Questions and Answers
Which component is NOT a part of Hadoop's major components?
What is the query language used by HIVE for processing data?
Which feature distinguishes HIVE from traditional SQL systems?
What programming language does Pig utilize?
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Which of the following functionalities is NOT provided by Mahout?
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How does Avro store the data definition?
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What aspect of machine learning does Mahout facilitate?
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After processing, where does Pig store the results?
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What is the main advantage of the multiple master nodes architecture in Hadoop 2 over Hadoop 1?
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What is a key advantage of using Hadoop in terms of data storage?
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How does Hadoop 2 handle data access compared to traditional RDBMS?
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What is a common expectation regarding server failures in a large distributed system with 1,000 servers?
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Which of the following describes the integrity level of Hadoop compared to traditional RDBMS?
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How does a Distributed File System ensure data reliability?
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What role does HDFS play in the Hadoop ecosystem?
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What is YARN used for in Hadoop 2?
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Which component of Hadoop is responsible for processing large data sets using distributed algorithms?
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What role does the Master Node play in Hadoop’s HDFS?
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What is a notable difference in data schema between Hadoop and traditional RDBMS?
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What is a typical chunk size used in a Distributed File System?
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Which function in MapReduce is responsible for aggregating data?
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Compared to Hadoop 1.0, what significant change was introduced in Hadoop 2.0 regarding data processing?
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What is the primary reason for bringing computation to data in a distributed environment?
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What is the primary function of YARN in the Hadoop system?
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Which of the following is NOT a common Hadoop distribution mentioned?
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How does Apache HBase enhance Hadoop's capabilities?
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Which programming model is commonly associated with Spark and Hadoop?
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Which characteristic is NOT associated with Hadoop?
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What is a key challenge in large-scale computing on commodity hardware as indicated in the context?
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What is a characteristic of typical usage patterns in a Distributed File System?
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What happens to chunks during machine or disk failures in a Reliable Distributed File System?
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What is the primary purpose of the Map() function in MapReduce?
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What is the primary purpose of the MapReduce programming model?
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In the MapReduce process, what does the 'Group by key' step do?
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Which of the following represents a common implementation of MapReduce?
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What is a key function of the MapReduce environment?
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What output does the Mapper produce in the MapReduce model?
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During the Reduce step of MapReduce, what is primarily combined?
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Which of the following statements best describes the Map function in MapReduce?
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What is a common application of the MapReduce model?
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Study Notes
Hadoop Overview
- Hadoop offers cost-effective solutions for managing large-scale data, scaling efficiently to petabytes.
- Provides faster performance by enabling parallel processing of data.
- Effective for specific big data challenges, outperforming traditional database systems.
Key Components of Hadoop
- HDFS (Hadoop Distributed File System): Core component for storing large datasets, organized across nodes while maintaining metadata via logs.
- Apache HBase: A NoSQL database capable of handling diverse data types, similar to Google’s BigTable, optimized for big data operations.
- MapReduce: A programming model for processing large datasets in a distributed manner using two functions, Map() for sorting/filtering, and Reduce() for aggregating results.
- YARN (Yet Another Resource Negotiator): Resource management layer, facilitating the scheduling and allocation of resources across clusters, composed of Resource Manager, Node Manager, and Application Manager.
- Hive: A data warehouse infrastructure for SQL-like querying of large datasets, using Hive Query Language (HQL), supporting real-time and batch processing.
- Pig: Developed by Yahoo, uses Pig Latin language for data flow management, processing large datasets, and executing commands while handling MapReduce operations.
- Mahout: Provides machine learning capabilities, offering tools for clustering, classification, and collaborative filtering based on user patterns and algorithms.
- Avro: Stores data definitions in JSON and the data itself in a binary format for efficiency; designed for compatibility with MapReduce processes.
Hadoop Evolution
- Hadoop 1: Employed a Master-Slave architecture, susceptible to a single point of failure. If the master node failed, the entire cluster became non-operational.
- Hadoop 2: Improved architecture with multiple masters, allowing for redundancy and failover capabilities, enhancing system reliability.
Hadoop Distributions
- Open Source: Apache Hadoop.
- Commercial: Cloudera, Hortonworks, MapR, AWS MapReduce, Microsoft Azure HDInsight.
Comparison: RDBMS vs. Hadoop
- RDBMS: Optimized for gigabytes to terabytes, providing immediate query responses and supporting high data integrity with a static schema.
- Hadoop: Handles data sizes from petabytes to exabytes, capable of batch and real-time processing, featuring dynamic schema and lower data integrity.
Storage and Programming Infrastructure
- Distributed File System: Utilizes chunk servers to split files into manageable chunks (64-128MB), which are replicated for reliability across different machines.
- MapReduce Programming Model: Facilitates easy parallel programming, autonomous hardware failure management, and efficient handling of very large datasets through a three-step process: Map, Group by Key, and Reduce.
Example: Word Counting in MapReduce
- Implements a task to count distinct words in a huge text document, demonstrating the practical applications of analysis on log data and machine translation.
Environment Management in MapReduce
- Automates data partitioning, scheduling, key grouping, managing machine failures, and inter-machine communication for optimal operation.
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Description
This quiz provides insights into the Hadoop ecosystem, focusing on its advantages such as cost-effectiveness, speed, and suitability for big data problems. It also covers companies utilizing Hadoop and forecasts for job market growth in this field.