# Load a local CSV into an Apache Delta Lake table on the local filesystem.
# Databricks (and Spark / Trino / DuckDB / Microsoft Fabric) can then read the
# table natively. Point `table_uri` at `s3://…` / `abfss://…` / `gs://…` and
# add a `credentials:` block to land in cloud object storage instead (requires
# the `delta-s3` / `delta-azure` / `delta-gcs` build feature).
#
# faucet validate cli/examples/csv_to_delta.yaml
# faucet run cli/examples/csv_to_delta.yaml
version: 1
name: csv_to_delta
pipeline:
source:
type: csv
config:
path: ./data/input.csv
sink:
type: delta
config:
# Local path (promoted to file://). Created on first write from the
# inferred schema when create_if_not_missing (the default) is true.
table_uri: ./out/delta/events
create_if_not_missing: true
# Optional Hive-style partitioning applied when the table is created:
# partition_by: ["region"]