DatriseAI-first ETL

Parquet File to Looker Integration

AI-first ETL from Parquet File into Looker. Governed entities, incremental sync, typed landing tables.

How Datrise loads Parquet File into Looker

Datrise syncs Parquet File's row groups, columns, schemas, partitions, file batches, and column statistics into Looker as governed warehouse tables with LookML-ready naming. Flexible or custom fields land in flattened columns (nested fields expanded for modeling), and timestamps such as created, updated, and status changes are typed as date/time dimension columns.

Sync is incremental: Datrise uses incremental refresh of the underlying warehouse tables Looker explores, so re-runs update only what changed. Date-partitioned fact tables for PDT performance. Looker models live in LookML on top of SQL, so Datrise lands clean, stable column names rather than churn that would break your views.

Ideal for governed, version-controlled BI on a warehouse.

Endpoints

Parquet File: Columnar Parquet files from lakes and exports.

Looker: Google Cloud BI with LookML semantic models and governed dashboards.

How Parquet File entities map to Looker

Parquet File entityLooker objectNotes
row groupsparquet_file_row_groupsid PK · custom fields → flattened columns (nested fields expanded for modeling)
columnsparquet_file_columnsid PK · linked to parquet_file_row_groups
schemasparquet_file_schemasid PK · linked to parquet_file_row_groups
partitionsparquet_file_partitionsid PK · linked to parquet_file_row_groups

FAQ

How does Datrise handle Parquet File's custom fields in Looker?

Flexible values are stored as flattened columns (nested fields expanded for modeling), so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Looker types.

How does the Parquet File to Looker sync stay up to date?

It runs incrementally — Datrise uses incremental refresh of the underlying warehouse tables Looker explores.

Related pipelines

Early access

Connect Parquet File to Looker the easy way

Skip brittle scripts and manual exports. Join the waitlist to get a guided setup, AI-assisted mapping, and reliable incremental sync for this integration.