Which is better for data storage: Parquet or ORC?
Both Parquet and ORC are columnar storage formats optimized for big data processing. Parquet is often preferred for its compatibility with various data processing frameworks, while ORC is optimized for Hive and offers better compression.
What are the main differences in compression between the two?
Parquet generally provides better compression ratios due to its use of various encoding techniques, while ORC also offers efficient compression but is more tailored for Hive's ecosystem.
Can you give me examples of use cases for each format?
Sure! Parquet is commonly used in data lakes and analytics platforms like Apache Spark, while ORC is often used in Hive for data warehousing solutions.
Is one format faster than the other for querying?
It depends on the query patterns and the tools used. Parquet may perform better with complex queries in Spark, while ORC can be faster for simple queries in Hive.
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