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  • SQL SERVER – What is Page Life Expectancy (PLE) Counter

    - by pinaldave
    During performance tuning consultation there are plenty of counters and values, I often come across. Today we will quickly talk about Page Life Expectancy counter, which is commonly known as PLE as well. You can find the value of the PLE by running following query. SELECT [object_name], [counter_name], [cntr_value] FROM sys.dm_os_performance_counters WHERE [object_name] LIKE '%Manager%' AND [counter_name] = 'Page life expectancy' The recommended value of the PLE counter is 300 seconds. I have seen on busy system this value to be as low as even 45 seconds and on unused system as high as 1250 seconds. Page Life Expectancy is number of seconds a page will stay in the buffer pool without references. In simple words, if your page stays longer in the buffer pool (area of the memory cache) your PLE is higher, leading to higher performance as every time request comes there are chances it may find its data in the cache itself instead of going to hard drive to read the data. Now check your system and post back what is this counter value for you during various time of the day. Is this counter any way relates to performance issues for your system? Note: There are various other counters which are important to discuss during the performance tuning and this counter is not everything. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, SQL, SQL Authority, SQL Optimization, SQL Performance, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQLServer, T SQL, Technology

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  • Trying to find the life expectancy of an unused flash card like SD

    - by wsams
    I read in the What's the life expectancy of an SD card? post SD cards are rated to hold data at something like 10 years sitting idle. I recall reading (not sure where) about re-energizing cards by occasionally inserting into a reader. Everything I read rates in read/write cycles and not physical decay. I'm wonder if buying a new sd card for every photo shoot would be beneficial if I could store the cards in a lock box? I was hoping for something much longer. Does anyone else agree with 10 years or maybe something more?

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  • Does having your page file on decrease the life expectancy of your hard drive?

    - by user695874
    If I have my page file turned on in Windows as opposed to having it turned off as shown below: Would having the page file turned on decrease the life expectancy on my Hard Drive? If so, how much would the life decrease say with regular use? (4 hours a day) I'm thinking it would decrease some just because there would be more writing to the hard drive, but I wasn't sure if it would be too negligible to even matter.

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  • Year dropdown range - when do we stop?

    - by Andrew Heath
    I attended a payroll software demo yesterday wherein the year dropdowns throughout the software ran from 2000 to 2200. Now, we've all been down this road before with 2 digit shortsight, but honestly - a 200 year service life for a Java & Oracle payroll system? Our Board of Directors would be thrilled if the company was even solvent for 1/4th that long. When forced to use a dropdown year select, where do you draw the line?

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  • SQL SERVER – Guest Post – Jonathan Kehayias – Wait Type – Day 16 of 28

    - by pinaldave
    Jonathan Kehayias (Blog | Twitter) is a MCITP Database Administrator and Developer, who got started in SQL Server in 2004 as a database developer and report writer in the natural gas industry. After spending two and a half years working in TSQL, in late 2006, he transitioned to the role of SQL Database Administrator. His primary passion is performance tuning, where he frequently rewrites queries for better performance and performs in depth analysis of index implementation and usage. Jonathan blogs regularly on SQLBlog, and was a coauthor of Professional SQL Server 2008 Internals and Troubleshooting. On a personal note, I think Jonathan is extremely positive person. In every conversation with him I have found that he is always eager to help and encourage. Every time he finds something needs to be approved, he has contacted me without hesitation and guided me to improve, change and learn. During all the time, he has not lost his focus to help larger community. I am honored that he has accepted to provide his views on complex subject of Wait Types and Queues. Currently I am reading his series on Extended Events. Here is the guest blog post by Jonathan: SQL Server troubleshooting is all about correlating related pieces of information together to indentify where exactly the root cause of a problem lies. In my daily work as a DBA, I generally get phone calls like, “So and so application is slow, what’s wrong with the SQL Server.” One of the funny things about the letters DBA is that they go so well with Default Blame Acceptor, and I really wish that I knew exactly who the first person was that pointed that out to me, because it really fits at times. A lot of times when I get this call, the problem isn’t related to SQL Server at all, but every now and then in my initial quick checks, something pops up that makes me start looking at things further. The SQL Server is slow, we see a number of tasks waiting on ASYNC_IO_COMPLETION, IO_COMPLETION, or PAGEIOLATCH_* waits in sys.dm_exec_requests and sys.dm_exec_waiting_tasks. These are also some of the highest wait types in sys.dm_os_wait_stats for the server, so it would appear that we have a disk I/O bottleneck on the machine. A quick check of sys.dm_io_virtual_file_stats() and tempdb shows a high write stall rate, while our user databases show high read stall rates on the data files. A quick check of some performance counters and Page Life Expectancy on the server is bouncing up and down in the 50-150 range, the Free Page counter consistently hits zero, and the Free List Stalls/sec counter keeps jumping over 10, but Buffer Cache Hit Ratio is 98-99%. Where exactly is the problem? In this case, which happens to be based on a real scenario I faced a few years back, the problem may not be a disk bottleneck at all; it may very well be a memory pressure issue on the server. A quick check of the system spec’s and it is a dual duo core server with 8GB RAM running SQL Server 2005 SP1 x64 on Windows Server 2003 R2 x64. Max Server memory is configured at 6GB and we think that this should be enough to handle the workload; or is it? This is a unique scenario because there are a couple of things happening inside of this system, and they all relate to what the root cause of the performance problem is on the system. If we were to query sys.dm_exec_query_stats for the TOP 10 queries, by max_physical_reads, max_logical_reads, and max_worker_time, we may be able to find some queries that were using excessive I/O and possibly CPU against the system in their worst single execution. We can also CROSS APPLY to sys.dm_exec_sql_text() and see the statement text, and also CROSS APPLY sys.dm_exec_query_plan() to get the execution plan stored in cache. Ok, quick check, the plans are pretty big, I see some large index seeks, that estimate 2.8GB of data movement between operators, but everything looks like it is optimized the best it can be. Nothing really stands out in the code, and the indexing looks correct, and I should have enough memory to handle this in cache, so it must be a disk I/O problem right? Not exactly! If we were to look at how much memory the plan cache is taking by querying sys.dm_os_memory_clerks for the CACHESTORE_SQLCP and CACHESTORE_OBJCP clerks we might be surprised at what we find. In SQL Server 2005 RTM and SP1, the plan cache was allowed to take up to 75% of the memory under 8GB. I’ll give you a second to go back and read that again. Yes, you read it correctly, it says 75% of the memory under 8GB, but you don’t have to take my word for it, you can validate this by reading Changes in Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2. In this scenario the application uses an entirely adhoc workload against SQL Server and this leads to plan cache bloat, and up to 4.5GB of our 6GB of memory for SQL can be consumed by the plan cache in SQL Server 2005 SP1. This in turn reduces the size of the buffer cache to just 1.5GB, causing our 2.8GB of data movement in this expensive plan to cause complete flushing of the buffer cache, not just once initially, but then another time during the queries execution, resulting in excessive physical I/O from disk. Keep in mind that this is not the only query executing at the time this occurs. Remember the output of sys.dm_io_virtual_file_stats() showed high read stalls on the data files for our user databases versus higher write stalls for tempdb? The memory pressure is also forcing heavier use of tempdb to handle sorting and hashing in the environment as well. The real clue here is the Memory counters for the instance; Page Life Expectancy, Free List Pages, and Free List Stalls/sec. The fact that Page Life Expectancy is fluctuating between 50 and 150 constantly is a sign that the buffer cache is experiencing constant churn of data, once every minute to two and a half minutes. If you add to the Page Life Expectancy counter, the consistent bottoming out of Free List Pages along with Free List Stalls/sec consistently spiking over 10, and you have the perfect memory pressure scenario. All of sudden it may not be that our disk subsystem is the problem, but is instead an innocent bystander and victim. Side Note: The Page Life Expectancy counter dropping briefly and then returning to normal operating values intermittently is not necessarily a sign that the server is under memory pressure. The Books Online and a number of other references will tell you that this counter should remain on average above 300 which is the time in seconds a page will remain in cache before being flushed or aged out. This number, which equates to just five minutes, is incredibly low for modern systems and most published documents pre-date the predominance of 64 bit computing and easy availability to larger amounts of memory in SQL Servers. As food for thought, consider that my personal laptop has more memory in it than most SQL Servers did at the time those numbers were posted. I would argue that today, a system churning the buffer cache every five minutes is in need of some serious tuning or a hardware upgrade. Back to our problem and its investigation: There are two things really wrong with this server; first the plan cache is excessively consuming memory and bloated in size and we need to look at that and second we need to evaluate upgrading the memory to accommodate the workload being performed. In the case of the server I was working on there were a lot of single use plans found in sys.dm_exec_cached_plans (where usecounts=1). Single use plans waste space in the plan cache, especially when they are adhoc plans for statements that had concatenated filter criteria that is not likely to reoccur with any frequency.  SQL Server 2005 doesn’t natively have a way to evict a single plan from cache like SQL Server 2008 does, but MVP Kalen Delaney, showed a hack to evict a single plan by creating a plan guide for the statement and then dropping that plan guide in her blog post Geek City: Clearing a Single Plan from Cache. We could put that hack in place in a job to automate cleaning out all the single use plans periodically, minimizing the size of the plan cache, but a better solution would be to fix the application so that it uses proper parameterized calls to the database. You didn’t write the app, and you can’t change its design? Ok, well you could try to force parameterization to occur by creating and keeping plan guides in place, or we can try forcing parameterization at the database level by using ALTER DATABASE <dbname> SET PARAMETERIZATION FORCED and that might help. If neither of these help, we could periodically dump the plan cache for that database, as discussed as being a problem in Kalen’s blog post referenced above; not an ideal scenario. The other option is to increase the memory on the server to 16GB or 32GB, if the hardware allows it, which will increase the size of the plan cache as well as the buffer cache. In SQL Server 2005 SP1, on a system with 16GB of memory, if we set max server memory to 14GB the plan cache could use at most 9GB  [(8GB*.75)+(6GB*.5)=(6+3)=9GB], leaving 5GB for the buffer cache.  If we went to 32GB of memory and set max server memory to 28GB, the plan cache could use at most 16GB [(8*.75)+(20*.5)=(6+10)=16GB], leaving 12GB for the buffer cache. Thankfully we have SQL Server 2005 Service Pack 2, 3, and 4 these days which include the changes in plan cache sizing discussed in the Changes to Caching Behavior between SQL Server 2000, SQL Server 2005 RTM and SQL Server 2005 SP2 blog post. In real life, when I was troubleshooting this problem, I spent a week trying to chase down the cause of the disk I/O bottleneck with our Server Admin and SAN Admin, and there wasn’t much that could be done immediately there, so I finally asked if we could increase the memory on the server to 16GB, which did fix the problem. It wasn’t until I had this same problem occur on another system that I actually figured out how to really troubleshoot this down to the root cause.  I couldn’t believe the size of the plan cache on the server with 16GB of memory when I actually learned about this and went back to look at it. SQL Server is constantly telling a story to anyone that will listen. As the DBA, you have to sit back and listen to all that it’s telling you and then evaluate the big picture and how all the data you can gather from SQL about performance relate to each other. One of the greatest tools out there is actually a free in the form of Diagnostic Scripts for SQL Server 2005 and 2008, created by MVP Glenn Alan Berry. Glenn’s scripts collect a majority of the information that SQL has to offer for rapid troubleshooting of problems, and he includes a lot of notes about what the outputs of each individual query might be telling you. When I read Pinal’s blog post SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28, I noticed that he referenced Checking Memory Related Performance Counters in his post, but there was no real explanation about why checking memory counters is so important when looking at an I/O related wait type. I thought I’d chat with him briefly on Google Talk/Twitter DM and point this out, and offer a couple of other points I noted, so that he could add the information to his blog post if he found it useful.  Instead he asked that I write a guest blog for this. I am honored to be a guest blogger, and to be able to share this kind of information with the community. The information contained in this blog post is a glimpse at how I do troubleshooting almost every day of the week in my own environment. SQL Server provides us with a lot of information about how it is running, and where it may be having problems, it is up to us to play detective and find out how all that information comes together to tell us what’s really the problem. This blog post is written by Jonathan Kehayias (Blog | Twitter). Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: MVP, Pinal Dave, PostADay, Readers Contribution, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Slow DB Performance. Seems to be memory related.

    - by David
    I am seeing a pooorly performing web app with a SQL 2005 backend. The db is on a w2k3 machine with 4GB RAM. When I run perfmon on it I see the following. Page life expectancy is low. Consistently under 300 while the Buffer cache hit ratio is always 99% +. The target server memory is always 1618304 and the total server memory is always a number just below that. So it seems that it isn't grabbing enough of the available memory. I have AWE enabled, with the lock pages right for the SQL service account and have set a maximum of 2.25Gb... but it doesn't go near that. When I restart the SQL service the page life expectancy goes much higher, 1000+, and the total target memory starts at 0 and slowly works its way back up to the previous limit. Then it hits the limit and the page life expectancy goes back down massively to <300. So I'm guessing there is something limiting the amount of memory. Any ideas on what that would be and how I can fix it?

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  • How harmful is a hard disk spin cycle?

    - by Gilles
    It is conventional wisdom¹ that each time you spin a hard disk down and back up, you shave some time off its life expectancy. The topic has been discussed before: Is turning off hard disks harmful? What's the effect of standby (spindown) mode on modern hard drives? Common explanations for why spindowns and spinups are harmful are that they induce more stress on the mechanical parts than ordinary running, and that they cause heat variations that are harmful to the device mechanics. Is there any data showing quantitatively how bad a spin cycle is? That is, how much life expectancy does a spin cycle cost? Or, more practically, if I know that I'm not going to need a disk for X seconds, how large should X be to warrant spinning down? ¹ But conventional wisdom has been wrong before; for example, it is commonly held that hard disks should be kept as cool as possible, but the one published study on the topic shows that cooler drives actually fail more. This study is no help here since all the disks surveyed were powered on 24/7.

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  • How harmful is a hard disk spin cycle?

    - by Gilles
    It is conventional wisdom¹ that each time you spin a hard disk down and back up, you shave some time off its life expectancy. The topic has been discussed before: Is turning off hard disks harmful? What's the effect of standby (spindown) mode on modern hard drives? Common explanations for why spindowns and spinups are harmful are that they induce more stress on the mechanical parts than ordinary running, and that they cause heat variations that are harmful to the device mechanics. Is there any data showing quantitatively how bad a spin cycle is? That is, how much life expectancy does a spin cycle cost? Or, more practically, if I know that I'm not going to need a disk for X seconds, how large should X be to warrant spinning down? ¹ But conventional wisdom has been wrong before; for example, it is commonly held that hard disks should be kept as cool as possible, but the one published study on the topic shows that cooler drives actually fail more. This study is no help here since all the disks surveyed were powered on 24/7.

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  • Software Engineering Practices &ndash; Different Projects should have different maturity levels

    - by Dylan Smith
    I’ve had a lot of discussions at the office lately about the drastically different sets of software engineering practices used on our various projects, if what we are doing is appropriate, and what factors should you be considering when determining what practices are most appropriate in a given context. I wanted to write up my thoughts in a little more detail on this subject, so here we go: If you compare any two software projects (specifically comparing their codebases) you’ll often see very different levels of maturity in the software engineering practices employed. By software engineering practices, I’m specifically referring to the quality of the code and the amount of technical debt present in the project. Things such as Test Driven Development, Domain Driven Design, Behavior Driven Development, proper adherence to the SOLID principles, etc. are all practices that you would expect at the mature end of the spectrum. At the other end of the spectrum would be the quick-and-dirty solutions that are done using something like an Access Database, Excel Spreadsheet, or maybe some quick “drag-and-drop coding”. For this blog post I’m going to refer to this as the Software Engineering Maturity Spectrum (SEMS). I believe there is a time and a place for projects at every part of that SEMS. The risks and costs associated with under-engineering solutions have been written about a million times over so I won’t bother going into them again here, but there are also (unnecessary) costs with over-engineering a solution. Sometimes putting multiple layers, and IoC containers, and abstracting out the persistence, etc is complete overkill if a one-time use Access database could solve the problem perfectly well. A lot of software developers I talk to seem to automatically jump to the very right-hand side of this SEMS in everything they do. A common rationalization I hear is that it may seem like a small trivial application today, but these things always grow and stick around for many years, then you’re stuck maintaining a big ball of mud. I think this is a cop-out. Sure you can’t always anticipate how an application will be used or grow over its lifetime (can you ever??), but that doesn’t mean you can’t manage it and evolve the underlying software architecture as necessary (even if that means having to toss the code out and re-write it at some point…maybe even multiple times). My thoughts are that we should be making a conscious decision around the start of each project approximately where on the SEMS we want the project to exist. I believe this decision should be based on 3 factors: 1. Importance - How important to the business is this application? What is the impact if the application were to suddenly stop working? 2. Complexity - How complex is the application functionality? 3. Life-Expectancy - How long is this application expected to be in use? Is this a one-time use application, does it fill a short-term need, or is it more strategic and is expected to be in-use for many years to come? Of course this isn’t an exact science. You can’t say that Project X should be at the 73% mark on the SEMS and expect that to be helpful. My point is not that you need to precisely figure out what point on the SEMS the project should be at then translate that into some prescriptive set of practices and techniques you should be using. Rather my point is that we need to be aware that there is a spectrum, and that not everything is going to be (or should be) at the edges of that spectrum, indeed a large number of projects should probably fall somewhere within the middle; and different projects should adopt a different level of software engineering practices and maturity levels based on the needs of that project. To give an example of this way of thinking from my day job: Every couple of years my company plans and hosts a large event where ~400 of our customers all fly in to one location for a multi-day event with various activities. We have some staff whose job it is to organize the logistics of this event, which includes tracking which flights everybody is booked on, arranging for transportation to/from airports, arranging for hotel rooms, name tags, etc The last time we arranged this event all these various pieces of data were tracked in separate spreadsheets and reconciliation and cross-referencing of all the data was literally done by hand using printed copies of the spreadsheets and several people sitting around a table going down each list row by row. Obviously there is some room for improvement in how we are using software to manage the event’s logistics. The next time this event occurs we plan to provide the event planning staff with a more intelligent tool (either an Excel spreadsheet or probably an Access database) that can track all the information in one location and make sure that the various pieces of data are properly linked together (so for example if a person cancels you only need to delete them from one place, and not a dozen separate lists). This solution would fall at or near the very left end of the SEMS meaning that we will just quickly create something with very little attention paid to using mature software engineering practices. If we examine this project against the 3 criteria I listed above for determining it’s place within the SEMS we can see why: Importance – If this application were to stop working the business doesn’t grind to a halt, revenue doesn’t stop, and in fact our customers wouldn’t even notice since it isn’t a customer facing application. The impact would simply be more work for our event planning staff as they revert back to the previous way of doing things (assuming we don’t have any data loss). Complexity – The use cases for this project are pretty straightforward. It simply needs to manage several lists of data, and link them together appropriately. Precisely the task that access (and/or Excel) can do with minimal custom development required. Life-Expectancy – For this specific project we’re only planning to create something to be used for the one event (we only hold these events every 2 years). If it works well this may change (see below). Let’s assume we hack something out quickly and it works great when we plan the next event. We may decide that we want to make some tweaks to the tool and adopt it for planning all future events of this nature. In that case we should examine where the current application is on the SEMS, and make a conscious decision whether something needs to be done to move it further to the right based on the new objectives and goals for this application. This may mean scrapping the access database and re-writing it as an actual web or windows application. In this case, the life-expectancy changed, but let’s assume the importance and complexity didn’t change all that much. We can still probably get away with not adopting a lot of the so-called “best practices”. For example, we can probably still use some of the RAD tooling available and might have an Autonomous View style design that connects directly to the database and binds to typed datasets (we might even choose to simply leave it as an access database and continue using it; this is a decision that needs to be made on a case-by-case basis). At Anvil Digital we have aspirations to become a primarily product-based company. So let’s say we use this tool to plan a handful of events internally, and everybody loves it. Maybe a couple years down the road we decide we want to package the tool up and sell it as a product to some of our customers. In this case the project objectives/goals change quite drastically. Now the tool becomes a source of revenue, and the impact of it suddenly stopping working is significantly less acceptable. Also as we hold focus groups, and gather feedback from customers and potential customers there’s a pretty good chance the feature-set and complexity will have to grow considerably from when we were using it only internally for planning a small handful of events for one company. In this fictional scenario I would expect the target on the SEMS to jump to the far right. Depending on how we implemented the previous release we may be able to refactor and evolve the existing codebase to introduce a more layered architecture, a robust set of automated tests, introduce a proper ORM and IoC container, etc. More likely in this example the jump along the SEMS would be so large we’d probably end up scrapping the current code and re-writing. Although, if it was a slow phased roll-out to only a handful of customers, where we collected feedback, made some tweaks, and then rolled out to a couple more customers, we may be able to slowly refactor and evolve the code over time rather than tossing it out and starting from scratch. The key point I’m trying to get across is not that you should be throwing out your code and starting from scratch all the time. But rather that you should be aware of when and how the context and objectives around a project changes and periodically re-assess where the project currently falls on the SEMS and whether that needs to be adjusted based on changing needs. Note: There is also the idea of “spectrum decay”. Since our industry is rapidly evolving, what we currently accept as mature software engineering practices (the right end of the SEMS) probably won’t be the same 3 years from now. If you have a project that you were to assess at somewhere around the 80% mark on the SEMS today, but don’t touch the code for 3 years and come back and re-assess its position, it will almost certainly have changed since the right end of the SEMS will have moved farther out (maybe the project is now only around 60% due to decay). Developer Skills Another important aspect to this whole discussion is around the skill sets of your architects and lead developers. When talking about the progression of a developers skills from junior->intermediate->senior->… they generally start by only being able to write code that belongs on the left side of the SEMS and as they gain more knowledge and skill they become capable of working at a higher and higher level along the SEMS. We all realize that the learning never stops, but eventually you’ll get to the point where you can comfortably develop at the right-end of the SEMS (the exact practices and techniques that translates to is constantly changing, but that’s not the point here). A critical skill that I’d love to see more evidence of in our industry is the most senior guys not only being able to work at the right-end of the SEMS, but more importantly be able to consciously work at any point along the SEMS as project needs dictate. An even more valuable skill would be if you could make the conscious decision to move a projects code further right on the SEMS (based on changing needs) and do so in an incremental manner without having to start from scratch. An exercise that I’m planning to go through with all of our projects here at Anvil in the near future is to map out where I believe each project currently falls within this SEMS, where I believe the project *should* be on the SEMS based on the business needs, and for those that don’t match up (i.e. most of them) come up with a plan to improve the situation.

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  • How many times can data be read from a USB flash drive?

    - by John
    While I am aware that performing writes on a USB flash drive degrades the life expectancy of the device. I have heard the quantity of writes is anywhere from 100 thousand to 10 million, but I have not heard about number of read operations. Does reading from the device count toward this total? I am interested in writing only once to a flash drive and setting it to read-only. Then reading files from the device a thousand or more times per day, but am wondering if (at say 1,000 reads per day), the flash drive will need to be replaced within 100 days (assuming a 100,000 r/w cycle lifetime)?

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  • Shopping for Fast USB Flash Drives

    - by Jim McKeeth
    I would like to pick up some really fast USB flash drives in the 16 - 64 GB range. When looking at drives they just list their size, their form factor (key chain hook, slider, etc.) and the fact that they are all Hi-Speed USB 2.0. It seems like I have heard that different drives have different performance and life expectancy. The sales guy tells me that they are all the same performance any more, but it wouldn't be the first time a sales guy had the wrong technical details. Our objective is to run Virtual PC images off of them, so good speed and resilience to rewrites it important.

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  • Stochastic calculus library in python

    - by LeMiz
    Hello, I am looking for a python library that would allow me to compute stochastic calculus stuff, like the (conditional) expectation of a random process I would define the diffusion. I had a look a at simpy (simpy.sourceforge.net), but it does not seem to cover my needs. This is for quick prototyping and experimentation. In java, I used with some success the (now inactive) http://martingale.berlios.de/Martingale.html library. The problem is not difficult in itself, but there is a lot non trivial, boilerplate things to do (efficient memory use, variable reduction techniques, and so on). Ideally, I would be able to write something like this (just illustrative): def my_diffusion(t, dt, past_values, world, **kwargs): W1, W2 = world.correlated_brownians_pair(correlation=kwargs['rho']) X = past_values[-1] sigma_1 = kwargs['sigma1'] sigma_2 = kwargs['sigma2'] dX = kwargs['mu'] * X * dt + sigma_1 * W1 * X * math.sqrt(dt) + sigma_2 * W2 * X * X * math.sqrt(dt) return X + dX X = RandomProcess(diffusion=my_diffusion, x0 = 1.0) print X.expectancy(T=252, dt = 1./252., N_simul= 50000, world=World(random_generator='sobol'), sigma1 = 0.3, sigma2 = 0.01, rho=-0.1) Does someone knows of something else than reimplementing it in numpy for example ?

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  • High Sqlservr.exe Memory Usage

    - by user18576
    I have a problem with sqlservr.exe (version 2008). It use a more memory. I checked on windows taskbar manager, sqlservr.exe usage ( Mem usage - 8GB Ram). I dont know how can I fix it.Got the following metrics of the server using Perfmon: SQLServer:Buffer Manager Buffer cache hit ratio 13 SQLServer:Buffer Manager Page lookups/sec 46026128096 SQLServer:Buffer Manager Free pages 129295 SQLServer:Buffer Manager Total pages 997309 SQLServer:Buffer Manager Target pages 1053560 SQLServer:Buffer Manager Database pages 484117 SQLServer:Buffer Manager Reserved pages 0 SQLServer:Buffer Manager Stolen pages 383897 SQLServer:Buffer Manager Lazy writes/sec 384369 SQLServer:Buffer Manager Readahead pages/sec 69315446 SQLServer:Buffer Manager Page reads/sec 71280353 SQLServer:Buffer Manager Page writes/sec 12408371 SQLServer:Buffer Manager Checkpoint pages/sec 7053801 SQLServer:Buffer Manager Page life expectancy 735262 SQLServer:General Statistics Active Temp Tables 161 SQLServer:General Statistics Temp Tables Creation Rate 3131845 SQLServer:General Statistics Logins/sec 2336011 SQLServer:General Statistics Logouts/sec 2335984 SQLServer:General Statistics User Connections 27 SQLServer:General Statistics Transactions 0 SQLServer:Access Methods Full Scans/sec 34422821 SQLServer:Access Methods Range Scans/sec 2027247756 SQLServer:Access Methods Workfiles Created/sec 49771600 SQLServer:Access Methods Worktables Created/sec 28205828 SQLServer:Access Methods Index Searches/sec 4890715219 SQLServer:Access Methods FreeSpace Scans/sec 21178928 SQLServer:Access Methods FreeSpace Page Fetches/sec 21226653 SQLServer:Access Methods Pages Allocated/sec 41483279 SQLServer:Access Methods Extents Allocated/sec 4743504 SQLServer:Access Methods Extent Deallocations/sec 4806606 SQLServer:Access Methods Page Deallocations/sec 41419137 SQLServer:Access Methods Page Splits/sec 23834799 SQLServer:Memory Manager SQL Cache Memory (KB) 29160 SQLServer:Memory Manager Target Server Memory (KB) 8428480 SQLServer:Memory Manager Total Server Memory (KB) 7978472 Some body could help me please.And I really want to know the cause for the above.

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  • Will disabling hyperthreading improve performance on our SQL Server install

    - by Sam Saffron
    Related to: Current wisdom on SQL Server and Hyperthreading Recently we upgraded our Windows 2008 R2 database server from an X5470 to a X5560. The theory is both CPUs have very similar performance, if anything the X5560 is slightly faster. However, SQL Server 2008 R2 performance has been pretty bad over the last day or so and CPU usage has been pretty high. Page life expectancy is massive, we are getting almost 100% cache hit for the pages, so memory is not a problem. When I ran: SELECT * FROM sys.dm_os_wait_stats order by signal_wait_time_ms desc I got: wait_type waiting_tasks_count wait_time_ms max_wait_time_ms signal_wait_time_ms ------------------------------------------------------------ -------------------- -------------------- -------------------- -------------------- XE_TIMER_EVENT 115166 2799125790 30165 2799125065 REQUEST_FOR_DEADLOCK_SEARCH 559393 2799053973 5180 2799053973 SOS_SCHEDULER_YIELD 152289883 189948844 960 189756877 CXPACKET 234638389 2383701040 141334 118796827 SLEEP_TASK 170743505 1525669557 1406 76485386 LATCH_EX 97301008 810738519 1107 55093884 LOGMGR_QUEUE 16525384 2798527632 20751319 4083713 WRITELOG 16850119 18328365 1193 2367880 PAGELATCH_EX 13254618 8524515 11263 1670113 ASYNC_NETWORK_IO 23954146 6981220 7110 1475699 (10 row(s) affected) I also ran -- Isolate top waits for server instance since last restart or statistics clear WITH Waits AS ( SELECT wait_type, wait_time_ms / 1000. AS [wait_time_s], 100. * wait_time_ms / SUM(wait_time_ms) OVER() AS [pct], ROW_NUMBER() OVER(ORDER BY wait_time_ms DESC) AS [rn] FROM sys.dm_os_wait_stats WHERE wait_type NOT IN ('CLR_SEMAPHORE','LAZYWRITER_SLEEP','RESOURCE_QUEUE', 'SLEEP_TASK','SLEEP_SYSTEMTASK','SQLTRACE_BUFFER_FLUSH','WAITFOR','LOGMGR_QUEUE', 'CHECKPOINT_QUEUE','REQUEST_FOR_DEADLOCK_SEARCH','XE_TIMER_EVENT','BROKER_TO_FLUSH', 'BROKER_TASK_STOP','CLR_MANUAL_EVENT','CLR_AUTO_EVENT','DISPATCHER_QUEUE_SEMAPHORE', 'FT_IFTS_SCHEDULER_IDLE_WAIT','XE_DISPATCHER_WAIT', 'XE_DISPATCHER_JOIN')) SELECT W1.wait_type, CAST(W1.wait_time_s AS DECIMAL(12, 2)) AS wait_time_s, CAST(W1.pct AS DECIMAL(12, 2)) AS pct, CAST(SUM(W2.pct) AS DECIMAL(12, 2)) AS running_pct FROM Waits AS W1 INNER JOIN Waits AS W2 ON W2.rn <= W1.rn GROUP BY W1.rn, W1.wait_type, W1.wait_time_s, W1.pct HAVING SUM(W2.pct) - W1.pct < 95; -- percentage threshold And got wait_type wait_time_s pct running_pct CXPACKET 554821.66 65.82 65.82 LATCH_EX 184123.16 21.84 87.66 SOS_SCHEDULER_YIELD 37541.17 4.45 92.11 PAGEIOLATCH_SH 19018.53 2.26 94.37 FT_IFTSHC_MUTEX 14306.05 1.70 96.07 That shows huge amounts of time synchronizing queries involving parallelism (high CXPACKET). Additionally, anecdotally many of these problem queries are being executed on multiple cores (we have no MAXDOP hints anywhere in our code) The server has not been under load for more than a day or so. We are experiencing a large amount of variance with query executions, typically many queries appear to be slower that they were on our previous DB server and CPU is really high. Will disabling Hyperthreading help at reducing our CPU usage and increase throughput?

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  • SQLAuthority News – Guest Post – Performance Counters Gathering using Powershell

    - by pinaldave
    Laerte Junior Laerte Junior has previously helped me personally to resolve the issue with Powershell installation on my computer. He did awesome job to help. He has send this another wonderful article regarding performance counter for readers of this blog. I really liked it and I expect all of you who are Powershell geeks, you will like the same as well. As a good DBA, you know that our social life is restricted to a few movies over the year and, when possible, a pizza in a restaurant next to your company’s place, of course. So what we have to do is to create methods through which we can facilitate our daily processes to go home early, and eventually have a nice time with our family (and not sleeping on the couch). As a consultant or fixed employee, one of our daily tasks is to monitor performance counters using Perfmom. To be honest, IDE is getting more complicated. To deal with this, I thought a solution using Powershell. Yes, with some lines of Powershell, you can configure which counters to use. And with one more line, you can already start collecting data. Let’s see one scenario: You are a consultant who has several clients and has just closed another project in troubleshooting an SQL Server environment. You are to use Perfmom to collect data from the server and you already have its XML configuration files made with the counters that you will be using- a file for memory bottleneck f, one for CPU, etc. With one Powershell command line for each XML file, you start collecting. The output of such a TXT file collection is set to up in an SQL Server. With two lines of command for each XML, you make the whole process of data collection. Creating an XML configuration File to Memory Counters: Get-PerfCounterCategory -CategoryName "Memory" | Get-PerfCounterInstance  | Get-PerfCounterCounters |Save-ConfigPerfCounter -PathConfigFile "c:\temp\ConfigfileMemory.xml" -newfile Creating an XML Configuration File to Buffer Manager, counters Page lookups/sec, Page reads/sec, Page writes/sec, Page life expectancy: Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Page*" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" –NewFile Then you start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\ConfigfileMemory.xml -PathOutputFile c:\temp\ConfigfileMemory.txt To let the Buffer Manager collect, you need one more counters, including the Buffer cache hit ratio. Just add a new counter to BufferManager.xml, omitting the new file parameter Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters -CounterName "Buffer cache hit ratio" | Save-ConfigPerfCounter -PathConfigFile "c:\temp\BufferManager.xml" And start the collection: Set-CollectPerfCounter -DateTimeStart "05/24/2010 08:00:00" -DateTimeEnd "05/24/2010 22:00:00" -Interval 10 -PathConfigFile c:\temp\BufferManager.xml -PathOutputFile c:\temp\BufferManager.txt You do not know which counters are in the Category Buffer Manager? Simple! Get-PerfCounterCategory -CategoryName "SQLServer:Buffer Manager" | Get-PerfCounterInstance | Get-PerfCounterCounters Let’s see one output file as shown below. It is ready to bulk insert into the SQL Server. As you can see, Powershell makes this process incredibly easy and fast. Do you want to see more examples? Visit my blog at Shell Your Experience You can find more about Laerte Junior over here: www.laertejuniordba.spaces.live.com www.simple-talk.com/author/laerte-junior www.twitter.com/laertejuniordba SQL Server Powershell Extension Team: http://sqlpsx.codeplex.com/ Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: SQL, SQL Add-On, SQL Authority, SQL Performance, SQL Query, SQL Server, SQL Tips and Tricks, SQL Utility, T SQL, Technology Tagged: Powershell

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  • Tuning Red Gate: #3 of Lots

    - by Grant Fritchey
    I'm drilling down into the metrics about SQL Server itself available to me in the Analysis tab of SQL Monitor to see what's up with our two problematic servers. In the previous post I'd noticed that rg-sql01 had quite a few CPU spikes. So one of the first things I want to check there is how much CPU is getting used by SQL Server itself. It's possible we're looking at some other process using up all the CPU Nope, It's SQL Server. I compared this to the rg-sql02 server: You can see that there is a more, consistently low set of CPU counters there. I clearly need to look at rg-sql01 and capture more specific data around the queries running on it to identify which ones are causing these CPU spikes. I always like to look at the Batch Requests/sec on a server, not because it's an indication of a problem, but because it gives you some idea of the load. Just how much is this server getting hit? Here are rg-sql01 and rg-sql02: Of the two, clearly rg-sql01 has a lot of activity. Remember though, that's all this is a measure of, activity. It doesn't suggest anything other than what it says, the number of requests coming in. But it's the kind of thing you want to know in order to understand how the system is used. Are you seeing a correlation between the number of requests and the CPU usage, or a reverse correlation, the number of requests drops as the CPU spikes? See, it's useful. Some of the details you can look at are Compilations/sec, Compilations/Batch and Recompilations/sec. These give you some idea of how the cache is getting used within the system. None of these showed anything interesting on either server. One metric that I like (even though I know it can be controversial) is the Page Life Expectancy. On the average server I expect see a series of mountains as the PLE climbs then drops due to a data load or something along those lines. That's not the case here: Those spikes back in January suggest that the servers weren't really being used much. The PLE on the rg-sql01 seems to be somewhat consistent growing to 3 hours or so then dropping, but the rg-sql02 PLE looks like it might be all over the map. Instead of continuing to look at this high level gathering data view, I'm going to drill down on rg-sql02 and see what it's done for the last week: And now we begin to see where we might have an issue. Memory on this system is getting flushed every 1/2 hour or so. I'm going to check another metric, scans: Whoa! I'm going back to the system real quick to look at some disk information again for rg-sql02. Here is the average disk queue length on the server: and the transfers Right, I think I have a guess as to what's up here. We're seeing memory get flushed constantly and we're seeing lots of scans. The disks are queuing, especially that F drive, and there are lots of requests that correspond to the scans and the memory flushes. In short, we've got queries that are scanning the data, a lot, so we either have bad queries or bad indexes. I'm going back to the server overview for rg-sql02 and check the Top 10 expensive queries. I'm modifying it to show me the last 3 days and the totals, so I'm not looking at some maintenance routine that ran 10 minutes ago and is skewing the results: OK. I need to look into these queries that are getting executed this much. They're generating a lot of reads, but which queries are generating the most reads: Ow, all still going against the same database. This is where I'm going to temporarily leave SQL Monitor. What I want to do is connect up to the server, validate that the Warehouse database is using the F:\ drive (which I'll put money down it is) and then start seeing what's up with these queries. Part 1 of the Series Part 2 of the Series

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  • SQL SERVER – ASYNC_IO_COMPLETION – Wait Type – Day 11 of 28

    - by pinaldave
    For any good system three things are vital: CPU, Memory and IO (disk). Among these three, IO is the most crucial factor of SQL Server. Looking at real-world cases, I do not see IT people upgrading CPU and Memory frequently. However, the disk is often upgraded for either improving the space, speed or throughput. Today we will look at another IO-related wait type. From Book On-Line: Occurs when a task is waiting for I/Os to finish. ASYNC_IO_COMPLETION Explanation: Any tasks are waiting for I/O to finish. If by any means your application that’s connected to SQL Server is processing the data very slowly, this type of wait can occur. Several long-running database operations like BACKUP, CREATE DATABASE, ALTER DATABASE or other operations can also create this wait type. Reducing ASYNC_IO_COMPLETION wait: When it is an issue related to IO, one should check for the following things associated to IO subsystem: Look at the programming and see if there is any application code which processes the data slowly (like inefficient loop, etc.). Note that it should be re-written to avoid this  wait type. Proper placing of the files is very important. We should check the file system for proper placement of the files – LDF and MDF on separate drive, TempDB on another separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is a higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. Check event log and error log for any errors or warnings related to IO. If you are using SAN (Storage Area Network), check the throughput of the SAN system as well as configuration of the HBA Queue Depth. In one of my recent projects, the SAN was performing really badly and so the SAN administrator did not accept it. After some investigations, he agreed to change the HBA Queue Depth on the development setup (test environment). As soon as we changed the HBA Queue Depth to quite a higher value, there was a sudden big improvement in the performance. It is very likely to happen that there are no proper indexes on the system and yet there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can effectively reduce lots of CPU, Memory and IO (considering cover index has lesser columns than cluster table and all other; it depends upon the situation). You can refer to the following two articles I wrote that talk about how to optimize indexes: Create Missing Indexes Drop Unused Indexes Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussions of Wait Stats in this blog are generic and vary from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – IO_COMPLETION – Wait Type – Day 10 of 28

    - by pinaldave
    For any good system three things are vital: CPU, Memory and IO (disk). Among these three, IO is the most crucial factor of SQL Server. Looking at real-world cases, I do not see IT people upgrading CPU and Memory frequently. However, the disk is often upgraded for either improving the space, speed or throughput. Today we will look at an IO-related wait types. From Book On-Line: Occurs while waiting for I/O operations to complete. This wait type generally represents non-data page I/Os. Data page I/O completion waits appear as PAGEIOLATCH_* waits. IO_COMPLETION Explanation: Any tasks are waiting for I/O to finish. This is a good indication that IO needs to be looked over here. Reducing IO_COMPLETION wait: When it is an issue concerning the IO, one should look at the following things related to IO subsystem: Proper placing of the files is very important. We should check the file system for proper placement of files – LDF and MDF on a separate drive, TempDB on another separate drive, hot spot tables on separate filegroup (and on separate disk),etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. Check event log and error log for any errors or warnings related to IO. If you are using SAN (Storage Area Network), check the throughput of the SAN system as well as the configuration of the HBA Queue Depth. In one of my recent projects, the SAN was performing really badly so the SAN administrator did not accept it. After some investigations, he agreed to change the HBA Queue Depth on development (test environment) set up and as soon as we changed the HBA Queue Depth to quite a higher value, there was a sudden big improvement in the performance. It is very possible that there are no proper indexes in the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can effectively reduce lots of CPU, Memory and IO (considering cover index has lesser columns than cluster table and all other; it depends upon the situation). You can refer to the two articles that I wrote; they are about how to optimize indexes: Create Missing Indexes Drop Unused Indexes Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussions of Wait Stats in this blog are generic and vary from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Types, SQL White Papers, T SQL, Technology

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  • How to analyze 'dbcc memorystatus' result in SQL Server 2008

    - by envykok
    Currently i am facing a sql memory pressure issue. i have run 'dbcc memorystatus', here is part of my result: Memory Manager KB VM Reserved 23617160 VM Committed 14818444 Locked Pages Allocated 0 Reserved Memory 1024 Reserved Memory In Use 0 Memory node Id = 0 KB VM Reserved 23613512 VM Committed 14814908 Locked Pages Allocated 0 MultiPage Allocator 387400 SinglePage Allocator 3265000 MEMORYCLERK_SQLBUFFERPOOL (node 0) KB VM Reserved 16809984 VM Committed 14184208 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 0 MultiPage Allocator 408 MEMORYCLERK_SQLCLR (node 0) KB VM Reserved 6311612 VM Committed 141616 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 1456 MultiPage Allocator 20144 CACHESTORE_SQLCP (node 0) KB VM Reserved 0 VM Committed 0 Locked Pages Allocated 0 SM Reserved 0 SM Committed 0 SinglePage Allocator 3101784 MultiPage Allocator 300328 Buffer Pool Value Committed 1742946 Target 1742946 Database 1333883 Dirty 940 In IO 1 Latched 18 Free 89 Stolen 408974 Reserved 2080 Visible 1742946 Stolen Potential 1579938 Limiting Factor 13 Last OOM Factor 0 Page Life Expectancy 5463 Process/System Counts Value Available Physical Memory 258572288 Available Virtual Memory 8771398631424 Available Paging File 16030617600 Working Set 15225597952 Percent of Committed Memory in WS 100 Page Faults 305556823 System physical memory high 1 System physical memory low 0 Process physical memory low 0 Process virtual memory low 0 Procedure Cache Value TotalProcs 11382 TotalPages 430160 InUsePages 28 Can you lead me to analyze this result ? Is it a lot execute plan have been cached causing the memory issue or other reasons?

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  • Screenscraping and reverse engineering health based web tool

    - by ArbInv
    Hi There is a publicly available free tool which has been built to help people understand the impact of various risk factors on their health / life expectancy. I am interested in understanding the data that sits behind the tool. To get this out it would require putting in a range of different socio-demographic factors and analyzing the resulting outputs. This would need to be done across many thousand different individual profiles. The tool was probably built on some standard BI platorm. I have no interest in how the tool was built but do want to get to the data within it. The site has a Terms of Use Agreement which includes: Not copying, distribute, adapt, create derivative works of, translate, or otherwise modify the said tool Not decompile, disassemble, reverse assemble, or otherwise reverse engineer the tool. The said institution retains all rights, title and interest in and to the Tool, and any and all modifications thereof, including all copyright, copyright registrations, trade secrets, trademarks, goodwill and confidential and proprietary information related thereto. Would i be in effect breaking the law if i were to point a screen scraping tool which downloaded the data that sits behind the tool in question?? Any advice welcomed? THANKS

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  • SQL SERVER – PAGEIOLATCH_DT, PAGEIOLATCH_EX, PAGEIOLATCH_KP, PAGEIOLATCH_SH, PAGEIOLATCH_UP – Wait Type – Day 9 of 28

    - by pinaldave
    It is very easy to say that you replace your hardware as that is not up to the mark. In reality, it is very difficult to implement. It is really hard to convince an infrastructure team to change any hardware because they are not performing at their best. I had a nightmare related to this issue in a deal with an infrastructure team as I suggested that they replace their faulty hardware. This is because they were initially not accepting the fact that it is the fault of their hardware. But it is really easy to say “Trust me, I am correct”, while it is equally important that you put some logical reasoning along with this statement. PAGEIOLATCH_XX is such a kind of those wait stats that we would directly like to blame on the underlying subsystem. Of course, most of the time, it is correct – the underlying subsystem is usually the problem. From Book On-Line: PAGEIOLATCH_DT Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Destroy mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_EX Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Exclusive mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_KP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Keep mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_SH Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Shared mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_UP Occurs when a task is waiting on a latch for a buffer that is in an I/O request. The latch request is in Update mode. Long waits may indicate problems with the disk subsystem. PAGEIOLATCH_XX Explanation: Simply put, this particular wait type occurs when any of the tasks is waiting for data from the disk to move to the buffer cache. ReducingPAGEIOLATCH_XX wait: Just like any other wait type, this is again a very challenging and interesting subject to resolve. Here are a few things you can experiment on: Improve your IO subsystem speed (read the first paragraph of this article, if you have not read it, I repeat that it is easy to say a step like this than to actually implement or do it). This type of wait stats can also happen due to memory pressure or any other memory issues. Putting aside the issue of a faulty IO subsystem, this wait type warrants proper analysis of the memory counters. If due to any reasons, the memory is not optimal and unable to receive the IO data. This situation can create this kind of wait type. Proper placing of files is very important. We should check file system for the proper placement of files – LDF and MDF on separate drive, TempDB on separate drive, hot spot tables on separate filegroup (and on separate disk), etc. Check the File Statistics and see if there is higher IO Read and IO Write Stall SQL SERVER – Get File Statistics Using fn_virtualfilestats. It is very possible that there are no proper indexes on the system and there are lots of table scans and heap scans. Creating proper index can reduce the IO bandwidth considerably. If SQL Server can use appropriate cover index instead of clustered index, it can significantly reduce lots of CPU, Memory and IO (considering cover index has much lesser columns than cluster table and all other it depends conditions). You can refer to the two articles’ links below previously written by me that talk about how to optimize indexes. Create Missing Indexes Drop Unused Indexes Updating statistics can help the Query Optimizer to render optimal plan, which can only be either directly or indirectly. I have seen that updating statistics with full scan (again, if your database is huge and you cannot do this – never mind!) can provide optimal information to SQL Server optimizer leading to efficient plan. Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All of the discussions of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Scripts, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • SQL SERVER – LCK_M_XXX – Wait Type – Day 15 of 28

    - by pinaldave
    Locking is a mechanism used by the SQL Server Database Engine to synchronize access by multiple users to the same piece of data, at the same time. In simpler words, it maintains the integrity of data by protecting (or preventing) access to the database object. From Book On-Line: LCK_M_BU Occurs when a task is waiting to acquire a Bulk Update (BU) lock. LCK_M_IS Occurs when a task is waiting to acquire an Intent Shared (IS) lock. LCK_M_IU Occurs when a task is waiting to acquire an Intent Update (IU) lock. LCK_M_IX Occurs when a task is waiting to acquire an Intent Exclusive (IX) lock. LCK_M_S Occurs when a task is waiting to acquire a Shared lock. LCK_M_SCH_M Occurs when a task is waiting to acquire a Schema Modify lock. LCK_M_SCH_S Occurs when a task is waiting to acquire a Schema Share lock. LCK_M_SIU Occurs when a task is waiting to acquire a Shared With Intent Update lock. LCK_M_SIX Occurs when a task is waiting to acquire a Shared With Intent Exclusive lock. LCK_M_U Occurs when a task is waiting to acquire an Update lock. LCK_M_UIX Occurs when a task is waiting to acquire an Update With Intent Exclusive lock. LCK_M_X Occurs when a task is waiting to acquire an Exclusive lock. LCK_M_XXX Explanation: I think the explanation of this wait type is the simplest. When any task is waiting to acquire lock on any resource, this particular wait type occurs. The common reason for the task to be waiting to put lock on the resource is that the resource is already locked and some other operations may be going on within it. This wait also indicates that resources are not available or are occupied at the moment due to some reasons. There is a good chance that the waiting queries start to time out if this wait type is very high. Client application may degrade the performance as well. You can use various methods to find blocking queries: EXEC sp_who2 SQL SERVER – Quickest Way to Identify Blocking Query and Resolution – Dirty Solution DMV – sys.dm_tran_locks DMV – sys.dm_os_waiting_tasks Reducing LCK_M_XXX wait: Check the Explicit Transactions. If transactions are very long, this wait type can start building up because of other waiting transactions. Keep the transactions small. Serialization Isolation can build up this wait type. If that is an acceptable isolation for your business, this wait type may be natural. The default isolation of SQL Server is ‘Read Committed’. One of my clients has changed their isolation to “Read Uncommitted”. I strongly discourage the use of this because this will probably lead to having lots of dirty data in the database. Identify blocking queries mentioned using various methods described above, and then optimize them. Partition can be one of the options to consider because this will allow transactions to execute concurrently on different partitions. If there are runaway queries, use timeout. (Please discuss this solution with your database architect first as timeout can work against you). Check if there is no memory and IO-related issue using the following counters: Checking Memory Related Perfmon Counters SQLServer: Memory Manager\Memory Grants Pending (Consistent higher value than 0-2) SQLServer: Memory Manager\Memory Grants Outstanding (Consistent higher value, Benchmark) SQLServer: Buffer Manager\Buffer Hit Cache Ratio (Higher is better, greater than 90% for usually smooth running system) SQLServer: Buffer Manager\Page Life Expectancy (Consistent lower value than 300 seconds) Memory: Available Mbytes (Information only) Memory: Page Faults/sec (Benchmark only) Memory: Pages/sec (Benchmark only) Checking Disk Related Perfmon Counters Average Disk sec/Read (Consistent higher value than 4-8 millisecond is not good) Average Disk sec/Write (Consistent higher value than 4-8 millisecond is not good) Average Disk Read/Write Queue Length (Consistent higher value than benchmark is not good) Read all the post in the Wait Types and Queue series. Note: The information presented here is from my experience and there is no way that I claim it to be accurate. I suggest reading Book OnLine for further clarification. All the discussion of Wait Stats in this blog is generic and varies from system to system. It is recommended that you test this on a development server before implementing it to a production server. Reference: Pinal Dave (http://blog.SQLAuthority.com) Filed under: Pinal Dave, PostADay, SQL, SQL Authority, SQL Query, SQL Server, SQL Tips and Tricks, SQL Wait Stats, SQL Wait Types, T SQL, Technology

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  • Stata - Multiple rotated plots on graph (including distributions on sides of axes)

    - by meerak
    I would like to produce a single graph containing both: (1) a scatter plot (2) either histograms or kernel density functions of the Y and X variables to the left of the Y axis and below the X axis. I found a graph that does this in MATLAB -- I would just like to produce something similar in Stata: That graph was produced using the following MATLAB code: n = 1000; rho = .7; Z = mvnrnd([0 0], [1 rho; rho 1], n); U = normcdf(Z); X = [gaminv(U(:,1),2,1) tinv(U(:,2),5)]; [n1,ctr1] = hist(X(:,1),20); [n2,ctr2] = hist(X(:,2),20); subplot(2,2,2); plot(X(:,1),X(:,2),'.'); axis([0 12 -8 8]); h1 = gca; title('1000 Simulated Dependent t and Gamma Values'); xlabel('X1 ~ Gamma(2,1)'); ylabel('X2 ~ t(5)'); subplot(2,2,4); bar(ctr1,-n1,1); axis([0 12 -max(n1)*1.1 0]); axis('off'); h2 = gca; subplot(2,2,1); barh(ctr2,-n2,1); axis([-max(n2)*1.1 0 -8 8]); axis('off'); h3 = gca; set(h1,'Position',[0.35 0.35 0.55 0.55]); set(h2,'Position',[.35 .1 .55 .15]); set(h3,'Position',[.1 .35 .15 .55]); colormap([.8 .8 1]); UPDATE: The Stata13 manual entry for "graph combine" has precisely this example (http://www.stata.com/manuals13/g-2graphcombine.pdf). Here is the code: use http://www.stata-press.com/data/r13/lifeexp, clear generate loggnp = log10(gnppc) label var loggnp "Log base 10 of GNP per capita" scatter lexp loggnp, ysca(alt) xsca(alt) xlabel(, grid gmax) fysize(25) saving(yx) twoway histogram lexp, fraction xsca(alt reverse) horiz fxsize(25) saving(hy) twoway histogram loggnp, fraction ysca(alt reverse) ylabel(,nogrid) xlabel(,grid gmax) saving(hx) graph combine hy.gph yx.gph hx.gph, hole(3) imargin(0 0 0 0) graphregion(margin(l=22 r=22)) title("Life expectancy at birth vs. GNP per capita") note("Source: 1998 data from The World Bank Group")

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