iparq 0.2.0

Display version compression and bloom filter information about a parquet file

iparq

After reading this blog, I began to wonder which Parquet version and compression methods the everyday tools we rely on actually use, only to find that there’s no straightforward way to determine this. That curiosity and the difficulty of quickly discovering such details motivated me to create iparq (Information Parquet). My goal with iparq is to help users easily identify the specifics of the Parquet files generated by different engines, making it clear which features—like newer encodings or certain compression algorithms—the creator of the parquet is using.

New Bloom filters information: Displays if there are bloom filters. Read more about bloom filters in this great article.

Installation

Zero installation - Recommended

1. Make sure to have Astral’s UV installed by following the steps here:

   https://docs.astral.sh/uv/getting-started/installation/

2. Execute the following command:

   uvx iparq yourparquet.parquet
   

Using pip

1. Install the package using pip:

   pip install iparq
   

2. Verify the installation by running:

   iparq --help
   

Using uv

1. Make sure to have Astral’s UV installed by following the steps here:

   https://docs.astral.sh/uv/getting-started/installation/

2. Execute the following command:

   uv pip install iparq
   

3. Verify the installation by running:

   iparq --help
   

Using Homebrew in a MAC

1. Run the following:

   brew tap MiguelElGallo/tap https://github.com/MiguelElGallo//homebrew-iparq.git
   brew install MiguelElGallo/tap/iparq
   iparq —help
   

Usage

Run

iparq <filename>

Replace <filename> with the path to your .parquet file. The utility will read the metadata of the file and print the compression codecs used in the parquet file.

Example ouput - Bloom Filters

ParquetMetaModel(
    created_by='DuckDB version v1.2.1 (build 8e52ec4395)',
    num_columns=1,
    num_rows=100000000,
    num_row_groups=10,
    format_version='1.0',
    serialized_size=1196
)
Column Compression Info:
Row Group 0:
  Column 'r' (Index 0): SNAPPY
Row Group 1:
  Column 'r' (Index 0): SNAPPY
Row Group 2:
  Column 'r' (Index 0): SNAPPY
Row Group 3:
  Column 'r' (Index 0): SNAPPY
Row Group 4:
  Column 'r' (Index 0): SNAPPY
Row Group 5:
  Column 'r' (Index 0): SNAPPY
Row Group 6:
  Column 'r' (Index 0): SNAPPY
Row Group 7:
  Column 'r' (Index 0): SNAPPY
Row Group 8:
  Column 'r' (Index 0): SNAPPY
Row Group 9:
  Column 'r' (Index 0): SNAPPY
Bloom Filter Info:
Row Group 0:
  Column 'r' (Index 0): Has bloom filter
Row Group 1:
  Column 'r' (Index 0): Has bloom filter
Row Group 2:
  Column 'r' (Index 0): Has bloom filter
Row Group 3:
  Column 'r' (Index 0): Has bloom filter
Row Group 4:
  Column 'r' (Index 0): Has bloom filter
Row Group 5:
  Column 'r' (Index 0): Has bloom filter
Row Group 6:
  Column 'r' (Index 0): Has bloom filter
Row Group 7:
  Column 'r' (Index 0): Has bloom filter
Row Group 8:
  Column 'r' (Index 0): Has bloom filter
Row Group 9:
  Column 'r' (Index 0): Has bloom filter
Compression codecs: {'SNAPPY'}

Example output

ParquetMetaModel(
    created_by='parquet-cpp-arrow version 14.0.2',
    num_columns=19,
    num_rows=2964624,
    num_row_groups=3,
    format_version='2.6',
    serialized_size=6357
)
Column Compression Info:
Row Group 0:
  Column 'VendorID' (Index 0): ZSTD
  Column 'tpep_pickup_datetime' (Index 1): ZSTD
  Column 'tpep_dropoff_datetime' (Index 2): ZSTD
  Column 'passenger_count' (Index 3): ZSTD
  Column 'trip_distance' (Index 4): ZSTD
  Column 'RatecodeID' (Index 5): ZSTD
  Column 'store_and_fwd_flag' (Index 6): ZSTD
  Column 'PULocationID' (Index 7): ZSTD
  Column 'DOLocationID' (Index 8): ZSTD
  Column 'payment_type' (Index 9): ZSTD
  Column 'fare_amount' (Index 10): ZSTD
  Column 'extra' (Index 11): ZSTD
  Column 'mta_tax' (Index 12): ZSTD
  Column 'tip_amount' (Index 13): ZSTD
  Column 'tolls_amount' (Index 14): ZSTD
  Column 'improvement_surcharge' (Index 15): ZSTD
  Column 'total_amount' (Index 16): ZSTD
  Column 'congestion_surcharge' (Index 17): ZSTD
  Column 'Airport_fee' (Index 18): ZSTD
Row Group 1:
  Column 'VendorID' (Index 0): ZSTD
  Column 'tpep_pickup_datetime' (Index 1): ZSTD
  Column 'tpep_dropoff_datetime' (Index 2): ZSTD
  Column 'passenger_count' (Index 3): ZSTD
  Column 'trip_distance' (Index 4): ZSTD
  Column 'RatecodeID' (Index 5): ZSTD
  Column 'store_and_fwd_flag' (Index 6): ZSTD
  Column 'PULocationID' (Index 7): ZSTD
  Column 'DOLocationID' (Index 8): ZSTD
  Column 'payment_type' (Index 9): ZSTD
  Column 'fare_amount' (Index 10): ZSTD
  Column 'extra' (Index 11): ZSTD
  Column 'mta_tax' (Index 12): ZSTD
  Column 'tip_amount' (Index 13): ZSTD
  Column 'tolls_amount' (Index 14): ZSTD
  Column 'improvement_surcharge' (Index 15): ZSTD
  Column 'total_amount' (Index 16): ZSTD
  Column 'congestion_surcharge' (Index 17): ZSTD
  Column 'Airport_fee' (Index 18): ZSTD
Row Group 2:
  Column 'VendorID' (Index 0): ZSTD
  Column 'tpep_pickup_datetime' (Index 1): ZSTD
  Column 'tpep_dropoff_datetime' (Index 2): ZSTD
  Column 'passenger_count' (Index 3): ZSTD
  Column 'trip_distance' (Index 4): ZSTD
  Column 'RatecodeID' (Index 5): ZSTD
  Column 'store_and_fwd_flag' (Index 6): ZSTD
  Column 'PULocationID' (Index 7): ZSTD
  Column 'DOLocationID' (Index 8): ZSTD
  Column 'payment_type' (Index 9): ZSTD
  Column 'fare_amount' (Index 10): ZSTD
  Column 'extra' (Index 11): ZSTD
  Column 'mta_tax' (Index 12): ZSTD
  Column 'tip_amount' (Index 13): ZSTD
  Column 'tolls_amount' (Index 14): ZSTD
  Column 'improvement_surcharge' (Index 15): ZSTD
  Column 'total_amount' (Index 16): ZSTD
  Column 'congestion_surcharge' (Index 17): ZSTD
  Column 'Airport_fee' (Index 18): ZSTD
Compression codecs: {'ZSTD'}