kumoai.connector

The Kumo Connector and SourceTable interfaces allow users to access and inspect raw data behind backing connectors. These data can be used to create Table and Graph objects, which are for machine learning downstream.

Uploading Your Own Data

Kumo supports uploading your own tables. Files >1GB are supported by default through automatic partitioning. Tables must be single Parquet or CSV file on your local machine. Tables can be uploaded with upload() and deleted with delete(). They can be used with FileUploadConnector.

Connector

Connectors support connecting Kumo with data in a backing data store. The Kumo SDK currently supports the Amazon S3 object store, the BigQuery data warehouse, the Snowflake data warehouse, and the Databricks data warehouse as stores for source tables.

S3Connector	Defines a connector to a table stored as a file (or partitioned set of files) on the Amazon S3 object store.
SnowflakeConnector	Establishes a connection to a Snowflake database.
DatabricksConnector	Establishes a connection to a Databricks database.
BigQueryConnector	Establishes a connection to a BigQuery database.
FileUploadConnector	Defines a connector to files directly uploaded to Kumo, either as 'parquet' or 'csv' (non-partitioned) data.

Source Data

Tables accessed from connectors are represented as SourceTable objects, with source columns represented as SourceColumn objects.

SourceTable	A source table is a reference to a table stored behind a backing Connector.
SourceTableFuture	A representation of an on-going SourceTable generation process.
LLMSourceTableFuture	A representation of an on-going SourceTable generation process for LLM.
SourceColumn	The metadata of a column in a source table.