Kyuseok Shim, MapReduce Algorithms for Big Data Analysis, DNIS 2013, LNCS 7813, pp. 44-48, 2013.Kyuseok Shim, "MapReduce Algorithms for Big Data Analysis", 2013, LNCS 7813, pp. 44-48.MapReduce Algorithms for Big Data Analysis. Kyuseok Shim. Proceedings of 8th International Workshop ...
[9] AMIRI F,YAZDANI N,SHAKERY A,et al.Hierarchical anonymization algorithms against background knowledge attack in data releasing[J].Knowledge-Based Systems,2016,101(c):71-89. [10] ZHANG X,DOU W,PEI J,et al.Proximity-aware local-recoding anonymization with MapReduce for scalable big data ...
The finding acknowledges that the traditional mining algorithms have not progressed to support big data analysis as required by current retail businesses owners. The job of finding unknown association rules from big data requires a lot of resources such as memory and processing engines. Moreover, ...
6. Problems Suited for MapReduce Host Size, Link analysis and graph processing, ML algorithms MapReduce Join Use a hash function ℎ from B-values to 1⋯𝑘 A Map process turns: Each input tuple 𝑅(𝑎,𝑏) into key-value pair (𝑏, (𝑎,𝑅)) Each input tuple 𝑆(𝑏,...
kafka spark hive hadoop bigdata kudu hbase olap hdfs mapreduce flink debezium bigdatalearning hudi Updated Nov 14, 2024 Shell mahmoudparsian / data-algorithms-book Star 1.1k Code Issues Pull requests MapReduce, Spark, Java, and Scala for Data Algorithms Book python java machine-learning...
Mapreduce: simplified data processing on large clusters Commun. ACM (2008) K. Shim, Mapreduce algorithms for big data analysis, in: Proceedings of the VLDB Endowment, vol. 5(12), 2012, pp... T. White Hadoop: the definitive guide (2012) There are more references available in the full...
In this article I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found on the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s Map...
Big Data for Supply Chain Management Big Data in Government In today's data-driven market, algorithms and applications are collecting data 24/7 about people, processes, systems, and organizations, resulting in huge volumes of data. The challenge, though, is how to process this massive amount of...
In this article I digested a number of MapReduce patterns and algorithms to give a systematic view of the different techniques that can be found on the web or scientific articles. Several practical case studies are also provided. All descriptions and code snippets use the standard Hadoop’s Map...
algorithms), scientific modeling or other predictive technologies (such as NN, NB, roughset, DT), decision analysis technologies (such as multicriteria decision, gray decision, and so on), performance assessment technologies (for example, fuzzy comprehensive evaluation and data envelopment analyses). ...