Singer target that loads data into DuckDB following the Singer spec.
First, make sure Python 3 is installed on your system or follow these installation instructions for Mac or Ubuntu.
It's recommended to use a virtualenv:
make venv
Like any other target that's following the singer specification:
some-singer-tap | target-duckdb --config [config.json]
It's reading incoming messages from STDIN and using the properties in config.json
to load data into DuckDB.
Note: To avoid version conflicts run tap
and targets
in separate virtual environments.
Running the target connector requires a config.json
file. An example with the minimal settings:
{
"path": "/path/to/local/file.duckdb",
"default_target_schema": "main"
}
Additional options in config.json
:
Property | Type | Required? | Description |
---|---|---|---|
path (alias: filepath) | String | Yes | The path to use for the duckdb.connect call; either a local file or a MotherDuck connection uri. |
dbname (alias: database) | String | The database name to write to; this will be inferred from the path property if it is not specified. | |
token | String | For MotherDuck connections, the auth token to use (this may also be set directly via the MOTHERDUCK_TOKEN environment variable. | |
delimiter | String | (Default: ',') The delimiter to use for the CSV files that are used for record imports. | |
quotechar | String | (Default: '"') The quote character to use for the CSV files that are used for record imports. | |
batch_size_rows | Integer | (Default: 100000) Maximum number of rows in each batch. At the end of each batch, the rows in the batch are loaded into DuckDB. | |
flush_all_streams | Boolean | (Default: False) Flush and load every stream into DuckDB when one batch is full. Warning: This may trigger the COPY command to use files with low number of records. | |
default_target_schema | String | Name of the schema where the tables will be created. If schema_mapping is not defined then every stream sent by the tap is loaded into this schema. |
|
schema_mapping | Object | Useful if you want to load multiple streams from one tap to multiple DuckDB schemas. If the tap sends the stream_id in <schema_name>-<table_name> format then this option overwrites the default_target_schema value. |
|
add_metadata_columns | Boolean | (Default: False) Metadata columns add extra row level information about data ingestions, (i.e. when was the row read in source, when was inserted or deleted in postgres etc.) Metadata columns are creating automatically by adding extra columns to the tables with a column prefix _SDC_ . The column names are following the stitch naming conventions documented at https://www.stitchdata.com/docs/data-structure/integration-schemas#sdc-columns. Enabling metadata columns will flag the deleted rows by setting the _SDC_DELETED_AT metadata column. Without the add_metadata_columns option the deleted rows from singer taps will not be recognisable in DuckDB. |
|
hard_delete | Boolean | (Default: False) When hard_delete option is true then DELETE SQL commands will be performed in DuckDB to delete rows in tables. It's achieved by continuously checking the _SDC_DELETED_AT metadata column sent by the singer tap. Due to deleting rows requires metadata columns, hard_delete option automatically enables the add_metadata_columns option as well. |
|
data_flattening_max_level | Integer | (Default: 0) Object type RECORD items from taps can be transformed to flattened columns by creating columns automatically. When value is 0 (default) then flattening functionality is turned off. |
|
primary_key_required | Boolean | (Default: True) Log based and Incremental replications on tables with no Primary Key cause duplicates when merging UPDATE events. When set to true, stop loading data if no Primary Key is defined. | |
validate_records | Boolean | (Default: False) Validate every single record message to the corresponding JSON schema. This option is disabled by default and invalid RECORD messages will fail only at load time by DuckDB. Enabling this option will detect invalid records earlier but could cause performance degradation. | |
temp_dir | String | (Default: platform-dependent) Directory of temporary CSV files with RECORD messages. |
- Install python dependencies in a virtual env and run unit and integration tests
make venv
- To run unit tests:
make unit_test
- To run integration tests:
make integration_test
- Install python dependencies and run python linter
make venv pylint
Apache License Version 2.0
See LICENSE to see the full text.