pipelinewise-tap-snowflake

Singer tap that extracts data from a Snowflake database and produces JSON-formatted data following the Singer spec.

This is a PipelineWise compatible tap connector.

How to use it

The recommended method of running this tap is to use it from PipelineWise. When running it from PipelineWise you don't need to configure this tap with JSON files and most of things are automated. Please check the related documentation at Tap Snowflake

If you want to run this Singer Tap independently please read further.

Install and Run

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:

  python3 -m venv venv
  pip install pipelinewise-tap-snowflake

or

  python3 -m venv venv
  . venv/bin/activate
  pip install --upgrade pip
  pip install .

Configuration

1. Create a config.json file with connection details to snowflake.

   {
     "account": "rtxxxxx.eu-central-1",
     "dbname": "database_name",
     "user": "my_user",
     "password": "password",
     "warehouse": "my_virtual_warehouse",
     "tables": "db.schema.table1,db.schema.table2"
   }

Optional Metadata can be provided in the config to define the syncing strategy for tables so that auto discovery creates a fully configured catalog.

{
   "account": "rtxxxxx.eu-central-1",
   "dbname": "database_name",
   "user": "my_user",
   "password": "password",
   "warehouse": "my_virtual_warehouse",
   "tables": "db.schema.table1,db.schema.table2",
   "metadata": {
       "db.schema.table1": {
           "table-key-properties": ["key1"],
           "replication-key": "column1",
           "replication-method": "INCREMENTAL",
           "selected": true
       }
   }
}

Note: tables is a mandatory parameter as well to avoid long running catalog discovery process. Please specify fully qualified table and view names and only that ones that you need to extract otherwise you can end up with very long running discovery mode of this tap. Discovery mode is analysing table structures but Snowflake doesn't like selecting lot of rows from INFORMATION_SCHEMA or running SHOW commands that returns lot of rows. Please be as specific as possible.

2. Run it in discovery mode to generate a properties.json

3. Edit the properties.json and select the streams to replicate

4. Run the tap like any other singer compatible tap:

  tap-snowflake --config config.json --properties properties.json --state state.json

Discovery mode

The tap can be invoked in discovery mode to find the available tables and columns in the database:

$ tap-snowflake --config config.json --discover

A discovered catalog is output, with a JSON-schema description of each table. A source table directly corresponds to a Singer stream.

Replication methods

The two ways to replicate a given table are FULL_TABLE and INCREMENTAL.

Note: Discovery does not include these values in the output catalog, you must add them to the metadata of the configured tables. Alternatively if you run the tap without a catalog then it will auto-discover and default to full table replication unless overridden by config metadata.

Full Table

Full-table replication extracts all data from the source table each time the tap is invoked.

  "metadata": {
    "replication-method": "FULL_TABLE",
    "selected-by-default": false,
    "database-name": "DB_123",
    "schema-name": "SCHEMA_456",
    "row-count": 0,
    "is-view": false,
    "selected": true
  }

Additionally, the full table sync can be configured to use a look back window to limit the size of the data set being synced. The look period is from the current time minus the configured rolling_lookback period. time_unit is any date or time part supported by snowflake and the time_amount is the positive integer of time units to look backwards.

   "rolling_lookback": {
      "db-schema-table": {
         "time_unit": "day",
         "time_amount": "7",
         "time_column": "DATE_OR_TS_COL_NAME"
      }
   }

Incremental

Incremental replication works in conjunction with a state file to only extract new records each time the tap is invoked. This requires a replication key to be specified in the table's metadata as well.

Below is an example of an incremental sync setting for a view. Replication is based on source data with UPDATED_DATE that's >= to the current bookmarked value provided in the state.json file. view-key-properties or table-key-properties defines the key properties associated with the view/table being replicated.

  "metadata": {
    "view-key-properties": [
      "ID"
    ],
    "replication-key": "UPDATED_DATE",
    "replication-method": "INCREMENTAL",
    "selected-by-default": false,
    "database-name": "DB_123",
    "schema-name": "SCHEMA_456",
    "row-count": 0,
    "is-view": true,
    "selected": true
  }

To run tests:

1. Define environment variables that requires running the tests

  export TAP_SNOWFLAKE_ACCOUNT=<snowflake-account-name>
  export TAP_SNOWFLAKE_DBNAME=<snowflake-database-name>
  export TAP_SNOWFLAKE_USER=<snowflake-user>
  export TAP_SNOWFLAKE_PASSWORD=<snowfale-password>
  export TAP_SNOWFLAKE_WAREHOUSE=<snowflake-warehouse>

NOTE: User must have permission to create/drop schema (TAP_SNOWFLAKE_TEST), create/drop table, insert into those tables. DEG's implementation uses DATA_DEG_TEST.TAP_SNOWFLAKE_TEST - credentials are in the 1Pass vault.

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

  python3 -m venv venv
  . venv/bin/activate
  pip install --upgrade pip
  pip install .
  pip install tox

3. To run unit tests:

  tox

License

Apache License Version 2.0

See LICENSE to see the full text.