Why would I convert Parquet to CSV?

Common reasons include: sharing data with users who don't have Parquet tools, importing data into systems that only support CSV, creating human-readable versions of data for inspection, or working with tools that require CSV input.

How does the converter handle complex Parquet schemas?

Our converter flattens nested structures in Parquet using dot notation for field names. For array types, we provide options to either expand arrays into multiple columns or serialize them as JSON strings within CSV cells.

Will I lose data when converting from Parquet to CSV?

While all data values are preserved, some metadata and type information may be lost since CSV has a simpler type system than Parquet. Our converter provides options to include type information in a separate metadata file if needed.

Convert Parquet to CSV

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Parquet

Parquet is a columnar storage file format designed for efficiency with big data processing frameworks like Apache Hadoop and Spark.

Technical Details

Parquet organizes data by columns rather than rows, which enables better compression and more efficient queries for analytical workloads. It supports nested data structures and is optimized for handling complex data.

Advantages

Highly efficient columnar storage and compression
Excellent query performance for analytical workloads
Support for nested data structures
Schema evolution capabilities

Limitations

Not human-readable like CSV or JSON
Less suitable for row-oriented operations
Requires specialized tools for viewing and editing
More complex than simpler formats

CSV

CSV (Comma-Separated Values) is a simple format for storing tabular data in plain text. Each row is a data record, and columns are separated by commas (or other delimiters).

Technical Details

CSV files represent data in a flat table structure. The first row typically contains column headers, and each subsequent row contains values. Fields containing commas, newlines, or quotes may be enclosed in double quotes.