target-snowflake

Singer target that loads data into Snowflake following the Singer spec.

This repository doesn't contain the code itself because that has not been open sourced (yet). If you are interested please contact to the owner of this repository at https://transferwise.com

Flow diagram

To run

Like any other target that's following the singer specificiation:

some-singer-tap | target-snowflake --config [config.json]

It's reading incoming messages from STDIN and using the properites in config.json to upload data into Snowflake

Configuration settings

Settings are stored in a config.json JSON and in a map

Property	Type	Required?	Description
account	String	Yes	Snowflake account name (i.e. rtXXXXX.eu-central-1)
dbname	String	Yes	Snowflake Database name
user	String	Yes	Snowflake User
password	String	Yes	Snowflake Password
warehouse	String	Yes	Snowflake virtual warehouse name
aws_access_key_id	String	Yes	S3 Access Key Id
aws_secret_access_key	String	Yes	S3 Secret Access Key
s3_bucket	String	Yes	S3 Bucket name
s3_key_prefix	String		(Default: None) A static prefix before the generated S3 key names. Using prefixes you can upload files into specific directories in the S3 bucket.
batch_size	Integer		(Default: 100000) Maximum number of rows in each batch. At the end of each batch, the rows in the batch are loaded into Snowflake.
schema	String		Name of the schema where the tables will be created
dynamic_schema_name	Boolean		(Default: False) When it's true, the schema names will be created automatically derived from the incoming stream name
dynamic_schema_name_postfix	String		(Default: None) Can be use together with the `dynamic_schema_name` option to add an optional postfix to the end of the generated schema name
grant_select_to	String or List of String		(Default: None) Grant USAGE privilege on newly created schemas and grant SELECT privilege on new created tables to a specific role or a list of roles.
disable_table_cache	Boolean		(Default: False) By default the connector caches the available table structures in Snowflake at startup. In this way it doesn't need to run additional queries when ingesting data to check if altering the target tables is required. With `disable_table_cache` option you can turn off this caching. You will always see the most recent table structures but will cause an extra query runtime.
client_side_encryption_master_key	String		(Default: None) When this is defined, Client-Side Encryption is enabled. The data in S3 will be encrypted, No third parties, including Amazon AWS and any ISPs, can see data in the clear. Snowflake COPY command will decrypt the data once it's in Snowflake. The master key must be 256-bit length and must be encoded as base64 string.
client_side_encryption_stage_object	String		(Default: None) Required when `client_side_encryption_master_key` is defined. The name of the encrypted stage object in Snowflake that created separately and using the same encryption master key.
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 snowflake 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 recongisable in Snowflake.
hard_delete	Boolean		(Default: False) When `hard_delete` option is true then DELETE SQL commands will be performed in Snowflake 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.

To run tests:

Define environment variables that requires running the tests

  export TARGET_SNOWFLAKE_ACCOUNT=<snowflake-account-name>
  export TARGET_SNOWFLAKE_DBNAME=<snowflake-database-name>
  export TARGET_SNOWFLAKE_USER=<snowflake-user>
  export TARGET_SNOWFLAKE_PASSWORD=<snowfale-password>
  export TARGET_SNOWFLAKE_WAREHOUSE=<snowflake-warehouse>
  export TARGET_SNOWFLAKE_SCHEMA=<snowflake-schema>
  export TARGET_SNOWFLAKE_AWS_ACCESS_KEY=<aws-access-key-id>
  export TARGET_SNOWFLAKE_AWS_SECRET_ACCESS_KEY=<aws-access-secret-access-key>
  export TARGET_SNOWFLAKE_S3_BUCKET=<s3-external-bucket>
  export TARGET_SNOWFLAKE_S3_KEY_PREFIX=<bucket-directory>
  export CLIENT_SIDE_ENCRYPTION_MASTER_KEY=<client_side_encryption_master_key>
  export CLIENT_SIDE_ENCRYPTION_STAGE_OBJECT=<client_side_encryption_stage_object>

Install python dependencies in a virtual env and run nose unit and integration tests

  python3 -m venv venv
  . venv/bin/activate
  cd singer-connectors/target-snowflake
  pip install --upgrade pip
  pip install .
  pip install nose

To run unit tests:

  nosetests --where=tests/unit

To run integration tests:

  nosetests --where=tests/integration

To run pylint:

Install python dependencies and run python linter