parquetread — Read Parquet columnar data into a table.

parquetread(filename) decodes a Parquet file with Arrow-backed Parquet support and returns a RunMat table. Common numeric, logical, string, date, and timestamp columns are mapped to table variables.

Syntax

parquetread(filename)

How parquetread works

  • SelectedVariableNames limits the imported variables, preserves the requested output order, and rejects unknown or duplicate names.
  • RowGroups accepts one-based row-group indices and decodes only those groups.
  • OutputType accepts "table"; "timetable" is rejected until timetable row-time synthesis for Parquet is implemented.
  • RowFilter is rejected until rowfilter predicate execution is available.
  • Unsupported nested or complex Parquet logical types raise deterministic import errors instead of producing partial columns.

Examples

Read a Parquet file

T = parquetread("measurements.parquet")

Expected output:

T = table

Read selected columns and row groups

T = parquetread("measurements.parquet", "SelectedVariableNames", ["time", "value"], "RowGroups", 2)

Expected output:

T = table

Using parquetread with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how parquetread changes the result.

Run a small parquetread example, explain the result, then change one input and compare the output.

FAQ

Does parquetread run on the GPU?

No. Parquet is a compressed columnar file format, so decoding and table construction happen on the host.

Open-source implementation

Unlike proprietary runtimes, every RunMat function is open-source. Read exactly how parquetread is executed, line by line, in Rust.

About RunMat

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