massive whiteboard

, and operating system performance, or even network adapters and switches. Iii. General paging display and storage process for small data volumes and massive data Creating a web application requires paging. This problem is very common in database processing. The typical data paging method is the ADO record set paging method, that is, using the paging function provided by ADO (using the cursor) to implement paging. However, this paging method is onl

In the file, the bank of contents is id = 2112112, email = xxx@163.com, and so on other, id = 2112112, email = xxx@163.com, and so on other, id = 2112112, email = xxx @ 1 massive log storage There are 10 log files under the log, each file is compressed after about 60 mleft, the file suffix is .gz, such as a.gzw. B .gz, the contents of the file is id = 2112112, email = xxx@163.com, and so on other, Id = 2112112, email = xxx@163.com, etc. other, Id = 21

long tail keywords. I will write an article about analyzing competitors separately in the future, this article mainly describes how to analyze competitors). We are working on optimization technologies. Now we have the way to obtain long tail keywords. Next, we need to optimize a large number of long tail keywords.3. Keyword tableA qualified SEOer must make a keyword table for the website. If it is a small website, we can ignore this step, however, most enterprise websites need to create a keywo

PHP generates a massive number of second-level domain names. could you please refer to my question: www.abc.com/aa.php? How can I implement the change of id = aa to aa.abc.com? for more information, see PHPcode $ str = 'www .abc.com/aa.php? Id = AA'; preg_match ('# id PHP generation of massive second-level domain names For example, I want www.abc.com/aa.php? How can I implement this by changing id = aa to

Developer benative over GitHub have a project called concepts which is a massive collection of Delphi modular demos feat Uring over twenty different language features, design patterns and some interresting frameworks, and components. A copy of the libraries The concepts project depends on is included to reduce the hassle of installing them Separa Tely.The modular demos include demonstrations of the following libraries: Delphi run-time Library (or

How to handle massive Concurrent Data Operations File Cache, database cache, optimized SQL, data shunting, horizontal and vertical division of database tables, and optimized code structure! Summary of lock statements I. Why should I introduce locks? When multiple users perform concurrent operations on the database, the following data inconsistency occurs: Update loss A and B read and modify the same data. The Modification result of one user dest

display and storage process for small data volumes and massive data Creating a web application requires paging. This problem is very common in database processing. The typical data paging method is the ADO record set paging method, that is, using the paging function provided by ADO (using the cursor) to implement paging. However, this paging method is only applicable to small data volumes, because the cursor itself has a disadvantage: the cursor is s

on a certain day with massive log data. Solution 1: the first is this day, and the IP addresses in the logs accessing Baidu are obtained and written to a large file one by one. Note that the IP address is a 32-bit IP address with a maximum of 2 ^ 32 IP addresses. You can also use the ing method, such as modulo 1000, to map the entire large file to 1000 small files, and then find the IP address with the highest frequency in each small text (hash_map c

5000 small files (marked as) based on this value. In this way, each file is about KB. If the size of some files exceeds 1 MB, you can continue to split the files in a similar way, knowing that the size of the small files to be decomposed cannot exceed 1 MB. For each small file, count the words in each file and the corresponding frequency (trie tree/hash_map can be used ), and take out the 100 words with the maximum frequency (the minimum heap containing 100 nodes can be used), and save the 100

improve system operation efficiency. If the system has multiple CPUs or multiple disk subsystems, you can achieve better performance through parallel operations. Therefore, partitioning a large table is a very efficient way to process massive data. This article describes how to create and modify a partition table and how to view the partition table through a specific example. 1 SQL Server 2005 　　 Microsoft launched SQL Server 2005 within five ye

Input and Output ==> Tested object ==> Dependency exception Test procedure: First use the minimum data volume, then the general data volume, and finally the massive data. Use the minimum data volume to test-driven development, implement basic functions, and create basic function tests. Test all functions with the data volume in normal applications Finally, we use massive data to test performance and li

of some files exceeds 1 MBMethodContinue to split down and know that the size of the small file to be decomposed cannot exceed 1 MB. For each small file, calculate the words in each file and the corresponding frequency (trie tree/hash_map can be used), and obtain the most frequently occurring100Words (can contain100Node), and100Words and the corresponding frequency are stored in the file, and then 5000 files are obtained. The next step is to merge the 5000 files (similar to the merge and sort f

Document directory 1 applications of near-Neighbor Search 2 shingling of documents 3 similarity-preserving summaries of Sets 4 locality-sensitive Hashing for documents 5 distance measures 6 The Theory of locality-sensitive functions 7 lsh families for other distance measures In the previous blog (http://www.cnblogs.com/fxjwind/archive/2011/07/05/2098642.html), I recorded the same issue with the relevant massive documentation, here we'll rec

be connected may be on another machine. The solution is to write a dedicated data access layer, but with the sharding again and again, the data access layer itself becomes very complex. Sharding itself is also very complicated. Many issues need to be considered when performing sharding operations. It is necessary to ensure that the data operations required by the business can still be completed after sharding, incorrect sharding can cause disastrous consequences to the system. Due to its comple

the database response time is physical I/O operations. One of the most effective ways to restrict physical I/O operations is to use top keywords. The top keyword is a system-optimized term in SQL Server used to extract the first few or the first few percentage data entries. Through the application of the author in practice, it is found that top is indeed very useful and efficient. However, this word does not exist in another large database oracle. This is not a pity, although other methods (suc

With the concept of big data gradually increasing, how to build an architecture system that can collect massive data is in front of everyone's eyes. How to achieve what you see is what you get, how to quickly structure and store irregular pages, how to meet the needs of more and more data collection within a limited time. This article is based on our own project experience. Let's take a look at how people get webpage data? 1. Open a browser and enter

ordered Read File, take hash (x) % 5000 for each word X and save it to 5000 small files (marked as x0, x1... x4999. In this way, each file is about KB. If the size of some files exceeds 1 MB, you can continue to split the files in a similar way, knowing that the size of the small files to be decomposed cannot exceed 1 MB. For each small file, count the words in each file and the corresponding frequency (trie tree/hash_map can be used ), and take out the 100 words with the maximum frequency (the

[mscorlib] system. idisposable: dispose () il_0045: NOP il_0046: endfinally} // end handler il_0047: Pop il_0048: Ret} // end of method program: Main (Red part)Now we can see the problem. It was originally two sections of code with the same function, but in method 2, there was an extra try .. in the finally module, an initial storage element is applied for CS $4 $0000, and many more rows are considered as address assignment operations. This is the main cause of low efficiency in method 2. Howev

Based on memory ing principleHigh-speed massive data collection and storage technology Cutedeer(Add my code) The memory ing file technology is a new file data access mechanism provided by the Windows operating system. Using the memory ing file technology, the system can reserve a part of the space for the file in the 2 GB address space, and map the file to this reserved space. Once the file is mapped, the operating system manages page ing, buffering,

Original title: Unity CEO Talk VR:VR will be available on a massive scale next yearat the VRLA 2017 Exposition, Unity John Riccitiello, chief executive, has brought some inspiration to the currently hot-fired VR industry. Riccitiello that the VR era is coming, it will be huge, but it is recommended that developers will focus on survival, if they want to seize the incredible opportunity in front of it, it is necessary to avoid speculation. People are v