Apache Parquet Data
Data & ScienceParquet is typed binary column-oriented storage, unlike plain CSV. It can represent nested structures. Multiple files may form a partitioned dataset; establish the dataset layout rather than assuming one file contains every row.
- What it is used for
- Typed column-oriented storage for analytics
- What the file contains
- Binary data
All sections, questions and sources
Content reviewed： · Editor：Kai
Opening steps
Choose your environment or purpose to see its steps.
Menu labels and support vary by app, OS and version. Preserve the original before making changes.
Troubleshooting by symptom
- Spreadsheet cannot open it: use compatible tools and export the needed subset.
- Missing rows: inspect partitions, file sets and filters.
- Changed times/numbers: check zones, integer widths, decimal precision and nulls.
- Too few rows: inspect the remaining partitions.
- Memory exhaustion: use required columns, row groups or batches.
- CSV alters IDs/times: inspect types, precision and timezone handling.
Parquet → CSV / Arrow
- Record the subset/schema and define how nested columns become a table.
- Compare counts, types, nulls and sample values; retain originals.
- Compare counts, types, time precision and partition scope.
CSV may lose types, nesting and metadata; full expansion may require substantially more memory than compressed size.
Use columnar access to start small
Inspect metadata first and select only required columns/ranges.
Compressed size does not equal memory usage; account for strings and nested data.
Source for these steps：Apache Software Foundation · Apache Parquet Documentation / Apache Arrow Project · Reading and Writing Apache Parquet
Validate the complete dataset
A partial folder copy can be readable but incomplete; record scope and counts.
Compare dates, nulls, duplicate IDs and types at the destination.
Source for these steps：Apache Software Foundation · Apache Parquet Documentation / Apache Arrow Project · Reading and Writing Apache Parquet
Related-format differences
| Format | Main role | What to check |
|---|---|---|
| Parquet | Columnar storage | Schema/partitions |
| Arrow IPC | Batch data interchange | File/stream framing |
| CSV | Text table | Types require separate documentation |
Handling and security
Review personal/sensitive fields; avoid blindly loading huge unknown datasets and inspect copies with maintained tools.
Questions and answers
Is it renamed CSV?
No; its binary structure differs.
Does one file contain everything?
It may be one dataset partition.
Will spreadsheet export preserve types?
Validate precision, timestamps and nesting.
Is Parquet a zipped spreadsheet?
A compatible columnar reader handles internal compression.
Why is a partition column absent from one file?
Some datasets derive partition fields from directories; compare file and dataset reads.
Format facts: name, steward and MIME type
- Formal name
- Apache Parquet
- Steward / specification
- Apache Software Foundation
- MIME type
- Depends on the producer or server; an extension alone does not establish a MIME type.
Primary and official sources
- Project documentationApache Parquet Documentation
Documentation for column-oriented storage and Parquet format.
Apache Software Foundation · Link checked： - Official documentationReading and Writing Apache Parquet
Schemas, selected columns and multi-file datasets.
Apache Arrow Project · Link checked：