COMP9313: Big Data Management Course web site: http://www.cse.unsw.edu.au/~cs9313/ Chapter 1.2 Introduction to HDFS, YARN, and MapReduce Part 1: HDFS File System ❖ A filesystem is the methods and data structures that an operating system uses to keep track of files on a disk or partition; that is, the way the files are organized on the […]
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Question 1. (4 marks) Based on your own experience of using Apache Pig and Apache Spark in this subject, briefly explain (i) the similarity of data processing between Apache Pig and Apache Spark, and (ii) the advantages of Apache Spark over Apache Pig. Question 2. (4 marks) A table named X contains a column of
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Cloud and Big Data IBM Research Course Objective Copyright By PowCoder代写 加微信 powcoder § Graduate level course on Cloud Computing – Focus is on learning how to design, build, deploy and manage extremely large scale systems and applications leveraging Cloud – Building blocks and design patterns in designing backend of typical Internet Scale application –
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Introduction to Big Data with Apache Spark UC BERKELEY This Lecture Copyright By PowCoder代写 加微信 powcoder Programming Distributed Datasets (RDDs) Creating an RDD Spark Transformations and Actions Model Python Spark (pySpark) We are using the Python programming interface to Spark (pySpark) pySpark provides an easy-to-use programming abstraction and parallel runtime: » “Here’s an operation, run
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Cloud Computing INFS3208/INFS7208 Re-cap – Lecture 7 • Database Background • Relational Data Bases – Revisit Relational DBs – ACID Properties * – Clustered RDBMs • Non-relational Data Bases – NoSQL concepts – CAP Theorem *** – MongoDB – Cassandra – HBase CRICOS code 00025B 2 Outline • Background of Distributed File Systems – Big
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Cloud Computing INFS3208 Updates CRICOS code 00025B 2 Cloud Computing INFS3208 Outline • Apache Spark and its Characteristics • Resilient Distributed Dataset (RDD) • RDD Operations – Transform & Action • Lazy evaluation and RDD Lineage graph • Terms in Spark • Narrow and Wide Dependencies • How Spark works CRICOS code 00025B 3 Cloud
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Cloud Computing INFS3208 Background – Big Data Era • “Big Data” has been in use since 1990s. • Data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. • Reasons of Big Data: – – – Hardware development: Storage (more cheaper),
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Recap – Course Structure This course includes 13 lectures and 10 tutorial/practical sessions Lecture 1 Introduction Lecture 2 Adv. topics&appl Lecture 3 Networks & Load Balancing Concepts Orchestration Storage Computation Others Programming and Linux experiences required! Lecture 4 VT: Docker I Lecture 5 VT: Docker II Lecture 6 VT: Docker III Lecture 7 DBs in
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Graph Anomaly Detection COMP90073 Security Analytics , CIS Semester 2, 2021 Outline • Whygraphs? • Extractingfeaturesfromgraphs • Randomwalk • GraphConvolutionalNetworks(GCNs) COMP90073 Security Analytics © University of Melbourne 2021 All Real-world Data Does Not “Live” on Grid Internet IoT networks COMP90073 Security Analytics © University of Melbourne 2021 Outliers vs. Graph Anomalies • Anomaliesanswerthequestionofwhatisinterestingaboutanetwork • Cannotalwaysbetreatedaspointslyinginamulti-dimensionalspace
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ECS 20 Discrete Math: Discussion 3, Mon 10/14/2013 To express a Boolean expression in CNF from a truth table, for example 𝐴𝐵𝑋 000 011 100 111 Write an equation in terms of what 𝑋 cannot be using the 0-rows. In this example 𝑋 cannot be 𝐴̅𝐵̅ and it cannot be 𝐴𝐵̅: ̅̅̅̅̅̅̅ ̅̅̅̅̅̅̅ 𝑋 =
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