Importing tables as datasets¶

For usage information and examples, see Importing tables as datasets

class dataikuapi.dss.project.TablesImportDefinition(client, project_key)¶

Temporary structure holding the list of tables to import

add_hive_table(hive_database, hive_table)¶

Add a Hive table to the list of tables to import

Parameters:

hive_database (str) – the name of the Hive database
hive_table (str) – the name of the Hive table

add_sql_table(connection, schema, table, catalog=None)¶

Add a SQL table to the list of tables to import

Parameters:

connection (str) – the name of the SQL connection
schema (str) – the schema of the table
table (str) – the name of the SQL table
catalog (str) – the database of the SQL table. Leave to None to use the default database associated with the connection

add_iceberg_table(connection, namespace, table)¶

Add a Iceberg table to the list of tables to import

Parameters:

connection (str) – the name of the Iceberg connection
namespace (str) – the namespace of the table
table (str) – the name of the table

add_elasticsearch_index_or_alias(connection, index_or_alias)¶: Add an Elastic Search index or alias to the list of tables to import

prepare()¶

Run the first step of the import process. In this step, DSS will check the tables whose import you have requested and prepare dataset names and target connections

Returns:: an object that allows you to finalize the import process
Return type:: TablesPreparedImport

class dataikuapi.dss.project.TablesPreparedImport(client, project_key, candidates)¶

Result of preparing a tables import. Import can now be finished

execute()¶

Starts executing the import in background and returns a dataikuapi.dss.future.DSSFuture to wait on the result

Returns:: a future to wait on the result
Return type:: dataikuapi.dss.future.DSSFuture