11 Questions
Which of the following is a primary characteristic of Big Data?
Variety
Which one of the following is a component of Hadoop?
YARN
What is the query language commonly used with Apache Hive for Big Data processing?
SQL
Which of the following accurately describes Hive?
A distributed file system
What is a benefit of using Apache Parquet for storing structured data?
Supports complex data types efficiently
Which feature is NOT typically associated with Apache Hive?
Real-time processing capabilities
What makes Apache HBase a valuable component in the Hadoop ecosystem?
Real-time random read/write access to big data
Which data format is NOT commonly used for storing data in Hadoop?
Protocol Buffers
Which is NOT a characteristic of PySpark?
Real-time processing
Which machine learning task is NOT commonly performed using PySpark?
Genome sequencing
Which is a benefit of using Hive in the Hadoop ecosystem?
High-level SQL-like interface
Study Notes
Big Data Characteristics
- One primary characteristic of Big Data is its massive scale and complexity.
Hadoop Components
- HDFS (Hadoop Distributed File System) is a component of Hadoop.
Apache Hive
- Hive uses HiveQL (Hive Query Language) for Big Data processing.
- Hive is a data warehousing and SQL-like query language for Hadoop.
- A benefit of using Hive in the Hadoop ecosystem is that it provides a way to process and analyze large datasets using familiar SQL-like queries.
- Hive is NOT typically associated with real-time data processing.
Apache Parquet
- A benefit of using Apache Parquet for storing structured data is that it provides efficient storage and querying of data.
Hadoop Data Formats
- AVRO is NOT commonly used for storing data in Hadoop.
Apache HBase
- Apache HBase is a valuable component in the Hadoop ecosystem because it provides a distributed, column-oriented NoSQL database for storing large amounts of semi-structured and structured data.
PySpark
- PySpark is NOT characterized by its use for real-time data processing.
- PySpark is NOT commonly used for machine learning tasks such as decision trees.
Machine Learning Tasks
- PySpark is commonly used for machine learning tasks such as clustering and regression analysis.
Test your knowledge on Big Data with these multiple choice questions covering topics like defining Big Data and its characteristics. Each question comes with options A, B, C, D and explanations for the correct answers.
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