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The Research and Practice of Performance Optimization Based on Hive
Author: YeWenZuo
Tutor: ZhengTao
School: Nanjing University
Course: Engineering
Keywords: Large - scale data processing Parallel computing Distributed computing systems HDFS HADOOP Hive Optimization
CLC: TP311.13
Type: Master's thesis
Year: 2011
Downloads: 367
Quote: 2
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Abstract
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With the dramatic growth of the rapid expansion of the market of network information processing and information processing amount of data , the distributed computing processing technology for large-scale and ultra large scale data engineering research topic attracting much attention . , Engineering research and development community is generally concerned about the Hadoop technology can be widely used in the Internet field , domestic universities and research institutes Hadoop data storage , resource management , job scheduling , performance optimization , high availability and security features conducting in-depth analysis . In this paper, the demand for Taobao e-commerce systems , storage processing transaction data and applications , system Hadoop - based data warehouse infrastructure - Hive performance optimization method . This paper first gives the definition of the the Hadoop system calculates characteristics , Hadoop Map / Reduce task allocation and file storage system HDFS . Divided into three levels to achieve the purpose of tuning leads to executable optimization method by introducing the analysis of the underlying parameters and change the value of parameters to achieve the effect . Describe and analyze the similarities and differences of a common database with distributed data processing based on the the the Hadoop system infrastructure Hive SQL-like language HQL . Typical code case , expounded the Hive 's logical characteristics , leads to the corresponding optimization direction and parameter adjustment program , respectively, from the data type of problem to solve data tilt problem with the internal optimizations to reduce the Job , combined with Taobao data demand characteristics such as a few aspects , modify the code script optimization data . The measured data show that the optimization algorithm has achieved good results .
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