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meltanolabs-target-snowflake

Singer target for Snowflake, built with the Meltano SDK for Singer Targets.

  • 0.14.0
  • PyPI
  • Socket score

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target-snowflake

Target for Snowflake.

Built with the Meltano Singer SDK.

Capabilities

  • about
  • stream-maps
  • schema-flattening
  • target-schema

Settings

SettingRequiredDefaultDescription
userTrueNoneThe login name for your Snowflake user.
passwordFalseNoneThe password for your Snowflake user.
private_keyFalseNoneThe private key contents. For KeyPair authentication either private_key or private_key_path must be provided.
private_key_pathFalseNonePath to file containing private key. For KeyPair authentication either private_key or private_key_path must be provided.
private_key_passphraseFalseNonePassphrase to decrypt private key if encrypted.
accountTrueNoneYour account identifier. See Account Identifiers.
databaseTrueNoneThe initial database for the Snowflake session.
schemaFalseNoneThe initial schema for the Snowflake session.
warehouseFalseNoneThe initial warehouse for the session.
roleFalseNoneThe initial role for the session.
add_record_metadataFalse1Whether to add metadata columns.
clean_up_batch_filesFalse1Whether to remove batch files after processing.
default_target_schemaFalseNoneThe default target database schema name to use for all streams.
hard_deleteFalse0Hard delete records.
load_methodFalseTargetLoadMethods.APPEND_ONLYThe method to use when loading data into the destination. append-only will always write all input records whether that records already exists or not. upsert will update existing records and insert new records. overwrite will delete all existing records and insert all input records.
batch_size_rowsFalseNoneMaximum number of rows in each batch.
validate_recordsFalse1Whether to validate the schema of the incoming streams.
stream_mapsFalseNoneConfig object for stream maps capability. For more information check out Stream Maps.
stream_map_configFalseNoneUser-defined config values to be used within map expressions.
faker_configFalseNoneConfig for the Faker instance variable fake used within map expressions. Only applicable if the plugin specifies faker as an addtional dependency (through the singer-sdk faker extra or directly).
faker_config.seedFalseNoneValue to seed the Faker generator for deterministic output: https://faker.readthedocs.io/en/master/#seeding-the-generator
faker_config.localeFalseNoneOne or more LCID locale strings to produce localized output for: https://faker.readthedocs.io/en/master/#localization
flattening_enabledFalseNone'True' to enable schema flattening and automatically expand nested properties.
flattening_max_depthFalseNoneThe max depth to flatten schemas.
use_browser_authenticationFalseFalseIf authentication should be done using SSO (via external browser). See See SSO browser authentication.

A full list of supported settings and capabilities is available by running: target-snowflake --about

Initializing a Snowflake Account

This target has an interactive feature that will help you get a Snowflake account initialized with everything needed to get started loading data.

  • User
  • Role
  • Warehouse
  • Database
  • Proper grants

The CLI will ask you to provide information about the new user/role/etc. you want to create but it will also need SYSADMIN credentials to execute the queries. You should prepare the following inputs:

  • Account
  • User that has SYSADMIN and SECURITYADMIN access. These comes default with the user that created the Snowflake account.
  • The password for your SYSADMIN user.

Run the following command to get started with the interactive CLI. Note - the CLI will print the SQL queries it is planning to run and confirm with you before it makes any changes.

poetry run target-snowflake --initialize

# Alternatively using Meltano CLI
meltano invoke target-snowflake --initialize

The CLI also has a "dry run" mode that will print the queries without executing them.

Check out the demo of this on YouTube.

Configure using environment variables

This Singer target will automatically import any environment variables within the working directory's .env if the --config=ENV is provided, such that config values will be considered if a matching environment variable is set either in the terminal context or in the .env file.

Usage

You can easily run target-snowflake by itself or in a pipeline using Meltano.

Executing the Target Directly

target-snowflake --version
target-snowflake --help
# Test using the "Carbon Intensity" sample:
tap-carbon-intensity | target-snowflake --config /path/to/target-snowflake-config.json

Developer Resources

Initialize your Development Environment

pipx install poetry
poetry install

Create and Run Tests

Create tests within the target_snowflake/tests subfolder and then run:

poetry run pytest

You can also test the target-snowflake CLI interface directly using poetry run:

poetry run target-snowflake --help

Testing with Meltano

Note: This target will work in any Singer environment and does not require Meltano. Examples here are for convenience and to streamline end-to-end orchestration scenarios.

Your project comes with a custom meltano.yml project file already created.

Next, install Meltano (if you haven't already) and any needed plugins:

# Install meltano
pipx install meltano
# Initialize meltano within this directory
cd target-snowflake
meltano install

Now you can test and orchestrate using Meltano:

# Test invocation:
meltano invoke target-snowflake --version
# OR run a test `elt` pipeline with the Carbon Intensity sample tap:
meltano run tap-carbon-intensity target-snowflake

SDK Dev Guide

See the dev guide for more instructions on how to use the Meltano SDK to develop your own Singer taps and targets.

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