大数据考试代考 Big Data代写 数据集代写 大数据代写
775Big Data 大数据考试代考 1. (a) A HDFS client reading data from a file on HDFS: a. Receives all file data through the NameNode a. Receives all file data through the NameNode 1. (a...
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大数据作业代写 Question 1 20 Marks A. Outline the steps that a read request goes through, starting when a client opens a file on HDFS (given a pathname)
A. Outline the steps that a read request goes through, starting when a client opens a file on HDFS (given a pathname). And ending when the requested data is in the client’s memory buffer. Also explain what happens if there is a network error in the process. [10 marks]
B. Explain how the in-memory filesystem image is restored to full working order when a HDFS NameNode starts up after a reboot. [10 marks]
A. You are given a large unlabelled directed graph stored in a text file, in which each line contains two numbers:
<Source node ID> <Target node ID>
That is, each line represents a directed edge in the graph (assume that each edge appears only once in the file). You are requested to design a MapReduce job to output all unique node IDs and the number of edges pointing to each of them (in-links/in-edges); that is, the output should contain one line per node, formatted like so:
<Node ID> <Number of in-links>
Define what your job would do to accomplish the above; that is, define what is the format of the key-value pairs at both the input and output of your mappers and reducers, as well as the kind of processing that goes on at the mappers/reducers.
How would your design change if you were requested to output the above information but only for those nodes with the top-k largest number of in-edges, for relatively small values of k?
While designing your jobs try to minimize disk I/O and network bandwidth utilisation. You don’t need to write code or pseudocode. But feel free to do so if it makes your explanation easier or clearer. [18 marks total: 9 marks for the first job, 9 marks for the second (top-k) job]
B. Briefly explain what happens after a mapper emits a key-value pair and until that key-value pair ends up in a reducer function’s input. [14 marks]
A. All NoSQL stores covered in the course are designed for high write throughput. Explain what mechanisms are in place to accomplish this design goal while achieving durability and briefly discuss the related trade-offs for read and write operations. [10 marks]
B.Explain the on-disk storage format of a row with multiple columns/attributes and multiple versions per column/attribute in a NoSQL store such as HBase. [5 marks]
C. List the consistency levels supported by Cassandra for single-datacentre deployments and briefly explain their behaviour for read and write operations. [8 marks]
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Big Data 大数据考试代考 1. (a) A HDFS client reading data from a file on HDFS: a. Receives all file data through the NameNode a. Receives all file data through the NameNode 1. (a...
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