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Quickstart - dbt users

This introduction assumes you are already using dbt in your company and tables you would like to monitor are managed by dbt. To fully use re_data you would need to install both:

We'll go over the steps required to do that & explain what possibilities those packages create for you.

Installing re_data dbt package

Add the re_data dbt package to your main dbt repo project. You need to update your packages.yml file with re_data package like that:

packages.yml

packages:
***

- package: re-data/re_data
version: [">=0.8.0", "<0.9.0"]

And then install dbt packages dependencies by running:

dbt deps

You can do that locally, in your dbt cloud environment, or Airflow etc. scheduler enviornment.

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On production, you most likely are already running dbt deps as part of dbt models computation. So this step maybe only necessary for your local environment.

Configuring tables

Computing metrics & anomalies for your dbt models & sources requires configuring them to be observed by re_data. You can do it in a couple of ways, all of them described in re_data configuration reference part. A simple configuration for a single model contains just information that the model should be monitored & timestamp expression (usually column name) to be used when computing re_data time-based stats.

<model_name>.sql
{{
config(
re_data_monitored=true,
re_data_time_filter='time_column_name',
)
}}
select ...

dbt package functionality

Let's go over some of the things you already can use with re_data dbt package.

For specifics look into reference section:

dbt auto generated documentation, together with our models graph is also available: here

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re_data macros don't require any configuration and can be just used after you add re_data into your environment.

Computing first metrics

To compute re_data models containing metrics & anomalies you can just run standard dbt command.

dbt run --models package:re_data
info

single re_data run produces single data points about your tables for a time window. The default time window when you run re_data without parameters is yesterday. (from yesterday's 00:00 AM up until today 00:00 AM) To compare tables over time you would need to run the re_data dbt package multiple times (by some scheduler, re_data python package or manually).

The following would create tables inside your {default_schema}_re schema of your database. This is configured in dbt and can be overwritten in your dbt_project.yml.

Storing tests history (optional)

re_data enables you to store dbt tests results to investigate them later on. You can enable this functionality by setting:

vars:
re_data:save_test_history: true

In your dbt_project.yml file. After that when you run:

dbt test

re_data will store test history and with option --store-failures is added, it will also store failures in re_data_test_history model.

Installing re_data python package

To generate re_data reliability UI, send re_data alerts to Slack and easily backfill re_data models you will need to install the re_data python library. For this step, you need to have a python environment (with dbt installation) setup. Install re_data by executing:

pip install re_data
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re_data python library should be installed in the same python environment where your dbt is installed. re_data makes use of dbt to run queries against your database. Because of that, you don't need to pass any DB credentials to re_data configuration. re_data by default will run dbt with the same credentials & profiles which you have in your dbt_project.yml and ~/.dbt/profiles.yml files. You can also change this behaviour by passing options to the re_data command.

Python package functionality

Python package add enabled you to use this functionality:

Generate & Serve UI

Let's go over 2 commands for generating & serving UI. It works quite similarly to dbt docs. First you create files by calling re_data overview generate and then serving already existing files by re_data overview serve. For more details on paramters accepted by this & other re_data commands check re_data CLI reference

re_data overview generate
re_data overview serve

Learning more

More detailed instrutions on running re_data are described in out toy_shop example tutorial 😊

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Got stuck anywhere?

If you have more questions, got stuck anywhere, or something is not working as expected, please let us know on Slack! 😊, we will help you asap, and it will help us improve this quick start guide.