The C Preprocessor Object Code Files • the C compiler can produce an object code version of a .c file that is machine language but not linked with other parts of your program Copyright By PowCoder代写 加微信 powcoder • these object code files end in .o Compiling multi-file programs Source code Name.c Declarations Name.h Assembly […]
COMP90015 Distributed Systems Indirect Communication School of Computing and Information Systems © The University of Melbourne Copyright By PowCoder代写 加微信 powcoder 2022 Semester II (School of Computing and InformaCtiOonMSPy9s0te0m15s ©DistTrihbeutUednivSeyrsstietymos f Melbourne) 2022 Semester II 1 Message Queues 2 Group Communication 3 Publish/Subscribe 4 Distributed Shared Memory Tuple Spaces 5 Comparison (School of Computing and
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Chapter 2.2: MapReduce II Overview of Previous Lecture ❖ Motivation of MapReduce ❖ Data Structures in MapReduce: (key, value) pairs ❖ Hadoop MapReduce Programming Output pairs do not need to be of the same types as input pairs. A given input pair may map to zero
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This exercise aims to get you to: • Analyze data using Spark shell • Monitor Spark tasks using Web UI Background The detailed Spark programming guide is available at: http://spark.apache.org/docs/latest/programming-guide.html The transformation and action functions examples are available at: http://homepage.cs.latrobe.edu.au/zhe/ZhenHeSparkRDDAPIExamples.html A tutorial of Scala 2 is available at: http://docs.scala-lang.org/tutorials/?_ga=1.99469143.850382266.1473265612 The answers to the questions are
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This exercise aims to get you to: • Compile, run, and debug MapReduce tasks via Command Line • Compile, run, and debug MapReduce tasks via Eclipse • Apply the design pattern “in-mapper combining” you have learned in Chapter 2.2 to MapReduce programming One Tip on Hadoop File System Shell Following are the three commands which
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ : NoSQL and HBase Part 1: Introduction to NoSQL What does RDBMS provide? ❖ Relational model with schemas ❖ Powerful, flexible query language (SQL) ❖ Transactional semantics: ACID ❖ Rich ecosystem, lots of tool support (MySQL, PostgreSQL, etc.) What is NoSQL? ❖ The name stands for Not
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Chapter 4.2: I Download and Configure Spark ❖ Current version: 3.1.2. https://spark.apache.org/downloads.html ➢ You also need to install Java first ❖ After downloading the package, unpack it and then configure the path variable in file ~/.bashrc export SPARK_HOME=/home/comp9313/workdir/spark export PATH=$SPARK_HOME/bin:$PATH ❖ Spark comes with four widely used
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Mining Data Streams II : Filtering Data Streams Filtering Data Streams ❖ Each element of data stream is a tuple ❖ Given a list of keys S ❖ Determine which tuples of stream are in S ❖ Obvious solution: Hash table ➢ But suppose we do not
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Chapter 4.1: Part 1: ntroduction Limitations of MapReduce ❖ MapReduce greatly simplified big data analysis on large, unreliable clusters. It is great at one-pass computation. ❖ But as soon as it got popular, users wanted more: ➢ More complex, multi-pass analytics (e.g. ML, graph) ➢ More interactive
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COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Chapter 1: Course Information and Introduction to Big Data Management Part 1: Course Information Course Info ❖ Lectures: 10:00 – 12:00 (Tuesday) and 14:00 – 16:00 (Thursday) ➢ Purely online (access through Moodle) ❖ Labs: Weeks 2-10 ❖ Consultation (Weeks 1-10): Questions regarding lectures, course materials, assignements,
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