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Which of the following describes a benefit of creating an external table from Parquet rather than CSV when using a CREATE TABLE AS SELECT statement?
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KKeng
A
Parquet files can be partitioned
B
CREATE TABLE AS SELECT statements cannot be used on files
C
Parquet files have a well-defined schema
D
Parquet files have the ability to be optimized
E
Parquet files will become Delta tables
Explanation:
Explanation:
Parquet files have a well-defined schema that is embedded within the file format itself, unlike CSV files which are schema-less and require schema inference or explicit schema definition. This is a key benefit when using CREATE TABLE AS SELECT (CTAS) statements because:
- Schema Preservation: Parquet files store schema metadata (column names, data types) directly in the file, ensuring data integrity and consistency.
- No Schema Inference Issues: With CSV files, Spark must infer the schema by scanning the data, which can lead to errors (e.g., incorrect data type detection, null value handling issues).
- Better Performance: Parquet's columnar format with embedded schema allows for more efficient data processing and querying.
- Data Type Support: Parquet supports complex data types (arrays, structs, maps) that CSV cannot natively represent.
While options A and D are also true about Parquet files (they can be partitioned and optimized), the most direct benefit specifically for CTAS operations is the well-defined schema, which eliminates schema-related issues that commonly occur with CSV files.
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