup Operation Errors Successful Restore Operations Let us look at each section next. Average Time Taken For Backup Operations Information shown in “Average Time Taken For Backup Operations” section is taken from a backupset table in the msdb database. Here is the query and the expanded version of that particular section USE msdb; SELECT (ROW_NUMBER() OVER (ORDER BY t1.TYPE))%2 AS l1 ,       1 AS l2 ,       1 AS l3 ,       t1.TYPE AS [type] ,       (AVG(DATEDIFF(ss,backup_start_date, backup_finish_date)))/60.0 AS AverageBackupDuration FROM backupset t1 INNER JOIN sys.databases t3 ON ( t1.database_name = t3.name) WHERE t3.name = N'AdventureWorks2014' GROUP BY t1.TYPE ORDER BY t1.TYPE On my small database the time taken for differential backup was less than a minute, hence the value of zero is displayed. This is an important piece of backup operation which might help you in planning maintenance windows. Successful Backup Operations Here is the expanded version of this section.   This information is derived from various backup tracking tables from msdb database.  Here is the simplified version of the query which can be used separately as well. SELECT * FROM sys.databases t1 INNER JOIN backupset t3 ON (t3.database_name = t1.name) LEFT OUTER JOIN backupmediaset t5 ON ( t3.media_set_id = t5.media_set_id) LEFT OUTER JOIN backupmediafamily t6 ON ( t6.media_set_id = t5.media_set_id) WHERE (t1.name = N'AdventureWorks2014') ORDER BY backup_start_date DESC,t3.backup_set_id,t6.physical_device_name; The report does some calculations to show the data in a more readable format. For example, the backup size is shown in KB, MB or GB. I have expanded first row by clicking on (+) on “Device type” column. That has shown me the path of the physical backup file. Personally looking at this section, the Backup Size, Device Type and Backup Name are critical and are worth a note. As mentioned in the previous section, this section also has the Duration embedded inside it. Backup Operation Errors This section of the report gets data from default trace. You might wonder how. One of the event which is tracked by default trace is “ErrorLog”. This means that whatever message is written to errorlog gets written to default trace file as well. Interestingly, whenever there is a backup failure, an error message is written to ERRORLOG and hence default trace. This section takes advantage of that and shows the information. We can read below message under this section, which confirms above logic. No backup operations errors occurred for (AdventureWorks2014) database in the recent past or default trace is not enabled. Successful Restore Operations This section may not be very useful in production server (do you perform a restore of database?) but might be useful in the development and log shipping secondary environment, where we might be interested to see restore operations for a particular database. Here is the expanded version of the section. To fill this section of the report, I have restored the same backups which were taken to populate earlier sections. Here is the simplified version of the query used to populate this output. USE msdb; SELECT * FROM restorehistory t1 LEFT OUTER JOIN restorefile t2 ON ( t1.restore_history_id = t2.restore_history_id) LEFT OUTER JOIN backupset t3 ON ( t1.backup_set_id = t3.backup_set_id) WHERE t1.destination_database_name = N'AdventureWorks2014' ORDER BY restore_date DESC,  t1.restore_history_id,t2.destination_phys_name Have you ever looked at the backup strategy of your key databases? Are they in sync and do we have scope for improvements? Then this is the report to analyze after a week or month of maintenance plans running in your database. Do chime in with what are the strategies you are using in your environments. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Backup and Restore, SQL Query, SQL Server, SQL Server Management Studio, SQL Tips and Tricks, T SQL Tagged: SQL Reports

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  • Big Data – Buzz Words: Importance of Relational Database in Big Data World – Day 9 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned what is HDFS. In this article we will take a quick look at the importance of the Relational Database in Big Data world. A Big Question? Here are a few questions I often received since the beginning of the Big Data Series - Does the relational database have no space in the story of the Big Data? Does relational database is no longer relevant as Big Data is evolving? Is relational database not capable to handle Big Data? Is it true that one no longer has to learn about relational data if Big Data is the final destination? Well, every single time when I hear that one person wants to learn about Big Data and is no longer interested in learning about relational database, I find it as a bit far stretched. I am not here to give ambiguous answers of It Depends. I am personally very clear that one who is aspiring to become Big Data Scientist or Big Data Expert they should learn about relational database. NoSQL Movement The reason for the NoSQL Movement in recent time was because of the two important advantages of the NoSQL databases. Performance Flexible Schema In personal experience I have found that when I use NoSQL I have found both of the above listed advantages when I use NoSQL database. There are instances when I found relational database too much restrictive when my data is unstructured as well as they have in the datatype which my Relational Database does not support. It is the same case when I have found that NoSQL solution performing much better than relational databases. I must say that I am a big fan of NoSQL solutions in the recent times but I have also seen occasions and situations where relational database is still perfect fit even though the database is growing increasingly as well have all the symptoms of the big data. Situations in Relational Database Outperforms Adhoc reporting is the one of the most common scenarios where NoSQL is does not have optimal solution. For example reporting queries often needs to aggregate based on the columns which are not indexed as well are built while the report is running, in this kind of scenario NoSQL databases (document database stores, distributed key value stores) database often does not perform well. In the case of the ad-hoc reporting I have often found it is much easier to work with relational databases. SQL is the most popular computer language of all the time. I have been using it for almost over 10 years and I feel that I will be using it for a long time in future. There are plenty of the tools, connectors and awareness of the SQL language in the industry. Pretty much every programming language has a written drivers for the SQL language and most of the developers have learned this language during their school/college time. In many cases, writing query based on SQL is much easier than writing queries in NoSQL supported languages. I believe this is the current situation but in the future this situation can reverse when No SQL query languages are equally popular. ACID (Atomicity Consistency Isolation Durability) – Not all the NoSQL solutions offers ACID compliant language. There are always situations (for example banking transactions, eCommerce shopping carts etc.) where if there is no ACID the operations can be invalid as well database integrity can be at risk. Even though the data volume indeed qualify as a Big Data there are always operations in the application which absolutely needs ACID compliance matured language. The Mixed Bag I have often heard argument that all the big social media sites now a days have moved away from Relational Database. Actually this is not entirely true. While researching about Big Data and Relational Database, I have found that many of the popular social media sites uses Big Data solutions along with Relational Database. Many are using relational databases to deliver the results to end user on the run time and many still uses a relational database as their major backbone. Here are a few examples: Facebook uses MySQL to display the timeline. (Reference Link) Twitter uses MySQL. (Reference Link) Tumblr uses Sharded MySQL (Reference Link) Wikipedia uses MySQL for data storage. (Reference Link) There are many for prominent organizations which are running large scale applications uses relational database along with various Big Data frameworks to satisfy their various business needs. Summary I believe that RDBMS is like a vanilla ice cream. Everybody loves it and everybody has it. NoSQL and other solutions are like chocolate ice cream or custom ice cream – there is a huge base which loves them and wants them but not every ice cream maker can make it just right  for everyone’s taste. No matter how fancy an ice cream store is there is always plain vanilla ice cream available there. Just like the same, there are always cases and situations in the Big Data’s story where traditional relational database is the part of the whole story. In the real world scenarios there will be always the case when there will be need of the relational database concepts and its ideology. It is extremely important to accept relational database as one of the key components of the Big Data instead of treating it as a substandard technology. Ray of Hope – NewSQL In this module we discussed that there are places where we need ACID compliance from our Big Data application and NoSQL will not support that out of box. There is a new termed coined for the application/tool which supports most of the properties of the traditional RDBMS and supports Big Data infrastructure – NewSQL. Tomorrow In tomorrow’s blog post we will discuss about NewSQL. 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

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  • SQL SERVER – Example of Performance Tuning for Advanced Users with DB Optimizer

    - by Pinal Dave
    Performance tuning is such a subject that everyone wants to master it. In beginning everybody is at a novice level and spend lots of time learning how to master the art of performance tuning. However, as we progress further the tuning of the system keeps on getting very difficult. I have understood in my early career there should be no need of ego in the technology field. There are always better solutions and better ideas out there and we should not resist them. Instead of resisting the change and new wave I personally adopt it. Here is a similar example, as I personally progress to the master level of performance tuning, I face that it is getting harder to come up with optimal solutions. In such scenarios I rely on various tools to teach me how I can do things better. Once I learn about tools, I am often able to come up with better solutions when I face the similar situation next time. A few days ago I had received a query where the user wanted to tune it further to get the maximum out of the performance. I have re-written the similar query with the help of AdventureWorks sample database. SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID; User had similar query to above query was used in very critical report and wanted to get best out of the query. When I looked at the query – here were my initial thoughts Use only column in the select statements as much as you want in the application Let us look at the query pattern and data workload and find out the optimal index for it Before I give further solutions I was told by the user that they need all the columns from all the tables and creating index was not allowed in their system. He can only re-write queries or use hints to further tune this query. Now I was in the constraint box – I believe * was not a great idea but if they wanted all the columns, I believe we can’t do much besides using *. Additionally, if I cannot create a further index, I must come up with some creative way to write this query. I personally do not like to use hints in my application but there are cases when hints work out magically and gives optimal solutions. Finally, I decided to use Embarcadero’s DB Optimizer. It is a fantastic tool and very helpful when it is about performance tuning. I have previously explained how it works over here. First open DBOptimizer and open Tuning Job from File >> New >> Tuning Job. Once you open DBOptimizer Tuning Job follow the various steps indicates in the following diagram. Essentially we will take our original script and will paste that into Step 1: New SQL Text and right after that we will enable Step 2 for Generating Various cases, Step 3 for Detailed Analysis and Step 4 for Executing each generated case. Finally we will click on Analysis in Step 5 which will generate the report detailed analysis in the result pan. The detailed pan looks like. It generates various cases of T-SQL based on the original query. It applies various hints and available hints to the query and generate various execution plans of the query and displays them in the resultant. You can clearly notice that original query had a cost of 0.0841 and logical reads about 607 pages. Whereas various options which are just following it has different execution cost as well logical read. There are few cases where we have higher logical read and there are few cases where as we have very low logical read. If we pay attention the very next row to original query have Merge_Join_Query in description and have lowest execution cost value of 0.044 and have lowest Logical Reads of 29. This row contains the query which is the most optimal re-write of the original query. Let us double click over it. Here is the query: SELECT * FROM HumanResources.Employee e INNER JOIN HumanResources.EmployeeDepartmentHistory edh ON e.BusinessEntityID = edh.BusinessEntityID INNER JOIN HumanResources.Shift s ON edh.ShiftID = s.ShiftID OPTION (MERGE JOIN) If you notice above query have additional hint of Merge Join. With the help of this Merge Join query hint this query is now performing much better than before. The entire process takes less than 60 seconds. Please note that it the join hint Merge Join was optimal for this query but it is not necessary that the same hint will be helpful in all the queries. Additionally, if the workload or data pattern changes the query hint of merge join may be no more optimal join. In that case, we will have to redo the entire exercise once again. This is the reason I do not like to use hints in my queries and I discourage all of my users to use the same. However, if you look at this example, this is a great case where hints are optimizing the performance of the query. It is humanly not possible to test out various query hints and index options with the query to figure out which is the most optimal solution. Sometimes, we need to depend on the efficiency tools like DB Optimizer to guide us the way and select the best option from the suggestion provided. Let me know what you think of this article as well your experience with DB Optimizer. Please leave a comment. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Joins, SQL Optimization, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • SQL – Quick Start with Explorer Sections of NuoDB – Query NuoDB Database

    - by Pinal Dave
    This is the third post in the series of the blog posts I am writing about NuoDB. NuoDB is very innovative and easy-to-use product. I can clearly see how one can scale-out NuoDB with so much ease and confidence. In my very first blog post we discussed how we can install NuoDB (link), and in my second post I discussed how we can manage the NuoDB database transaction engines and storage managers with a few clicks (link). Note: You can Download NuoDB from here. In this post, we will learn how we can use the Explorer feature of NuoDB to do various SQL operations. NuoDB has a browser-based Explorer, which is very powerful and has many of the features any IDE would normally have. Let us see how it works in the following step-by-step tutorial. Let us go to the NuoDBNuoDB Console by typing the following URL in your browser: http://localhost:8080/ It will bring you to the QuickStart screen. Make sure that you have created the sample database. If you have not created sample database, click on Create Database and create it successfully. Now go to the NuoDB Explorer by clicking on the main tab, and it will ask you for your domain username and password. Enter the username as a domain and password as a bird. Alternatively you can also enter username as a quickstart and password as a quickstart. Once you enter the password you will be able to see the databases. In our example we have installed the Sample Database hence you will see the Test database in our Database Hierarchy screen. When you click on database it will ask for the database login. Note that Database Login is different from Domain login and you will have to enter your database login over here. In our case the database username is dba and password is goalie. Once you enter a valid username and password it will display your database. Further expand your database and you will notice various objects in your database. Once you explore various objects, select any database and click on Open. When you click on execute, it will display the SQL script to select the data from the table. The autogenerated script displays entire result set from the database. The NuoDB Explorer is very powerful and makes the life of developers very easy. If you click on List SQL Statements it will list all the available SQL statements right away in Query Editor. You can see the popup window in following image. Here is the cool thing for geeks. You can even click on Query Plan and it will display the text based query plan as well. In case of a SELECT, the query plan will be much simpler, however, when we write complex queries it will be very interesting. We can use the query plan tab for performance tuning of the database. Here is another feature, when we click on List Tables in NuoDB Explorer.  It lists all the available tables in the query editor. This is very helpful when we are writing a long complex query. Here is a relatively complex example I have built using Inner Join syntax. Right below I have displayed the Query Plan. The query plan displays all the little details related to the query. Well, we just wrote multi-table query and executed it against the NuoDB database. You can use the NuoDB Admin section and do various analyses of the query and its performance. NuoDB is a distributed database built on a patented emergent architecture with full support for SQL and ACID guarantees.  It allows you to add Transaction Engine processes to a running system to improve the performance of your system.  You can also add a second Storage Engine to your running system for redundancy purposes.  Conversely, you can shut down processes when you don’t need the extra database resources. NuoDB also provides developers and administrators with a single intuitive interface for centrally monitoring deployments. If you have read my blog posts and have not tried out NuoDB, I strongly suggest that you download it today and catch up with the learnings with me. Trust me though the product is very powerful, it is extremely easy to learn and use. 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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  • Big Data – Role of Cloud Computing in Big Data – Day 11 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned the importance of the NewSQL. In this article we will understand the role of Cloud in Big Data Story What is Cloud? Cloud is the biggest buzzword around from last few years. Everyone knows about the Cloud and it is extremely well defined online. In this article we will discuss cloud in the context of the Big Data. Cloud computing is a method of providing a shared computing resources to the application which requires dynamic resources. These resources include applications, computing, storage, networking, development and various deployment platforms. The fundamentals of the cloud computing are that it shares pretty much share all the resources and deliver to end users as a service.  Examples of the Cloud Computing and Big Data are Google and Amazon.com. Both have fantastic Big Data offering with the help of the cloud. We will discuss this later in this blog post. There are two different Cloud Deployment Models: 1) The Public Cloud and 2) The Private Cloud Public Cloud Public Cloud is the cloud infrastructure build by commercial providers (Amazon, Rackspace etc.) creates a highly scalable data center that hides the complex infrastructure from the consumer and provides various services. Private Cloud Private Cloud is the cloud infrastructure build by a single organization where they are managing highly scalable data center internally. Here is the quick comparison between Public Cloud and Private Cloud from Wikipedia:   Public Cloud Private Cloud Initial cost Typically zero Typically high Running cost Unpredictable Unpredictable Customization Impossible Possible Privacy No (Host has access to the data Yes Single sign-on Impossible Possible Scaling up Easy while within defined limits Laborious but no limits Hybrid Cloud Hybrid Cloud is the cloud infrastructure build with the composition of two or more clouds like public and private cloud. Hybrid cloud gives best of the both the world as it combines multiple cloud deployment models together. Cloud and Big Data – Common Characteristics There are many characteristics of the Cloud Architecture and Cloud Computing which are also essentially important for Big Data as well. They highly overlap and at many places it just makes sense to use the power of both the architecture and build a highly scalable framework. Here is the list of all the characteristics of cloud computing important in Big Data Scalability Elasticity Ad-hoc Resource Pooling Low Cost to Setup Infastructure Pay on Use or Pay as you Go Highly Available Leading Big Data Cloud Providers There are many players in Big Data Cloud but we will list a few of the known players in this list. Amazon Amazon is arguably the most popular Infrastructure as a Service (IaaS) provider. The history of how Amazon started in this business is very interesting. They started out with a massive infrastructure to support their own business. Gradually they figured out that their own resources are underutilized most of the time. They decided to get the maximum out of the resources they have and hence  they launched their Amazon Elastic Compute Cloud (Amazon EC2) service in 2006. Their products have evolved a lot recently and now it is one of their primary business besides their retail selling. Amazon also offers Big Data services understand Amazon Web Services. Here is the list of the included services: Amazon Elastic MapReduce – It processes very high volumes of data Amazon DynammoDB – It is fully managed NoSQL (Not Only SQL) database service Amazon Simple Storage Services (S3) – A web-scale service designed to store and accommodate any amount of data Amazon High Performance Computing – It provides low-tenancy tuned high performance computing cluster Amazon RedShift – It is petabyte scale data warehousing service Google Though Google is known for Search Engine, we all know that it is much more than that. Google Compute Engine – It offers secure, flexible computing from energy efficient data centers Google Big Query – It allows SQL-like queries to run against large datasets Google Prediction API – It is a cloud based machine learning tool Other Players Besides Amazon and Google we also have other players in the Big Data market as well. Microsoft is also attempting Big Data with the Cloud with Microsoft Azure. Additionally Rackspace and NASA together have initiated OpenStack. The goal of Openstack is to provide a massively scaled, multitenant cloud that can run on any hardware. Thing to Watch The cloud based solutions provides a great integration with the Big Data’s story as well it is very economical to implement as well. However, there are few things one should be very careful when deploying Big Data on cloud solutions. Here is a list of a few things to watch: Data Integrity Initial Cost Recurring Cost Performance Data Access Security Location Compliance Every company have different approaches to Big Data and have different rules and regulations. Based on various factors, one can implement their own custom Big Data solution on a cloud. Tomorrow In tomorrow’s blog post we will discuss about various Operational Databases supporting Big Data. 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

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  • Big Data – What is Big Data – 3 Vs of Big Data – Volume, Velocity and Variety – Day 2 of 21

    - by Pinal Dave
    Data is forever. Think about it – it is indeed true. Are you using any application as it is which was built 10 years ago? Are you using any piece of hardware which was built 10 years ago? The answer is most certainly No. However, if I ask you – are you using any data which were captured 50 years ago, the answer is most certainly Yes. For example, look at the history of our nation. I am from India and we have documented history which goes back as over 1000s of year. Well, just look at our birthday data – atleast we are using it till today. Data never gets old and it is going to stay there forever.  Application which interprets and analysis data got changed but the data remained in its purest format in most cases. As organizations have grown the data associated with them also grew exponentially and today there are lots of complexity to their data. Most of the big organizations have data in multiple applications and in different formats. The data is also spread out so much that it is hard to categorize with a single algorithm or logic. The mobile revolution which we are experimenting right now has completely changed how we capture the data and build intelligent systems.  Big organizations are indeed facing challenges to keep all the data on a platform which give them a  single consistent view of their data. This unique challenge to make sense of all the data coming in from different sources and deriving the useful actionable information out of is the revolution Big Data world is facing. Defining Big Data The 3Vs that define Big Data are Variety, Velocity and Volume. Volume We currently see the exponential growth in the data storage as the data is now more than text data. We can find data in the format of videos, musics and large images on our social media channels. It is very common to have Terabytes and Petabytes of the storage system for enterprises. As the database grows the applications and architecture built to support the data needs to be reevaluated quite often. Sometimes the same data is re-evaluated with multiple angles and even though the original data is the same the new found intelligence creates explosion of the data. The big volume indeed represents Big Data. Velocity The data growth and social media explosion have changed how we look at the data. There was a time when we used to believe that data of yesterday is recent. The matter of the fact newspapers is still following that logic. However, news channels and radios have changed how fast we receive the news. Today, people reply on social media to update them with the latest happening. On social media sometimes a few seconds old messages (a tweet, status updates etc.) is not something interests users. They often discard old messages and pay attention to recent updates. The data movement is now almost real time and the update window has reduced to fractions of the seconds. This high velocity data represent Big Data. Variety Data can be stored in multiple format. For example database, excel, csv, access or for the matter of the fact, it can be stored in a simple text file. Sometimes the data is not even in the traditional format as we assume, it may be in the form of video, SMS, pdf or something we might have not thought about it. It is the need of the organization to arrange it and make it meaningful. It will be easy to do so if we have data in the same format, however it is not the case most of the time. The real world have data in many different formats and that is the challenge we need to overcome with the Big Data. This variety of the data represent  represent Big Data. Big Data in Simple Words Big Data is not just about lots of data, it is actually a concept providing an opportunity to find new insight into your existing data as well guidelines to capture and analysis your future data. It makes any business more agile and robust so it can adapt and overcome business challenges. Tomorrow In tomorrow’s blog post we will try to answer discuss Evolution of Big Data. 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

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  • SQL SERVER – An Efficiency Tool to Compare and Synchronize SQL Server Databases

    - by Pinal Dave
    There is no need to reinvent the wheel if it is already invented and if the wheel is already available at ease, there is no need to wait to grab it. Here is the similar situation. I came across a very interesting situation and I had to look for an efficient tool which can make my life easier and solve my business problem. Here is the scenario. One of the developers had deleted few rows from the very important mapping table of our development server (thankfully, it was not the production server). Though it was a development server, the entire development team had to stop working as the application started to crash on every page. Think about the lost of manpower and efficiency which we started to loose.  Pretty much every department had to stop working as our internal development application stopped working. Thankfully, we even take a backup of our development server and we had access to full backup of the entire database at 6 AM morning. We do not take as a frequent backup of development server as production server (naturally!). Even though we had a full backup, the solution was not to restore the database. Think about it, there were plenty of the other operations since the last good full backup and if we restore a full backup, we will pretty much overwrite on the top of the work done by developers since morning. Now, as restoring the full backup was not an option we decided to restore the same database on another server. Once we had restored our database to another server, the challenge was to compare the table from where the database was deleted. The mapping table from where the data were deleted contained over 5000 rows and it was humanly impossible to compare both the tables manually. Finally we decided to use efficiency tool dbForge Data Compare for SQL Server from DevArt. dbForge Data Compare for SQL Server is a powerful, fast and easy to use SQL compare tool, capable of using native SQL Server backups as metadata source. (FYI we Downloaded dbForge Data Compare) Once we discovered the product, we immediately downloaded the product and installed on our development server. After we installed the product, we were greeted with the following screen. We clicked on the New Data Comparision to start our new comparison project. It brought up following screen. Here is the best part of the product, we just had to enter our database connection username and password along with source and destination details and we are done. The entire process is very simple and self intuiting. The best part was that for the source, we can either select database or even backup. This was indeed fantastic feature. Think about this, if you have a very big database, it will take long time to restore on the server. Once it is restored, you will be able to work with it. However, when you are working with dbForge Data Compare it will accept database backup as your source or destination. Once I click on the execute it brought up following screen where it displayed an excellent summary of the data compare. It has dedicated tabs for the what is changing in what table as well had details of the changed data. The best part is that, once we had reviewed the change. We click on the Synchronize button in the menu bar and it brought up following screen. You can see that the screen has very simple straight forward but very powerful features. You can generate a script to synchronize from target to source or even from source to target. Additionally, the database is a very complicated world and there are extensive options to configure various database options on the next screen. We also have the option to either generate script or directly execute the script to target server. I like to play on the safe side and I generated the script for my synchronization and later on after review I deployed the scripts on the server. Well, my team and we were able to get going from our disaster in less than 10 minutes. There were few people in our team were indeed disappointed as they were thinking of going home early that day but in less than 10 minutes they had to get back to work. There are so many other features in  dbForge Data Compare for SQL Server, I am already planning to make this product company wide recommended product for Data Compare tool. Hats off to the team who have build this product. Here are few of the features salient features of the dbForge Data Compare for SQL Server Perform SQL Server database comparison to detect changes Compare SQL Server backups with live databases Analyze data differences between two databases Synchronize two databases that went out of sync Restore data of a particular table from the backup Generate data comparison reports in Excel and HTML formats Copy look-up data from development database to production Automate routine data synchronization tasks with command-line interface Go Ahead and Download the dbForge Data Compare for SQL Server right away. It is always a good idea to get familiar with the important tools before hand instead of learning it under pressure of disaster. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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  • SQL SERVER – Auditing and Profiling Database Made Easy with SQL Audit and Comply

    - by Pinal Dave
    Do you like auditing your database, or can you think of about a million other things you’d rather do?  Unfortunately, auditing is incredibly important.  As with tax audits, it is important to audit databases to ensure they are following all the rules, but they are also important for troubleshooting and security. There are several ways to audit SQL Server.  There is manual auditing, which is going through your database “by hand,” and obviously takes a long time and is quite inefficient.  SQL Server also provides programs to help you audit your systems.  Different administrators will have different opinions about best practices and which tools to use, and each one will be perfected for certain systems and certain users. Today, though, I would like to talk about Apex SQL Audit.  It is an auditing tool that acts like “track changes” in a word processing document.  It will log what has changed on the database, who made the changes, and what effects these changes have had (i.e. what objects were affected down the line).  All this information is logged, and can be easily viewed or printed for easy access. One of the best features of Apex is that it is so customizable (and easy to use!).  First, start Apex.  Then you can connect to the database you would like to monitor. Once you select your database, you can select which table you want to audit. You can customize right down to the field you’d like to audit, and then select which types of actions you’d like tracked – insert, delete, or update.  Repeat these steps for every database you want monitored. To create the logs, choose “Create triggers” in the menu.  The script written here will be what logs each insert, delete, and update function.  Press F5 to execute.  All this tracking information will be stored in AUDIT_LOG_DATA and AUDIT_LOG_TRANSACTIONS tables.  View these tables using ApexSQL Audit reports. These transaction logs can be extremely detailed – especially on very busy servers, where every move it traced.  Reading them can be overwhelming, to say the least.  Apex has tried to make things easier for the average DBA, though. You can read these tracking logs in Apex, and it will display data and objects that affect your server – even things that were happening on your server before you installed Apex! To read these logs, open Apex, and connect to that database you want to audit. Go to the Transaction Logs tab, and add the logs you want to read. To narrow down what results you want to see, you can use the Filter tab to choose time, operation type, name, users, and more. Click Open, and you can see the results in a grid (as shown below).  You can export these results to CSV, HTML, XML or SQL files and save on the hard disk. One of the advantages is that since there are no triggers here, there are no other processes that will affect SQL Server performance.  Using this method is also how to view history from your database that occurred before Apex was installed.  This type of tracking does require storage space for the data sources, as the database must be fully running, and the transaction logs must exist (things not stored in the transactions logs will not be recoverable). Apex can also replace SQL Server Profiler and SQL Server Traces – which are much more complex and error-prone – with its ApexSQL Comply.  It can do fault tolerant auditing, centralized reporting, and “who saw what” information in an easy-to-use interface.  The tracking settings can be altered by the user, or the default options will provide solutions to the most common auditing problems. To get started: open ApexSQL Comply, and selected Database Filter Settings to choose which database you’d like to audit.  You can select which tracking you’re like in Operation Types – DML, DDL, queries executed, execute statements, and more.  To get started, click Start Auditing. After this, every action will be stored in the central repository database (ApexSQLCrd).  You can view the audit and create a report (or view the standard default report) using a wizard. You can see how easy it is to use ApexSQL Comply.  You can easily set audits, including the type and time, and create customized reports.  Remote users can easily access the reports through the user interface (available online, as well), and security concerns are all taken care of by the program.  Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology

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  • SQL SERVER – Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2

    - by Pinal Dave
    This is the second part of the series Incremental Statistics. Here is the index of the complete series. What is Incremental Statistics? – Performance improvements in SQL Server 2014 – Part 1 Simple Example of Incremental Statistics – Performance improvements in SQL Server 2014 – Part 2 DMV to Identify Incremental Statistics – Performance improvements in SQL Server 2014 – Part 3 In part 1 we have understood what is incremental statistics and now in this second part we will see a simple example of incremental statistics. This blog post is heavily inspired from my friend Balmukund’s must read blog post. If you have partitioned table and lots of data, this feature can be specifically very useful. Prerequisite Here are two things you must know before you start with the demonstrations. AdventureWorks – For the demonstration purpose I have installed AdventureWorks 2012 as an AdventureWorks 2014 in this demonstration. Partitions – You should know how partition works with databases. Setup Script Here is the setup script for creating Partition Function, Scheme, and the Table. We will populate the table based on the SalesOrderDetails table from AdventureWorks. -- Use Database USE AdventureWorks2014 GO -- Create Partition Function CREATE PARTITION FUNCTION IncrStatFn (INT) AS RANGE LEFT FOR VALUES (44000, 54000, 64000, 74000) GO -- Create Partition Scheme CREATE PARTITION SCHEME IncrStatSch AS PARTITION [IncrStatFn] TO ([PRIMARY], [PRIMARY], [PRIMARY], [PRIMARY], [PRIMARY]) GO -- Create Table Incremental_Statistics CREATE TABLE [IncrStatTab]( [SalesOrderID] [int] NOT NULL, [SalesOrderDetailID] [int] NOT NULL, [CarrierTrackingNumber] [nvarchar](25) NULL, [OrderQty] [smallint] NOT NULL, [ProductID] [int] NOT NULL, [SpecialOfferID] [int] NOT NULL, [UnitPrice] [money] NOT NULL, [UnitPriceDiscount] [money] NOT NULL, [ModifiedDate] [datetime] NOT NULL) ON IncrStatSch(SalesOrderID) GO -- Populate Table INSERT INTO [IncrStatTab]([SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate]) SELECT     [SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate] FROM       [Sales].[SalesOrderDetail] WHERE      SalesOrderID < 54000 GO Check Details Now we will check details in the partition table IncrStatSch. -- Check the partition SELECT * FROM sys.partitions WHERE OBJECT_ID = OBJECT_ID('IncrStatTab') GO You will notice that only a few of the partition are filled up with data and remaining all the partitions are empty. Now we will create statistics on the Table on the column SalesOrderID. However, here we will keep adding one more keyword which is INCREMENTAL = ON. Please note this is the new keyword and feature added in SQL Server 2014. It did not exist in earlier versions. -- Create Statistics CREATE STATISTICS IncrStat ON [IncrStatTab] (SalesOrderID) WITH FULLSCAN, INCREMENTAL = ON GO Now we have successfully created statistics let us check the statistical histogram of the table. Now let us once again populate the table with more data. This time the data are entered into a different partition than earlier populated partition. -- Populate Table INSERT INTO [IncrStatTab]([SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate]) SELECT     [SalesOrderID], [SalesOrderDetailID], [CarrierTrackingNumber], [OrderQty], [ProductID], [SpecialOfferID], [UnitPrice],   [UnitPriceDiscount], [ModifiedDate] FROM       [Sales].[SalesOrderDetail] WHERE      SalesOrderID > 54000 GO Let us check the status of the partition once again with following script. -- Check the partition SELECT * FROM sys.partitions WHERE OBJECT_ID = OBJECT_ID('IncrStatTab') GO Statistics Update Now here has the new feature come into action. Previously, if we have to update the statistics, we will have to FULLSCAN the entire table irrespective of which partition got the data. However, in SQL Server 2014 we can just specify which partition we want to update in terms of Statistics. Here is the script for the same. -- Update Statistics Manually UPDATE STATISTICS IncrStatTab (IncrStat) WITH RESAMPLE ON PARTITIONS(3, 4) GO Now let us check the statistics once again. -- Show Statistics DBCC SHOW_STATISTICS('IncrStatTab', IncrStat) WITH HISTOGRAM GO Upon examining statistics histogram, you will notice that now the distribution has changed and there is way more rows in the histogram. Summary The new feature of Incremental Statistics is indeed a boon for the scenario where there are partitions and statistics needs to be updated frequently on the partitions. In earlier version to update statistics one has to do FULLSCAN on the entire table which was wasting too many resources. With the new feature in SQL Server 2014, now only those partitions which are significantly changed can be specified in the script to update statistics. Cleanup You can clean up the database by executing following scripts. -- Clean up DROP TABLE [IncrStatTab] DROP PARTITION SCHEME [IncrStatSch] DROP PARTITION FUNCTION [IncrStatFn] GO Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: PostADay, SQL, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SQL Statistics, Statistics

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  • SQL SERVER – Parsing SSIS Catalog Messages – Notes from the Field #030

    - by Pinal Dave
    [Note from Pinal]: This is a new episode of Notes from the Field series. SQL Server Integration Service (SSIS) is one of the most key essential part of the entire Business Intelligence (BI) story. It is a platform for data integration and workflow applications. The tool may also be used to automate maintenance of SQL Server databases and updates to multidimensional cube data. In this episode of the Notes from the Field series I requested SSIS Expert Andy Leonard to discuss one of the most interesting concepts of SSIS Catalog Messages. There are plenty of interesting and useful information captured in the SSIS catalog and we will learn together how to explore the same. The SSIS Catalog captures a lot of cool information by default. Here’s a query I use to parse messages from the catalog.operation_messages table in the SSISDB database, where the logged messages are stored. This query is set up to parse a default message transmitted by the Lookup Transformation. It’s one of my favorite messages in the SSIS log because it gives me excellent information when I’m tuning SSIS data flows. The message reads similar to: Data Flow Task:Information: The Lookup processed 4485 rows in the cache. The processing time was 0.015 seconds. The cache used 1376895 bytes of memory. The query: USE SSISDB GO DECLARE @MessageSourceType INT = 60 DECLARE @StartOfIDString VARCHAR(100) = 'The Lookup processed ' DECLARE @ProcessingTimeString VARCHAR(100) = 'The processing time was ' DECLARE @CacheUsedString VARCHAR(100) = 'The cache used ' DECLARE @StartOfIDSearchString VARCHAR(100) = '%' + @StartOfIDString + '%' DECLARE @ProcessingTimeSearchString VARCHAR(100) = '%' + @ProcessingTimeString + '%' DECLARE @CacheUsedSearchString VARCHAR(100) = '%' + @CacheUsedString + '%' SELECT operation_id , SUBSTRING(MESSAGE, (PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1)) - (PATINDEX(@StartOfIDSearchString, MESSAGE) + LEN(@StartOfIDString) + 1))) AS LookupRowsCount , SUBSTRING(MESSAGE, (PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1)) - (PATINDEX(@ProcessingTimeSearchString, MESSAGE) + LEN(@ProcessingTimeString) + 1))) AS LookupProcessingTime , CASE WHEN (CONVERT(numeric(3,3),SUBSTRING(MESSAGE, (PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1)) - (PATINDEX(@ProcessingTimeSearchString, MESSAGE) + LEN(@ProcessingTimeString) + 1))))) = 0 THEN 0 ELSE CONVERT(bigint,SUBSTRING(MESSAGE, (PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1)) - (PATINDEX(@StartOfIDSearchString, MESSAGE) + LEN(@StartOfIDString) + 1)))) / CONVERT(numeric(3,3),SUBSTRING(MESSAGE, (PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@ProcessingTimeSearchString,MESSAGE) + LEN(@ProcessingTimeString) + 1)) - (PATINDEX(@ProcessingTimeSearchString, MESSAGE) + LEN(@ProcessingTimeString) + 1)))) END AS LookupRowsPerSecond , SUBSTRING(MESSAGE, (PATINDEX(@CacheUsedSearchString,MESSAGE) + LEN(@CacheUsedString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@CacheUsedSearchString,MESSAGE) + LEN(@CacheUsedString) + 1)) - (PATINDEX(@CacheUsedSearchString, MESSAGE) + LEN(@CacheUsedString) + 1))) AS LookupBytesUsed ,CASE WHEN (CONVERT(bigint,SUBSTRING(MESSAGE, (PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1)) - (PATINDEX(@StartOfIDSearchString, MESSAGE) + LEN(@StartOfIDString) + 1)))))= 0 THEN 0 ELSE CONVERT(bigint,SUBSTRING(MESSAGE, (PATINDEX(@CacheUsedSearchString,MESSAGE) + LEN(@CacheUsedString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@CacheUsedSearchString,MESSAGE) + LEN(@CacheUsedString) + 1)) - (PATINDEX(@CacheUsedSearchString, MESSAGE) + LEN(@CacheUsedString) + 1)))) / CONVERT(bigint,SUBSTRING(MESSAGE, (PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1), ((CHARINDEX(' ', MESSAGE, PATINDEX(@StartOfIDSearchString,MESSAGE) + LEN(@StartOfIDString) + 1)) - (PATINDEX(@StartOfIDSearchString, MESSAGE) + LEN(@StartOfIDString) + 1)))) END AS LookupBytesPerRow FROM [catalog].[operation_messages] WHERE message_source_type = @MessageSourceType AND MESSAGE LIKE @StartOfIDSearchString GO Note that you have to set some parameter values: @MessageSourceType [int] – represents the message source type value from the following results: Value     Description 10           Entry APIs, such as T-SQL and CLR Stored procedures 20           External process used to run package (ISServerExec.exe) 30           Package-level objects 40           Control Flow tasks 50           Control Flow containers 60           Data Flow task 70           Custom execution message Note: Taken from Reza Rad’s (excellent!) helper.MessageSourceType table found here. @StartOfIDString [VarChar(100)] – use this to uniquely identify the message field value you wish to parse. In this case, the string ‘The Lookup processed ‘ identifies all the Lookup Transformation messages I desire to parse. @ProcessingTimeString [VarChar(100)] – this parameter is message-specific. I use this parameter to specifically search the message field value for the beginning of the Lookup Processing Time value. For this execution, I use the string ‘The processing time was ‘. @CacheUsedString [VarChar(100)] – this parameter is also message-specific. I use this parameter to specifically search the message field value for the beginning of the Lookup Cache  Used value. It returns the memory used, in bytes. For this execution, I use the string ‘The cache used ‘. The other parameters are built from variations of the parameters listed above. The query parses the values into text. The string values are converted to numeric values for ratio calculations; LookupRowsPerSecond and LookupBytesPerRow. Since ratios involve division, CASE statements check for denominators that equal 0. Here are the results in an SSMS grid: This is not the only way to retrieve this information. And much of the code lends itself to conversion to functions. If there is interest, I will share the functions in an upcoming post. If you want to get started with SSIS 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 Backup and Restore, SQL Query, SQL Server, SQL Tips and Tricks, T SQL Tagged: SSIS

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  • SQL SERVER – SSMS: Top Object and Batch Execution Statistics Reports

    - by Pinal Dave
    The month of June till mid of July has been the fever of sports. First, it was Wimbledon Tennis and then the Soccer fever was all over. There is a huge number of fan followers and it is great to see the level at which people sometimes worship these sports. Being an Indian, I cannot forget to mention the India tour of England later part of July. Following these sports and as the events unfold to the finals, there are a number of ways the statisticians can slice and dice the numbers. Cue from soccer I can surely say there is a team performance against another team and then there is individual member fairs against a particular opponent. Such statistics give us a fair idea to how a team in the past or in the recent past has fared against each other, head-to-head stats during World cup and during other neutral venue games. All these statistics are just pointers. In reality, they don’t reflect the calibre of the current team because the individuals who performed in each of these games are totally different (Typical example being the Brazil Vs Germany semi-final match in FIFA 2014). So at times these numbers are misleading. It is worth investigating and get the next level information. Similar to these statistics, SQL Server Management studio is also equipped with a number of reports like a) Object Execution Statistics report and b) Batch Execution Statistics reports. As discussed in the example, the team scorecard is like the Batch Execution statistics and individual stats is like Object Level statistics. The analogy can be taken only this far, trust me there is no correlation between SQL Server functioning and playing sports – It is like I think about diet all the time except while I am eating. Performance – Batch Execution Statistics Let us view the first report which can be invoked from Server Node -> Reports -> Standard Reports -> Performance – Batch Execution Statistics. Most of the values that are displayed in this report come from the DMVs sys.dm_exec_query_stats and sys.dm_exec_sql_text(sql_handle). This report contains 3 distinctive sections as outline below.   Section 1: This is a graphical bar graph representation of Average CPU Time, Average Logical reads and Average Logical Writes for individual batches. The Batch numbers are indicative and the details of individual batch is available in section 3 (detailed below). Section 2: This represents a Pie chart of all the batches by Total CPU Time (%) and Total Logical IO (%) by batches. This graphical representation tells us which batch consumed the highest CPU and IO since the server started, provided plan is available in the cache. Section 3: This is the section where we can find the SQL statements associated with each of the batch Numbers. This also gives us the details of Average CPU / Average Logical Reads and Average Logical Writes in the system for the given batch with object details. Expanding the rows, I will also get the # Executions and # Plans Generated for each of the queries. Performance – Object Execution Statistics The second report worth a look is Object Execution statistics. This is a similar report as the previous but turned on its head by SQL Server Objects. The report has 3 areas to look as above. Section 1 gives the Average CPU, Average IO bar charts for specific objects. The section 2 is a graphical representation of Total CPU by objects and Total Logical IO by objects. The final section details the various objects in detail with the Avg. CPU, IO and other details which are self-explanatory. At a high-level both the reports are based on queries on two DMVs (sys.dm_exec_query_stats and sys.dm_exec_sql_text) and it builds values based on calculations using columns in them: SELECT * FROM    sys.dm_exec_query_stats s1 CROSS APPLY sys.dm_exec_sql_text(sql_handle) AS s2 WHERE   s2.objectid IS NOT NULL AND DB_NAME(s2.dbid) IS NOT NULL ORDER BY  s1.sql_handle; This is one of the simplest form of reports and in future blogs we will look at more complex reports. I truly hope that these reports can give DBAs and developers a hint about what is the possible performance tuning area. As a closing point I must emphasize that all above reports pick up data from the plan cache. If a particular query has consumed a lot of resources earlier, but plan is not available in the cache, none of the above reports would show that bad query. Reference: Pinal Dave (http://blog.sqlauthority.com)Filed under: 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 – Planned and Unplanned Availablity Group Failovers – Notes from the Field #031

    - by Pinal Dave
    [Note from Pinal]: This is a new episode of Notes from the Fields series. AlwaysOn is a very complex subject and not everyone knows many things about this. The matter of the fact is there is very little information available on this subject online and not everyone knows everything about this. This is why when a very common question related to AlwaysOn comes, people get confused. In this episode of the Notes from the Field series database expert John Sterrett (Group Principal at Linchpin People) explains a very common issue DBAs and Developer faces in their career and is related to Planned and Unplanned Availablity Group Failovers. Linchpin People are database coaches and wellness experts for a data driven world. Read the experience of John in his own words. Whenever a disaster occurs it will be a stressful scenario regardless of how small or big the disaster is. This gets multiplied when it is your first time working with newer technology or the first time you are going through a disaster without a proper run book. Today, were going to help you establish a run book for creating a planned failover with availability groups. To make today’s session simple were going to have two instances of SQL Server 2012 included in an availability group and walk through the steps of doing an unplanned failover.  We will focus on using the user interface and T-SQL to complete the failovers. We are going to use a two replica Availability Group where each replica is in another location. Therefore, we will be covering Asynchronous (non automatic failover) the following is a breakdown of our availability group utilized today. Seeing the following screen might be scary the first time you come across an unplanned failover.  It looks like our test database used in this Availability Group is not functional and it currently isn’t. The database status is not synchronizing which makes sense because the primary replica went down so it couldn’t synchronize. With that said, we can still failover and make it functional while we troubleshoot why we lost our primary replica. To start we are going to right click on the availability group that needs to be restarted and select failover. This will bring up the following wizard, which will walk you through several steps needed to complete the failover using the graphical user interface provided with SQL Server Management Studio (SSMS). You are going to see warning messages simply because we are in Asynchronous commit mode and can not guarantee ‘no data loss’ when we do failover. Just incase you missed it; you get another screen warning you about potential data loss because we are in Asynchronous mode. Next we get to connect to the specific replica we want to become the primary replica after the failover occurs. In our case, we only have two replicas so this is trivial. In order to failover, it’s required to connect to the replica that will become primary.  The following screen shows that the connection has been made successfully. Next, you will see the final summary screen. Once again, this reminds you that the failover action will cause data loss as were using Asynchronous commit mode due to the distance between instances used for disaster recovery. Finally, once the failover is completed you will see the following screen. If you followed along this long you might be wondering what T-SQL scripts are generated for clicking through all the sections of the wizard. If you have used Database Mirroring in the past you might be surprised.  It’s not too different, which makes sense because the data is being replicated via SQL Server endpoints just like the good old database mirroring. Now were going to take a look at how to do a failover with just T-SQL. First, were going to need to open a new query window and run our query in SQLCMD mode. Just incase you haven’t used SQLCMD mode before we will show you how to enable it below. Now you can run the following statement. Notice, we connect to the replica we want to become primary after failover and specify to force failover to allow data loss. We can use the following script to failback over when our primary instance comes back online. -- YOU MUST EXECUTE THE FOLLOWING SCRIPT IN SQLCMD MODE. :Connect SQL2012PROD1 ALTER AVAILABILITY GROUP [AGSQL2] FORCE_FAILOVER_ALLOW_DATA_LOSS; GO Are your servers running at optimal speed or are you facing any SQL Server Performance Problems? If you want to get started with the help of experts read more over here: 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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  • Big Data – Evolution of Big Data – Day 3 of 21

    - by Pinal Dave
    In yesterday’s blog post we answered what is the Big Data. Today we will understand why and how the evolution of Big Data has happened. Though the answer is very simple, I would like to tell it in the form of a history lesson. Data in Flat File In earlier days data was stored in the flat file and there was no structure in the flat file.  If any data has to be retrieved from the flat file it was a project by itself. There was no possibility of retrieving the data efficiently and data integrity has been just a term discussed without any modeling or structure around. Database residing in the flat file had more issues than we would like to discuss in today’s world. It was more like a nightmare when there was any data processing involved in the application. Though, applications developed at that time were also not that advanced the need of the data was always there and there was always need of proper data management. Edgar F Codd and 12 Rules Edgar Frank Codd was a British computer scientist who, while working for IBM, invented the relational model for database management, the theoretical basis for relational databases. He presented 12 rules for the Relational Database and suddenly the chaotic world of the database seems to see discipline in the rules. Relational Database was a promising land for all the unstructured database users. Relational Database brought into the relationship between data as well improved the performance of the data retrieval. Database world had immediately seen a major transformation and every single vendors and database users suddenly started to adopt the relational database models. Relational Database Management Systems Since Edgar F Codd proposed 12 rules for the RBDMS there were many different vendors who started them to build applications and tools to support the relationship between database. This was indeed a learning curve for many of the developer who had never worked before with the modeling of the database. However, as time passed by pretty much everybody accepted the relationship of the database and started to evolve product which performs its best with the boundaries of the RDBMS concepts. This was the best era for the databases and it gave the world extreme experts as well as some of the best products. The Entity Relationship model was also evolved at the same time. In software engineering, an Entity–relationship model (ER model) is a data model for describing a database in an abstract way. Enormous Data Growth Well, everything was going fine with the RDBMS in the database world. As there were no major challenges the adoption of the RDBMS applications and tools was pretty much universal. There was a race at times to make the developer’s life much easier with the RDBMS management tools. Due to the extreme popularity and easy to use system pretty much every data was stored in the RDBMS system. New age applications were built and social media took the world by the storm. Every organizations was feeling pressure to provide the best experience for their users based the data they had with them. While this was all going on at the same time data was growing pretty much every organization and application. Data Warehousing The enormous data growth now presented a big challenge for the organizations who wanted to build intelligent systems based on the data and provide near real time superior user experience to their customers. Various organizations immediately start building data warehousing solutions where the data was stored and processed. The trend of the business intelligence becomes the need of everyday. Data was received from the transaction system and overnight was processed to build intelligent reports from it. Though this is a great solution it has its own set of challenges. The relational database model and data warehousing concepts are all built with keeping traditional relational database modeling in the mind and it still has many challenges when unstructured data was present. Interesting Challenge Every organization had expertise to manage structured data but the world had already changed to unstructured data. There was intelligence in the videos, photos, SMS, text, social media messages and various other data sources. All of these needed to now bring to a single platform and build a uniform system which does what businesses need. The way we do business has also been changed. There was a time when user only got the features what technology supported, however, now users ask for the feature and technology is built to support the same. The need of the real time intelligence from the fast paced data flow is now becoming a necessity. Large amount (Volume) of difference (Variety) of high speed data (Velocity) is the properties of the data. The traditional database system has limits to resolve the challenges this new kind of the data presents. Hence the need of the Big Data Science. We need innovation in how we handle and manage data. We need creative ways to capture data and present to users. Big Data is Reality! Tomorrow In tomorrow’s blog post we will try to answer discuss Basics of Big Data Architecture. 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

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  • SQL SERVER – SSIS Parameters in Parent-Child ETL Architectures – Notes from the Field #040

    - by Pinal Dave
    [Notes from Pinal]: SSIS is very well explored subject, however, there are so many interesting elements when we read, we learn something new. A similar concept has been Parent-Child ETL architecture’s relationship in SSIS. Linchpin People are database coaches and wellness experts for a data driven world. In this 40th episode of the Notes from the Fields series database expert Tim Mitchell (partner at Linchpin People) shares very interesting conversation related to how to understand SSIS Parameters in Parent-Child ETL Architectures. In this brief Notes from the Field post, I will review the use of SSIS parameters in parent-child ETL architectures. A very common design pattern used in SQL Server Integration Services is one I call the parent-child pattern.  Simply put, this is a pattern in which packages are executed by other packages.  An ETL infrastructure built using small, single-purpose packages is very often easier to develop, debug, and troubleshoot than large, monolithic packages.  For a more in-depth look at parent-child architectures, check out my earlier blog post on this topic. When using the parent-child design pattern, you will frequently need to pass values from the calling (parent) package to the called (child) package.  In older versions of SSIS, this process was possible but not necessarily simple.  When using SSIS 2005 or 2008, or even when using SSIS 2012 or 2014 in package deployment mode, you would have to create package configurations to pass values from parent to child packages.  Package configurations, while effective, were not the easiest tool to work with.  Fortunately, starting with SSIS in SQL Server 2012, you can now use package parameters for this purpose. In the example I will use for this demonstration, I’ll create two packages: one intended for use as a child package, and the other configured to execute said child package.  In the parent package I’m going to build a for each loop container in SSIS, and use package parameters to pass in a value – specifically, a ClientID – for each iteration of the loop.  The child package will be executed from within the for each loop, and will create one output file for each client, with the source query and filename dependent on the ClientID received from the parent package. Configuring the Child and Parent Packages When you create a new package, you’ll see the Parameters tab at the package level.  Clicking over to that tab allows you to add, edit, or delete package parameters. As shown above, the sample package has two parameters.  Note that I’ve set the name, data type, and default value for each of these.  Also note the column entitled Required: this allows me to specify whether the parameter value is optional (the default behavior) or required for package execution.  In this example, I have one parameter that is required, and the other is not. Let’s shift over to the parent package briefly, and demonstrate how to supply values to these parameters in the child package.  Using the execute package task, you can easily map variable values in the parent package to parameters in the child package. The execute package task in the parent package, shown above, has the variable vThisClient from the parent package mapped to the pClientID parameter shown earlier in the child package.  Note that there is no value mapped to the child package parameter named pOutputFolder.  Since this parameter has the Required property set to False, we don’t have to specify a value for it, which will cause that parameter to use the default value we supplied when designing the child pacakge. The last step in the parent package is to create the for each loop container I mentioned earlier, and place the execute package task inside it.  I’m using an object variable to store the distinct client ID values, and I use that as the iterator for the loop (I describe how to do this more in depth here).  For each iteration of the loop, a different client ID value will be passed into the child package parameter. The final step is to configure the child package to actually do something meaningful with the parameter values passed into it.  In this case, I’ve modified the OleDB source query to use the pClientID value in the WHERE clause of the query to restrict results for each iteration to a single client’s data.  Additionally, I’ll use both the pClientID and pOutputFolder parameters to dynamically build the output filename. As shown, the pClientID is used in the WHERE clause, so we only get the current client’s invoices for each iteration of the loop. For the flat file connection, I’m setting the Connection String property using an expression that engages both of the parameters for this package, as shown above. Parting Thoughts There are many uses for package parameters beyond a simple parent-child design pattern.  For example, you can create standalone packages (those not intended to be used as a child package) and still use parameters.  Parameter values may be supplied to a package directly at runtime by a SQL Server Agent job, through the command line (via dtexec.exe), or through T-SQL. Also, you can also have project parameters as well as package parameters.  Project parameters work in much the same way as package parameters, but the parameters apply to all packages in a project, not just a single package. Conclusion Of the numerous advantages of using catalog deployment model in SSIS 2012 and beyond, package parameters are near the top of the list.  Parameters allow you to easily share values from parent to child packages, enabling more dynamic behavior and better code encapsulation. If you want me to take a look at your server and its settings, or if your server is facing any issue we can 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 – The Story of a Lesser Known Startup Parameter in SQL Server – Guest Post by Balmukund Lakhani

    - by Pinal Dave
    This is a fantastic blog post from my dear friend Balmukund ( blog | twitter | facebook ). He had presented a fantastic session in our last UG and there were lots of requests from attendees that he blogs about it. Well, here is the blog post about the same very popular UG session. Let us read the entire blog post in the voice of the Balmukund himself. During my last session in SQL Bangalore User Group (Facebook) meeting, I was lucky enough to deliver a session on SQL Server Startup issue. The name of the session was “SQL Engine Starting Trouble – How to start?” From the feedback, I realized that one of the “not well known” startup parameter is “-m”. Okay, you might say “I know that this is used to start the SQL in single user mode”. But what you might not know is that you can pass a string with -m which has special meaning and use. I have used this parameter in my blog here but looks like not many of you have seen that. It happens most of the time when we want to start SQL Server in single user mode, someone else makes connection before you can. The only choice you have is to repeat same process again till you succeed. Some smart DBAs may disable the remote network protocols (TCP/IP and Named Pipes) of SQL Instance and allow only local connections to SQL. Once the activity is complete, our dear smart DBA has to remember to re-enable network protocols. Sometimes, it may be a local service or application getting connection to SQL before we can. There is a better way to deal with it. Yes, you have guessed it correctly: -m parameter which a string. Since I work with SQL Product Support team, I may know little more undocumented commands and parameters, but this is not an undocumented stuff. It’s already documented in books online. So in this blog, I am going to show a demo of its usage. As documentation shows, “Do not use this option as a security feature.” So please read this blog as knowledge enhancer and troubleshooting issues not security feature. In my laptop, I have a default instance of SQL Server 2012 and here is what we would in the configuration manager. Now, I would go ahead and stop SQL Service by selecting SQL Server (MSSQLServer) > Right Click > Stop. There are multiple ways to start SQL with startup parameter. 1) Use Net Start Command from command prompt Net Start MSSQLServer /mSQLCMD The above command is the simplest way to add startup parameter to SQL. This parameter would be cleared once we stop and start SQL. 2) Add Startup Parameter via configuration manager. Step is already listed here. We need to add -mSQLCMD If we compare 1 and 2, it’s clear that unless we modify startup parameter and remove -m, it would be in effect. 3) Start SQL Service via command line SQLServr.exe –mSQLCMD –s<InstanceName> Wait, what does SQLCMD mean with /m? It’s the instruction to SQL that start SQL Server in Single User Mode and allow only the application which is SQLCMD. Any other application would fail with Login Failed for User Error message. It would be important to note that string is case sensitive. This value should be picked up from application_name column from sys.dm_exec_sessions. I have made a connection using SQLCMD and as we can see it comes as upper case “SQLCMD”. If we want only management studio query windows to connect then we need to give -m” Microsoft SQL Server Management Studio – Query” as startup parameter. In below example, I have given it as SQLCMd (lower case d at the end) and we would notice that we would not be able to connect to SQL Instance. Above proves that parameter works as expected and it’s case sensitive. Error Log would show below information. How to get error log location? I have already blogged about it. Hope you have learned something new. 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, Technology

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  • Big Data – Various Learning Resources – How to Start with Big Data? – Day 20 of 21

    - by Pinal Dave
    In yesterday’s blog post we learned how to become a Data Scientist for Big Data. In this article we will go over various learning resources related to Big Data. In this series we have covered many of the most essential details about Big Data. At the beginning of this series, I have encouraged readers to send me questions. One of the most popular questions is - “I want to learn more about Big Data. Where can I learn it?” This is indeed a great question as there are plenty of resources out to learn about Big Data and it is indeed difficult to select on one resource to learn Big Data. Hence I decided to write here a few of the very important resources which are related to Big Data. Learn from Pluralsight Pluralsight is a global leader in high-quality online training for hardcore developers.  It has fantastic Big Data Courses and I started to learn about Big Data with the help of Pluralsight. Here are few of the courses which are directly related to Big Data. Big Data: The Big Picture Big Data Analytics with Tableau NoSQL: The Big Picture Understanding NoSQL Data Analysis Fundamentals with Tableau I encourage all of you start with this video course as they are fantastic fundamentals to learn Big Data. Learn from Apache Resources at Apache are single point the most authentic learning resources. If you want to learn fundamentals and go deep about every aspect of the Big Data, I believe you must understand various concepts in Apache’s library. I am pretty impressed with the documentation and I am personally referencing it every single day when I work with Big Data. I strongly encourage all of you to bookmark following all the links for authentic big data learning. Haddop - The Apache Hadoop® project develops open-source software for reliable, scalable, distributed computing. Ambari: A web-based tool for provisioning, managing, and monitoring Apache Hadoop clusters which include support for Hadoop HDFS, Hadoop MapReduce, Hive, HCatalog, HBase, ZooKeeper, Oozie, Pig and Sqoop. Ambari also provides a dashboard for viewing cluster health such as heat maps and ability to view MapReduce, Pig and Hive applications visually along with features to diagnose their performance characteristics in a user-friendly manner. Avro: A data serialization system. Cassandra: A scalable multi-master database with no single points of failure. Chukwa: A data collection system for managing large distributed systems. HBase: A scalable, distributed database that supports structured data storage for large tables. Hive: A data warehouse infrastructure that provides data summarization and ad hoc querying. Mahout: A Scalable machine learning and data mining library. Pig: A high-level data-flow language and execution framework for parallel computation. ZooKeeper: A high-performance coordination service for distributed applications. Learn from Vendors One of the biggest issues with about learning Big Data is setting up the environment. Every Big Data vendor has different environment request and there are lots of things require to set up Big Data framework. Many of the users do not start with Big Data as they are afraid about the resources required to set up framework as well as a time commitment. Here Hortonworks have created fantastic learning environment. They have created Sandbox with everything one person needs to learn Big Data and also have provided excellent tutoring along with it. Sandbox comes with a dozen hands-on tutorial that will guide you through the basics of Hadoop as well it contains the Hortonworks Data Platform. I think Hortonworks did a fantastic job building this Sandbox and Tutorial. Though there are plenty of different Big Data Vendors I have decided to list only Hortonworks due to their unique setup. Please leave a comment if there are any other such platform to learn Big Data. I will include them over here as well. Learn from Books There are indeed few good books out there which one can refer to learn Big Data. Here are few good books which I have read. I will update the list as I will learn more. Ethics of Big Data Balancing Risk and Innovation Big Data for Dummies Head First Data Analysis: A Learner’s Guide to Big Numbers, Statistics, and Good Decisions If you search on Amazon there are millions of the books but I think above three books are a great set of books and it will give you great ideas about Big Data. Once you go through above books, you will have a clear idea about what is the next step you should follow in this series. You will be capable enough to make the right decision for yourself. Tomorrow In tomorrow’s blog post we will wrap up this series of Big Data. 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

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  • SQL SERVER – SSMS: Database Consistency History Report

    - by Pinal Dave
    Doctor and Database The last place I like to visit is always a hospital. With the monsoon season starting, intermittent rains, it has become sort of a routine to get a cycle of fever every other year (seriously I hate it). So when I visit my doctor, it is always interesting in the way he quizzes me. The routine question of – “How many days have you had this?”, “Is there any pattern?”, “Did you drench in rain?”, “Do you have any other symptom?” and so on. The idea here is that the doctor wants to find any anomaly or a pattern that will guide him to a viral or bacterial type. Most of the time they get it based on experience and sometimes after a battery of tests. So if there is consistent behavior to your problem, there is always a solution out. SQL Server has its way to find if the server data / files are in consistent state using the DBCC commands. Back to SQL Server In real life, Database consistency check is one of the critical operations a DBA generally doesn’t give much priority. Many readers of my blogs have asked many times, how do we know if the database is consistent? How do I read output of DBCC CHECKDB and find if everything is right or not? My common answer to all of them is – look at the bottom of checkdb (or checktable) output and look for below line. CHECKDB found 0 allocation errors and 0 consistency errors in database ‘DatabaseName’. Above is a “good sign” because we are seeing zero allocation and zero consistency error. If you are seeing non-zero errors then there is some problem with the database. Sample output is shown as below: CHECKDB found 0 allocation errors and 2 consistency errors in database ‘DatabaseName’. repair_allow_data_loss is the minimum repair level for the errors found by DBCC CHECKDB (DatabaseName). If we see non-zero error then most of the time (not always) we get repair options depending on the level of corruption. There is risk involved with above option (repair_allow_data_loss), that is – we would lose the data. Sometimes the option would be repair_rebuild which is little safer. Though these options are available, it is important to find the root cause to the problem. In standard report, there is a report which can show the history of checkdb executed for the selected database. Since this is a database level report, we need to right click on database, click Reports, click Standard Reports and then choose “Database Consistency History” report. The information in this report is picked from default trace. If default trace is disabled or there is no checkdb run or information is not there in default trace (because it’s rolled over), we would get report like below. As we can see report says it very clearly: Currently, no execution history of CHECKDB is available or default trace is not enabled. To demonstrate, I have caused corruption in one of the database and did below steps. Run CheckDB so that errors are reported. Fix the corruption by losing the data using repair option Run CheckDB again to check if corruption is cleared. After that I have launched the report and below is what we would see. If you are lazy like me and don’t want to run the report manually for each database then below query would be handy to provide same report for all database. This query is runs behind the scenes by the report. All I have done is remove the filter for database name (at the last – highlighted). DECLARE @curr_tracefilename VARCHAR(500); DECLARE @base_tracefilename VARCHAR(500); DECLARE @indx INT; SELECT @curr_tracefilename = path FROM sys.traces WHERE is_default = 1; SET @curr_tracefilename = REVERSE(@curr_tracefilename); SELECT @indx  = PATINDEX('%\%', @curr_tracefilename) ; SET @curr_tracefilename = REVERSE(@curr_tracefilename); SET @base_tracefilename = LEFT( @curr_tracefilename,LEN(@curr_tracefilename) - @indx) + '\log.trc'; SELECT  SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),36, PATINDEX('%executed%',TEXTData)-36) AS command ,       LoginName ,       StartTime ,       CONVERT(INT,SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%found%',TEXTData) +6,PATINDEX('%errors %',TEXTData)-PATINDEX('%found%',TEXTData)-6)) AS errors ,       CONVERT(INT,SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%repaired%',TEXTData) +9,PATINDEX('%errors.%',TEXTData)-PATINDEX('%repaired%',TEXTData)-9)) repaired ,       SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%time:%',TEXTData)+6,PATINDEX('%hours%',TEXTData)-PATINDEX('%time:%',TEXTData)-6)+':'+SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%hours%',TEXTData) +6,PATINDEX('%minutes%',TEXTData)-PATINDEX('%hours%',TEXTData)-6)+':'+SUBSTRING(CONVERT(NVARCHAR(MAX),TEXTData),PATINDEX('%minutes%',TEXTData) +8,PATINDEX('%seconds.%',TEXTData)-PATINDEX('%minutes%',TEXTData)-8) AS time FROM::fn_trace_gettable( @base_tracefilename, DEFAULT) WHERE EventClass = 22 AND SUBSTRING(TEXTData,36,12) = 'DBCC CHECKDB' -- AND DatabaseName = @DatabaseName; Don’t get worried about the logic above. All it is doing is reading the trace files, parsing below entry and getting out information for underlined words. DBCC CHECKDB (CorruptedDatabase) executed by sa found 2 errors and repaired 0 errors. Elapsed time: 0 hours 0 minutes 0 seconds.  Internal database snapshot has split point LSN = 00000029:00000030:0001 and first LSN = 00000029:00000020:0001. Hopefully now onwards you would run checkdb and understand the importance of it. As responsible DBAs I am sure you are already doing it, let me know how often do you actually run them on you production environment? 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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