Search 大数据, 63 result(s) found

Collect Hadoop 1.0.0

Research on data source The project includes these modules: Hadoop Common: The common utilities that support the other Hadoop modules. Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data....

k-means java实现 Iris四大数据

通过优化的k-means算法 采用了密度和优化评测函数实现了对Iris等数据集的聚类。 ...

Big storm required of a data-processing tools the latest version

Storm can be very reliable for handling huge data stream to process bulk data in Hadoop. Storm is very simple, supports many programming languages. Is the processing of large data's right-hand man....

Data processing tools enhance performance on the General map

Modify the General map, map upgrade for c++ programs to use everywhere. Affect the performance of application performance bottlenecks are often the map. Especially in case of large data and tie closely to business associate could not be implemented for distributed and parallel processing of data. Ma...

BCH of large quantities of data coding

This is a BCH coded program, previously seen are small amounts of data in less loops, the loop statement is used, so it solves the problem of large amount of data. When using only the data you want to import into it is completely OK, do not believe you can have a try....

GDAL data images

The code can handle large image data via GDAL can read a wide variety of data formats, and can be used in remote sensing image processing available for your reference....

Big data read and write

For large data, read and write large files quickly, minimize memory consumption, increase efficiency, save time, and compatibility of data, classification can extract data from large files, and displays and comprehensive analysis....

Information on Hadoop

Hadoop Map Reduce can provide a better understanding of the content, and explain how to install a Hadoop, how to configure Hadoop and Linux environments, such as SSH, and Hadoop in data processing applications, such as....

Data processing of frequent itemsets

Achieving goals ( 1 ), Each user downloads movies collection is considered to be a shopping basket ( 2 )求 k=2 Frequent itemsets, and support is given We adopt Apriori algorithm Apriori algorithm Uses a bottom-up approach, from the 1- Frequent start, gradually find out high frequency set...

Big data processing: Data clustering

Enables users of movie data k-means Clustering gives an optimum number of clustering. Using k-means algorithm realization for clustering large data, get the best number of clusters. K-means algorithm is typical of a distance-based clustering algorithm using evaluation as a similarity index, whi...

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