In a scenario where a data scientist prefers Python for Hadoop analytics, which library would be the most suitable for complex data processing tasks?
- Hadoop Streaming
- NumPy
- Pandas
- PySpark
For complex data processing tasks in a Hadoop environment using Python, PySpark is the most suitable library. PySpark provides a Python API for Apache Spark, allowing data scientists to leverage the power of Spark for distributed and parallel processing of large datasets.
Loading...
Related Quiz
- What is a significant challenge in implementing real-time processing in a Hadoop environment?
- How does Crunch optimize the process of creating MapReduce jobs in Hadoop?
- How does the Rack Awareness feature affect the Hadoop cluster's data storage strategy?
- Which Hadoop ecosystem component is utilized for complex data transformation and analysis using a scripting language?
- During a massive data ingestion process, what mechanisms in Hadoop ensure data is not lost in case of system failure?