New: Cookbooks and AI ExplanationsStep-by-Step recipes to solve problems connected to Roadmaps and Cheat Sheets. Need more details? Use AI buttons for structured and simple explanations with concrete examples throughout the whole platform.Take a look
The table has years of Parquet files in it, and a full rewrite would tie up the cluster all weekend.
What you'll have at the end
The same Parquet files now readable through an Iceberg snapshot, with the original Hive table left untouched as a fallback
You need
A Hive-style external table already cataloged in your lakehouse's metastore, its partitions stored as Parquet, Avro, or ORC files in object storage, and a Spark environment with the Iceberg runtime on its classpath.
Not covered
Rewriting the table's data files, repartitioning it, or fixing a small-files problem as part of the move: those need a real rewrite, a separate and slower path than this one.
Leans on
Pick a catalog so Spark and Trino can query the same lakehouse table
if the real goal is wiring a second query engine to this table rather than switching its format, that recipe handles the catalog side, not a single table's migration.
Evolve a lakehouse table's schema without silently orphaning old data
once the twin is the table of record, schema changes go through Iceberg's own evolution rules instead of anything Hive-specific.
Checked 26 Aug 2026
Part of the Data Lakehouse cookbook