Podcast
Questions and Answers
Which of the following is a primary characteristic of Big Data?
Which of the following is a primary characteristic of Big Data?
- Validity
- Variety (correct)
- Velocity
- Volume
Which one of the following is a component of Hadoop?
Which one of the following is a component of Hadoop?
- MongoDB
- SQL
- HDFS
- YARN (correct)
What is the query language commonly used with Apache Hive for Big Data processing?
What is the query language commonly used with Apache Hive for Big Data processing?
- HiveQL
- SQL (correct)
- NoSQL
- Python
Which of the following accurately describes Hive?
Which of the following accurately describes Hive?
What is a benefit of using Apache Parquet for storing structured data?
What is a benefit of using Apache Parquet for storing structured data?
Which feature is NOT typically associated with Apache Hive?
Which feature is NOT typically associated with Apache Hive?
What makes Apache HBase a valuable component in the Hadoop ecosystem?
What makes Apache HBase a valuable component in the Hadoop ecosystem?
Which data format is NOT commonly used for storing data in Hadoop?
Which data format is NOT commonly used for storing data in Hadoop?
Which is NOT a characteristic of PySpark?
Which is NOT a characteristic of PySpark?
Which machine learning task is NOT commonly performed using PySpark?
Which machine learning task is NOT commonly performed using PySpark?
Which is a benefit of using Hive in the Hadoop ecosystem?
Which is a benefit of using Hive in the Hadoop ecosystem?
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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.
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