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a. A Sequence File contains a binary encoding of an arbitrary number of homogeneous writable objects. b. A Sequence File contains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be of same type. c. A Sequence File contains a binary encoding of an arbitrary number of heterogeneous writeable objects. d. A Sequence File contains a binary encoding of an arbitrary number of Writable Comparable objects, in sorted order.
Ans. A Sequence File contains a binary encoding of an arbitrary number key-value pairs. Each key must be the same type. Each value must be of same type.
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a. One Key and One Value b. Multiple Keys and Multiple associated Values c. Multiple Keys and One associated values with each d. One key and associated values.
Ans. One key and associated values.
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LikeDiscussCorrect / Improve  hadoop   bigdata   big data   map-reduce   map reduce   reduce function
Q11. Which of the following is the implementation language for Map Reduce Framework ?
a. Big Data b. Hadoop c. Java d. C++
Ans. Java
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LikeDiscussCorrect / Improve  hadoop   bigdata   big data   map-reduce   map reduce framework
Q12. What are the two main components of Hadoop System ?
Ans. Hadoop is an open source framework , written in java by apche software foundation. This framework is used to write applications to process vast amount of data. Processing happens in parallel on large clusters which could have 1000 of computers. It processes data in a very reliable and fault tolerant manner.
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Ans. Combiners are used to increase the efficiency of a Map Reduce program. They are used to aggregate intermediate map output locally on individual mapper outputs. Combiners can help you reduce the amount of data that needs to be transferred across to the reducers.
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It supports only MapReduce (MR) processing model.
It has limited scaling of nodes. Limited to 4000 nodes per cluster.
It has single Namenode to manage the entire namespace.
It has Single-Point-of-Failure (SPOF)
Works on concepts of slots – slots can run either a Map task or a Reduce task
MR has to do both processing and cluster resource management.
Hadoop 2.x
It supports MR as well as other distributed computing models like Spark, Hama, etc
It has better scalability. Scalable up to 10000 nodes per cluster.
Works on concepts of containers. Using containers can run generic tasks.
It has Multiple Namenode servers manage multiple namespace.
YARN does cluster resource management and processing is done using different processing models.
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