Hadoop Mahout MCQs
This section focuses on "Mahout" in Hadoop. These Multiple Choice Questions (MCQ) should be practiced to improve the hadoop skills required for various interviews (campus interviews, walk-in interviews, company interviews), placements, entrance exams and other competitive examinations.
1. Which of the following is true about mahout?
Explanation: All the above statement is true.
2. In which year Apache Mahout started?
Explanation: Apache Mahout started as a sub-project of Apache's Lucene in 2008.
3. Mahout provides ____________ libraries for common and primitive Java collections.
Explanation: Maths operations are focused on linear algebra and statistics.
4. Which of the following is not a features of Mahout?
Explanation: All of the above is feature of Mahout.
5. Mahout provides an implementation of a ______________ identification algorithm which scores collocations using log-likelihood ratio.
Explanation: The log-likelihood score indicates the relative usefulness of a collocation with regards other term combinations in the text.
6. Point out the wrong statement.
Explanation: There are a couple ways to run the llr-based collocation algorithm in mahout.
7. ____________ generates NGrams and counts frequencies for ngrams, head and tail subgrams.
Explanation: Each call to the mapper passes in the full set of tokens for the corresponding document using a StringTuple.
8. ________ phase merges the counts for unique ngrams or ngram fragments across multiple documents.
Explanation: The combiner treats the entire GramKey as the key and as such, identical tuples from separate documents are passed into a single call to the combiner's reduce method, their frequencies are summed and a single tuple is passed out via the collector.
9. How many classification does Naive Bayes Classifier have?
Explanation: Mahout uses the Naive Bayes classifier algorithm. It uses two implementations: Distributed Naive Bayes classification and Complementary Naive Bayes classification
10. How many algorithms mahout supports for clustering?
Explanation: Mahout supports two main algorithms for clustering namely: Canopy clustering and K-means clustering