Apache ORC (.orc)
.orcApache Hadoop, Hive, Spark, Presto/Trino, and enterprise big data pipelines
What it is
Optimized Row Columnar (ORC) format from the Apache big-data ecosystem, designed for high compression and fast columnar scans. Read via a bundled Python/PyArrow bridge.
Who produces it
Data engineering and analytics pipelines exporting query results from data warehouses and big-data lakes in ORC format.
What we read / what we don't read
What we read
- Flat numeric (int, float, decimal), string, boolean, and date/timestamp columns via PyArrow ORC reader
- All rows and columns across compressed stripes
What we don't read
- Complex nested map, struct, or list columns
- ACID transactional delta tables and uncommitted Hive streaming partitions
How to import it into AltaiPlot
- Open AltaiPlot and drag your .orc file onto the window, or use File → Import.
- AltaiPlot recognizes the ORC header and invokes the bundled Python reader.
- Preview the schema and column names.
- Click Import to load the data.
Auditability note: this page's capability claims are sourced fromresources/python/app_sidecar.py:1581 — see the full format list for every extension AltaiPlot recognizes.