massive whiteboard

suitable for queries of large-capacity databases. I hope that through the analysis of the above stored procedures, we can provide some inspiration and improve the efficiency of our work. At the same time, I hope our peers can propose better real-time data paging algorithms. 4. Importance of clustered indexes and how to select clustered Indexes In the title of the previous section, I wrote: The general paging display stored process for small data volumes and

Http://blog.csdn.net/axman/article/details/2200840 For the insertion and update of massive data, ADO. NET is indeed inferior to JDBC, and JDBC has a unified model for batch operations.Very convenient:Preparedstatement PS = conn. preparestatement ("insert or update arg1, args2 ....");Then you canFor (INT I = 0; I PS. setxxx (realarg );.....PS. addbatch ();If (I % 500 = 0) {// assume that five hundred entries are submitted once.Ps.exe cutebatch ();// C

Rapid online updating of massive data (zt) http://www.itpub.net/thread-1052077-1-2.html using rowid Recently, I have been tossing the issue of updating large tables, and today I have made a breakthrough. I am excited to post a post to share my experiences with you and discuss whether it may further increase the processing speed.The problem is that there is no partition in a 0.5 billion-record table. Because a redundant field is added, you need to upd

1. Introduction:Pagedgeometry is a plug-in of the Ogre engine. It provides optimization policies for rendering massive grids in (infinite) regions. It is very suitable for dense forests and outdoor scenarios, where there are a large number of scenario objects such as trees, grass, rocks, and bushes. 2. pagedgeometry Management Pagedgeometry class This class is responsible for loading the scene ry that requires immediate (or rapid) visibility without l

Detailed code for thinkphp processing of massive data table mechanism The thinkphp built-in sub-table algorithm is applied to process millions user data. Data sheet: house_member_0 house_member_1 house_member_2 house_member_3 model class Membermodel extends Advmodel {protected　　$partition = Array (' field ' = ' username ', ' type ' = ' id ', ' num ' = ' 4 ');　　Public Function Getdao ($data =array ()) {$data = empty ($data)? $_post: $data;　　$table =

, Figure 3-13, and Figure 3-14 show the number of tasks at each time point. MAPS has only one phase, while reduces has three phases: shuffle, merge, and reduce. Shuffle transfers data from maps, and merge does not need it during testing. The reduce stage performs the final aggregation and writes it to HDFS. If you compare these figures with Figure 3-6, you will find that the task creation speed is faster. In Figure 3-6, it takes 40 seconds to create a task for each heartbeat task. Now, a tasktra

Bitmap bitmap is often used to deal with massive data, such as 0.3 billion and 0.7 billion QQ re-query problems, telephone number de-duplication problems, can be processed using bitmap. The bitmap method is simple, that is, to apply for a table composed of bits, you can set it to 0 or 1 at the corresponding position, so as to quickly achieve quick search without wasting space. The bitmap method is described in more detail on the Internet. This article

point in scripting language: to try to use the language provided by the function, do not implement the algorithm itself, especially the kind of loop, execution speed is not an order of magnitude. To process large quantities of data, split the steps to generate intermediate files. A large number of complex data operations to small batches of small batches of slowly debugging, the result is correct to gradually switch to real data. Multithreading in the operation-intensive scene is no aut

MySQL tutorial massive data paging optimization codePage represents page numberPageSize represents the number of displays per pageConditon represents some conditions view sourceprint?1 select * FROM table where Conditon order by ID limit (page-1) *pagesize,pagesize;Such pagination in the early days did not appear any problems, but when the table and the data reached 100W, slowly appeared problems, search hundreds of pages, often to use more than 2 sec

Recently done a database analysis of a project, to achieve the import of massive data, that is, a maximum of 2 million data imported into SQL Server, if the use of ordinary insert statement to write, I am afraid that not a few hours to complete the task, first consider using bcp, but this is based on the command line, Friendly to the user is too bad, is unlikely to be used; The final decision is to use the BULK INSERT statement to implement, BULK inse

clustered indexes and how to select clustered Indexes In the title of the previous section, I write a general paging display stored procedure that implements small data and massive data. This is because in the practice of applying this stored procedure to the "Office automation" system, the author discovers that this third kind of stored procedure has the following phenomena in the case of small data quantity: 1, paging speed generally maintained bet

project that needs to deploy a worldwide sensor network, and all the sensors will produce a huge amount of data. Or you're studying the DNA sequence. If you understand or think you are facing a massive data storage requirement, there are billions of rows and millions of columns, you should consider hbase. This new database design is designed to be done from the infrastructure to the level expansion phase in a commercial server cluster without the nee

On the afternoon of August 27, in the IT168 System Architect Conference Storage and system architecture sub-forum, the Chairman of the Taobao Technical committee, Taobao core engineer Zhangwensong to us a detailed description of the Taobao image processing and storage system architecture. Dr. Zhangwensong's lecture schedule includes the entire system architecture of Taobao, the architecture of Taobao image storage System, the independent development of the TFS cluster file system in Taobao, the

ALTER event ' MyEvent ' On completion PRESERVE ENABLE; --Closes ALTER EVENT ' myevent ' on completion PRESERVE DISABLE; MySQL does not start the event by default, so you need to modify your My.ini or my.cnf[mysqld] to add the following as Downlink Event_scheduler=1 Three simulated materialized views 1) First build a base table. SQL code CREATE TABLE ' user ' ( ' Id ' int () NOT NULL auto_increment, ' name ' varchar (255) DEFAULT null, ' age ' int (one) DE FA

server|sqlserver| data recently done a database analysis of a project, to achieve the import of massive data, that is, the maximum of 2 million data imported into SQL Server, if the use of ordinary insert statement to write, I am afraid not a few hours to complete the task, First consider using bcp, but this is based on the command line, unfriendly to the user, very unlikely to be used, and finally decided to use the BULK INSERT statement, BULK Insert

Absrtact: June 29 2016 Cloud Habitat Chengdu Summit opened the curtain, Aliyun senior experts Jianzhi brought "massive game log storage and analysis" important speech. From data, cloud computing to change the game industry, and then talk about the whole process of log service, including the role of log, log processing challenges, as well as the principle of log channel, model, and finally analyzed the log service part of the function and typical appli

1. Method principle: Based on the basic principle of hbase storage System, this paper presents an effective solution to the Mapfile file of HDFs with "state Mark Bit", which is not perfect to support append processing, which solves the problem of small file storage of HDFs, and solves the problem of mapfile immediate modification. 2. Method Description: In the massive picture background, the storage form of the picture is an important part to ensure t

table method, you should first look for a set-based solution to solve the problem, and the set-based approach is usually more efficient. 27. As with temporary tables, cursors are not unusable. Using cursors on small datasets FAST_FORWARD is often preferable to other progressive processing methods, especially if you have to reference several tables to get the data you need. Routines that include "totals" in the result set are typically faster than using cursors. If development time permits, a cu

cursors on small datasets is often preferable to other progressive processing methods, especially if you must reference several tables to obtain the required data. Routines that include "totals" in the result set are typically faster than using cursors. If development time permits, a cursor-based approach and a set-based approach can all be tried to see which method works better.28. Set NOCOUNT on at the beginning of all stored procedures and triggers, set NOCOUNT OFF at the end. You do not nee

read, close the FIFO file and remove, Then rebuild the FIFO file and print more rows. This will ensure that you can read the number of lines you read until the read is complete. Note This tool can only work on Unix-like operating systems.Common options:--fifo/tmp/pt-fifo-split, specifying the path to the FIFO file;--offset 0, if you do not intend to start reading from the first line, you can set this parameter;--lines 1000, number of rows per read;--force, if the FIFO file already exists, delet