Which distributed computing framework is known for its ability to handle real-time stream processing and complex event processing (CEP)?
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Data Science · all questionsBig Data and Distributed Computing
Big Data and Distributed Computing
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What is the primary advantage of using Apache Kafka in a big data architecture?
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In distributed computing, what is the purpose of a "Reducer" in the MapReduce programming model?
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Which distributed computing framework is designed for processing large-scale graph data, such as social networks or network analysis?
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What is the primary goal of shuffling and sorting in the MapReduce programming model?
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In the context of big data processing, what does the term "ETL" stand for?
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What is the primary role of a "Name Node" in the Hadoop Distributed File System (HDFS)?
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Which distributed computing framework is known for its support of graph algorithms and is often used for analyzing large-scale graph data?
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In big data analytics, what is the primary challenge associated with "data silos"?
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What is the primary purpose of a "Mapper" in the MapReduce programming model?
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What is the primary advantage of using data compression techniques in big data storage and processing?
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In the context of big data, what does the term "data skew" refer to?
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Which Apache project provides a real-time stream processing framework for handling and analyzing data streams in real-time?
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What is the primary benefit of using a columnar storage format like Parquet in big data analytics?
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In the context of big data, what is the purpose of "data sampling"?
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Which distributed computing framework is commonly used for batch processing of large datasets and is often associated with Hadoop?
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What is the primary purpose of "data replication" in a distributed computing environment?
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In big data analytics, what is the term for the process of transforming and preparing raw data for analysis, often involving cleaning and structuring the data?
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What does the term "YARN" stand for in the context of Hadoop and distributed computing?
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Which technology is commonly used for streamlining the data velocity aspect of big data, allowing for real-time data collection and analysis?
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