target-elasticsearch
is a Singer target for Elastic.
Some target development because I am currently hacking together something together with a bash script Built with the Meltano Tap SDK for Singer Taps.
Setting | Required | Default | Description |
---|---|---|---|
scheme | True | http | http scheme used for connecting to elasticsearch |
host | True | localhost | host used to connect to elasticsearch |
port | True | 9200 | port use to connect to elasticsearch |
username | False | None | basic auth username as per elastic documentation |
password | False | None | basic auth password as per elastic documentation |
bearer_token | False | None | Bearer token for bearer authorization as per elastic documentation |
api_key_id | False | None | api key id for auth key authorization as per elastic documentation |
api_key | False | None | api key for auth key authorization as per elastic documentation |
ssl_ca_file | False | None | location of the the SSL certificate for cert verification ie. /some/path as per elastic documentation |
index_format | False | ecs-{{ stream_name }}-{{ current_timestamp_daily }} | can be used to handle custom index formatting such as specifying -latest index. Default options: Daily {{ current_timestamp_daily }} , Monthly {{ current_timestamp_monthly }} , or Yearly {{ current_timestamp_yearly }} . You should use fields specified in index_schema_fields such as {{ _id }} or {{ timestamp }} . There are also helper fuctions such as {{ to_daily(timestamp) }}`. |
index_schema_fields | False | None | this id map allows you to specify specific record values via jsonpath from the stream to be used in index formulation. |
metadata_fields | false | None | this should be used to pull out specific fields via jsonpath to be used on for ecs metadata patters |
A full list of supported settings and capabilities is available by running: target-elasticsearch --about
git clone git@github.com:dtmirizzi/target_elasticsearch.git
cd target_elasticsearch
pipx install .
A full list of supported settings and capabilities for this tap is available by running:
target_elasticsearch --about
You can easily run target-elasticsearch
by itself or in a pipeline using Meltano.
target_elasticsearch --version
target_elasticsearch --help
target_elasticsearch --config CONFIG --discover > ./catalog.json
pipx install poetry
poetry install
poetry run pre-commit install
- Create tests within the
target_elasticsearch/tests
subfolder - To Run tests, first set environment variables in your current shell for all required settings from the Settings section above. Example for UNIX base systems running
export Target_elasticsearch_USER_ID="xxxxx"
then run:
poetry run pytest
You can also test the target-elasticsearch
CLI interface directly using poetry run
:
poetry run target_elasticsearch --help
Testing with Meltano
Note: This tap 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-elasticsearch
meltano install
# You can spin up elastic locally
make local-es
Now you can test and orchestrate using Meltano:
meltano install
# Test invocation:
meltano invoke target-elasticsearch --version
# test configuration
meltano config target-elasticsearch set --interactive
# OR run a test `elt` pipeline:
meltano elt tap-smoke-test target-elasticsearch
See the dev guide for more instructions on how to use the SDK to develop your own taps and targets.