How deeply does DuckDB in Action cover read_parquet?

Explains schema inference, metadata-based counts, globbing, and file lists without detailing function arguments or schema overrides.

Read_parquet

As explained in DuckDB in Action

read_parquet_auto is a DuckDB table function that reads Parquet data while automatically deriving its structure from the supplied source.

read_parquet is a DuckDB table function for querying Parquet files directly. It uses Parquet’s embedded schema to derive column names and types, while keeping the data available to ordinary SQL queries. section 5.2 section 10.4.2

Use the function when the input selection or workflow needs explicit control:

Query one file explicitly instead of relying on filename-extension inference. section 10.4.2
Pass a list of files to combine selected Parquet datasets and unify their schemas. section 5.2 section 10.4.2
Let metadata answer counts quickly without reading the full data payload. section 10.4.2

Count selected Parquet files

SELECT count(*) FROM read_parquet([ 's3://.../yellow_tripdata_2021-06.parquet', 's3://.../yellow_tripdata_2022-06.parquet' ]); -- 6,392,388

How DuckDB in Action covers it

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Related concepts

table functionkind of · A table function is a callable query component that returns a relation consisting of rows and columns.
metadatauses · Metadata is information that describes, identifies, or provides context about other data, resources, or artifacts.
pandaspart of · pandas is an open-source Python library that provides labeled data structures and tools for manipulating and analyzing tabular and other structured data.
parquet_schemaconfigured by · parquet_schema is a DuckDB table function that returns the schema metadata stored inside a Parquet file.

This explainer was generated by Manning's knowledge graph from the text of DuckDB in Action. The section links point to the parts of the book it draws on.