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The core of the core of the big data solutions -- Map

1 réponse
Title: The core of the core of the big data solutions -- Map
Author: pengwenwei
Email: =20
Language: c++
Platform: Windows, linux
Technology: Perfect hash algorithm
Level: Advanced
Description: Map algorithm with high performance
Section MFC c++ map stl
SubSection c++ algorithm
License: (GPLv3)

Download demo project - 1070 Kb
Download source - 1070 Kb

For the c++ program, map is used everywhere.And bottleneck of program perfo=
rmance is often the performance of map.Especially in the case of large data=
,and the business association closely and unable to realize the data distri=
bution and parallel processing condition.So the performance of map becomes =
the key technology.

In the work experience with telecommunications industry and the information=
security industry, I was dealing with the big bottom data,especially the m=
ost complex information security industry data,all can't do without map.

For example, IP table, MAC table, telephone number list, domain name resolu=
tion table, ID number table query, the Trojan horse virus characteristic co=
de of cloud killing etc..

The map of STL library using binary chop, its has the worst performance.Goo=
gle Hash map has the optimal performance and memory at present, but it has =
repeated collision probability.Now the big data rarely use a collision prob=
ability map,especially relating to fees, can't be wrong.

Now I put my algorithms out here,there are three kinds of map,after the bui=
ld is Hash map.We can test the comparison,my algorithm has the zero probabi=
lity of collision,but its performance is also better than the hash algorith=
m, even its ordinary performance has no much difference with Google.

My algorithm is perfect hash algorithm,its key index and the principle of c=
ompression algorithm is out of the ordinary,the most important is a complet=
ely different structure,so the key index compression is fundamentally diff=
erent.The most direct benefit for program is that for the original map need=
ten servers for solutions but now I only need one server.
Declare: the code can not be used for commercial purposes, if for commercia=
l applications,you can contact me with QQ 75293192.

First,modern warfare can't be without the mass of information query, if the=
query of enemy target information slows down a second, it could lead to th=
e delaying fighter, leading to failure of the entire war. Information retri=
eval is inseparable from the map, if military products use pwwhashMap inste=
ad of the traditional map,you must be the winner.

Scond,the performance of the router determines the surfing speed, just repl=
ace open source router code map for pwwHashMap, its speed can increase ten =
There are many tables to query and set in the router DHCP ptotocol,such as =
IP,Mac ,and all these are completed by map.But until now,all map are using=
STL liabrary,its performance is very low,and using the Hash map has error =
probability,so it can only use multi router packet dispersion treatment.If =
using pwwHashMap, you can save at least ten sets of equipment.

Third,Hadoop is recognized as the big data solutions at present,and its mos=
t fundamental thing is super heavy use of the map,instead of SQL and table.=
Hadoop assumes the huge amounts of data so that the data is completely unab=
le to move, people must carry on the data analysis in the local.But as long=
as the open source Hadoop code of the map changes into pwwHashMap, the per=
formance will increase hundredfold without any problems.

Background to this article that may be useful such as an introduction to th=
e basic ideas presented:

1 réponse

Wenwei Peng
Title: The core of the big data solutions -- Map.
Author: pengwenwei
Language: c++
Platform: Windows, linux
Technology: Perfect hash algorithm
Level: Advanced
Description: A high performance map algorithm
Section MFC c++ map stl
SubSection c++ algorithm
License: (GPLv3)

Map is widely used in c++ programs. Its performance is critical to programs ' performance. Especially in big data and the scenarios which can't realiz e data distribution and parallel processing.

I have been working on big data analysis for many years in telecommunition and information security industry. The data analysis is so complicated that they can't work without map. Especially in information security industry, the data is much more complicated than others. For example, ip table, mac t able, telephone numbers table, dns table etc.

Currently, the STL map and Google's hash map are the most popular maps. But they have some disadvantages. The STL map is based on binary chop, which c auses a bad performance. Google Hash map has the best performance at presen t, but it has probability of collision. For big data analysis, the collisio n probability is unacceptable.

Now I would like to publish pwwMap. It includes three different maps for di fferent scenarios:
1. Memory Map(memMap): It has a good access speed. But its size is limited by memory size.
2. Harddisk Map(diskMap): It utilizes hard disk to store data. So it could accept much more data than memory map.
3. Hashmap(hashMap): It has the best performance and a great lookup speed, but it doesn't have 'insert' and 'delete' functionality.

MemMap and diskMap could be converted to hashMap by function memMap2HashMap and diskMap2HashMap. According to the test result, my algorithms' collisio n probability is zero. About performance, memMap has a comparable performan ce with google, and hashMap's performance is 100 times better than Google's hashmap.

In summary, pwwhash are perfect hash algorithms with zero collision probabi lity. You can refer to following artical to find the key index and compress algorithm theory:

Source code and documents: