PySpark
What are the main disadvantages of PySpark for data processing?
Answer:
The main disadvantages of using PySpark are higher latency for small-scale tasks, which can reduce performance for lightweight jobs, and a steeper learning curve compared with simpler Python tools. It also requires JVM-based infrastructure, increasing dependence on external systems.
Related PySpark Questions And Answers
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- PySpark vs Scala Spark: which is better for Spark teams?
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- PySpark vs SQL: why is PySpark used for large-scale data processing?
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- PySpark vs Databricks: what is the difference in enterprise data environments?
- PySpark vs Hadoop: which is more efficient for big data analytics?
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