polars.LazyFrame.sink_parquet#

LazyFrame.sink_parquet(
path: str | Path,
*,
compression: str = 'zstd',
compression_level: int | None = None,
statistics: bool | str | dict[str, bool] = True,
row_group_size: int | None = None,
data_page_size: int | None = None,
maintain_order: bool = True,
type_coercion: bool = True,
_type_check: bool = True,
predicate_pushdown: bool = True,
projection_pushdown: bool = True,
simplify_expression: bool = True,
slice_pushdown: bool = True,
collapse_joins: bool = True,
no_optimization: bool = False,
storage_options: dict[str, Any] | None = None,
credential_provider: CredentialProviderFunction | Literal['auto'] | None = 'auto',
retries: int = 2,
sync_on_close: SyncOnCloseMethod | None = None,
mkdir: bool = False,
lazy: bool = False,
engine: EngineType = 'auto',
) → LazyFrame | None[source]#

Evaluate the query in streaming mode and write to a Parquet file.

Warning

Streaming mode is considered unstable. It may be changed at any point without it being considered a breaking change.

This allows streaming results that are larger than RAM to be written to disk.

Parameters:
path

File path to which the file should be written.

compression{‘lz4’, ‘uncompressed’, ‘snappy’, ‘gzip’, ‘lzo’, ‘brotli’, ‘zstd’}

Choose “zstd” for good compression performance. Choose “lz4” for fast compression/decompression. Choose “snappy” for more backwards compatibility guarantees when you deal with older parquet readers.

compression_level

The level of compression to use. Higher compression means smaller files on disk.

  • “gzip” : min-level: 0, max-level: 10.

  • “brotli” : min-level: 0, max-level: 11.

  • “zstd” : min-level: 1, max-level: 22.

statistics

Write statistics to the parquet headers. This is the default behavior.

Possible values:

  • True: enable default set of statistics (default). Some statistics may be disabled.

  • False: disable all statistics

  • “full”: calculate and write all available statistics. Cannot be combined with use_pyarrow.

  • { "statistic-key": True / False, ... }. Cannot be combined with use_pyarrow. Available keys:

    • “min”: column minimum value (default: True)

    • “max”: column maximum value (default: True)

    • “distinct_count”: number of unique column values (default: False)

    • “null_count”: number of null values in column (default: True)

row_group_size

Size of the row groups in number of rows. If None (default), the chunks of the DataFrame are used. Writing in smaller chunks may reduce memory pressure and improve writing speeds.

data_page_size

Size limit of individual data pages. If not set defaults to 1024 * 1024 bytes

maintain_order

Maintain the order in which data is processed. Setting this to False will be slightly faster.

type_coercion

Do type coercion optimization.

predicate_pushdown

Do predicate pushdown optimization.

projection_pushdown

Do projection pushdown optimization.

simplify_expression

Run simplify expressions optimization.

slice_pushdown

Slice pushdown optimization.

collapse_joins

Collapse a join and filters into a faster join

no_optimization

Turn off (certain) optimizations.

storage_options

Options that indicate how to connect to a cloud provider.

The cloud providers currently supported are AWS, GCP, and Azure. See supported keys here:

  • aws

  • gcp

  • azure

  • Hugging Face (hf://): Accepts an API key under the token parameter: {'token': '...'}, or by setting the HF_TOKEN environment variable.

If storage_options is not provided, Polars will try to infer the information from environment variables.

credential_provider

Provide a function that can be called to provide cloud storage credentials. The function is expected to return a dictionary of credential keys along with an optional credential expiry time.

Warning

This functionality is considered unstable. It may be changed at any point without it being considered a breaking change.

retries

Number of retries if accessing a cloud instance fails.

sync_on_close: { None, ‘data’, ‘all’ }

Sync to disk when before closing a file.

  • None does not sync.

  • data syncs the file contents.

  • all syncs the file contents and metadata.

mkdir: bool

Recursively create all the directories in the path.

lazy: bool

Wait to start execution until collect is called.

engine

Select the engine used to process the query, optional. At the moment, if set to "auto" (default), the query is run using the polars streaming engine. Polars will also attempt to use the engine set by the POLARS_ENGINE_AFFINITY environment variable. If it cannot run the query using the selected engine, the query is run using the polars streaming engine.

Note

The GPU engine is currently not supported.

Returns:
DataFrame

Examples

>>> lf = pl.scan_csv("/path/to/my_larger_than_ram_file.csv")  
>>> lf.sink_parquet("out.parquet")