Explain how the hadoop system deals with datanode failures

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Reference no: EM131207919

1. Assume you have 3 documents with the following terms:

• D1 = "computer", "web", "storage", "options"
• D2 = "computer", "game", "development"
• D3 = "web", "development", "frameworks"

If the query Q is composed of terms "computer" and "development", what is the relevance of each document to the query using the TF.IDF measure?

2. Explain in detail how the Hadoop system deals with DataNode failures.

3. Explain and write the pseudocode for a Mapper/Reducer that takes as input a large file (possibly split into chucks) of integers and outputs:

a. The sum of the squares of each integer
b. The maximum integer

4. Explain in detail why MapReduce may be a better solution than OLAP for some problems. Provide concrete examples.

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The solution file is prepared in ms word which answered all questions related to data mining and machine learning. The topics covered in this are Mapper/Reducer,queries using SQL,Jaccard similarities,3-shingles,signature matrix,column/column and signature/signature similarities,hierarchical clustering,k--means algorithm and Euclidean distance,A-Priori Algorithm,triangular matrix to count pairs,Orange Canvas data mining software,k-Nearest Neighbor algorithm to classify the test data,Compute the confusion matrix, accuracy, precision, recall, and F1 measures and use WEKA data mining toolkit to analysis the data.

Reference no: EM131207919

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