Real-time database: Benefits and quotes

1 references

(1) Introduction to real-time database, http://blog.csdn.net/liqfyiyi/article/details/6862886

(2) Real-time database introduction and comparison, http://www.cnblogs.com/zljini/archive/2006/05/17/402422.html

(3) Real-time database introduction, http://wenku.baidu.com/link?url= 0iqofeyetgz8duhkb-lci-kypl9v3ivohysglihjgxpq-f-1dbcapdfw3jiiam6nsbvsd_hud6qusvxlfhbftl8k1nitc2kzj78bh2iqz6k

2 Introduction to Real-time databases

The real-time database (rtdb-real) is a branch of database system development, which is produced by the combination of database technology and real-time processing technology. Real-time database is " database management system of time-scale information with high real-time requirement "

Real-time database is a system software, but more is an application platform software, the reason is that the real-time database has not a standard like SQL, and its function is too comprehensive, each manufacturer launched product features have focused.

2.1 Characteristics of database applications in the field of industrial monitoring

The definition of industrial monitoring system is very large, all need to operate equipment automation monitoring, control system can be defined as industrial monitoring system, which includes thermal power plant level monitoring System (SIS), in such applications, database applications have the following characteristics:

?  large number of measuring points

A new 300WM Thermal power plant sis system, the number of points to be processed more than 10,000 points, these measurement points of the change cycle is usually within 1 seconds, that is, more than 10,000 points need to be stored in the database in 1 seconds.

?  Large storage capacity

The core of real-time database is to deal with a lot of real-time information, because the carries data will occupy a lot of hard disk space. For example, the 10,000-point system, which is stored every 1 seconds, consumes 8 bytes at a time, then the amount of data saved for 10 years will be 10000*8*10*365*86400=25228800000000 bytes, which is 23TGB. If you use a 80GB HDD storage, you need to store 293 hard drives!

Comments: It is obvious that this amount of data is not comparable to what our system can do.

?  Strong Timeliness

The value of each measurement point that needs to be processed is related to the time, and the data after one second may be different from the data that precedes the second, so it is necessary to record the corresponding time in a certain way while saving the measured point value.

2.2 Reasons for not selecting a relational database

relational database, it is more difficult to deal with the industrial control field data. The main reasons are:

?  Slow insertion Speed

The general relational database is transaction-based, and the job is rolled back after the processing has failed. So at least two places, the mechanism to slow down, both using today's Intel P4 dual Xeon Class CPU, 2000 points in the insertion of the use of more than 10s of time. The industrial monitoring system is faced with tens of thousands of-point real-time data at the second-level interval of data storage.

?  Maintenance Difficulties

Commercial database to ensure integrity, all content is often placed in a file, which is difficult to maintain the storage of large amounts of data. If there is a number of 200G

A full backup can take one day, according to the library. An error in the backup file could invalidate the 200G backup file, so it is not practical.

?  cannot meet the needs of real-time applications

Using database to store real-time data and query methods can not meet the needs of real-time applications. A simple example is the assumption that the data is stored at 1-second intervals, with 604800 groups of data in a week, but it is now difficult to implement the standard SQL syntax by taking 10080 of them at 60-second intervals or taking out 8888 groups with equal-interval principle.

Therefore, in the field of industrial monitoring and the SIS application of power plant, it is necessary to find real-time database system suitable for real-time application.

Introduction of compression algorithm for 2.3 real-time database

The core technology of real-time database system is data compression. The data needs to be compressed and then saved to the hard disk, and the data on the hard drive is decompressed when data is needed. At present, the compression algorithms used in real-time databases at home and abroad are usually divided into two types: lossless compression and lossy compression.

2.3.1 Lossless compression

Most of the information expression has a certain degree of redundancy, by using a certain model and coding method, can reduce this redundancy. Huffman coding is one of the most famous algorithms in lossless compression. Software like WinRAR and WinZip uses a compression method similar to Huffman encoding. The common feature of these compression methods is that the information does not change during compression and decompression.

In the real-time database, you can also use these lossless compression technology, but in the implementation, it is necessary to consider the efficiency of compression and decompression, if a compression algorithm is very high compression ratio, but its decompression speed is very slow, it is certainly not used in real-time database, otherwise, people in the query data, will wait to lose patience.

2.3.2 lossy compression

In contrast to lossless compression, compression is certain to lose some information, but it is important to ensure that the lost information does not affect the accuracy of the system data. We have also encountered in other areas of lossy compression applications, such as: JPG image compression is a lossy compression, MP3 sound compression is also a lossy compression.

In the real-time database, there are two main methods of lossy compression: dead-Zone compression and trend compression.

? Dead Zone compression

The so-called dead zone is defined as the constant range of values for a given measurement point. The use of dead-zone compression is to record data values outside the dead zone of the point. For example, there is a test point A, the dead zone is defined as 1%, the last recorded measured point value is 110.00, then the measured point value of the acquisition is 111.00, then the difference (111-110)/110<1%, then the value of the measured point in the dead zone of the point, it is considered not to change, that is not recorded. If the next measured point value is 120.00, then the difference (120-110)/110>1%, then the value of the measured point is considered to be outside the dead range of the point, it is considered to be changed, recorded.

? Trend Compression

Trend compression, which is compressed according to the periodic trend of the measured points, only records the starting and ending points that meet the trend conditions in principle. The rotary gate compression technique of Pi is a model of this kind of algorithm.

The general trend compression is as shown, T1 to T2 time the value of a measured point hold the trend, then the trend of the two tolerance line will be the next point in the dead zone range, if the next moment T3 between the two two tolerance lines, then do not record this value, two tolerance line will apply to the next moment, if the next moment T4 This value is recorded in addition to the two two tolerance lines, the trend changes, two tolerance lines change, and the next point of measurement is judged by the changed tolerance line.

2.4 How real-time databases are accessed

? Using the APIs provided by the live database

This is the most efficient and simple way to do this.

? Using ODBC

Most real-time databases provide a standard ODBC interface, as well as a SQL query language that enables users to use a real-time database as a standard database. But this approach is slow and does not reflect the full benefits of real-time data.

? Using the OPC method (OLE for Process Control)

Because too many databases and DCs use their own API way to access data, the algorithm can not be common, because industrial monitoring filed a standard access interface, which is OPC, now has more than 200 manufacturers to join the OPC organization, the mammoth.

3 main contents of real-time database system

Real-time database technology is a combination of real-time system and database technology, the main contents of real-time database system include:

Real-time database model;

Real-time transaction scheduling: including concurrency control, conflict resolution, deadlock and other content;

Fault tolerance and error recovery;

Memory organization and management;

Access Admission Control;

I/O and disk scheduling;

Main memory database system;

The problem of inaccurate calculation;

The serializable problem of relaxation;

real-time SQL;

Predictability of real-time transactions;

4 space consumption of real-time databases

Pi using the rotary door compression patented technology and unique two times filter technology, so that the data into the PI database has been the most effective compression, greatly saving the hard disk space. According to the calculation, 10,000 points per second of data storage for one year, only 4G of space, that is, a normal hard disk can also store 5-10 years of data.

http://blog.csdn.net/liqfyiyi/article/details/6862886

5 Real-time database access performance

Each PI server can hold 1.5 million points (high-end servers) and can process 1.5 million points of data per second in the high-end product server of pi. On the client software Processbook, 1000 points can be taken from 2-year or 3-year history in a second time period.

Refer to the data provided by the OSI Company: The data value of the real-time information point is 1 days with an average change of 500, each information point occupies 3 bytes of storage space, that 10,000 points of storage for 1 years online is:

Number of changes × single point of storage x information points x1 years = Total space requirements

500x3x10000x365 = 5.475GB

6 real-time database prices

For example, 5,000-point database and 20-client application, several database prices are:

PI----$ 100,000, $6000 per interface, OPC interface charges;

infoplus.21----$ 110,000, 10,000 USD per interface, OPC interface no charge;

Industrial SQL Server----$ 65,000, each IDAS1200 USD, OPC link free.

7 Common real-time databases

At present, enter the domestic market more mature real-time database products are listed as follows:

? American OSIsoft Company, PI;

? American Wonderware Company, Industrialsql Server, abbreviated as INSQL;

? American Ge,intellution Company, Ihistorian;

? American InStep Company, EDNA;

? Honeywell, United States, Process history Database, referred to as PhD;

? American AspenTech Company, Infoplus;

In general, foreign real-time database products in the industrial monitoring industry occupies a monopoly position. OSIsoft Company's PI using the rotary door compression patented technology and unique two times filtration technology, so that the data into the PI database through the most effective compression, greatly saving the hard disk space, is the most efficient, the simplest use, the most widely used real-time database. Because of its outstanding performance, PI has increased its price several times.

7.1InSQL

This is the product of Wonderware company, formerly known as industrial SQL Server, from this name can be seen, he is based on SQL Server, is a real-time database based on a relational database. The latest name, Wonderware Historian,wonderwaer, has been bought by Schneider, and it is estimated that the name has been changed after the acquisition, and I can see that the latest version of Insql on the internet is probably about 2005 years or so of the 9.0 version.

Http://global.wonderware.com/CN/Pages/WonderwareHistorian.aspx

7.1.1 Overview

Wonderware historian History Library software is a high-performance real-time database for industrial enterprises that delivers unmatched scalability and supports up to 500,000 labels, with greater retrieval throughput compared to previous products. Historian can be configured as a single data collection and aggregation system, or as part of a larger, multi-tiered architecture system. If local facilities have high-resolution data, they require detailed troubleshooting, and enterprise decision makers can compare the performance of multiple plants with aggregated data.

For geographically dispersed plants, Wonderware Historian is the ideal choice because it has the ability to maintain data integrity when processing intermittent, delayed, or fragmented data.

Many industrial enterprises require uninterrupted access to process data for 7 days and 24 hours, while maintaining isolation between their management networks and commercial networks. Wonderware Historian provides cost-effective solutions for both of these requirements. Our redundant History library options provide a simple, low-cost, high-availability solution while enabling cost-effective isolation between the management network and the Business network.

With the new features and versatility of the Wonderware Historian client, you can quickly see where the problem is in your process and quickly make decisions, troubleshoot, and process optimization. As a result, Historian can be SQL compatible with a number of other reporting solutions that can access your process data.

New PRODUCTS debut!!! Wonderware Historian is now available in the form of cloud-managed solutions to businesses looking to reduce capex and IT burdens. Partnering with Microsoft, Microsoft's Windows Azure Cloud Environment provides this innovative software as a software-as-a-service (SaaS) guarantee for data security and high availability of critical process data. The Wonderware Historian online version collects and aggregates data from other wonderware historians, as well as data reporting and analysis clients, and is a complete operational information management solution.

Reprinted from: http://www.cnblogs.com/strinkbug/p/4905663.html

Real-time database: Benefits and quotes