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When optimizing data storage and query performance in Databricks by selecting a partition column, which of the following considerations is most important?
When optimizing data storage and query performance in Databricks by selecting a partition column, which of the following considerations is most important?
Real Exam
Explanation:
Choosing a column with low cardinality that evenly distributes data is correct because it ensures efficient storage and query performance through effective partition pruning. High cardinality columns can lead to uneven distribution and increased overhead. Frequent updates to a partition column can reduce the effectiveness of partition pruning. Complex data types complicate partitioning and query performance. Using an unrelated column for partitioning does not improve efficiency and may lead to confusion.