Databricks Certified Data Engineer - Professional
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Explain the concept of data skew in PySpark and its impact on performance. Discuss strategies to detect and mitigate data skew in your data processing jobs.
A
Data skew occurs when data is unevenly distributed across partitions, leading to inefficient resource utilization and slower processing times.
B
Data skew is not a concern in PySpark as the framework automatically balances data across partitions.
C
Data skew only affects storage and has no impact on processing performance.
D
Data skew can be mitigated by always using the default number of partitions, which ensures even data distribution.