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  • SQLAuthority News – TechEd India – April 12-14, 2010 Bangalore – An Unforgettable Experience – An Op

    - by pinaldave
    TechEd India was one of the largest Technology events in India led by Microsoft. This event was attended by more than 3,000 technology enthusiasts, making it one of the most well-organized events of the year. Though I attempted to attend almost all the technology events here, I have not seen any bigger or better event in Indian subcontinents other than this. There are 21 Technical Tracks at Tech·Ed India 2010 that span more than 745 learning opportunities. I was fortunate enough to be a part of this whole event as a speaker and a delegate, as well. TechEd India Speaker Badge and A Token of Lifetime Hotel Selection I presented three different sessions at TechEd India and was also a part of panel discussion. (The details of the sessions are given at the end of this blog post.) Due to extensive traveling, I stay away from my family occasionally. For this reason, I took my wife – Nupur and daughter Shaivi (8 months old) to the event along with me. We stayed at the same hotel where the event was organized so as to maximize my time bonding with my family and to have more time in networking with technology community, at the same time. The hotel Lalit Ashok is the largest and most luxurious venue one can find in Bangalore, located in the middle of the city. The cost of the hotel was a bit pricey, but looking at all the advantages, I had decided to ask for a booking there. Hotel Lalit Ashok Nupur Dave and Shaivi Dave Arrival Day – DAY 0 – April 11, 2010 I reached the event a day earlier, and that was one wise decision for I was able to relax a bit and go over my presentation for the next day’s course. I am a kind of person who likes to get everything ready ahead of time. I was also able to enjoy a pleasant evening with several Microsoft employees and my family friends. I even checked out the location where I would be doing presentations the next day. I was fortunate enough to meet Bijoy Singhal from Microsoft who helped me out with a few of the logistics issues that occured the day before. I was not aware of the fact that the very next day he was going to be “The Man” of the TechEd 2010 event. Vinod Kumar from Microsoft was really very kind as he talked to me regarding my subsequent session. He gave me some suggestions which were really helpful that I was able to incorporate them during my presentation. Finally, I was able to meet Abhishek Kant from Microsoft; his valuable suggestions and unlimited passion have inspired many people like me to work with the Community. Pradipta from Microsoft was also around, being extremely busy with logistics; however, in those busy times, he did find some good spare time to have a chat with me and the other Community leaders. I also met Harish Ranganathan and Sachin Rathi, both from Microsoft. It was so interesting to listen to both of them talking about SharePoint. I just have no words to express my overwhelmed spirit because of all these passionate young guys - Pradipta,Vinod, Bijoy, Harish, Sachin and Ahishek (of course!). Map of TechEd India 2010 Event Day 1 – April 12, 2010 From morning until night time, today was truly a very busy day for me. I had two presentations and one panel discussion for the day. Needless to say, I had a few meetings to attend as well. The day started with a keynote from S. Somaseger where he announced the launch of Visual Studio 2010. The keynote area was really eye-catching because of the very large, bigger-than- life uniform screen. This was truly one to show. The title music of the keynote was very interesting and it featured Bijoy Singhal as the model. It was interesting to talk to him afterwards, when we laughed at jokes together about his modeling assignment. TechEd India Keynote Opening Featuring Bijoy TechEd India 2010 Keynote – S. Somasegar Time: 11:15pm – 11:45pm Session 1: True Lies of SQL Server – SQL Myth Buster Following the excellent keynote, I had my very first session on the subject of SQL Server Myth Buster. At first, I was a bit nervous as right after the keynote, for this was my very first session and during my presentation I saw lots of Microsoft Product Team members. Well, it really went well and I had a really good discussion with attendees of the session. I felt that a well begin was half-done and my confidence was regained. Right after the session, I met a few of my Community friends and had meaningful discussions with them on many subjects. The abstract of the session is as follows: In this 30-minute demo session, I am going to briefly demonstrate few SQL Server Myths and their resolutions as I back them up with some demo. This demo presentation is a must-attend for all developers and administrators who would come to the event. This is going to be a very quick yet fun session. Pinal Presenting session at TechEd India 2010 Time: 1:00 PM – 2:00 PM Lunch with Somasegar After the session I went to see my daughter, and then I headed right away to the lunch with S. Somasegar – the keynote speaker and senior vice president of the Developer Division at Microsoft. I really thank to Abhishek who made it possible for us. Because of his efforts, all the MVPs had the opportunity to meet such a legendary person and had to talk with them on Microsoft Technology. Though Somasegar is currently holding such a high position in Microsoft, he is very polite and a real gentleman, and how I wish that everybody in industry is like him. Believe me, if you spread love and kindness, then that is what you will receive back. As soon as lunch time was over, I ran to the session hall as my second presentation was about to start. Time: 2:30pm – 3:30pm Session 2: Master Data Services in Microsoft SQL Server 2008 R2 Business Intelligence is a subject which was widely talked about at TechEd. Everybody was interested in this subject, and I did not excuse myself from this great concept as well. I consider myself fortunate as I was presenting on the subject of Master Data Services at TechEd. When I had initially learned this subject, I had a bit of confusion about the usage of this tool. Later on, I decided that I would tackle about how we all developers and DBAs are not able to understand something so simple such as this, and even worst, creating confusion about the technology. During system designing, it is very important to have a reference material or master lookup tables. Well, I talked about the same subject and presented the session keeping that as my center talk. The session went very well and I received lots of interesting questions. I got many compliments for talking about this subject on the real-life scenario. I really thank Rushabh Mehta (CEO, Solid Quality Mentors India) for his supportive suggestions that helped me prepare the slide deck, as well as the subject. Pinal Presenting session at TechEd India 2010 The abstract of the session is as follows: SQL Server Master Data Services will ship with SQL Server 2008 R2 and will improve Microsoft’s platform appeal. This session provides an in-depth demonstration of MDS features and highlights important usage scenarios. Master Data Services enables consistent decision-making process by allowing you to create, manage and propagate changes from a single master view of your business entities. Also, MDS – Master Data-hub which is a vital component, helps ensure the consistency of reporting across systems and deliver faster and more accurate results across the enterprise. We will talk about establishing the basis for a centralized approach to defining, deploying, and managing master data in the enterprise. Pinal Presenting session at TechEd India 2010 The day was still not over for me. I had ran into several friends but we were not able keep our enthusiasm under control about all the rumors saying that SQL Server 2008 R2 was about to be launched tomorrow in the keynote. I then ran to my third and final technical event for the day- a panel discussion with the top technologies of India. Time: 5:00pm – 6:00pm Panel Discussion: Harness the power of Web – SEO and Technical Blogging As I have delivered two technical sessions by this time, I was a bit tired but  not less enthusiastic when I had to talk about Blog and Technology. We discussed many different topics there. I told them that the most important aspect for any blog is its content. We discussed in depth the issues with plagiarism and how to avoid it. Another topic of discussion was how we technology bloggers can create awareness in the Community about what the right kind of blogging is and what morally and technically wrong acts are. A couple of questions were raised about what type of liberty a person can have in terms of writing blogs. Well, it was generically agreed that a blog is mainly a representation of our ideas and thoughts; it should not be governed by external entities. As long as one is writing what they really want to say, but not providing incorrect information or not practicing plagiarism, a blogger should be allowed to express himself. This panel discussion was supposed to be over in an hour, but the interest of the participants was remarkable and so it was extended for 30 minutes more. Finally, we decided to bring to a close the discussion and agreed that we will continue the topic next year. TechEd India Panel Discussion on Web, Technology and SEO Surprisingly, the day was just beginning after doing all of these. By this time, I have almost met all the MVP who arrived at the event, as well as many Microsoft employees. There were lots of Community folks present, too. I decided that I would go to meet several friends from the Community and continue to communicate with me on SQLAuthority.com. I also met Abhishek Baxi and had a good talk with him regarding Win Mobile and Twitter. He also took a very quick video of me wherein I spoke in my mother’s tongue, Gujarati. It was funny that I talked in Gujarati almost all the day, but when I was talking in the interview I could not find the right Gujarati words to speak. I think we all think in English when we think about Technology, so as to address universality. After meeting them, I headed towards the Speakers’ Dinner. Time: 8:00 PM – onwards Speakers Dinner The Speakers’ dinner was indeed a wonderful opportunity for all the speakers to get together and relax. We talked so many different things, from XBOX to Hindi Movies, and from SQL to Samosas. I just could not express how much fun I had. After a long evening, when I returned tmy room and met Shaivi, I just felt instantly relaxed. Kids are really gifts from God. Today was a really long but exciting day. So many things happened in just one day: Visual Studio Lanch, lunch with Somasegar, 2 technical sessions, 1 panel discussion, community leaders meeting, speakers dinner and, last but not leas,t playing with my child! A perfect day! Day 2 – April 13, 2010 Today started with a bang with the excellent keynote by Kamal Hathi who launched SQL Server 2008 R2 in India and demonstrated the power of PowerPivot to all of us. 101 Million Rows in Excel brought lots of applause from the audience. Kamal Hathi Presenting Keynote at TechEd India 2010 The day was a bit easier one for me. I had no sessions today and no events planned. I had a few meetings planned for the second day of the event. I sat in the speaker’s lounge for half a day and met many people there. I attended nearly 9 different meetings today. The subjects of the meetings were very different. Here is a list of the topics of the Community-related meetings: SQL PASS and its involvement in India and subcontinents How to start community blogging Forums and developing aptitude towards technology Ahmedabad/Gandhinagar User Groups and their developments SharePoint and SQL Business Meeting – a client meeting Business Meeting – a potential performance tuning project Business Meeting – Solid Quality Mentors (SolidQ) And family friends Pinal Dave at TechEd India The day passed by so quickly during this meeting. In the evening, I headed to Partners Expo with friends and checked out few of the booths. I really wanted to talk about some of the products, but due to the freebies there was so much crowd that I finally decided to just take the contact details of the partner. I will now start sending them with my queries and, hopefully, I will have my questions answered. Nupur and Shaivi had also one meeting to attend; it was with our family friend Vijay Raj. Vijay is also a person who loves Technology and loves it more than anybody. I see him growing and learning every day, but still remaining as a ‘human’. I believe that if someone acquires as much knowledge as him, that person will become either a computer or cyborg. Here, Vijay is still a kind gentleman and is able to stay as our close family friend. Shaivi was really happy to play with Uncle Vijay. Pinal Dave and Vijay Raj Renuka Prasad, a Microsoft MVP, impressed me with his passion and knowledge of SQL. Every time he gives me credit for his success, I believe that he is very humble. He has way more certifications than me and has worked many more years with SQL compared to me. He is an excellent photographer as well. Most of the photos in this blog post have been taken by him. I told him if ever he wants to do a part time job, he can do the photography very well. Pinal Dave and Renuka Prasad I also met L Srividya from Microsoft, whom I was looking forward to meet. She is a bundle of knowledge that everyone would surely learn a lot from her. I was able to get a few minutes from her and well, I felt confident. She enlightened me with SQL Server BI concepts, domain management and SQL Server security and few other interesting details. I also had a wonderful time talking about SharePoint with fellow Solid Quality Mentor Joy Rathnayake. He is very passionate about SharePoint but when you talk .NET and SQL with him, he is still overwhelmingly knowledgeable. In fact, while talking to him, I figured out that the recent training he delivered was on SQL Server 2008 R2. I told him a joke that it hurts my ego as he is more popular now in SQL training and consulting than me. I am sure all of you agree that working with good people is a gift from God. I am fortunate enough to work with the best of the best Industry experts. It was a great pleasure to hang out with my Community friends – Ahswin Kini, HimaBindu Vejella, Vasudev G, Suprotim Agrawal, Dhananjay, Vikram Pendse, Mahesh Dhola, Mahesh Mitkari,  Manu Zacharia, Shobhan, Hardik Shah, Ashish Mohta, Manan, Subodh Sohani and Sanjay Shetty (of course!) .  (Please let me know if I have met you at the event and forgot your name to list here). Time: 8:00 PM – onwards Community Leaders Dinner After lots of meetings, I headed towards the Community Leaders dinner meeting and met almost all the folks I met in morning. The discussion was almost the same but the real good thing was that we were enjoying it. The food was really good. Nupur was invited in the event, but Shaivi could not come. When Nupur tried to enter the event, she was stopped as Shaivi did not have the pass to enter the dinner. Nupur expressed that Shaivi is only 8 months old and does not eat outside food as well and could not stay by herself at this age, but the door keeper did not agree and asked that without the entry details Shaivi could not go in, but Nupur could. Nupur called me on phone and asked me to help her out. By the time, I was outside; the organizer of the event reached to the door and happily approved Shaivi to join the party. Once in the party, Shaivi had lots of fun meeting so many people. Shaivi Dave and Abhishek Kant Dean Guida (Infragistics President and CEO) and Pinal Dave (SQLAuthority.com) Day 3 – April 14, 2010 Though, it was last day, I was very much excited today as I was about to present my very favorite session. Query Optimization and Performance Tuning is my domain expertise and I make my leaving by consulting and training the same. Today’s session was on the same subject and as an additional twist, another subject about Spatial Database was presented. I was always intrigued with Spatial Database and I have enjoyed learning about it; however, I have never thought about Spatial Indexing before it was decided that I will do this session. I really thank Solid Quality Mentor Dr. Greg Low for his assistance in helping me prepare the slide deck and also review the content. Furthermore, today was really what I call my ‘learning day’ . So far I had not attended any session in TechEd and I felt a bit down for that. Everybody spends their valuable time & money to learn something new and exciting in TechEd and I had not attended a single session at the moment thinking that it was already last day of the event. I did have a plan for the day and I attended two technical sessions before my session of spatial database. I attended 2 sessions of Vinod Kumar. Vinod is a natural storyteller and there was no doubt that his sessions would be jam-packed. People attended his sessions simply because Vinod is syhe speaker. He did not have a single time disappointed audience; he is truly a good speaker. He knows his stuff very well. I personally do not think that in India he can be compared to anyone for SQL. Time: 12:30pm-1:30pm SQL Server Query Optimization, Execution and Debugging Query Performance I really had a fun time attending this session. Vinod made this session very interactive. The entire audience really got into the presentation and started participating in the event. Vinod was presenting a small problem with Query Tuning, which any developer would have encountered and solved with their help in such a fashion that a developer feels he or she have already resolved it. In one question, I was the only one who was ready to answer and Vinod told me in a light tone that I am now allowed to answer it! The audience really found it very amusing. There was a huge crowd around Vinod after the session. Vinod – A master storyteller! Time: 3:45pm-4:45pm Data Recovery / consistency with CheckDB This session was much heavier than the earlier one, and I must say this is my most favorite session I EVER attended in India. In this TechEd I have only attended two sessions, but in my career, I have attended numerous technical sessions not only in India, but all over the world. This session had taken my breath away. One by one, Vinod took the different databases, and started to corrupt them in different ways. Each database has some unique ways to get corrupted. Once that was done, Vinod started to show the DBCC CEHCKDB and demonstrated how it can solve your problem. He finally fixed all the databases with this single tool. I do have a good knowledge of this subject, but let me honestly admit that I have learned a lot from this session. I enjoyed and cheered during this session along with other attendees. I had total satisfaction that, just like everyone, I took advantage of the event and learned something. I am now TECHnically EDucated. Pinal Dave and Vinod Kumar After two very interactive and informative SQL Sessions from Vinod Kumar, the next turn me presenting on Spatial Database and Indexing. I got once again nervous but Vinod told me to stay natural and do my presentation. Well, once I got a huge stage with a total of four projectors and a large crowd, I felt better. Time: 5:00pm-6:00pm Session 3: Developing with SQL Server Spatial and Deep Dive into Spatial Indexing Pinal Presenting session at TechEd India 2010 Pinal Presenting session at TechEd India 2010 I kicked off this session with Michael J Swart‘s beautiful spatial image. This session was the last one for the day but, to my surprise, I had more than 200+ attendees. Slowly, the rain was starting outside and I was worried that the hall would not be full; despite this, there was not a single seat available in the first five minutes of the session. Thanks to all of you for attending my presentation. I had demonstrated the map of world (and India) and quickly explained what  Geographic and Geometry data types in Spatial Database are. This session had interesting story of Indexing and Comparison, as well as how different traditional indexes are from spatial indexing. Pinal Presenting session at TechEd India 2010 Due to the heavy rain during this event, the power went off for about 22 minutes (just an accident – nobodies fault). During these minutes, there were no audio, no video and no light. I continued to address the mass of 200+ people without any audio device and PowerPoint. I must thank the audience because not a single person left from the session. They all stayed in their place, some moved closure to listen to me properly. I noticed that the curiosity and eagerness to learn new things was at the peak even though it was the very last session of the TechEd. Everybody wanted get the maximum knowledge out of this whole event. I was touched by the support from audience. They listened and participated in my session even without any kinds of technology (no ppt, no mike, no AC, nothing). During these 22 minutes, I had completed my theory verbally. Pinal Presenting session at TechEd India 2010 After a while, we got the projector back online and we continued with some exciting demos. Many thanks to Microsoft people who worked energetically in background to get the backup power for project up. I had a very interesting demo wherein I overlaid Bangalore and Hyderabad on the India Map and find their aerial distance between them. After finding the aerial distance, we browsed online and found that SQL Server estimates the exact aerial distance between these two cities, as compared to the factual distance. There was a huge applause from the crowd on the subject that SQL Server takes into the count of the curvature of the earth and finds the precise distances based on details. During the process of finding the distance, I demonstrated a few examples of the indexes where I expressed how one can use those indexes to find these distances and how they can improve the performance of similar query. I also demonstrated few examples wherein we were able to see in which data type the Index is most useful. We finished the demos with a few more internal stuff. Pinal Presenting session at TechEd India 2010 Despite all issues, I was mostly satisfied with my presentation. I think it was the best session I have ever presented at any conference. There was no help from Technology for a while, but I still got lots of appreciation at the end. When we ended the session, the applause from the audience was so loud that for a moment, the rain was not audible. I was truly moved by the dedication of the Technology enthusiasts. Pinal Dave After Presenting session at TechEd India 2010 The abstract of the session is as follows: The Microsoft SQL Server 2008 delivers new spatial data types that enable you to consume, use, and extend location-based data through spatial-enabled applications. Attend this session to learn how to use spatial functionality in next version of SQL Server to build and optimize spatial queries. This session outlines the new geography data type to store geodetic spatial data and perform operations on it, use the new geometry data type to store planar spatial data and perform operations on it, take advantage of new spatial indexes for high performance queries, use the new spatial results tab to quickly and easily view spatial query results directly from within Management Studio, extend spatial data capabilities by building or integrating location-enabled applications through support for spatial standards and specifications and much more. Time: 8:00 PM – onwards Dinner by Sponsors After the lively session during the day, there was another dinner party courtesy of one of the sponsors of TechEd. All the MVPs and several Community leaders were present at the dinner. I would like to express my gratitude to Abhishek Kant for organizing this wonderful event for us. It was a blast and really relaxing in all angles. We all stayed there for a long time and talked about our sweet and unforgettable memories of the event. Pinal Dave and Bijoy Singhal It was really one wonderful event. After writing this much, I say that I have no words to express about how much I enjoyed TechEd. However, it is true that I shared with you only 1% of the total activities I have done at the event. There were so many people I have met, yet were not mentioned here although I wanted to write their names here, too . Anyway, I have learned so many things and up until now, I am not able to get over all the fun I had in this event. Pinal Dave at TechEd India 2010 The Next Days – April 15, 2010 – till today I am still not able to get my mind out of the whole experience I had at TechEd India 2010. It was like a whole Microsoft Family working together to celebrate a happy occasion. TechEd India – Truly An Unforgettable Experience! Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, MVP, Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, SQLAuthority News, SQLServer, T SQL, Technology Tagged: TechEd, TechEdIn

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  • SQLAuthority News – TechEd India – April 12-14, 2010 Bangalore – An Unforgettable Experience – An Op

    - by pinaldave
    TechEd India was one of the largest Technology events in India led by Microsoft. This event was attended by more than 3,000 technology enthusiasts, making it one of the most well-organized events of the year. Though I attempted to attend almost all the technology events here, I have not seen any bigger or better event in Indian subcontinents other than this. There are 21 Technical Tracks at Tech·Ed India 2010 that span more than 745 learning opportunities. I was fortunate enough to be a part of this whole event as a speaker and a delegate, as well. TechEd India Speaker Badge and A Token of Lifetime Hotel Selection I presented three different sessions at TechEd India and was also a part of panel discussion. (The details of the sessions are given at the end of this blog post.) Due to extensive traveling, I stay away from my family occasionally. For this reason, I took my wife – Nupur and daughter Shaivi (8 months old) to the event along with me. We stayed at the same hotel where the event was organized so as to maximize my time bonding with my family and to have more time in networking with technology community, at the same time. The hotel Lalit Ashok is the largest and most luxurious venue one can find in Bangalore, located in the middle of the city. The cost of the hotel was a bit pricey, but looking at all the advantages, I had decided to ask for a booking there. Hotel Lalit Ashok Nupur Dave and Shaivi Dave Arrival Day – DAY 0 – April 11, 2010 I reached the event a day earlier, and that was one wise decision for I was able to relax a bit and go over my presentation for the next day’s course. I am a kind of person who likes to get everything ready ahead of time. I was also able to enjoy a pleasant evening with several Microsoft employees and my family friends. I even checked out the location where I would be doing presentations the next day. I was fortunate enough to meet Bijoy Singhal from Microsoft who helped me out with a few of the logistics issues that occured the day before. I was not aware of the fact that the very next day he was going to be “The Man” of the TechEd 2010 event. Vinod Kumar from Microsoft was really very kind as he talked to me regarding my subsequent session. He gave me some suggestions which were really helpful that I was able to incorporate them during my presentation. Finally, I was able to meet Abhishek Kant from Microsoft; his valuable suggestions and unlimited passion have inspired many people like me to work with the Community. Pradipta from Microsoft was also around, being extremely busy with logistics; however, in those busy times, he did find some good spare time to have a chat with me and the other Community leaders. I also met Harish Ranganathan and Sachin Rathi, both from Microsoft. It was so interesting to listen to both of them talking about SharePoint. I just have no words to express my overwhelmed spirit because of all these passionate young guys - Pradipta,Vinod, Bijoy, Harish, Sachin and Ahishek (of course!). Map of TechEd India 2010 Event Day 1 – April 12, 2010 From morning until night time, today was truly a very busy day for me. I had two presentations and one panel discussion for the day. Needless to say, I had a few meetings to attend as well. The day started with a keynote from S. Somaseger where he announced the launch of Visual Studio 2010. The keynote area was really eye-catching because of the very large, bigger-than- life uniform screen. This was truly one to show. The title music of the keynote was very interesting and it featured Bijoy Singhal as the model. It was interesting to talk to him afterwards, when we laughed at jokes together about his modeling assignment. TechEd India Keynote Opening Featuring Bijoy TechEd India 2010 Keynote – S. Somasegar Time: 11:15pm – 11:45pm Session 1: True Lies of SQL Server – SQL Myth Buster Following the excellent keynote, I had my very first session on the subject of SQL Server Myth Buster. At first, I was a bit nervous as right after the keynote, for this was my very first session and during my presentation I saw lots of Microsoft Product Team members. Well, it really went well and I had a really good discussion with attendees of the session. I felt that a well begin was half-done and my confidence was regained. Right after the session, I met a few of my Community friends and had meaningful discussions with them on many subjects. The abstract of the session is as follows: In this 30-minute demo session, I am going to briefly demonstrate few SQL Server Myths and their resolutions as I back them up with some demo. This demo presentation is a must-attend for all developers and administrators who would come to the event. This is going to be a very quick yet fun session. Pinal Presenting session at TechEd India 2010 Time: 1:00 PM – 2:00 PM Lunch with Somasegar After the session I went to see my daughter, and then I headed right away to the lunch with S. Somasegar – the keynote speaker and senior vice president of the Developer Division at Microsoft. I really thank to Abhishek who made it possible for us. Because of his efforts, all the MVPs had the opportunity to meet such a legendary person and had to talk with them on Microsoft Technology. Though Somasegar is currently holding such a high position in Microsoft, he is very polite and a real gentleman, and how I wish that everybody in industry is like him. Believe me, if you spread love and kindness, then that is what you will receive back. As soon as lunch time was over, I ran to the session hall as my second presentation was about to start. Time: 2:30pm – 3:30pm Session 2: Master Data Services in Microsoft SQL Server 2008 R2 Business Intelligence is a subject which was widely talked about at TechEd. Everybody was interested in this subject, and I did not excuse myself from this great concept as well. I consider myself fortunate as I was presenting on the subject of Master Data Services at TechEd. When I had initially learned this subject, I had a bit of confusion about the usage of this tool. Later on, I decided that I would tackle about how we all developers and DBAs are not able to understand something so simple such as this, and even worst, creating confusion about the technology. During system designing, it is very important to have a reference material or master lookup tables. Well, I talked about the same subject and presented the session keeping that as my center talk. The session went very well and I received lots of interesting questions. I got many compliments for talking about this subject on the real-life scenario. I really thank Rushabh Mehta (CEO, Solid Quality Mentors India) for his supportive suggestions that helped me prepare the slide deck, as well as the subject. Pinal Presenting session at TechEd India 2010 The abstract of the session is as follows: SQL Server Master Data Services will ship with SQL Server 2008 R2 and will improve Microsoft’s platform appeal. This session provides an in-depth demonstration of MDS features and highlights important usage scenarios. Master Data Services enables consistent decision-making process by allowing you to create, manage and propagate changes from a single master view of your business entities. Also, MDS – Master Data-hub which is a vital component, helps ensure the consistency of reporting across systems and deliver faster and more accurate results across the enterprise. We will talk about establishing the basis for a centralized approach to defining, deploying, and managing master data in the enterprise. Pinal Presenting session at TechEd India 2010 The day was still not over for me. I had ran into several friends but we were not able keep our enthusiasm under control about all the rumors saying that SQL Server 2008 R2 was about to be launched tomorrow in the keynote. I then ran to my third and final technical event for the day- a panel discussion with the top technologies of India. Time: 5:00pm – 6:00pm Panel Discussion: Harness the power of Web – SEO and Technical Blogging As I have delivered two technical sessions by this time, I was a bit tired but  not less enthusiastic when I had to talk about Blog and Technology. We discussed many different topics there. I told them that the most important aspect for any blog is its content. We discussed in depth the issues with plagiarism and how to avoid it. Another topic of discussion was how we technology bloggers can create awareness in the Community about what the right kind of blogging is and what morally and technically wrong acts are. A couple of questions were raised about what type of liberty a person can have in terms of writing blogs. Well, it was generically agreed that a blog is mainly a representation of our ideas and thoughts; it should not be governed by external entities. As long as one is writing what they really want to say, but not providing incorrect information or not practicing plagiarism, a blogger should be allowed to express himself. This panel discussion was supposed to be over in an hour, but the interest of the participants was remarkable and so it was extended for 30 minutes more. Finally, we decided to bring to a close the discussion and agreed that we will continue the topic next year. TechEd India Panel Discussion on Web, Technology and SEO Surprisingly, the day was just beginning after doing all of these. By this time, I have almost met all the MVP who arrived at the event, as well as many Microsoft employees. There were lots of Community folks present, too. I decided that I would go to meet several friends from the Community and continue to communicate with me on SQLAuthority.com. I also met Abhishek Baxi and had a good talk with him regarding Win Mobile and Twitter. He also took a very quick video of me wherein I spoke in my mother’s tongue, Gujarati. It was funny that I talked in Gujarati almost all the day, but when I was talking in the interview I could not find the right Gujarati words to speak. I think we all think in English when we think about Technology, so as to address universality. After meeting them, I headed towards the Speakers’ Dinner. Time: 8:00 PM – onwards Speakers Dinner The Speakers’ dinner was indeed a wonderful opportunity for all the speakers to get together and relax. We talked so many different things, from XBOX to Hindi Movies, and from SQL to Samosas. I just could not express how much fun I had. After a long evening, when I returned tmy room and met Shaivi, I just felt instantly relaxed. Kids are really gifts from God. Today was a really long but exciting day. So many things happened in just one day: Visual Studio Lanch, lunch with Somasegar, 2 technical sessions, 1 panel discussion, community leaders meeting, speakers dinner and, last but not leas,t playing with my child! A perfect day! Day 2 – April 13, 2010 Today started with a bang with the excellent keynote by Kamal Hathi who launched SQL Server 2008 R2 in India and demonstrated the power of PowerPivot to all of us. 101 Million Rows in Excel brought lots of applause from the audience. Kamal Hathi Presenting Keynote at TechEd India 2010 The day was a bit easier one for me. I had no sessions today and no events planned. I had a few meetings planned for the second day of the event. I sat in the speaker’s lounge for half a day and met many people there. I attended nearly 9 different meetings today. The subjects of the meetings were very different. Here is a list of the topics of the Community-related meetings: SQL PASS and its involvement in India and subcontinents How to start community blogging Forums and developing aptitude towards technology Ahmedabad/Gandhinagar User Groups and their developments SharePoint and SQL Business Meeting – a client meeting Business Meeting – a potential performance tuning project Business Meeting – Solid Quality Mentors (SolidQ) And family friends Pinal Dave at TechEd India The day passed by so quickly during this meeting. In the evening, I headed to Partners Expo with friends and checked out few of the booths. I really wanted to talk about some of the products, but due to the freebies there was so much crowd that I finally decided to just take the contact details of the partner. I will now start sending them with my queries and, hopefully, I will have my questions answered. Nupur and Shaivi had also one meeting to attend; it was with our family friend Vijay Raj. Vijay is also a person who loves Technology and loves it more than anybody. I see him growing and learning every day, but still remaining as a ‘human’. I believe that if someone acquires as much knowledge as him, that person will become either a computer or cyborg. Here, Vijay is still a kind gentleman and is able to stay as our close family friend. Shaivi was really happy to play with Uncle Vijay. Pinal Dave and Vijay Raj Renuka Prasad, a Microsoft MVP, impressed me with his passion and knowledge of SQL. Every time he gives me credit for his success, I believe that he is very humble. He has way more certifications than me and has worked many more years with SQL compared to me. He is an excellent photographer as well. Most of the photos in this blog post have been taken by him. I told him if ever he wants to do a part time job, he can do the photography very well. Pinal Dave and Renuka Prasad I also met L Srividya from Microsoft, whom I was looking forward to meet. She is a bundle of knowledge that everyone would surely learn a lot from her. I was able to get a few minutes from her and well, I felt confident. She enlightened me with SQL Server BI concepts, domain management and SQL Server security and few other interesting details. I also had a wonderful time talking about SharePoint with fellow Solid Quality Mentor Joy Rathnayake. He is very passionate about SharePoint but when you talk .NET and SQL with him, he is still overwhelmingly knowledgeable. In fact, while talking to him, I figured out that the recent training he delivered was on SQL Server 2008 R2. I told him a joke that it hurts my ego as he is more popular now in SQL training and consulting than me. I am sure all of you agree that working with good people is a gift from God. I am fortunate enough to work with the best of the best Industry experts. It was a great pleasure to hang out with my Community friends – Ahswin Kini, HimaBindu Vejella, Vasudev G, Suprotim Agrawal, Dhananjay, Vikram Pendse, Mahesh Dhola, Mahesh Mitkari,  Manu Zacharia, Shobhan, Hardik Shah, Ashish Mohta, Manan, Subodh Sohani and Sanjay Shetty (of course!) .  (Please let me know if I have met you at the event and forgot your name to list here). Time: 8:00 PM – onwards Community Leaders Dinner After lots of meetings, I headed towards the Community Leaders dinner meeting and met almost all the folks I met in morning. The discussion was almost the same but the real good thing was that we were enjoying it. The food was really good. Nupur was invited in the event, but Shaivi could not come. When Nupur tried to enter the event, she was stopped as Shaivi did not have the pass to enter the dinner. Nupur expressed that Shaivi is only 8 months old and does not eat outside food as well and could not stay by herself at this age, but the door keeper did not agree and asked that without the entry details Shaivi could not go in, but Nupur could. Nupur called me on phone and asked me to help her out. By the time, I was outside; the organizer of the event reached to the door and happily approved Shaivi to join the party. Once in the party, Shaivi had lots of fun meeting so many people. Shaivi Dave and Abhishek Kant Dean Guida (Infragistics President and CEO) and Pinal Dave (SQLAuthority.com) Day 3 – April 14, 2010 Though, it was last day, I was very much excited today as I was about to present my very favorite session. Query Optimization and Performance Tuning is my domain expertise and I make my leaving by consulting and training the same. Today’s session was on the same subject and as an additional twist, another subject about Spatial Database was presented. I was always intrigued with Spatial Database and I have enjoyed learning about it; however, I have never thought about Spatial Indexing before it was decided that I will do this session. I really thank Solid Quality Mentor Dr. Greg Low for his assistance in helping me prepare the slide deck and also review the content. Furthermore, today was really what I call my ‘learning day’ . So far I had not attended any session in TechEd and I felt a bit down for that. Everybody spends their valuable time & money to learn something new and exciting in TechEd and I had not attended a single session at the moment thinking that it was already last day of the event. I did have a plan for the day and I attended two technical sessions before my session of spatial database. I attended 2 sessions of Vinod Kumar. Vinod is a natural storyteller and there was no doubt that his sessions would be jam-packed. People attended his sessions simply because Vinod is syhe speaker. He did not have a single time disappointed audience; he is truly a good speaker. He knows his stuff very well. I personally do not think that in India he can be compared to anyone for SQL. Time: 12:30pm-1:30pm SQL Server Query Optimization, Execution and Debugging Query Performance I really had a fun time attending this session. Vinod made this session very interactive. The entire audience really got into the presentation and started participating in the event. Vinod was presenting a small problem with Query Tuning, which any developer would have encountered and solved with their help in such a fashion that a developer feels he or she have already resolved it. In one question, I was the only one who was ready to answer and Vinod told me in a light tone that I am now allowed to answer it! The audience really found it very amusing. There was a huge crowd around Vinod after the session. Vinod – A master storyteller! Time: 3:45pm-4:45pm Data Recovery / consistency with CheckDB This session was much heavier than the earlier one, and I must say this is my most favorite session I EVER attended in India. In this TechEd I have only attended two sessions, but in my career, I have attended numerous technical sessions not only in India, but all over the world. This session had taken my breath away. One by one, Vinod took the different databases, and started to corrupt them in different ways. Each database has some unique ways to get corrupted. Once that was done, Vinod started to show the DBCC CEHCKDB and demonstrated how it can solve your problem. He finally fixed all the databases with this single tool. I do have a good knowledge of this subject, but let me honestly admit that I have learned a lot from this session. I enjoyed and cheered during this session along with other attendees. I had total satisfaction that, just like everyone, I took advantage of the event and learned something. I am now TECHnically EDucated. Pinal Dave and Vinod Kumar After two very interactive and informative SQL Sessions from Vinod Kumar, the next turn me presenting on Spatial Database and Indexing. I got once again nervous but Vinod told me to stay natural and do my presentation. Well, once I got a huge stage with a total of four projectors and a large crowd, I felt better. Time: 5:00pm-6:00pm Session 3: Developing with SQL Server Spatial and Deep Dive into Spatial Indexing Pinal Presenting session at TechEd India 2010 Pinal Presenting session at TechEd India 2010 I kicked off this session with Michael J Swart‘s beautiful spatial image. This session was the last one for the day but, to my surprise, I had more than 200+ attendees. Slowly, the rain was starting outside and I was worried that the hall would not be full; despite this, there was not a single seat available in the first five minutes of the session. Thanks to all of you for attending my presentation. I had demonstrated the map of world (and India) and quickly explained what  Geographic and Geometry data types in Spatial Database are. This session had interesting story of Indexing and Comparison, as well as how different traditional indexes are from spatial indexing. Pinal Presenting session at TechEd India 2010 Due to the heavy rain during this event, the power went off for about 22 minutes (just an accident – nobodies fault). During these minutes, there were no audio, no video and no light. I continued to address the mass of 200+ people without any audio device and PowerPoint. I must thank the audience because not a single person left from the session. They all stayed in their place, some moved closure to listen to me properly. I noticed that the curiosity and eagerness to learn new things was at the peak even though it was the very last session of the TechEd. Everybody wanted get the maximum knowledge out of this whole event. I was touched by the support from audience. They listened and participated in my session even without any kinds of technology (no ppt, no mike, no AC, nothing). During these 22 minutes, I had completed my theory verbally. Pinal Presenting session at TechEd India 2010 After a while, we got the projector back online and we continued with some exciting demos. Many thanks to Microsoft people who worked energetically in background to get the backup power for project up. I had a very interesting demo wherein I overlaid Bangalore and Hyderabad on the India Map and find their aerial distance between them. After finding the aerial distance, we browsed online and found that SQL Server estimates the exact aerial distance between these two cities, as compared to the factual distance. There was a huge applause from the crowd on the subject that SQL Server takes into the count of the curvature of the earth and finds the precise distances based on details. During the process of finding the distance, I demonstrated a few examples of the indexes where I expressed how one can use those indexes to find these distances and how they can improve the performance of similar query. I also demonstrated few examples wherein we were able to see in which data type the Index is most useful. We finished the demos with a few more internal stuff. Pinal Presenting session at TechEd India 2010 Despite all issues, I was mostly satisfied with my presentation. I think it was the best session I have ever presented at any conference. There was no help from Technology for a while, but I still got lots of appreciation at the end. When we ended the session, the applause from the audience was so loud that for a moment, the rain was not audible. I was truly moved by the dedication of the Technology enthusiasts. Pinal Dave After Presenting session at TechEd India 2010 The abstract of the session is as follows: The Microsoft SQL Server 2008 delivers new spatial data types that enable you to consume, use, and extend location-based data through spatial-enabled applications. Attend this session to learn how to use spatial functionality in next version of SQL Server to build and optimize spatial queries. This session outlines the new geography data type to store geodetic spatial data and perform operations on it, use the new geometry data type to store planar spatial data and perform operations on it, take advantage of new spatial indexes for high performance queries, use the new spatial results tab to quickly and easily view spatial query results directly from within Management Studio, extend spatial data capabilities by building or integrating location-enabled applications through support for spatial standards and specifications and much more. Time: 8:00 PM – onwards Dinner by Sponsors After the lively session during the day, there was another dinner party courtesy of one of the sponsors of TechEd. All the MVPs and several Community leaders were present at the dinner. I would like to express my gratitude to Abhishek Kant for organizing this wonderful event for us. It was a blast and really relaxing in all angles. We all stayed there for a long time and talked about our sweet and unforgettable memories of the event. Pinal Dave and Bijoy Singhal It was really one wonderful event. After writing this much, I say that I have no words to express about how much I enjoyed TechEd. However, it is true that I shared with you only 1% of the total activities I have done at the event. There were so many people I have met, yet were not mentioned here although I wanted to write their names here, too . Anyway, I have learned so many things and up until now, I am not able to get over all the fun I had in this event. Pinal Dave at TechEd India 2010 The Next Days – April 15, 2010 – till today I am still not able to get my mind out of the whole experience I had at TechEd India 2010. It was like a whole Microsoft Family working together to celebrate a happy occasion. TechEd India – Truly An Unforgettable Experience! Reference : Pinal Dave (http://blog.SQLAuthority.com) Filed under: About Me, MVP, Pinal Dave, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQLAuthority Author Visit, SQLAuthority News, SQLServer, T SQL, Technology Tagged: TechEd, TechEdIn

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  • How John Got 15x Improvement Without Really Trying

    - by rchrd
    The following article was published on a Sun Microsystems website a number of years ago by John Feo. It is still useful and worth preserving. So I'm republishing it here.  How I Got 15x Improvement Without Really Trying John Feo, Sun Microsystems Taking ten "personal" program codes used in scientific and engineering research, the author was able to get from 2 to 15 times performance improvement easily by applying some simple general optimization techniques. Introduction Scientific research based on computer simulation depends on the simulation for advancement. The research can advance only as fast as the computational codes can execute. The codes' efficiency determines both the rate and quality of results. In the same amount of time, a faster program can generate more results and can carry out a more detailed simulation of physical phenomena than a slower program. Highly optimized programs help science advance quickly and insure that monies supporting scientific research are used as effectively as possible. Scientific computer codes divide into three broad categories: ISV, community, and personal. ISV codes are large, mature production codes developed and sold commercially. The codes improve slowly over time both in methods and capabilities, and they are well tuned for most vendor platforms. Since the codes are mature and complex, there are few opportunities to improve their performance solely through code optimization. Improvements of 10% to 15% are typical. Examples of ISV codes are DYNA3D, Gaussian, and Nastran. Community codes are non-commercial production codes used by a particular research field. Generally, they are developed and distributed by a single academic or research institution with assistance from the community. Most users just run the codes, but some develop new methods and extensions that feed back into the general release. The codes are available on most vendor platforms. Since these codes are younger than ISV codes, there are more opportunities to optimize the source code. Improvements of 50% are not unusual. Examples of community codes are AMBER, CHARM, BLAST, and FASTA. Personal codes are those written by single users or small research groups for their own use. These codes are not distributed, but may be passed from professor-to-student or student-to-student over several years. They form the primordial ocean of applications from which community and ISV codes emerge. Government research grants pay for the development of most personal codes. This paper reports on the nature and performance of this class of codes. Over the last year, I have looked at over two dozen personal codes from more than a dozen research institutions. The codes cover a variety of scientific fields, including astronomy, atmospheric sciences, bioinformatics, biology, chemistry, geology, and physics. The sources range from a few hundred lines to more than ten thousand lines, and are written in Fortran, Fortran 90, C, and C++. For the most part, the codes are modular, documented, and written in a clear, straightforward manner. They do not use complex language features, advanced data structures, programming tricks, or libraries. I had little trouble understanding what the codes did or how data structures were used. Most came with a makefile. Surprisingly, only one of the applications is parallel. All developers have access to parallel machines, so availability is not an issue. Several tried to parallelize their applications, but stopped after encountering difficulties. Lack of education and a perception that parallelism is difficult prevented most from trying. I parallelized several of the codes using OpenMP, and did not judge any of the codes as difficult to parallelize. Even more surprising than the lack of parallelism is the inefficiency of the codes. I was able to get large improvements in performance in a matter of a few days applying simple optimization techniques. Table 1 lists ten representative codes [names and affiliation are omitted to preserve anonymity]. Improvements on one processor range from 2x to 15.5x with a simple average of 4.75x. I did not use sophisticated performance tools or drill deep into the program's execution character as one would do when tuning ISV or community codes. Using only a profiler and source line timers, I identified inefficient sections of code and improved their performance by inspection. The changes were at a high level. I am sure there is another factor of 2 or 3 in each code, and more if the codes are parallelized. The study’s results show that personal scientific codes are running many times slower than they should and that the problem is pervasive. Computational scientists are not sloppy programmers; however, few are trained in the art of computer programming or code optimization. I found that most have a working knowledge of some programming language and standard software engineering practices; but they do not know, or think about, how to make their programs run faster. They simply do not know the standard techniques used to make codes run faster. In fact, they do not even perceive that such techniques exist. The case studies described in this paper show that applying simple, well known techniques can significantly increase the performance of personal codes. It is important that the scientific community and the Government agencies that support scientific research find ways to better educate academic scientific programmers. The inefficiency of their codes is so bad that it is retarding both the quality and progress of scientific research. # cacheperformance redundantoperations loopstructures performanceimprovement 1 x x 15.5 2 x 2.8 3 x x 2.5 4 x 2.1 5 x x 2.0 6 x 5.0 7 x 5.8 8 x 6.3 9 2.2 10 x x 3.3 Table 1 — Area of improvement and performance gains of 10 codes The remainder of the paper is organized as follows: sections 2, 3, and 4 discuss the three most common sources of inefficiencies in the codes studied. These are cache performance, redundant operations, and loop structures. Each section includes several examples. The last section summaries the work and suggests a possible solution to the issues raised. Optimizing cache performance Commodity microprocessor systems use caches to increase memory bandwidth and reduce memory latencies. Typical latencies from processor to L1, L2, local, and remote memory are 3, 10, 50, and 200 cycles, respectively. Moreover, bandwidth falls off dramatically as memory distances increase. Programs that do not use cache effectively run many times slower than programs that do. When optimizing for cache, the biggest performance gains are achieved by accessing data in cache order and reusing data to amortize the overhead of cache misses. Secondary considerations are prefetching, associativity, and replacement; however, the understanding and analysis required to optimize for the latter are probably beyond the capabilities of the non-expert. Much can be gained simply by accessing data in the correct order and maximizing data reuse. 6 out of the 10 codes studied here benefited from such high level optimizations. Array Accesses The most important cache optimization is the most basic: accessing Fortran array elements in column order and C array elements in row order. Four of the ten codes—1, 2, 4, and 10—got it wrong. Compilers will restructure nested loops to optimize cache performance, but may not do so if the loop structure is too complex, or the loop body includes conditionals, complex addressing, or function calls. In code 1, the compiler failed to invert a key loop because of complex addressing do I = 0, 1010, delta_x IM = I - delta_x IP = I + delta_x do J = 5, 995, delta_x JM = J - delta_x JP = J + delta_x T1 = CA1(IP, J) + CA1(I, JP) T2 = CA1(IM, J) + CA1(I, JM) S1 = T1 + T2 - 4 * CA1(I, J) CA(I, J) = CA1(I, J) + D * S1 end do end do In code 2, the culprit is conditionals do I = 1, N do J = 1, N If (IFLAG(I,J) .EQ. 0) then T1 = Value(I, J-1) T2 = Value(I-1, J) T3 = Value(I, J) T4 = Value(I+1, J) T5 = Value(I, J+1) Value(I,J) = 0.25 * (T1 + T2 + T5 + T4) Delta = ABS(T3 - Value(I,J)) If (Delta .GT. MaxDelta) MaxDelta = Delta endif enddo enddo I fixed both programs by inverting the loops by hand. Code 10 has three-dimensional arrays and triply nested loops. The structure of the most computationally intensive loops is too complex to invert automatically or by hand. The only practical solution is to transpose the arrays so that the dimension accessed by the innermost loop is in cache order. The arrays can be transposed at construction or prior to entering a computationally intensive section of code. The former requires all array references to be modified, while the latter is cost effective only if the cost of the transpose is amortized over many accesses. I used the second approach to optimize code 10. Code 5 has four-dimensional arrays and loops are nested four deep. For all of the reasons cited above the compiler is not able to restructure three key loops. Assume C arrays and let the four dimensions of the arrays be i, j, k, and l. In the original code, the index structure of the three loops is L1: for i L2: for i L3: for i for l for l for j for k for j for k for j for k for l So only L3 accesses array elements in cache order. L1 is a very complex loop—much too complex to invert. I brought the loop into cache alignment by transposing the second and fourth dimensions of the arrays. Since the code uses a macro to compute all array indexes, I effected the transpose at construction and changed the macro appropriately. The dimensions of the new arrays are now: i, l, k, and j. L3 is a simple loop and easily inverted. L2 has a loop-carried scalar dependence in k. By promoting the scalar name that carries the dependence to an array, I was able to invert the third and fourth subloops aligning the loop with cache. Code 5 is by far the most difficult of the four codes to optimize for array accesses; but the knowledge required to fix the problems is no more than that required for the other codes. I would judge this code at the limits of, but not beyond, the capabilities of appropriately trained computational scientists. Array Strides When a cache miss occurs, a line (64 bytes) rather than just one word is loaded into the cache. If data is accessed stride 1, than the cost of the miss is amortized over 8 words. Any stride other than one reduces the cost savings. Two of the ten codes studied suffered from non-unit strides. The codes represent two important classes of "strided" codes. Code 1 employs a multi-grid algorithm to reduce time to convergence. The grids are every tenth, fifth, second, and unit element. Since time to convergence is inversely proportional to the distance between elements, coarse grids converge quickly providing good starting values for finer grids. The better starting values further reduce the time to convergence. The downside is that grids of every nth element, n > 1, introduce non-unit strides into the computation. In the original code, much of the savings of the multi-grid algorithm were lost due to this problem. I eliminated the problem by compressing (copying) coarse grids into continuous memory, and rewriting the computation as a function of the compressed grid. On convergence, I copied the final values of the compressed grid back to the original grid. The savings gained from unit stride access of the compressed grid more than paid for the cost of copying. Using compressed grids, the loop from code 1 included in the previous section becomes do j = 1, GZ do i = 1, GZ T1 = CA(i+0, j-1) + CA(i-1, j+0) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) S1 = T1 + T4 - 4 * CA1(i+0, j+0) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 enddo enddo where CA and CA1 are compressed arrays of size GZ. Code 7 traverses a list of objects selecting objects for later processing. The labels of the selected objects are stored in an array. The selection step has unit stride, but the processing steps have irregular stride. A fix is to save the parameters of the selected objects in temporary arrays as they are selected, and pass the temporary arrays to the processing functions. The fix is practical if the same parameters are used in selection as in processing, or if processing comprises a series of distinct steps which use overlapping subsets of the parameters. Both conditions are true for code 7, so I achieved significant improvement by copying parameters to temporary arrays during selection. Data reuse In the previous sections, we optimized for spatial locality. It is also important to optimize for temporal locality. Once read, a datum should be used as much as possible before it is forced from cache. Loop fusion and loop unrolling are two techniques that increase temporal locality. Unfortunately, both techniques increase register pressure—as loop bodies become larger, the number of registers required to hold temporary values grows. Once register spilling occurs, any gains evaporate quickly. For multiprocessors with small register sets or small caches, the sweet spot can be very small. In the ten codes presented here, I found no opportunities for loop fusion and only two opportunities for loop unrolling (codes 1 and 3). In code 1, unrolling the outer and inner loop one iteration increases the number of result values computed by the loop body from 1 to 4, do J = 1, GZ-2, 2 do I = 1, GZ-2, 2 T1 = CA1(i+0, j-1) + CA1(i-1, j+0) T2 = CA1(i+1, j-1) + CA1(i+0, j+0) T3 = CA1(i+0, j+0) + CA1(i-1, j+1) T4 = CA1(i+1, j+0) + CA1(i+0, j+1) T5 = CA1(i+2, j+0) + CA1(i+1, j+1) T6 = CA1(i+1, j+1) + CA1(i+0, j+2) T7 = CA1(i+2, j+1) + CA1(i+1, j+2) S1 = T1 + T4 - 4 * CA1(i+0, j+0) S2 = T2 + T5 - 4 * CA1(i+1, j+0) S3 = T3 + T6 - 4 * CA1(i+0, j+1) S4 = T4 + T7 - 4 * CA1(i+1, j+1) CA(i+0, j+0) = CA1(i+0, j+0) + DD * S1 CA(i+1, j+0) = CA1(i+1, j+0) + DD * S2 CA(i+0, j+1) = CA1(i+0, j+1) + DD * S3 CA(i+1, j+1) = CA1(i+1, j+1) + DD * S4 enddo enddo The loop body executes 12 reads, whereas as the rolled loop shown in the previous section executes 20 reads to compute the same four values. In code 3, two loops are unrolled 8 times and one loop is unrolled 4 times. Here is the before for (k = 0; k < NK[u]; k++) { sum = 0.0; for (y = 0; y < NY; y++) { sum += W[y][u][k] * delta[y]; } backprop[i++]=sum; } and after code for (k = 0; k < KK - 8; k+=8) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (y = 0; y < NY; y++) { sum0 += W[y][0][k+0] * delta[y]; sum1 += W[y][0][k+1] * delta[y]; sum2 += W[y][0][k+2] * delta[y]; sum3 += W[y][0][k+3] * delta[y]; sum4 += W[y][0][k+4] * delta[y]; sum5 += W[y][0][k+5] * delta[y]; sum6 += W[y][0][k+6] * delta[y]; sum7 += W[y][0][k+7] * delta[y]; } backprop[k+0] = sum0; backprop[k+1] = sum1; backprop[k+2] = sum2; backprop[k+3] = sum3; backprop[k+4] = sum4; backprop[k+5] = sum5; backprop[k+6] = sum6; backprop[k+7] = sum7; } for one of the loops unrolled 8 times. Optimizing for temporal locality is the most difficult optimization considered in this paper. The concepts are not difficult, but the sweet spot is small. Identifying where the program can benefit from loop unrolling or loop fusion is not trivial. Moreover, it takes some effort to get it right. Still, educating scientific programmers about temporal locality and teaching them how to optimize for it will pay dividends. Reducing instruction count Execution time is a function of instruction count. Reduce the count and you usually reduce the time. The best solution is to use a more efficient algorithm; that is, an algorithm whose order of complexity is smaller, that converges quicker, or is more accurate. Optimizing source code without changing the algorithm yields smaller, but still significant, gains. This paper considers only the latter because the intent is to study how much better codes can run if written by programmers schooled in basic code optimization techniques. The ten codes studied benefited from three types of "instruction reducing" optimizations. The two most prevalent were hoisting invariant memory and data operations out of inner loops. The third was eliminating unnecessary data copying. The nature of these inefficiencies is language dependent. Memory operations The semantics of C make it difficult for the compiler to determine all the invariant memory operations in a loop. The problem is particularly acute for loops in functions since the compiler may not know the values of the function's parameters at every call site when compiling the function. Most compilers support pragmas to help resolve ambiguities; however, these pragmas are not comprehensive and there is no standard syntax. To guarantee that invariant memory operations are not executed repetitively, the user has little choice but to hoist the operations by hand. The problem is not as severe in Fortran programs because in the absence of equivalence statements, it is a violation of the language's semantics for two names to share memory. Codes 3 and 5 are C programs. In both cases, the compiler did not hoist all invariant memory operations from inner loops. Consider the following loop from code 3 for (y = 0; y < NY; y++) { i = 0; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += delta[y] * I1[i++]; } } } Since dW[y][u] can point to the same memory space as delta for one or more values of y and u, assignment to dW[y][u][k] may change the value of delta[y]. In reality, dW and delta do not overlap in memory, so I rewrote the loop as for (y = 0; y < NY; y++) { i = 0; Dy = delta[y]; for (u = 0; u < NU; u++) { for (k = 0; k < NK[u]; k++) { dW[y][u][k] += Dy * I1[i++]; } } } Failure to hoist invariant memory operations may be due to complex address calculations. If the compiler can not determine that the address calculation is invariant, then it can hoist neither the calculation nor the associated memory operations. As noted above, code 5 uses a macro to address four-dimensional arrays #define MAT4D(a,q,i,j,k) (double *)((a)->data + (q)*(a)->strides[0] + (i)*(a)->strides[3] + (j)*(a)->strides[2] + (k)*(a)->strides[1]) The macro is too complex for the compiler to understand and so, it does not identify any subexpressions as loop invariant. The simplest way to eliminate the address calculation from the innermost loop (over i) is to define a0 = MAT4D(a,q,0,j,k) before the loop and then replace all instances of *MAT4D(a,q,i,j,k) in the loop with a0[i] A similar problem appears in code 6, a Fortran program. The key loop in this program is do n1 = 1, nh nx1 = (n1 - 1) / nz + 1 nz1 = n1 - nz * (nx1 - 1) do n2 = 1, nh nx2 = (n2 - 1) / nz + 1 nz2 = n2 - nz * (nx2 - 1) ndx = nx2 - nx1 ndy = nz2 - nz1 gxx = grn(1,ndx,ndy) gyy = grn(2,ndx,ndy) gxy = grn(3,ndx,ndy) balance(n1,1) = balance(n1,1) + (force(n2,1) * gxx + force(n2,2) * gxy) * h1 balance(n1,2) = balance(n1,2) + (force(n2,1) * gxy + force(n2,2) * gyy)*h1 end do end do The programmer has written this loop well—there are no loop invariant operations with respect to n1 and n2. However, the loop resides within an iterative loop over time and the index calculations are independent with respect to time. Trading space for time, I precomputed the index values prior to the entering the time loop and stored the values in two arrays. I then replaced the index calculations with reads of the arrays. Data operations Ways to reduce data operations can appear in many forms. Implementing a more efficient algorithm produces the biggest gains. The closest I came to an algorithm change was in code 4. This code computes the inner product of K-vectors A(i) and B(j), 0 = i < N, 0 = j < M, for most values of i and j. Since the program computes most of the NM possible inner products, it is more efficient to compute all the inner products in one triply-nested loop rather than one at a time when needed. The savings accrue from reading A(i) once for all B(j) vectors and from loop unrolling. for (i = 0; i < N; i+=8) { for (j = 0; j < M; j++) { sum0 = 0.0; sum1 = 0.0; sum2 = 0.0; sum3 = 0.0; sum4 = 0.0; sum5 = 0.0; sum6 = 0.0; sum7 = 0.0; for (k = 0; k < K; k++) { sum0 += A[i+0][k] * B[j][k]; sum1 += A[i+1][k] * B[j][k]; sum2 += A[i+2][k] * B[j][k]; sum3 += A[i+3][k] * B[j][k]; sum4 += A[i+4][k] * B[j][k]; sum5 += A[i+5][k] * B[j][k]; sum6 += A[i+6][k] * B[j][k]; sum7 += A[i+7][k] * B[j][k]; } C[i+0][j] = sum0; C[i+1][j] = sum1; C[i+2][j] = sum2; C[i+3][j] = sum3; C[i+4][j] = sum4; C[i+5][j] = sum5; C[i+6][j] = sum6; C[i+7][j] = sum7; }} This change requires knowledge of a typical run; i.e., that most inner products are computed. The reasons for the change, however, derive from basic optimization concepts. It is the type of change easily made at development time by a knowledgeable programmer. In code 5, we have the data version of the index optimization in code 6. Here a very expensive computation is a function of the loop indices and so cannot be hoisted out of the loop; however, the computation is invariant with respect to an outer iterative loop over time. We can compute its value for each iteration of the computation loop prior to entering the time loop and save the values in an array. The increase in memory required to store the values is small in comparison to the large savings in time. The main loop in Code 8 is doubly nested. The inner loop includes a series of guarded computations; some are a function of the inner loop index but not the outer loop index while others are a function of the outer loop index but not the inner loop index for (j = 0; j < N; j++) { for (i = 0; i < M; i++) { r = i * hrmax; R = A[j]; temp = (PRM[3] == 0.0) ? 1.0 : pow(r, PRM[3]); high = temp * kcoeff * B[j] * PRM[2] * PRM[4]; low = high * PRM[6] * PRM[6] / (1.0 + pow(PRM[4] * PRM[6], 2.0)); kap = (R > PRM[6]) ? high * R * R / (1.0 + pow(PRM[4]*r, 2.0) : low * pow(R/PRM[6], PRM[5]); < rest of loop omitted > }} Note that the value of temp is invariant to j. Thus, we can hoist the computation for temp out of the loop and save its values in an array. for (i = 0; i < M; i++) { r = i * hrmax; TEMP[i] = pow(r, PRM[3]); } [N.B. – the case for PRM[3] = 0 is omitted and will be reintroduced later.] We now hoist out of the inner loop the computations invariant to i. Since the conditional guarding the value of kap is invariant to i, it behooves us to hoist the computation out of the inner loop, thereby executing the guard once rather than M times. The final version of the code is for (j = 0; j < N; j++) { R = rig[j] / 1000.; tmp1 = kcoeff * par[2] * beta[j] * par[4]; tmp2 = 1.0 + (par[4] * par[4] * par[6] * par[6]); tmp3 = 1.0 + (par[4] * par[4] * R * R); tmp4 = par[6] * par[6] / tmp2; tmp5 = R * R / tmp3; tmp6 = pow(R / par[6], par[5]); if ((par[3] == 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp5; } else if ((par[3] == 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * tmp4 * tmp6; } else if ((par[3] != 0.0) && (R > par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp5; } else if ((par[3] != 0.0) && (R <= par[6])) { for (i = 1; i <= imax1; i++) KAP[i] = tmp1 * TEMP[i] * tmp4 * tmp6; } for (i = 0; i < M; i++) { kap = KAP[i]; r = i * hrmax; < rest of loop omitted > } } Maybe not the prettiest piece of code, but certainly much more efficient than the original loop, Copy operations Several programs unnecessarily copy data from one data structure to another. This problem occurs in both Fortran and C programs, although it manifests itself differently in the two languages. Code 1 declares two arrays—one for old values and one for new values. At the end of each iteration, the array of new values is copied to the array of old values to reset the data structures for the next iteration. This problem occurs in Fortran programs not included in this study and in both Fortran 77 and Fortran 90 code. Introducing pointers to the arrays and swapping pointer values is an obvious way to eliminate the copying; but pointers is not a feature that many Fortran programmers know well or are comfortable using. An easy solution not involving pointers is to extend the dimension of the value array by 1 and use the last dimension to differentiate between arrays at different times. For example, if the data space is N x N, declare the array (N, N, 2). Then store the problem’s initial values in (_, _, 2) and define the scalar names new = 2 and old = 1. At the start of each iteration, swap old and new to reset the arrays. The old–new copy problem did not appear in any C program. In programs that had new and old values, the code swapped pointers to reset data structures. Where unnecessary coping did occur is in structure assignment and parameter passing. Structures in C are handled much like scalars. Assignment causes the data space of the right-hand name to be copied to the data space of the left-hand name. Similarly, when a structure is passed to a function, the data space of the actual parameter is copied to the data space of the formal parameter. If the structure is large and the assignment or function call is in an inner loop, then copying costs can grow quite large. While none of the ten programs considered here manifested this problem, it did occur in programs not included in the study. A simple fix is always to refer to structures via pointers. Optimizing loop structures Since scientific programs spend almost all their time in loops, efficient loops are the key to good performance. Conditionals, function calls, little instruction level parallelism, and large numbers of temporary values make it difficult for the compiler to generate tightly packed, highly efficient code. Conditionals and function calls introduce jumps that disrupt code flow. Users should eliminate or isolate conditionls to their own loops as much as possible. Often logical expressions can be substituted for if-then-else statements. For example, code 2 includes the following snippet MaxDelta = 0.0 do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) if (Delta > MaxDelta) MaxDelta = Delta enddo enddo if (MaxDelta .gt. 0.001) goto 200 Since the only use of MaxDelta is to control the jump to 200 and all that matters is whether or not it is greater than 0.001, I made MaxDelta a boolean and rewrote the snippet as MaxDelta = .false. do J = 1, N do I = 1, M < code omitted > Delta = abs(OldValue ? NewValue) MaxDelta = MaxDelta .or. (Delta .gt. 0.001) enddo enddo if (MaxDelta) goto 200 thereby, eliminating the conditional expression from the inner loop. A microprocessor can execute many instructions per instruction cycle. Typically, it can execute one or more memory, floating point, integer, and jump operations. To be executed simultaneously, the operations must be independent. Thick loops tend to have more instruction level parallelism than thin loops. Moreover, they reduce memory traffice by maximizing data reuse. Loop unrolling and loop fusion are two techniques to increase the size of loop bodies. Several of the codes studied benefitted from loop unrolling, but none benefitted from loop fusion. This observation is not too surpising since it is the general tendency of programmers to write thick loops. As loops become thicker, the number of temporary values grows, increasing register pressure. If registers spill, then memory traffic increases and code flow is disrupted. A thick loop with many temporary values may execute slower than an equivalent series of thin loops. The biggest gain will be achieved if the thick loop can be split into a series of independent loops eliminating the need to write and read temporary arrays. I found such an occasion in code 10 where I split the loop do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do into two disjoint loops do i = 1, n do j = 1, m A24(j,i)= S24(j,i) * T24(j,i) + S25(j,i) * U25(j,i) B24(j,i)= S24(j,i) * T25(j,i) + S25(j,i) * U24(j,i) A25(j,i)= S24(j,i) * C24(j,i) + S25(j,i) * V24(j,i) B25(j,i)= S24(j,i) * U25(j,i) + S25(j,i) * V25(j,i) end do end do do i = 1, n do j = 1, m C24(j,i)= S26(j,i) * T26(j,i) + S27(j,i) * U26(j,i) D24(j,i)= S26(j,i) * T27(j,i) + S27(j,i) * V26(j,i) C25(j,i)= S27(j,i) * S28(j,i) + S26(j,i) * U28(j,i) D25(j,i)= S27(j,i) * T28(j,i) + S26(j,i) * V28(j,i) end do end do Conclusions Over the course of the last year, I have had the opportunity to work with over two dozen academic scientific programmers at leading research universities. Their research interests span a broad range of scientific fields. Except for two programs that relied almost exclusively on library routines (matrix multiply and fast Fourier transform), I was able to improve significantly the single processor performance of all codes. Improvements range from 2x to 15.5x with a simple average of 4.75x. Changes to the source code were at a very high level. I did not use sophisticated techniques or programming tools to discover inefficiencies or effect the changes. Only one code was parallel despite the availability of parallel systems to all developers. Clearly, we have a problem—personal scientific research codes are highly inefficient and not running parallel. The developers are unaware of simple optimization techniques to make programs run faster. They lack education in the art of code optimization and parallel programming. I do not believe we can fix the problem by publishing additional books or training manuals. To date, the developers in questions have not studied the books or manual available, and are unlikely to do so in the future. Short courses are a possible solution, but I believe they are too concentrated to be much use. The general concepts can be taught in a three or four day course, but that is not enough time for students to practice what they learn and acquire the experience to apply and extend the concepts to their codes. Practice is the key to becoming proficient at optimization. I recommend that graduate students be required to take a semester length course in optimization and parallel programming. We would never give someone access to state-of-the-art scientific equipment costing hundreds of thousands of dollars without first requiring them to demonstrate that they know how to use the equipment. Yet the criterion for time on state-of-the-art supercomputers is at most an interesting project. Requestors are never asked to demonstrate that they know how to use the system, or can use the system effectively. A semester course would teach them the required skills. Government agencies that fund academic scientific research pay for most of the computer systems supporting scientific research as well as the development of most personal scientific codes. These agencies should require graduate schools to offer a course in optimization and parallel programming as a requirement for funding. About the Author John Feo received his Ph.D. in Computer Science from The University of Texas at Austin in 1986. After graduate school, Dr. Feo worked at Lawrence Livermore National Laboratory where he was the Group Leader of the Computer Research Group and principal investigator of the Sisal Language Project. In 1997, Dr. Feo joined Tera Computer Company where he was project manager for the MTA, and oversaw the programming and evaluation of the MTA at the San Diego Supercomputer Center. In 2000, Dr. Feo joined Sun Microsystems as an HPC application specialist. He works with university research groups to optimize and parallelize scientific codes. Dr. Feo has published over two dozen research articles in the areas of parallel parallel programming, parallel programming languages, and application performance.

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  • ?12c database ????Adaptive Execution Plans ????????

    - by Liu Maclean(???)
    12c R1 ????SQL??????- Adaptive Execution Plans ????????,???????optimizer ??????(runtime)???????????????, ????????????????????? SQL???????? ????????????, ?????????????????????????????????????????????????????????????adaptive plan ????????????????????????????????????,?????subplan???????????????????? ??????, ???????? ???????????????,?????????, ?????? ???????????????”???”????, ???????????????????buffer ???????  ????????????,?????,??????????????????? ???optimizer ?????????????????????????,?????????????????????????????????????????plan???? ??12C?????????????, ???????????????????,?????? ???????????? ????????????2???: Dynamic Plans????: ???????????????????????;??????,???optimizer??????????subplans??????????????, ???????????????????,?????????????? Reoptimization????: ?Dynamic Plans????,Reoptimization??????????????????????Reoptimization??,?????????????????????????,??reoptimization????? OPTIMIZER_ADAPTIVE_REPORTING_ONLY ???? report-only????????????????TRUE,?????????report-only????,???????????????,??????????????? Dynamic Plans ??????????????,????????????????????????, ?????????????,???????????,????????????????????????????????????????? ?????????????final plan??????????????default plan, ??final plan?default plan???????,????????????? subplan ???????????????,???????????????????????? ??????,???????statistics collector ?buffer???????????statistics collector?????????????????,???????????????????????????? ?????????????????????????????????????????,??????????,?????????????? ???????????,???????buffer???? ???????????????,?????????????????????????????,??????buffer,??????final plan? ????????,???????????????????????,????????????????? ?V$SQL??????IS_RESOLVED_DYNAMIC_PLAN??????????final plan???default plan? ??????dynamic plan ???????SQL PLAN directives?????? declare cursor PLAN_DIRECTIVE_IDS is select directive_id from DBA_SQL_PLAN_DIRECTIVES; begin for z in PLAN_DIRECTIVE_IDS loop DBMS_SPD.DROP_SQL_PLAN_DIRECTIVE(z.directive_id); end loop; end; / explain plan for select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; select * from table(dbms_xplan.display()); Plan hash value: 1255158658 www.askmaclean.com ------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Rows | Bytes | Cost (%CPU)| Time | ------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 4 | 128 | 7 (0)| 00:00:01 | | 1 | NESTED LOOPS | | | | | | | 2 | NESTED LOOPS | | 4 | 128 | 7 (0)| 00:00:01 | |* 3 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 (0)| 00:00:01 | |* 4 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK | 1 | | 0 (0)| 00:00:01 | | 5 | TABLE ACCESS BY INDEX ROWID| PRODUCT_INFORMATION | 1 | 20 | 1 (0)| 00:00:01 | ------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 3 - filter("O"."UNIT_PRICE"=15 AND "QUANTITY">1) 4 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") alter session set events '10053 trace name context forever,level 1'; OR alter session set events 'trace[SQL_Plan_Directive] disk highest'; select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id; ---------------------------------------------------------------+-----------------------------------+ | Id | Operation | Name | Rows | Bytes | Cost | Time | ---------------------------------------------------------------+-----------------------------------+ | 0 | SELECT STATEMENT | | | | 7 | | | 1 | HASH JOIN | | 4 | 128 | 7 | 00:00:01 | | 2 | NESTED LOOPS | | | | | | | 3 | NESTED LOOPS | | 4 | 128 | 7 | 00:00:01 | | 4 | STATISTICS COLLECTOR | | | | | | | 5 | TABLE ACCESS FULL | ORDER_ITEMS | 4 | 48 | 3 | 00:00:01 | | 6 | INDEX UNIQUE SCAN | PRODUCT_INFORMATION_PK| 1 | | 0 | | | 7 | TABLE ACCESS BY INDEX ROWID | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | | 8 | TABLE ACCESS FULL | PRODUCT_INFORMATION | 1 | 20 | 1 | 00:00:01 | ---------------------------------------------------------------+-----------------------------------+ Predicate Information: ---------------------- 1 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") 5 - filter(("O"."UNIT_PRICE"=15 AND "QUANTITY">1)) 6 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID") ===================================== SPD: BEGIN context at statement level ===================================== Stmt: ******* UNPARSED QUERY IS ******* SELECT /*+ OPT_ESTIMATE (@"SEL$1" JOIN ("P"@"SEL$1" "O"@"SEL$1") ROWS=13.000000 ) OPT_ESTIMATE (@"SEL$1" TABLE "O"@"SEL$1" ROWS=13.000000 ) */ "P"."PRODUCT_NAME" "PRODUCT_NAME" FROM "OE"."ORDER_ITEMS" "O","OE"."PRODUCT_INFORMATION" "P" WHERE "O"."UNIT_PRICE"=15 AND "O"."QUANTITY">1 AND "P"."PRODUCT_ID"="O"."PRODUCT_ID" Objects referenced in the statement PRODUCT_INFORMATION[P] 92194, type = 1 ORDER_ITEMS[O] 92197, type = 1 Objects in the hash table Hash table Object 92197, type = 1, ownerid = 6573730143572393221: No Dynamic Sampling Directives for the object Hash table Object 92194, type = 1, ownerid = 17822962561575639002: No Dynamic Sampling Directives for the object Return code in qosdInitDirCtx: ENBLD =================================== SPD: END context at statement level =================================== ======================================= SPD: BEGIN context at query block level ======================================= Query Block SEL$1 (#0) Return code in qosdSetupDirCtx4QB: NOCTX ===================================== SPD: END context at query block level ===================================== SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Inserted felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: qosdCreateFindingSingTab retCode = CREATED, fid = 2896834833840853267 SPD: qosdCreateDirCmp retCode = CREATED, fid = 2896834833840853267 SPD: Return code in qosdDSDirSetup: NOCTX, estType = TABLE SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SKIP_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = JOIN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_SCAN SPD: Return code in qosdDSDirSetup: NOCTX, estType = INDEX_FILTER SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92197, objtyp = 1, vecsize = 6, colvec = [4, 5, ], fid = 2896834833840853267 SPD: Modified felem, fid=2896834833840853267, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = YES, keep = YES SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 5618517328604016300 SPD: Modified felem, fid=5618517328604016300, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 1, objcnt = 1, obItr = 0, objid = 92194, objtyp = 1, vecsize = 2, colvec = [1, ], fid = 1142802697078608149 SPD: Modified felem, fid=1142802697078608149, ftype = 1, freason = 1, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO SPD: Generating finding id: type = 1, reason = 2, objcnt = 2, obItr = 0, objid = 92194, objtyp = 1, vecsize = 0, obItr = 1, objid = 92197, objtyp = 1, vecsize = 0, fid = 1437680122701058051 SPD: Modified felem, fid=1437680122701058051, ftype = 1, freason = 2, dtype = 0, dstate = 0, dflag = 0, ver = NO, keep = NO select * from table(dbms_xplan.display_cursor(format=>'report')) ; ????report????adaptive plan Adaptive plan: ------------- This cursor has an adaptive plan, but adaptive plans are enabled for reporting mode only.  The plan that would be executed if adaptive plans were enabled is displayed below. ------------------------------------------------------------------------------------------ | Id  | Operation          | Name                | Rows  | Bytes | Cost (%CPU)| Time     | ------------------------------------------------------------------------------------------ |   0 | SELECT STATEMENT   |                     |       |       |     7 (100)|          | |*  1 |  HASH JOIN         |                     |     4 |   128 |     7   (0)| 00:00:01 | |*  2 |   TABLE ACCESS FULL| ORDER_ITEMS         |     4 |    48 |     3   (0)| 00:00:01 | |   3 |   TABLE ACCESS FULL| PRODUCT_INFORMATION |     1 |    20 |     1   (0)| 00:00:01 | ------------------------------------------------------------------------------------------ SQL> select SQL_ID,IS_RESOLVED_DYNAMIC_PLAN,sql_text from v$SQL WHERE SQL_TEXT like '%MALCEAN%' and sql_text not like '%like%'; SQL_ID IS -------------------------- -- SQL_TEXT -------------------------------------------------------------------------------- 6ydj1bn1bng17 Y select /*MALCEAN*/ product_name from oe.order_items o, oe.product_information p where o.unit_price=15 and quantity>1 and p.product_id=o.product_id ???? explain plan for ????default plan, ??????optimizer???final plan,??V$SQL.IS_RESOLVED_DYNAMIC_PLAN???Y,????????????? DBA_SQL_PLAN_DIRECTIVES?????????????SQL PLAN DIRECTIVES, ???12c? ???MMON?????DML ???column usage??????????,????SMON??? MMON????SGA??PLAN DIRECTIVES??? ?????DBMS_SPD.flush_sql_plan_directive???? select directive_id,type,reason from DBA_SQL_PLAN_DIRECTIVES / DIRECTIVE_ID TYPE REASON ----------------------------------- -------------------------------- ----------------------------- 10321283028317893030 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 4757086536465754886 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE 16085268038103121260 DYNAMIC_SAMPLING JOIN CARDINALITY MISESTIMATE SQL> set pages 9999 SQL> set lines 300 SQL> col state format a5 SQL> col subobject_name format a11 SQL> col col_name format a11 SQL> col object_name format a13 SQL> select d.directive_id, o.object_type, o.object_name, o.subobject_name col_name, d.type, d.state, d.reason 2 from dba_sql_plan_directives d, dba_sql_plan_dir_objects o 3 where d.DIRECTIVE_ID=o.DIRECTIVE_ID 4 and o.object_name in ('ORDER_ITEMS') 5 order by d.directive_id; DIRECTIVE_ID OBJECT_TYPE OBJECT_NAME COL_NAME TYPE STATE REASON ------------ ------------ ------------- ----------- -------------------------------- ----- ------------------------------------- --- 1.8156E+19 COLUMN ORDER_ITEMS UNIT_PRICE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 TABLE ORDER_ITEMS DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1.8156E+19 COLUMN ORDER_ITEMS QUANTITY DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE DBA_SQL_PLAN_DIRECTIVES????? _BASE_OPT_DIRECTIVE ? _BASE_OPT_FINDING SELECT d.dir_own#, d.dir_id, d.f_id, decode(type, 1, 'DYNAMIC_SAMPLING', 'UNKNOWN'), decode(state, 1, 'NEW', 2, 'MISSING_STATS', 3, 'HAS_STATS', 4, 'CANDIDATE', 5, 'PERMANENT', 6, 'DISABLED', 'UNKNOWN'), decode(bitand(flags, 1), 1, 'YES', 'NO'), cast(d.created as timestamp), cast(d.last_modified as timestamp), -- Please see QOSD_DAYS_TO_UPDATE and QOSD_PLUS_SECONDS for more details -- about 6.5 cast(d.last_used as timestamp) - NUMTODSINTERVAL(6.5, 'day') FROM sys.opt_directive$ d ??dbms_spd??? SQL PLAN DIRECTIVES, SQL PLAN DIRECTIVES???retention ???53?: Package: DBMS_SPD This package provides subprograms for managing Sql Plan Directives(SPD). SPD are objects generated automatically by Oracle server. For example, if server detects that the single table cardinality estimated by optimizer is off from the actual number of rows returned when accessing the table, it will automatically create a directive to do dynamic sampling for the table. When any Sql statement referencing the table is compiled, optimizer will perform dynamic sampling for the table to get more accurate estimate. Notes: DBMSL_SPD is a invoker-rights package. The invoker requires ADMINISTER SQL MANAGEMENT OBJECT privilege for executing most of the subprograms of this package. Also the subprograms commit the current transaction (if any), perform the operation and commit it again. DBA view dba_sql_plan_directives shows all the directives created in the system and the view dba_sql_plan_dir_objects displays the objects that are included in the directives. -- Default value for SPD_RETENTION_WEEKS SPD_RETENTION_WEEKS_DEFAULT CONSTANT varchar2(4) := '53'; | STATE : NEW : Newly created directive. | : MISSING_STATS : The directive objects do not | have relevant stats. | : HAS_STATS : The objects have stats. | : PERMANENT : A permanent directive. Server | evaluated effectiveness and these | directives are useful. | | AUTO_DROP : YES : Directive will be dropped | automatically if not | used for SPD_RETENTION_WEEKS. | This is the default behavior. | NO : Directive will not be dropped | automatically. Procedure: flush_sql_plan_directive This procedure allows manually flushing the Sql Plan directives that are automatically recorded in SGA memory while executing sql statements. The information recorded in SGA are periodically flushed by oracle background processes. This procedure just provides a way to flush the information manually. ????”_optimizer_dynamic_plans”(enable dynamic plans)????????,???TRUE??DYNAMIC PLAN? ???FALSE???????????? ????,Dynamic Plan????????????Nested Loop?Hash Join???case ,????????Nested loop???????????HASH JOIN,?HASH JOIN????????????????? ????????subplan?????,???? pass?? ?join method???,?????STATISTICS COLLECTOR???cardinality?,???????HASH JOIN?????Nested Loop,????????????subplan?????access path; ???????Sales??????????????????,????HASH JOIN,??SUBPLAN??customers?????????;?????Nested Loop,???????cust_id?????Range Scan+Access by Rowid? Cardinality feedback Cardinality feedback????????11.2????,????????re-optimization???;  ???????????,Cardinality feedback?????????????????????????? ???????????????????,?????????????????,??????????Cardinality feedback????????????? ????????????????????????? ??????????????Cardinality feedback ??: ????????,???????????,??????????,????????????????selectivity ??? ????????????: ??????,?????????????????????????????????,??????????????????? ????????????????????????????????????????,?????????????????????????? ?????????,???????????????,?????????? ??????????Cardinality ????,??????join Cardinality ????????? Cardinality feedback???????cursor?,?Cursor???aged out????? SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ---------------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | OMem | 1Mem | Used-Mem | ---------------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | 20 | | | | |* 1 | HASH JOIN | | 1 | 4 | 13 |00:00:00.01 | 24 | 20 | 2061K| 2061K| 429K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 4 | 13 |00:00:00.01 | 7 | 6 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 1 | 288 |00:00:00.01 | 17 | 14 | | | | ---------------------------------------------------------------------------------------------------------------------------------------- SELECT /*+ gather_plan_statistics */ product_name FROM order_items o, product_information p WHERE o.unit_price = 15 AND quantity > 1 AND p.product_id = o.product_id Plan hash value: 1553478007 ------------------------------------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | OMem | 1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 13 |00:00:00.01 | 24 | | | | |* 1 | HASH JOIN | | 1 | 13 | 13 |00:00:00.01 | 24 | 2061K| 2061K| 413K (0)| |* 2 | TABLE ACCESS FULL| ORDER_ITEMS | 1 | 13 | 13 |00:00:00.01 | 7 | | | | | 3 | TABLE ACCESS FULL| PRODUCT_INFORMATION | 1 | 288 | 288 |00:00:00.01 | 17 | | | | ------------------------------------------------------------------------------------------------------------------------------- Note ----- - statistics feedback used for this statement SQL> select count(*) from v$SQL where SQL_ID='cz0hg2zkvd10y'; COUNT(*) ---------- 2 SQL>select sql_ID,USE_FEEDBACK_STATS FROM V$SQL_SHARED_CURSOR where USE_FEEDBACK_STATS ='Y'; SQL_ID U ------------- - cz0hg2zkvd10y Y ????????Cardinality feedback????,???????????????????????????,????????????order_items???????? ????2??????plan hash value??(??????????),?????2????child cursor??????gather_plan_statistics???actual : A-ROWS  estimate :E-ROWS????????? Automatic Re-optimization ???dynamic plan, Re-optimization???????????????  ?  ??????????????? ????????????????????????????????  ???????????,??????????????, ???????????????????? ???????????  Re-optimization??, ????????????????????? Re-optimization????dynamic plan??????????  dynamic plan????????????????????, ???????????????????? ????,??????????join order ??????????????,?????????????join order????? ??????,????????Re-optimization, ??Re-optimization ??????????????????? ?Oracle database 12c?,join statistics?????????????????????,??????????????????????Re-optimization???????????adaptive cursor sharing????? ????????????????,???????????? ????? ???????statistics collectors ????????????????????Re-optimization??????2?????????????,???????????????? ??????????????Re-optimization?????,?????????????????????? ???v$SQL??????IS_REOPTIMIZABLE?????????????????????Re-optimization,??????????Re-optimization???,?????Re-optimization ,???????reporting????? IS_REOPTIMIZABLE VARCHAR2(1) This columns shows whether the next execution matching this child cursor will trigger a reoptimization. The values are:   Y: If the next execution will trigger a reoptimization R: If the child cursor contains reoptimization information, but will not trigger reoptimization because the cursor was compiled in reporting mode N: If the child cursor has no reoptimization information ??1: select plan_table_output from table (dbms_xplan.display_cursor('gwf99gfnm0t7g',NULL,'ALLSTATS LAST')); SQL_ID  gwf99gfnm0t7g, child number 0 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 1906736282 ------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation             | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | ------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT      |                     |      1 |        |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   1 |  NESTED LOOPS         |                     |      1 |      1 |    269 |00:00:00.02 |    1336 |     18 |       |       |          | |   2 |   MERGE JOIN CARTESIAN|                     |      1 |      4 |   9135 |00:00:00.02 |      34 |     15 |       |       |          | |*  3 |    TABLE ACCESS FULL  | PRODUCT_INFORMATION |      1 |      1 |     87 |00:00:00.01 |      33 |     14 |       |       |          | |   4 |    BUFFER SORT        |                     |     87 |    105 |   9135 |00:00:00.01 |       1 |      1 |  4096 |  4096 | 4096  (0)| |   5 |     INDEX FULL SCAN   | ORDER_PK            |      1 |    105 |    105 |00:00:00.01 |       1 |      1 |       |       |          | |*  6 |   INDEX UNIQUE SCAN   | ORDER_ITEMS_UK      |   9135 |      1 |    269 |00:00:00.01 |    1302 |      3 |       |       |          | ------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    6 - access("O"."ORDER_ID"="ORDER_ID" AND "P"."PRODUCT_ID"="O"."PRODUCT_ID") SQL_ID  gwf99gfnm0t7g, child number 1 ------------------------------------- SELECT /*+ SFTEST gather_plan_statistics */ o.order_id, v.product_name FROM  orders o,   ( SELECT order_id, product_name FROM order_items o, product_information p     WHERE  p.product_id = o.product_id AND list_price < 50 AND min_price < 40  ) v WHERE o.order_id = v.order_id Plan hash value: 35479787 -------------------------------------------------------------------------------------------------------------------------------------------- | Id  | Operation              | Name                | Starts | E-Rows | A-Rows |   A-Time   | Buffers | Reads  |  OMem |  1Mem | Used-Mem | -------------------------------------------------------------------------------------------------------------------------------------------- |   0 | SELECT STATEMENT       |                     |      1 |        |    269 |00:00:00.01 |      63 |      3 |       |       |          | |   1 |  NESTED LOOPS          |                     |      1 |    269 |    269 |00:00:00.01 |      63 |      3 |       |       |          | |*  2 |   HASH JOIN            |                     |      1 |    313 |    269 |00:00:00.01 |      42 |      3 |  1321K|  1321K| 1234K (0)| |*  3 |    TABLE ACCESS FULL   | PRODUCT_INFORMATION |      1 |     87 |     87 |00:00:00.01 |      16 |      0 |       |       |          | |   4 |    INDEX FAST FULL SCAN| ORDER_ITEMS_UK      |      1 |    665 |    665 |00:00:00.01 |      26 |      3 |       |       |          | |*  5 |   INDEX UNIQUE SCAN    | ORDER_PK            |    269 |      1 |    269 |00:00:00.01 |      21 |      0 |       |       |          | -------------------------------------------------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): ---------------------------------------------------    2 - access("P"."PRODUCT_ID"="O"."PRODUCT_ID")    3 - filter(("MIN_PRICE"<40 AND "LIST_PRICE"<50))    5 - access("O"."ORDER_ID"="ORDER_ID") Note -----    - statistics feedback used for this statement    SQL> select IS_REOPTIMIZABLE,child_number FROM V$SQL  A where A.SQL_ID='gwf99gfnm0t7g'; IS CHILD_NUMBER -- ------------ Y             0 N             1    1* select child_number,other_xml From v$SQL_PLAN  where SQL_ID='gwf99gfnm0t7g' and other_xml is not nul SQL> / CHILD_NUMBER OTHER_XML ------------ --------------------------------------------------------------------------------            1 <other_xml><info type="cardinality_feedback">yes</info><info type="db_version">1              2.1.0.1</info><info type="parse_schema"><![CDATA["OE"]]></info><info type="plan_              hash">35479787</info><info type="plan_hash_2">3382491761</info><outline_data><hi              nt><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]></hint><hint><![CDATA[OPTIMIZER_FEATUR              ES_ENABLE('12.1.0.1')]]></hint><hint><![CDATA[DB_VERSION('12.1.0.1')]]></hint><h              int><![CDATA[ALL_ROWS]]></hint><hint><![CDATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></              hint><hint><![CDATA[MERGE(@"SEL$2")]]></hint><hint><![CDATA[OUTLINE(@"SEL$1")]]>              </hint><hint><![CDATA[OUTLINE(@"SEL$2")]]></hint><hint><![CDATA[FULL(@"SEL$F5BB7              4E1" "P"@"SEL$2")]]></hint><hint><![CDATA[INDEX_FFS(@"SEL$F5BB74E1" "O"@"SEL$2"              ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PRODUCT_ID"))]]></hint><hint><![CDATA[I              NDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA[              LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$2" "O"@"SEL$1")]]></hint><hint><![C              DATA[USE_HASH(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint><hint><![CDATA[USE_NL(@"SEL$              F5BB74E1" "O"@"SEL$1")]]></hint></outline_data></other_xml>            0 <other_xml><info type="db_version">12.1.0.1</info><info type="parse_schema"><![C              DATA["OE"]]></info><info type="plan_hash">1906736282</info><info type="plan_hash              _2">2579473118</info><outline_data><hint><![CDATA[IGNORE_OPTIM_EMBEDDED_HINTS]]>              </hint><hint><![CDATA[OPTIMIZER_FEATURES_ENABLE('12.1.0.1')]]></hint><hint><![CD              ATA[DB_VERSION('12.1.0.1')]]></hint><hint><![CDATA[ALL_ROWS]]></hint><hint><![CD              ATA[OUTLINE_LEAF(@"SEL$F5BB74E1")]]></hint><hint><![CDATA[MERGE(@"SEL$2")]]></hi              nt><hint><![CDATA[OUTLINE(@"SEL$1")]]></hint><hint><![CDATA[OUTLINE(@"SEL$2")]]>              </hint><hint><![CDATA[FULL(@"SEL$F5BB74E1" "P"@"SEL$2")]]></hint><hint><![CDATA[              INDEX(@"SEL$F5BB74E1" "O"@"SEL$1" ("ORDERS"."ORDER_ID"))]]></hint><hint><![CDATA              [INDEX(@"SEL$F5BB74E1" "O"@"SEL$2" ("ORDER_ITEMS"."ORDER_ID" "ORDER_ITEMS"."PROD              UCT_ID"))]]></hint><hint><![CDATA[LEADING(@"SEL$F5BB74E1" "P"@"SEL$2" "O"@"SEL$1              " "O"@"SEL$2")]]></hint><hint><![CDATA[USE_MERGE_CARTESIAN(@"SEL$F5BB74E1" "O"@"              SEL$1")]]></hint><hint><![CDATA[USE_NL(@"SEL$F5BB74E1" "O"@"SEL$2")]]></hint></o              utline_data></other_xml> ??2: SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 0 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 -------------------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | Reads | -------------------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | 14 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 8 | 29 |00:00:00.01 | 17 | 14 | -------------------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OWNER OBJECT_NAME COL_NAME OBJECT TYPE STATE REASON ----------------------- ----- ------------- ----------- ------ ---------------- ----- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING NEW SINGLE TABLE CARDINALITY MISESTIMATE SELECT /*+gather_plan_statistics*/ * FROM customers WHERE cust_state_province='CA' AND country_id='US'; ELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID b74nw722wjvy3, child number 1 ------------------------------------- select /*+gather_plan_statistics*/ * from customers where CUST_STATE_PROVINCE='CA' and country_id='US' Plan hash value: 1683234692 ----------------------------------------------------------------------------------------- | Id | Operation | Name | Starts | E-Rows | A-Rows | A-Time | Buffers | ----------------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 29 |00:00:00.01 | 17 | |* 1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 29 | 29 |00:00:00.01 | 17 | ----------------------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='CA' AND "COUNTRY_ID"='US')) Note ----- - cardinality feedback used for this statement SELECT SQL_ID, CHILD_NUMBER, SQL_TEXT, IS_REOPTIMIZABLE FROM V$SQL WHERE SQL_TEXT LIKE 'SELECT /*+gather_plan_statistics*/%'; SQL_ID CHILD_NUMBER SQL_TEXT I ------------- ------------ ----------- - b74nw722wjvy3 0 select /*+g Y ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' b74nw722wjvy3 1 select /*+g N ather_plan_ statistics* / * from cu stomers whe re CUST_STA TE_PROVINCE ='CA' and c ountry_id=' US' SELECT /*+gather_plan_statistics*/ CUST_EMAIL FROM CUSTOMERS WHERE CUST_STATE_PROVINCE='MA' AND COUNTRY_ID='US'; SELECT * FROM TABLE(DBMS_XPLAN.DISPLAY_CURSOR(FORMAT=>'ALLSTATS LAST')); PLAN_TABLE_OUTPUT ------------------------------------- SQL_ID 3tk6hj3nkcs2u, child number 0 ------------------------------------- Select /*+gather_plan_statistics*/ cust_email From customers Where cust_state_province='MA' And country_id='US' Plan hash value: 1683234692 ------------------------------------------------------------------------------- |Id | Operation | Name | Starts|E-Rows|A-Rows| A-Time |Buffers| ------------------------------------------------------------------------------- | 0 | SELECT STATEMENT | | 1 | | 2 |00:00:00.01| 16 | |*1 | TABLE ACCESS FULL| CUSTOMERS | 1 | 2| 2 |00:00:00.01| 16 | ----------------------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(("CUST_STATE_PROVINCE"='MA' AND "COUNTRY_ID"='US')) Note ----- - dynamic sampling used for this statement (level=2) - 1 Sql Plan Directive used for this statement EXEC DBMS_SPD.FLUSH_SQL_PLAN_DIRECTIVE; SELECT TO_CHAR(d.DIRECTIVE_ID) dir_id, o.OWNER, o.OBJECT_NAME, o.SUBOBJECT_NAME col_name, o.OBJECT_TYPE, d.TYPE, d.STATE, d.REASON FROM DBA_SQL_PLAN_DIRECTIVES d, DBA_SQL_PLAN_DIR_OBJECTS o WHERE d.DIRECTIVE_ID=o.DIRECTIVE_ID AND o.OWNER IN ('SH') ORDER BY 1,2,3,4,5; DIR_ID OW OBJECT_NA COL_NAME OBJECT TYPE STATE REASON ------------------- -- --------- ---------- ------- --------------- ------------- ------------------------ 1484026771529551585 SH CUSTOMERS COUNTRY_ID COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE 1484026771529551585 SH CUSTOMERS CUST_STATE_ COLUMN DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY PROVINCE MISESTIMATE 1484026771529551585 SH CUSTOMERS TABLE DYNAMIC_SAMPLING MISSING_STATS SINGLE TABLE CARDINALITY MISESTIMATE

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  • Valgrind says "stack allocation," I say "heap allocation"

    - by Joel J. Adamson
    Dear Friends, I am trying to trace a segfault with valgrind. I get the following message from valgrind: ==3683== Conditional jump or move depends on uninitialised value(s) ==3683== at 0x4C277C5: sparse_mat_mat_kron (sparse.c:165) ==3683== by 0x4C2706E: rec_mating (rec.c:176) ==3683== by 0x401C1C: age_dep_iterate (age_dep.c:287) ==3683== by 0x4014CB: main (age_dep.c:92) ==3683== Uninitialised value was created by a stack allocation ==3683== at 0x401848: age_dep_init_params (age_dep.c:131) ==3683== ==3683== Conditional jump or move depends on uninitialised value(s) ==3683== at 0x4C277C7: sparse_mat_mat_kron (sparse.c:165) ==3683== by 0x4C2706E: rec_mating (rec.c:176) ==3683== by 0x401C1C: age_dep_iterate (age_dep.c:287) ==3683== by 0x4014CB: main (age_dep.c:92) ==3683== Uninitialised value was created by a stack allocation ==3683== at 0x401848: age_dep_init_params (age_dep.c:131) However, here's the offending line: /* allocate mating table */ age_dep_data->mtable = malloc (age_dep_data->geno * sizeof (double *)); if (age_dep_data->mtable == NULL) error (ENOMEM, ENOMEM, nullmsg, __LINE__); for (int j = 0; j < age_dep_data->geno; j++) { 131=> age_dep_data->mtable[j] = calloc (age_dep_data->geno, sizeof (double)); if (age_dep_data->mtable[j] == NULL) error (ENOMEM, ENOMEM, nullmsg, __LINE__); } What gives? I thought any call to malloc or calloc allocated heap space; there is no other variable allocated here, right? Is it possible there's another allocation going on (the offending stack allocation) that I'm not seeing? You asked to see the code, here goes: /* Copyright 2010 Joel J. Adamson <[email protected]> $Id: age_dep.c 1010 2010-04-21 19:19:16Z joel $ age_dep.c:main file Joel J. Adamson -- http://www.unc.edu/~adamsonj Servedio Lab University of North Carolina at Chapel Hill CB #3280, Coker Hall Chapel Hill, NC 27599-3280 This file is part of an investigation of age-dependent sexual selection. This code is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with haploid. If not, see <http://www.gnu.org/licenses/>. */ #include "age_dep.h" /* global variables */ extern struct argp age_dep_argp; /* global error message variables */ char * nullmsg = "Null pointer: %i"; /* error message for conversions: */ char * errmsg = "Representation error: %s"; /* precision for formatted output: */ const char prec[] = "%-#9.8f "; const size_t age_max = AGEMAX; /* maximum age of males */ static int keep_going_p = 1; int main (int argc, char ** argv) { /* often used counters: */ int i, j; /* read the command line */ struct age_dep_args age_dep_args = { NULL, NULL, NULL }; argp_parse (&age_dep_argp, argc, argv, 0, 0, &age_dep_args); /* set the parameters here: */ /* initialize an age_dep_params structure, set the members */ age_dep_params_t * params = malloc (sizeof (age_dep_params_t)); if (params == NULL) error (ENOMEM, ENOMEM, nullmsg, __LINE__); age_dep_init_params (params, &age_dep_args); /* initialize frequencies: this initializes a list of pointers to initial frqeuencies, terminated by a NULL pointer*/ params->freqs = age_dep_init (&age_dep_args); params->by = 0.0; /* what range of parameters do we want, and with what stepsize? */ /* we should go from 0 to half-of-theta with a step size of about 0.01 */ double from = 0.0; double to = params->theta / 2.0; double stepsz = 0.01; /* did you think I would spell the whole word? */ unsigned int numparts = floor(to / stepsz); do { #pragma omp parallel for private(i) firstprivate(params) \ shared(stepsz, numparts) for (i = 0; i < numparts; i++) { params->by = i * stepsz; int tries = 0; while (keep_going_p) { /* each time through, modify mfreqs and mating table, then go again */ keep_going_p = age_dep_iterate (params, ++tries); if (keep_going_p == ERANGE) error (ERANGE, ERANGE, "Failure to converge\n"); } fprintf (stdout, "%i iterations\n", tries); } /* for i < numparts */ params->freqs = params->freqs->next; } while (params->freqs->next != NULL); return 0; } inline double age_dep_pmate (double age_dep_t, unsigned int genot, double bp, double ba) { /* the probability of mating between these phenotypes */ /* the female preference depends on whether the female has the preference allele, the strength of preference (parameter bp) and the male phenotype (age_dep_t); if the female lacks the preference allele, then this will return 0, which is not quite accurate; it should return 1 */ return bits_isset (genot, CLOCI)? 1.0 - exp (-bp * age_dep_t) + ba: 1.0; } inline double age_dep_trait (int age, unsigned int genot, double by) { /* return the male trait, a function of the trait locus, age, the age-dependent scaling parameter (bx) and the males condition genotype */ double C; double T; /* get the male's condition genotype */ C = (double) bits_popcount (bits_extract (0, CLOCI, genot)); /* get his trait genotype */ T = bits_isset (genot, CLOCI + 1)? 1.0: 0.0; /* return the trait value */ return T * by * exp (age * C); } int age_dep_iterate (age_dep_params_t * data, unsigned int tries) { /* main driver routine */ /* number of bytes for female frequencies */ size_t geno = data->age_dep_data->geno; size_t genosize = geno * sizeof (double); /* female frequencies are equal to male frequencies at birth (before selection) */ double ffreqs[geno]; if (ffreqs == NULL) error (ENOMEM, ENOMEM, nullmsg, __LINE__); /* do not set! Use memcpy (we need to alter male frequencies (selection) without altering female frequencies) */ memmove (ffreqs, data->freqs->freqs[0], genosize); /* for (int i = 0; i < geno; i++) */ /* ffreqs[i] = data->freqs->freqs[0][i]; */ #ifdef PRMTABLE age_dep_pr_mfreqs (data); #endif /* PRMTABLE */ /* natural selection: */ age_dep_ns (data); /* normalized mating table with new frequencies */ age_dep_norm_mtable (ffreqs, data); #ifdef PRMTABLE age_dep_pr_mtable (data); #endif /* PRMTABLE */ double * newfreqs; /* mutate here */ /* i.e. get the new frequency of 0-year-olds using recombination; */ newfreqs = rec_mating (data->age_dep_data); /* return block */ { if (sim_stop_ck (data->freqs->freqs[0], newfreqs, GENO, TOL) == 0) { /* if we have converged, stop the iterations and handle the data */ age_dep_sim_out (data, stdout); return 0; } else if (tries > MAXTRIES) return ERANGE; else { /* advance generations */ for (int j = age_max - 1; j < 0; j--) memmove (data->freqs->freqs[j], data->freqs->freqs[j-1], genosize); /* advance the first age-class */ memmove (data->freqs->freqs[0], newfreqs, genosize); return 1; } } } void age_dep_ns (age_dep_params_t * data) { /* calculate the new frequency of genotypes given additive fitness and selection coefficient s */ size_t geno = data->age_dep_data->geno; double w[geno]; double wbar, dtheta, ttheta, dcond, tcond; double t, cond; /* fitness parameters */ double mu, nu; mu = data->wparams[0]; nu = data->wparams[1]; /* calculate fitness */ for (int j = 0; j < age_max; j++) { int i; for (i = 0; i < geno; i++) { /* calculate male trait: */ t = age_dep_trait(j, i, data->by); /* calculate condition: */ cond = (double) bits_popcount (bits_extract(0, CLOCI, i)); /* trait-based fitness term */ dtheta = data->theta - t; ttheta = (dtheta * dtheta) / (2.0 * nu * nu); /* condition-based fitness term */ dcond = CLOCI - cond; tcond = (dcond * dcond) / (2.0 * mu * mu); /* calculate male fitness */ w[i] = 1 + exp(-tcond) - exp(-ttheta); } /* calculate mean fitness */ /* as long as we calculate wbar before altering any values of freqs[], we're safe */ wbar = gen_mean (data->freqs->freqs[j], w, geno); for (i = 0; i < geno; i++) data->freqs->freqs[j][i] = (data->freqs->freqs[j][i] * w[i]) / wbar; } } void age_dep_norm_mtable (double * ffreqs, age_dep_params_t * params) { /* this function produces a single mating table that forms the input for recombination () */ /* i is female genotype; j is male genotype; k is male age */ int i,j,k; double norm_denom; double trait; size_t geno = params->age_dep_data->geno; for (i = 0; i < geno; i++) { double norm_mtable[geno]; /* initialize the denominator: */ norm_denom = 0.0; /* find the probability of mating and add it to the denominator */ for (j = 0; j < geno; j++) { /* initialize entry: */ norm_mtable[j] = 0.0; for (k = 0; k < age_max; k++) { trait = age_dep_trait (k, j, params->by); norm_mtable[j] += age_dep_pmate (trait, i, params->bp, params->ba) * (params->freqs->freqs)[k][j]; } norm_denom += norm_mtable[j]; } /* now calculate entry (i,j) */ for (j = 0; j < geno; j++) params->age_dep_data->mtable[i][j] = (ffreqs[i] * norm_mtable[j]) / norm_denom; } } My current suspicion is the array newfreqs: I can't memmove, memcpy or assign a stack variable then hope it will persist, can I? rec_mating() returns double *.

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  • Is there a Telecommunications Reference Architecture?

    - by raul.goycoolea
    @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Abstract   Reference architecture provides needed architectural information that can be provided in advance to an enterprise to enable consistent architectural best practices. Enterprise Reference Architecture helps business owners to actualize their strategies, vision, objectives, and principles. It evaluates the IT systems, based on Reference Architecture goals, principles, and standards. It helps to reduce IT costs by increasing functionality, availability, scalability, etc. Telecom Reference Architecture provides customers with the flexibility to view bundled service bills online with the provision of multiple services. It provides real-time, flexible billing and charging systems, to handle complex promotions, discounts, and settlements with multiple parties. This paper attempts to describe the Reference Architecture for the Telecom Enterprises. It lays the foundation for a Telecom Reference Architecture by articulating the requirements, drivers, and pitfalls for telecom service providers. It describes generic reference architecture for telecom enterprises and moves on to explain how to achieve Enterprise Reference Architecture by using SOA.   Introduction   A Reference Architecture provides a methodology, set of practices, template, and standards based on a set of successful solutions implemented earlier. These solutions have been generalized and structured for the depiction of both a logical and a physical architecture, based on the harvesting of a set of patterns that describe observations in a number of successful implementations. It helps as a reference for the various architectures that an enterprise can implement to solve various problems. It can be used as the starting point or the point of comparisons for various departments/business entities of a company, or for the various companies for an enterprise. It provides multiple views for multiple stakeholders.   Major artifacts of the Enterprise Reference Architecture are methodologies, standards, metadata, documents, design patterns, etc.   Purpose of Reference Architecture   In most cases, architects spend a lot of time researching, investigating, defining, and re-arguing architectural decisions. It is like reinventing the wheel as their peers in other organizations or even the same organization have already spent a lot of time and effort defining their own architectural practices. This prevents an organization from learning from its own experiences and applying that knowledge for increased effectiveness.   Reference architecture provides missing architectural information that can be provided in advance to project team members to enable consistent architectural best practices.   Enterprise Reference Architecture helps an enterprise to achieve the following at the abstract level:   ·       Reference architecture is more of a communication channel to an enterprise ·       Helps the business owners to accommodate to their strategies, vision, objectives, and principles. ·       Evaluates the IT systems based on Reference Architecture Principles ·       Reduces IT spending through increasing functionality, availability, scalability, etc ·       A Real-time Integration Model helps to reduce the latency of the data updates Is used to define a single source of Information ·       Provides a clear view on how to manage information and security ·       Defines the policy around the data ownership, product boundaries, etc. ·       Helps with cost optimization across project and solution portfolios by eliminating unused or duplicate investments and assets ·       Has a shorter implementation time and cost   Once the reference architecture is in place, the set of architectural principles, standards, reference models, and best practices ensure that the aligned investments have the greatest possible likelihood of success in both the near term and the long term (TCO).     Common pitfalls for Telecom Service Providers   Telecom Reference Architecture serves as the first step towards maturity for a telecom service provider. During the course of our assignments/experiences with telecom players, we have come across the following observations – Some of these indicate a lack of maturity of the telecom service provider:   ·       In markets that are growing and not so mature, it has been observed that telcos have a significant amount of in-house or home-grown applications. In some of these markets, the growth has been so rapid that IT has been unable to cope with business demands. Telcos have shown a tendency to come up with workarounds in their IT applications so as to meet business needs. ·       Even for core functions like provisioning or mediation, some telcos have tried to manage with home-grown applications. ·       Most of the applications do not have the required scalability or maintainability to sustain growth in volumes or functionality. ·       Applications face interoperability issues with other applications in the operator's landscape. Integrating a new application or network element requires considerable effort on the part of the other applications. ·       Application boundaries are not clear, and functionality that is not in the initial scope of that application gets pushed onto it. This results in the development of the multiple, small applications without proper boundaries. ·       Usage of Legacy OSS/BSS systems, poor Integration across Multiple COTS Products and Internal Systems. Most of the Integrations are developed on ad-hoc basis and Point-to-Point Integration. ·       Redundancy of the business functions in different applications • Fragmented data across the different applications and no integrated view of the strategic data • Lot of performance Issues due to the usage of the complex integration across OSS and BSS systems   However, this is where the maturity of the telecom industry as a whole can be of help. The collaborative efforts of telcos to overcome some of these problems have resulted in bodies like the TM Forum. They have come up with frameworks for business processes, data, applications, and technology for telecom service providers. These could be a good starting point for telcos to clean up their enterprise landscape.   Industry Trends in Telecom Reference Architecture   Telecom reference architectures are evolving rapidly because telcos are facing business and IT challenges.   “The reality is that there probably is no killer application, no silver bullet that the telcos can latch onto to carry them into a 21st Century.... Instead, there are probably hundreds – perhaps thousands – of niche applications.... And the only way to find which of these works for you is to try out lots of them, ramp up the ones that work, and discontinue the ones that fail.” – Martin Creaner President & CTO TM Forum.   The following trends have been observed in telecom reference architecture:   ·       Transformation of business structures to align with customer requirements ·       Adoption of more Internet-like technical architectures. The Web 2.0 concept is increasingly being used. ·       Virtualization of the traditional operations support system (OSS) ·       Adoption of SOA to support development of IP-based services ·       Adoption of frameworks like Service Delivery Platforms (SDPs) and IP Multimedia Subsystem ·       (IMS) to enable seamless deployment of various services over fixed and mobile networks ·       Replacement of in-house, customized, and stove-piped OSS/BSS with standards-based COTS products ·       Compliance with industry standards and frameworks like eTOM, SID, and TAM to enable seamless integration with other standards-based products   Drivers of Reference Architecture   The drivers of the Reference Architecture are Reference Architecture Goals, Principles, and Enterprise Vision and Telecom Transformation. The details are depicted below diagram. @font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }div.Section1 { page: Section1; } Figure 1. Drivers for Reference Architecture @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Today’s telecom reference architectures should seamlessly integrate traditional legacy-based applications and transition to next-generation network technologies (e.g., IP multimedia subsystems). This has resulted in new requirements for flexible, real-time billing and OSS/BSS systems and implications on the service provider’s organizational requirements and structure.   Telecom reference architectures are today expected to:   ·       Integrate voice, messaging, email and other VAS over fixed and mobile networks, back end systems ·       Be able to provision multiple services and service bundles • Deliver converged voice, video and data services ·       Leverage the existing Network Infrastructure ·       Provide real-time, flexible billing and charging systems to handle complex promotions, discounts, and settlements with multiple parties. ·       Support charging of advanced data services such as VoIP, On-Demand, Services (e.g.  Video), IMS/SIP Services, Mobile Money, Content Services and IPTV. ·       Help in faster deployment of new services • Serve as an effective platform for collaboration between network IT and business organizations ·       Harness the potential of converging technology, networks, devices and content to develop multimedia services and solutions of ever-increasing sophistication on a single Internet Protocol (IP) ·       Ensure better service delivery and zero revenue leakage through real-time balance and credit management ·       Lower operating costs to drive profitability   Enterprise Reference Architecture   The Enterprise Reference Architecture (RA) fills the gap between the concepts and vocabulary defined by the reference model and the implementation. Reference architecture provides detailed architectural information in a common format such that solutions can be repeatedly designed and deployed in a consistent, high-quality, supportable fashion. This paper attempts to describe the Reference Architecture for the Telecom Application Usage and how to achieve the Enterprise Level Reference Architecture using SOA.   • Telecom Reference Architecture • Enterprise SOA based Reference Architecture   Telecom Reference Architecture   Tele Management Forum’s New Generation Operations Systems and Software (NGOSS) is an architectural framework for organizing, integrating, and implementing telecom systems. NGOSS is a component-based framework consisting of the following elements:   ·       The enhanced Telecom Operations Map (eTOM) is a business process framework. ·       The Shared Information Data (SID) model provides a comprehensive information framework that may be specialized for the needs of a particular organization. ·       The Telecom Application Map (TAM) is an application framework to depict the functional footprint of applications, relative to the horizontal processes within eTOM. ·       The Technology Neutral Architecture (TNA) is an integrated framework. TNA is an architecture that is sustainable through technology changes.   NGOSS Architecture Standards are:   ·       Centralized data ·       Loosely coupled distributed systems ·       Application components/re-use  ·       A technology-neutral system framework with technology specific implementations ·       Interoperability to service provider data/processes ·       Allows more re-use of business components across multiple business scenarios ·       Workflow automation   The traditional operator systems architecture consists of four layers,   ·       Business Support System (BSS) layer, with focus toward customers and business partners. Manages order, subscriber, pricing, rating, and billing information. ·       Operations Support System (OSS) layer, built around product, service, and resource inventories. ·       Networks layer – consists of Network elements and 3rd Party Systems. ·       Integration Layer – to maximize application communication and overall solution flexibility.   Reference architecture for telecom enterprises is depicted below. @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Figure 2. Telecom Reference Architecture   The major building blocks of any Telecom Service Provider architecture are as follows:   1. Customer Relationship Management   CRM encompasses the end-to-end lifecycle of the customer: customer initiation/acquisition, sales, ordering, and service activation, customer care and support, proactive campaigns, cross sell/up sell, and retention/loyalty.   CRM also includes the collection of customer information and its application to personalize, customize, and integrate delivery of service to a customer, as well as to identify opportunities for increasing the value of the customer to the enterprise.   The key functionalities related to Customer Relationship Management are   ·       Manage the end-to-end lifecycle of a customer request for products. ·       Create and manage customer profiles. ·       Manage all interactions with customers – inquiries, requests, and responses. ·       Provide updates to Billing and other south bound systems on customer/account related updates such as customer/ account creation, deletion, modification, request bills, final bill, duplicate bills, credit limits through Middleware. ·       Work with Order Management System, Product, and Service Management components within CRM. ·       Manage customer preferences – Involve all the touch points and channels to the customer, including contact center, retail stores, dealers, self service, and field service, as well as via any media (phone, face to face, web, mobile device, chat, email, SMS, mail, the customer's bill, etc.). ·       Support single interface for customer contact details, preferences, account details, offers, customer premise equipment, bill details, bill cycle details, and customer interactions.   CRM applications interact with customers through customer touch points like portals, point-of-sale terminals, interactive voice response systems, etc. The requests by customers are sent via fulfillment/provisioning to billing system for ordering processing.   2. Billing and Revenue Management   Billing and Revenue Management handles the collection of appropriate usage records and production of timely and accurate bills – for providing pre-bill usage information and billing to customers; for processing their payments; and for performing payment collections. In addition, it handles customer inquiries about bills, provides billing inquiry status, and is responsible for resolving billing problems to the customer's satisfaction in a timely manner. This process grouping also supports prepayment for services.   The key functionalities provided by these applications are   ·       To ensure that enterprise revenue is billed and invoices delivered appropriately to customers. ·       To manage customers’ billing accounts, process their payments, perform payment collections, and monitor the status of the account balance. ·       To ensure the timely and effective fulfillment of all customer bill inquiries and complaints. ·       Collect the usage records from mediation and ensure appropriate rating and discounting of all usage and pricing. ·       Support revenue sharing; split charging where usage is guided to an account different from the service consumer. ·       Support prepaid and post-paid rating. ·       Send notification on approach / exceeding the usage thresholds as enforced by the subscribed offer, and / or as setup by the customer. ·       Support prepaid, post paid, and hybrid (where some services are prepaid and the rest of the services post paid) customers and conversion from post paid to prepaid, and vice versa. ·       Support different billing function requirements like charge prorating, promotion, discount, adjustment, waiver, write-off, account receivable, GL Interface, late payment fee, credit control, dunning, account or service suspension, re-activation, expiry, termination, contract violation penalty, etc. ·       Initiate direct debit to collect payment against an invoice outstanding. ·       Send notification to Middleware on different events; for example, payment receipt, pre-suspension, threshold exceed, etc.   Billing systems typically get usage data from mediation systems for rating and billing. They get provisioning requests from order management systems and inquiries from CRM systems. Convergent and real-time billing systems can directly get usage details from network elements.   3. Mediation   Mediation systems transform/translate the Raw or Native Usage Data Records into a general format that is acceptable to billing for their rating purposes.   The following lists the high-level roles and responsibilities executed by the Mediation system in the end-to-end solution.   ·       Collect Usage Data Records from different data sources – like network elements, routers, servers – via different protocol and interfaces. ·       Process Usage Data Records – Mediation will process Usage Data Records as per the source format. ·       Validate Usage Data Records from each source. ·       Segregates Usage Data Records coming from each source to multiple, based on the segregation requirement of end Application. ·       Aggregates Usage Data Records based on the aggregation rule if any from different sources. ·       Consolidates multiple Usage Data Records from each source. ·       Delivers formatted Usage Data Records to different end application like Billing, Interconnect, Fraud Management, etc. ·       Generates audit trail for incoming Usage Data Records and keeps track of all the Usage Data Records at various stages of mediation process. ·       Checks duplicate Usage Data Records across files for a given time window.   4. Fulfillment   This area is responsible for providing customers with their requested products in a timely and correct manner. It translates the customer's business or personal need into a solution that can be delivered using the specific products in the enterprise's portfolio. This process informs the customers of the status of their purchase order, and ensures completion on time, as well as ensuring a delighted customer. These processes are responsible for accepting and issuing orders. They deal with pre-order feasibility determination, credit authorization, order issuance, order status and tracking, customer update on customer order activities, and customer notification on order completion. Order management and provisioning applications fall into this category.   The key functionalities provided by these applications are   ·       Issuing new customer orders, modifying open customer orders, or canceling open customer orders; ·       Verifying whether specific non-standard offerings sought by customers are feasible and supportable; ·       Checking the credit worthiness of customers as part of the customer order process; ·       Testing the completed offering to ensure it is working correctly; ·       Updating of the Customer Inventory Database to reflect that the specific product offering has been allocated, modified, or cancelled; ·       Assigning and tracking customer provisioning activities; ·       Managing customer provisioning jeopardy conditions; and ·       Reporting progress on customer orders and other processes to customer.   These applications typically get orders from CRM systems. They interact with network elements and billing systems for fulfillment of orders.   5. Enterprise Management   This process area includes those processes that manage enterprise-wide activities and needs, or have application within the enterprise as a whole. They encompass all business management processes that   ·       Are necessary to support the whole of the enterprise, including processes for financial management, legal management, regulatory management, process, cost, and quality management, etc.;   ·       Are responsible for setting corporate policies, strategies, and directions, and for providing guidelines and targets for the whole of the business, including strategy development and planning for areas, such as Enterprise Architecture, that are integral to the direction and development of the business;   ·       Occur throughout the enterprise, including processes for project management, performance assessments, cost assessments, etc.     (i) Enterprise Risk Management:   Enterprise Risk Management focuses on assuring that risks and threats to the enterprise value and/or reputation are identified, and appropriate controls are in place to minimize or eliminate the identified risks. The identified risks may be physical or logical/virtual. Successful risk management ensures that the enterprise can support its mission critical operations, processes, applications, and communications in the face of serious incidents such as security threats/violations and fraud attempts. Two key areas covered in Risk Management by telecom operators are:   ·       Revenue Assurance: Revenue assurance system will be responsible for identifying revenue loss scenarios across components/systems, and will help in rectifying the problems. The following lists the high-level roles and responsibilities executed by the Revenue Assurance system in the end-to-end solution. o   Identify all usage information dropped when networks are being upgraded. o   Interconnect bill verification. o   Identify where services are routinely provisioned but never billed. o   Identify poor sales policies that are intensifying collections problems. o   Find leakage where usage is sent to error bucket and never billed for. o   Find leakage where field service, CRM, and network build-out are not optimized.   ·       Fraud Management: Involves collecting data from different systems to identify abnormalities in traffic patterns, usage patterns, and subscription patterns to report suspicious activity that might suggest fraudulent usage of resources, resulting in revenue losses to the operator.   The key roles and responsibilities of the system component are as follows:   o   Fraud management system will capture and monitor high usage (over a certain threshold) in terms of duration, value, and number of calls for each subscriber. The threshold for each subscriber is decided by the system and fixed automatically. o   Fraud management will be able to detect the unauthorized access to services for certain subscribers. These subscribers may have been provided unauthorized services by employees. The component will raise the alert to the operator the very first time of such illegal calls or calls which are not billed. o   The solution will be to have an alarm management system that will deliver alarms to the operator/provider whenever it detects a fraud, thus minimizing fraud by catching it the first time it occurs. o   The Fraud Management system will be capable of interfacing with switches, mediation systems, and billing systems   (ii) Knowledge Management   This process focuses on knowledge management, technology research within the enterprise, and the evaluation of potential technology acquisitions.   Key responsibilities of knowledge base management are to   ·       Maintain knowledge base – Creation and updating of knowledge base on ongoing basis. ·       Search knowledge base – Search of knowledge base on keywords or category browse ·       Maintain metadata – Management of metadata on knowledge base to ensure effective management and search. ·       Run report generator. ·       Provide content – Add content to the knowledge base, e.g., user guides, operational manual, etc.   (iii) Document Management   It focuses on maintaining a repository of all electronic documents or images of paper documents relevant to the enterprise using a system.   (iv) Data Management   It manages data as a valuable resource for any enterprise. For telecom enterprises, the typical areas covered are Master Data Management, Data Warehousing, and Business Intelligence. It is also responsible for data governance, security, quality, and database management.   Key responsibilities of Data Management are   ·       Using ETL, extract the data from CRM, Billing, web content, ERP, campaign management, financial, network operations, asset management info, customer contact data, customer measures, benchmarks, process data, e.g., process inputs, outputs, and measures, into Enterprise Data Warehouse. ·       Management of data traceability with source, data related business rules/decisions, data quality, data cleansing data reconciliation, competitors data – storage for all the enterprise data (customer profiles, products, offers, revenues, etc.) ·       Get online update through night time replication or physical backup process at regular frequency. ·       Provide the data access to business intelligence and other systems for their analysis, report generation, and use.   (v) Business Intelligence   It uses the Enterprise Data to provide the various analysis and reports that contain prospects and analytics for customer retention, acquisition of new customers due to the offers, and SLAs. It will generate right and optimized plans – bolt-ons for the customers.   The following lists the high-level roles and responsibilities executed by the Business Intelligence system at the Enterprise Level:   ·       It will do Pattern analysis and reports problem. ·       It will do Data Analysis – Statistical analysis, data profiling, affinity analysis of data, customer segment wise usage patterns on offers, products, service and revenue generation against services and customer segments. ·       It will do Performance (business, system, and forecast) analysis, churn propensity, response time, and SLAs analysis. ·       It will support for online and offline analysis, and report drill down capability. ·       It will collect, store, and report various SLA data. ·       It will provide the necessary intelligence for marketing and working on campaigns, etc., with cost benefit analysis and predictions.   It will advise on customer promotions with additional services based on loyalty and credit history of customer   ·       It will Interface with Enterprise Data Management system for data to run reports and analysis tasks. It will interface with the campaign schedules, based on historical success evidence.   (vi) Stakeholder and External Relations Management   It manages the enterprise's relationship with stakeholders and outside entities. Stakeholders include shareholders, employee organizations, etc. Outside entities include regulators, local community, and unions. Some of the processes within this grouping are Shareholder Relations, External Affairs, Labor Relations, and Public Relations.   (vii) Enterprise Resource Planning   It is used to manage internal and external resources, including tangible assets, financial resources, materials, and human resources. Its purpose is to facilitate the flow of information between all business functions inside the boundaries of the enterprise and manage the connections to outside stakeholders. ERP systems consolidate all business operations into a uniform and enterprise wide system environment.   The key roles and responsibilities for Enterprise System are given below:   ·        It will handle responsibilities such as core accounting, financial, and management reporting. ·       It will interface with CRM for capturing customer account and details. ·       It will interface with billing to capture the billing revenue and other financial data. ·       It will be responsible for executing the dunning process. Billing will send the required feed to ERP for execution of dunning. ·       It will interface with the CRM and Billing through batch interfaces. Enterprise management systems are like horizontals in the enterprise and typically interact with all major telecom systems. E.g., an ERP system interacts with CRM, Fulfillment, and Billing systems for different kinds of data exchanges.   6. External Interfaces/Touch Points   The typical external parties are customers, suppliers/partners, employees, shareholders, and other stakeholders. External interactions from/to a Service Provider to other parties can be achieved by a variety of mechanisms, including:   ·       Exchange of emails or faxes ·       Call Centers ·       Web Portals ·       Business-to-Business (B2B) automated transactions   These applications provide an Internet technology driven interface to external parties to undertake a variety of business functions directly for themselves. These can provide fully or partially automated service to external parties through various touch points.   Typical characteristics of these touch points are   ·       Pre-integrated self-service system, including stand-alone web framework or integration front end with a portal engine ·       Self services layer exposing atomic web services/APIs for reuse by multiple systems across the architectural environment ·       Portlets driven connectivity exposing data and services interoperability through a portal engine or web application   These touch points mostly interact with the CRM systems for requests, inquiries, and responses.   7. Middleware   The component will be primarily responsible for integrating the different systems components under a common platform. It should provide a Standards-Based Platform for building Service Oriented Architecture and Composite Applications. The following lists the high-level roles and responsibilities executed by the Middleware component in the end-to-end solution.   ·       As an integration framework, covering to and fro interfaces ·       Provide a web service framework with service registry. ·       Support SOA framework with SOA service registry. ·       Each of the interfaces from / to Middleware to other components would handle data transformation, translation, and mapping of data points. ·       Receive data from the caller / activate and/or forward the data to the recipient system in XML format. ·       Use standard XML for data exchange. ·       Provide the response back to the service/call initiator. ·       Provide a tracking until the response completion. ·       Keep a store transitional data against each call/transaction. ·       Interface through Middleware to get any information that is possible and allowed from the existing systems to enterprise systems; e.g., customer profile and customer history, etc. ·       Provide the data in a common unified format to the SOA calls across systems, and follow the Enterprise Architecture directive. ·       Provide an audit trail for all transactions being handled by the component.   8. Network Elements   The term Network Element means a facility or equipment used in the provision of a telecommunications service. Such terms also includes features, functions, and capabilities that are provided by means of such facility or equipment, including subscriber numbers, databases, signaling systems, and information sufficient for billing and collection or used in the transmission, routing, or other provision of a telecommunications service.   Typical network elements in a GSM network are Home Location Register (HLR), Intelligent Network (IN), Mobile Switching Center (MSC), SMS Center (SMSC), and network elements for other value added services like Push-to-talk (PTT), Ring Back Tone (RBT), etc.   Network elements are invoked when subscribers use their telecom devices for any kind of usage. These elements generate usage data and pass it on to downstream systems like mediation and billing system for rating and billing. They also integrate with provisioning systems for order/service fulfillment.   9. 3rd Party Applications   3rd Party systems are applications like content providers, payment gateways, point of sale terminals, and databases/applications maintained by the Government.   Depending on applicability and the type of functionality provided by 3rd party applications, the integration with different telecom systems like CRM, provisioning, and billing will be done.   10. Service Delivery Platform   A service delivery platform (SDP) provides the architecture for the rapid deployment, provisioning, execution, management, and billing of value added telecom services. SDPs are based on the concept of SOA and layered architecture. They support the delivery of voice, data services, and content in network and device-independent fashion. They allow application developers to aggregate network capabilities, services, and sources of content. SDPs typically contain layers for web services exposure, service application development, and network abstraction.   SOA Reference Architecture   SOA concept is based on the principle of developing reusable business service and building applications by composing those services, instead of building monolithic applications in silos. It’s about bridging the gap between business and IT through a set of business-aligned IT services, using a set of design principles, patterns, and techniques.   In an SOA, resources are made available to participants in a value net, enterprise, line of business (typically spanning multiple applications within an enterprise or across multiple enterprises). It consists of a set of business-aligned IT services that collectively fulfill an organization’s business processes and goals. We can choreograph these services into composite applications and invoke them through standard protocols. SOA, apart from agility and reusability, enables:   ·       The business to specify processes as orchestrations of reusable services ·       Technology agnostic business design, with technology hidden behind service interface ·       A contractual-like interaction between business and IT, based on service SLAs ·       Accountability and governance, better aligned to business services ·       Applications interconnections untangling by allowing access only through service interfaces, reducing the daunting side effects of change ·       Reduced pressure to replace legacy and extended lifetime for legacy applications, through encapsulation in services   ·       A Cloud Computing paradigm, using web services technologies, that makes possible service outsourcing on an on-demand, utility-like, pay-per-usage basis   The following section represents the Reference Architecture of logical view for the Telecom Solution. The new custom built application needs to align with this logical architecture in the long run to achieve EA benefits.   Packaged implementation applications, such as ERP billing applications, need to expose their functions as service providers (as other applications consume) and interact with other applications as service consumers.   COT applications need to expose services through wrappers such as adapters to utilize existing resources and at the same time achieve Enterprise Architecture goal and objectives.   The following are the various layers for Enterprise level deployment of SOA. This diagram captures the abstract view of Enterprise SOA layers and important components of each layer. Layered architecture means decomposition of services such that most interactions occur between adjacent layers. However, there is no strict rule that top layers should not directly communicate with bottom layers.   The diagram below represents the important logical pieces that would result from overall SOA transformation. @font-face { font-family: "Arial"; }@font-face { font-family: "Courier New"; }@font-face { font-family: "Wingdings"; }@font-face { font-family: "Cambria"; }p.MsoNormal, li.MsoNormal, div.MsoNormal { margin: 0cm 0cm 0.0001pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoCaption, li.MsoCaption, div.MsoCaption { margin: 0cm 0cm 10pt; font-size: 9pt; font-family: "Times New Roman"; color: rgb(79, 129, 189); font-weight: bold; }p.MsoListParagraph, li.MsoListParagraph, div.MsoListParagraph { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpFirst, li.MsoListParagraphCxSpFirst, div.MsoListParagraphCxSpFirst { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpMiddle, li.MsoListParagraphCxSpMiddle, div.MsoListParagraphCxSpMiddle { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }p.MsoListParagraphCxSpLast, li.MsoListParagraphCxSpLast, div.MsoListParagraphCxSpLast { margin: 0cm 0cm 0.0001pt 36pt; font-size: 12pt; font-family: "Times New Roman"; }div.Section1 { page: Section1; }ol { margin-bottom: 0cm; }ul { margin-bottom: 0cm; } Figure 3. Enterprise SOA Reference Architecture 1.          Operational System Layer: This layer consists of all packaged applications like CRM, ERP, custom built applications, COTS based applications like Billing, Revenue Management, Fulfilment, and the Enterprise databases that are essential and contribute directly or indirectly to the Enterprise OSS/BSS Transformation.   ERP holds the data of Asset Lifecycle Management, Supply Chain, and Advanced Procurement and Human Capital Management, etc.   CRM holds the data related to Order, Sales, and Marketing, Customer Care, Partner Relationship Management, Loyalty, etc.   Content Management handles Enterprise Search and Query. Billing application consists of the following components:   ·       Collections Management, Customer Billing Management, Invoices, Real-Time Rating, Discounting, and Applying of Charges ·       Enterprise databases will hold both the application and service data, whether structured or unstructured.   MDM - Master data majorly consists of Customer, Order, Product, and Service Data.     2.          Enterprise Component Layer:   This layer consists of the Application Services and Common Services that are responsible for realizing the functionality and maintaining the QoS of the exposed services. This layer uses container-based technologies such as application servers to implement the components, workload management, high availability, and load balancing.   Application Services: This Service Layer enables application, technology, and database abstraction so that the complex accessing logic is hidden from the other service layers. This is a basic service layer, which exposes application functionalities and data as reusable services. The three types of the Application access services are:   ·       Application Access Service: This Service Layer exposes application level functionalities as a reusable service between BSS to BSS and BSS to OSS integration. This layer is enabled using disparate technology such as Web Service, Integration Servers, and Adaptors, etc.   ·       Data Access Service: This Service Layer exposes application data services as a reusable reference data service. This is done via direct interaction with application data. and provides the federated query.   ·       Network Access Service: This Service Layer exposes provisioning layer as a reusable service from OSS to OSS integration. This integration service emphasizes the need for high performance, stateless process flows, and distributed design.   Common Services encompasses management of structured, semi-structured, and unstructured data such as information services, portal services, interaction services, infrastructure services, and security services, etc.   3.          Integration Layer:   This consists of service infrastructure components like service bus, service gateway for partner integration, service registry, service repository, and BPEL processor. Service bus will carry the service invocation payloads/messages between consumers and providers. The other important functions expected from it are itinerary based routing, distributed caching of routing information, transformations, and all qualities of service for messaging-like reliability, scalability, and availability, etc. Service registry will hold all contracts (wsdl) of services, and it helps developers to locate or discover service during design time or runtime.   • BPEL processor would be useful in orchestrating the services to compose a complex business scenario or process. • Workflow and business rules management are also required to support manual triggering of certain activities within business process. based on the rules setup and also the state machine information. Application, data, and service mediation layer typically forms the overall composite application development framework or SOA Framework.   4.          Business Process Layer: These are typically the intermediate services layer and represent Shared Business Process Services. At Enterprise Level, these services are from Customer Management, Order Management, Billing, Finance, and Asset Management application domains.   5.          Access Layer: This layer consists of portals for Enterprise and provides a single view of Enterprise information management and dashboard services.   6.          Channel Layer: This consists of various devices; applications that form part of extended enterprise; browsers through which users access the applications.   7.          Client Layer: This designates the different types of users accessing the enterprise applications. The type of user typically would be an important factor in determining the level of access to applications.   8.          Vertical pieces like management, monitoring, security, and development cut across all horizontal layers Management and monitoring involves all aspects of SOA-like services, SLAs, and other QoS lifecycle processes for both applications and services surrounding SOA governance.     9.          EA Governance, Reference Architecture, Roadmap, Principles, and Best Practices:   EA Governance is important in terms of providing the overall direction to SOA implementation within the enterprise. This involves board-level involvement, in addition to business and IT executives. At a high level, this involves managing the SOA projects implementation, managing SOA infrastructure, and controlling the entire effort through all fine-tuned IT processes in accordance with COBIT (Control Objectives for Information Technology).   Devising tools and techniques to promote reuse culture, and the SOA way of doing things needs competency centers to be established in addition to training the workforce to take up new roles that are suited to SOA journey.   Conclusions   Reference Architectures can serve as the basis for disparate architecture efforts throughout the organization, even if they use different tools and technologies. Reference architectures provide best practices and approaches in the independent way a vendor deals with technology and standards. Reference Architectures model the abstract architectural elements for an enterprise independent of the technologies, protocols, and products that are used to implement an SOA. Telecom enterprises today are facing significant business and technology challenges due to growing competition, a multitude of services, and convergence. Adopting architectural best practices could go a long way in meeting these challenges. The use of SOA-based architecture for communication to each of the external systems like Billing, CRM, etc., in OSS/BSS system has made the architecture very loosely coupled, with greater flexibility. Any change in the external systems would be absorbed at the Integration Layer without affecting the rest of the ecosystem. The use of a Business Process Management (BPM) tool makes the management and maintenance of the business processes easy, with better performance in terms of lead time, quality, and cost. Since the Architecture is based on standards, it will lower the cost of deploying and managing OSS/BSS applications over their lifecycles.

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