What are the best use cases for Parquet?
Parquet is ideal for big data processing, especially in analytics and data warehousing. It excels in scenarios where you need efficient storage and fast query performance.
Can you give me some specific examples?
Sure! Parquet is commonly used in data lakes, ETL processes, and with frameworks like Apache Spark and Hive for analytics.
Why is Parquet preferred over other formats?
Parquet's columnar storage format allows for better compression and encoding schemes, which leads to reduced storage costs and improved query performance.
Are there any limitations to using Parquet?
Yes, while Parquet is great for analytical workloads, it may not be the best choice for transactional systems where row-level operations are frequent.
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