Concurrency Mechanism In Software Engineering

Concurrency Mechanism In Software Engineering' title='Concurrency Mechanism In Software Engineering' />SQL Server performance with many concurrent, long running queries. CPUEach request coming to the server ie. The task are queued up on a scheduler, which is roughly speaking a CPU core, see sys. Each schedulers have several workers ie. This scheduling mechanism applies to everything inside SQL, including system tasks, CLR running code and so on and so forth. The number of tasks that can be created is limited by available memory. Requests batches do not equate one to one to tasks since some requests once started schedule more tasks to be executed, parallel queries being the typical example. The number of workers in the system is dynamic, but capped by the max worker threads configuration setting. If the workers cap was reached, then new scheduled tasks will be queued up in the schedulers but not picked up until a worker frees up finishes a task and becomes available. When this condition is reached, is called worker starvation and result in an unresponsive server, since new client login handshakes requires the login tasks to be executed server appears to reject connections and existing clients new requests will be queued up behind waiting tasks server takes long time to respond to trivial requests. Concurrency Mechanism In Software Engineering' title='Concurrency Mechanism In Software Engineering' />Nginx pronounced engine x is a free open source web server written by Igor Sysoev, a Russian software engineer. Since its public launch in 2004, nginx has focused. Free SAP Hybris, FlexBox, Axure RP, OpenShift, Apache Bench, qTest, TestLodge, Power BI, Jython, Financial Accounting, text and video tutorials for UPSC, IAS, PCS. So if you have a large number of parallel, long running queries you will consume a large number of workers doing many, long running, tasks. This reduces the size of the free workers pool, resulting in fewer workers available to service other, short tasks that are coming to the server like OLTP requests, login handshakes etc. The server appears to be unresponsive because the tasks are piling up in the schedulers queues this can be seen in the sys. DMV workqueuecount column. On extreme cases, you can effectively starve the system of workers, making the server completely unresponsive until some of the workers are free. Memory. A query plan containing parallel operations is usually associated with full scans of large indexes large tables. Scanning an index is done by traversing its leaf pages, and reading all leaf pages in a large table means that all those pages have to be present in memory at one time or another during the execution of the query. This in turn creates a demand for free pages from the buffer pool, to house the scanned pages. The demand for free pages produces memory pressure that results in caches being notified to start evicting old entries and in old accessed data pages in the buffer pool being removed. The cache notifications can be witnessed in sys. The data page evictions can be controlled by checking the good ole Page Life Expectancy performance counter. Evicting cache entries has the effect that the next time the evicted entry is needed being a compiled plan, a permission token, or whatever it has to be created from scratch, resulting in more CPU, memory and IO consumed, an effect that can manifest itself even after the long running queries have finished. Concurrency Mechanism In Software Engineering' title='Concurrency Mechanism In Software Engineering' />I have a SQL Server database with 500,000 records in table main. There are also three other tables called child1, child2, and child3. The many to many relationships. Im wondering how executing many longrunning queries simultaneously will impact SQL Servers ability to service each query in a timely fashion. Edit It wasnt my. Now it may be the case that your system has such gargantuan amounts of RAM installed that scanning a few large tables makes no difference, your RAM can accommodate your entire database with room to spare. In that case there is no problem. But most times this is not the case. Tags Concurrency, multithreading, Python. This entry was posted on Saturday, June 28th, 2008 at 105 am and is filed under Concurrency, Python. Some lab experiments must be performed using any circuit simulation software e. PSPICE. BACHELOR OF TECHNOLOGY Electrical Electronics Engineering. In computer science, software transactional memory STM is a concurrency control mechanism analogous to database transactions for controlling access to shared memory. Download Lg Lcd Screen Driver more. MSDN Magazine Issues and Downloads. Read the magazine online, download a formatted digital version of each issue, or grab sample code and apps. IOThis is related to the point above the MEMORY. All those page read to satisfy the index scan have to be transferred into memory, which means a potentially large portion of the IO bandwidth is consumed by the long running queries. Also, all dirty data pages that are evicted from the buffer pool have to be written to the disk, resulting in more IO. And the clean pages that were evicted are likely going to be needed back some time in the future, so even more IO. If the IO generated by the scans exceed the bandwidth of your system, the IO operations start queuing up on the disk controllers. Physical DiskAvg Queue Length performance counters. Contention. And finally, the biggest problem lock contention. As explained, parallel queries almost always imply table scans. And table scans take a shared lock on each row they visit. Its true that they release the lock as soon as the record is read in normal operations mode, but still you are guaranteed that youll request an S lock on every row in the table. This pretty much guarantees that these scans will hit a row that is locked X by an update. When this happens the scan has to stop and wait for the X lock to be released, which happens when the update transactions finally commits. The result is that even moderate OLTP activity on the table blocks the long running queries. Ideally that is all what happens, and the result is just poor performance. But things can get ugly quickly if the long running query does anything fancy, like acquire page locks instead of row locks. Since these scans traverse the indexes end to end and theyre guaranteed to enter in conflict with updates, the higher granularity locks acquired by these queries no longer just conflicts with the update locks, but it actually leads to deadlocks. Explaining how this can happen is beyond the point of this reply. To eliminate the contention, when the queries are legitimately doing full scans, the best alternative is to use the magic snapshot either database snapshots created for reporting, or using the snapshot isolation levels. Note that some may recommend using dirty reads, Im yet to find a case when that was actually acceptable. The Architecture of Open Source Applications Volume 2 nginxnginx pronounced engine x is a free open source web server. Igor Sysoev, a Russian software engineer. Since its public. Additional features on top of the. Currently nginx is the second most. Internet. 1. 4. 1. Why Is High Concurrency Important These days the Internet is so widespread and ubiquitous its hard to. It has greatly evolved. HTML producing clickable text, based on NCSA and then on. Apache web servers, to an always on communication medium used by more. With the proliferation of permanently. PCs, mobile devices and recently tablets, the Internet. Online services have become much more elaborate with. Security aspects of running online business have also. Accordingly, websites are now much more complex. One of the biggest challenges for a website architect has always been. Since the beginning of web services, the level of. Its not uncommon for a. A decade ago, the major cause of concurrency was. ADSL or dial up connections. Nowadays. concurrency is caused by a combination of mobile clients and newer. Another important factor contributing. To illustrate the problem with slow clients, imagine a simple. Apache based web server which produces a relatively short 1. KB. responsea web page with text or an image. It can be merely a. KBs. Essentially, the web server would relatively quickly pull 1. KB of content, and then it would be busy for 1. Now imagine. that you have 1,0. If only 1 MB of additional memory is. MB about 1 GB of. KB of. content. In reality, a typical web server based on Apache commonly. MB of additional memory per connection, and. Although the situation with sending content to a slow. With persistent connections the problem of handling concurrency is. HTTP connections, clients would stay connected, and. Consequently, to handle the increased workloads associated with. While the other parts of the equation. CPU, memory, disks, network capacity, application. Thus, the web server should be able to scale nonlinearly. Isnt Apache SuitableApache, the web server software that still largely dominates the. Internet today, has its roots in the beginning of the. Originally, its architecture matched the then existing. Internet, where a website was typically a standalone physical server. Apache. By the beginning of the 2. Although. Apache provided a solid foundation for future development, it was. Eventually. Apache became a general purpose web server focusing on having many. However, nothing comes without a price and the downside. CPU and. memory usage per connection. Thus, when server hardware, operating systems and network resources. Around ten years ago, Daniel Kegel, a prominent software. Internet cloud services. Kegels C1. 0K manifest spurred a. Aimed at solving the C1. K problem of 1. 0,0. Apaches style of spawning new. The end result is that. CPU usage remain manageable. When the first version of nginx was released, it was meant to be. Apache such that static content like HTML, CSS. Java. Script and images were handled by nginx to offload concurrency and. Apache based application servers. Over the. course of its development, nginx has added integration with. Fast. CGI, uswgi or SCGI protocols, and. Other useful functionality like reverse proxy with. These additional. In February 2. 01. Apache 2. 4. x branch was released to the public. Although. this latest release of Apache has added new multi processing core modules and. It would be very nice to. Apache application servers scale better with the new version, though, as it. Apache web configurations. Are There More Advantages to Using nginxHandling high concurrency with high performance and efficiency has. However, there. are now even more interesting benefits. In the last few years, web architects have embraced the idea of. However, what would previously exist in the form of a LAMP. Linux, Apache, My. SQL, PHP, Python or Perl based website, might now. LEMP based one E standing for Engine. SSL. secure sockets layer, static content, compression and caching. HTTP media streaming. It also allows integrating directly with memcachedRedis or. No. SQL solutions, to boost performance when serving a large. With recent flavors of development kits and programming languages. The first lines of nginx were written in 2. In 2. 00. 4 it was released. BSD license. The number of nginx. The nginx codebase is original and was written entirely from scratch. C programming language. Linux, Free. BSD. Solaris, Mac OS X, AIX and Microsoft Windows. C library, except for zlib, PCRE and Open. SSL which can be. A few words about the Windows version of nginx. While nginx works in a. Windows environment, the Windows version of nginx is more like a. There are. certain limitations of the nginx and Windows kernel architectures that. The known issues of the nginx. Windows include a much lower number of concurrent. Future versions of nginx for Windows will match the. Overview of nginx Architecture. Traditional process or thread based models of handling concurrent. Depending on the application, it can be very inefficient. CPU consumption. Spawning a separate process or. Additional CPU time is also spent creating these. All of these complications. Apaches. This is a tradeoff between offering a rich set of generally. From the very beginning, nginx was meant to be a specialized tool to. It was actually inspired by the ongoing. What resulted is a modular, event driven. Connections are processed in a. Within each worker nginx can. Code Structure. The nginx worker code includes the core and the functional. The core of nginx is responsible for maintaining a tight. Modules constitute most of the. Modules read from. At this time, nginx doesnt support. However, support for loadable modules and ABI is. More detailed information about. Section 1. 4. 4. While handling a variety of actions associated with accepting. IO. performance enhancements in Linux, Solaris and BSD based operating. The. goal is to provide as many hints to the operating system as possible. The usage of different methods for multiplexing. IO operations is heavily optimized for every Unix based. A high level overview of nginx architecture is presented in. Figure 1. 4. 1. Figure 1. Diagram of nginxs architecture. Workers Model. As previously mentioned, nginx doesnt spawn a process or thread for. Instead, worker processes accept new requests. Theres no specialized arbitration or distribution of. OS. kernel mechanisms. Upon startup, an initial set of. HTTP requests and. The run loop is the most complicated part of the nginx worker. It includes comprehensive inner calls and relies heavily on the. Asynchronous operations are. Overall, the key principle. The only situation where nginx. Because nginx does not fork a process or thread per connection, memory. CPU cycles as well because theres. What nginx. does is check the state of the network and storage, initialize new. Combined with the careful use of. CPU usage even under extreme workloads. Because nginx spawns several workers to handle connections, it. Generally, a separate worker. Theres no resource starvation. This model also allows more. IO. As a result, server. With some disk use and CPU load patterns, the number of nginx. The rules are somewhat basic here. General recommendations might be the following if. CPU intensivefor instance, handling a lot of. TCPIP, doing SSL, or compressionthe number of nginx workers. CPU cores if the load is mostly disk IO. Some engineers choose the number of. One major problem that the developers of nginx will be solving in upcoming.