E-commerce Quickstart
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Requirements
In addition to dbt being installed and a web events dataset being available in your database:
- A dataset of e-commerce events from the Snowplow JavaScript tracker, or the iOS/Android trackers must be available in the database.
- Have the
webPagecontext enabled. (Note if you have only tracked mobile e-commerce events, you will need other events in your warehouse to have used this context as we require the column to exist). - Have the following e-commerce contexts enabled:
cart,checkout_step,pagetransaction,user - Track the e-commerce tracking action events on your website/mobile application
Installation
Make sure to create a new dbt project and import this package via the packages.yml as recommended by dbt, or add to an existing top level project. Do not fork the packages themselves.
Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages. If you are using multiple packages you may need to up/downgrade a specific package to ensure compatibility.
packages:
- package: snowplow/snowplow_ecommerce
version: 0.9.0
Make sure to run the dbt deps command after updating your packages.yml to ensure you have the specified version of each package installed in your project.
Setup
1. Override the dispatch order in your project
To take advantage of the optimized upsert that the Snowplow packages offer you need to ensure that certain macros are called from snowplow_utils first before dbt-core. This can be achieved by adding the following to the top level of your dbt_project.yml file:
dispatch:
- macro_namespace: dbt
search_order: ['snowplow_utils', 'dbt']
If you do not do this the package will still work, but the incremental upserts will become more costly over time.
2. Adding the selectors.yml file
Within the packages we have provided a suite of suggested selectors to run and test the models within the package together with the e-commerce model. This leverages dbt's selector flag. You can find out more about each selector in the YAML Selectors section.
These are defined in the selectors.yml file (source) within the package, however in order to use these selectors you will need to copy this file into your own dbt project directory. This is a top-level file and therefore should sit alongside your dbt_project.yml file. If you are using multiple packages in your project you will need to combine the contents of these into a single file.
3. Check source data
This package will by default assume your Snowplow events data is contained in the atomic schema of your target.database, in the table labeled events. In order to change this, please add the following to your dbt_project.yml file:
vars:
snowplow_ecommerce:
snowplow__atomic_schema: schema_with_snowplow_events
snowplow__database: database_with_snowplow_events
snowplow__events_table: table_of_snowplow_events
Please note that your target.database is NULL if using Databricks. In Databricks, schemas and databases are used interchangeably and in the dbt implementation of Databricks therefore we always use the schema value, so adjust your snowplow__atomic_schema value if you need to.
4. Filter your data set
You can specify both start_date at which to start processing events, the app_id's to filter for, and the event_name value to filter on. By default the start_date is set to 2020-01-01, all app_id's are selected, and only the snowplow_ecommerce_action name is being surfaced. To change this please add/modify the following in your dbt_project.yml file:
vars:
snowplow_ecommerce:
snowplow__start_date: 'yyyy-mm-dd'
snowplow__app_id: ['my_app_1','my_app_2']
snowplow__ecommerce_event_names: ['snowplow_ecommerce_action', 'my_custom_ecommerce_event']
5. Additional vendor specific configuration
Verify which column your events table is partitioned on. It will likely be partitioned on collector_tstamp or derived_tstamp. If it is partitioned on collector_tstamp you should set snowplow__derived_tstamp_partitioned to false. This will ensure only the collector_tstamp column is used for partition pruning when querying the events table:
vars:
snowplow_ecommerce:
snowplow__derived_tstamp_partitioned: false
6. Removing unused modules
The e-commerce package creates tables that depend on the existence of certain entities that are a part of the Snowplow e-commerce JS plugin. If, for some reason, you have not implemented them and would like to streamline your data modeling not to create empty tables, then you need to add that configuration to your dbt_project.yml file. Below you can see an example of what that would look like if you wanted to disable the cart entity
Disabling the cart module in dbt_project.yml (recommended)
...
vars:
snowplow_ecommerce:
snowplow__disable_ecommerce_carts: true
...
models:
snowplow_ecommerce:
carts:
+enabled: false
Adding these two configurations to your dbt_project.yml will ensure that the carts module is disabled.
Disabling the cart module using dbt run
If you want to temporarily disable a module, or you just find it easier to use the command line, you can also do this in the command line when executing the dbt run command. You will need to run the following command to disable the carts module
dbt run --exclude carts --select snowplow_ecommerce --vars '{snowplow__disable_ecommerce_carts: true}'
7. Enable mobile e-commerce events
Mobile e-commerce events may be processed in the package, if they have a domain_sessionid and are in your listed app_ids, however to correctly source the mobile session and screen view ids you need to set the following in your dbt_project.yml:
vars:
snowplow_ecommerce:
snowplow__enable_mobile_events: true
8. Optimize your project
There are ways how you can deal with high volume optimizations at a later stage, if needed, but you can do a lot upfront by selecting carefully which variable to use for snowplow__session_timestamp, which helps identify the timestamp column used for sessionization. This timestamp column should ideally be set to the column your event table is partitioned on. It is defaulted to collector_tstamp but depending on your loader it can be the load_tstamp as the sensible value to use:
vars:
snowplow_ecommerce:
snowplow__session_timestamp: 'load_tstamp'
9. Verify your variables using our Config guides (Optional)
If you are unsure whether the default values set are good enough in your case or you would already like to maximize the potential of your models, you can dive deeper into the meaning behind our variables on our Config page. It includes a Config Generator to help you create all your variable configurations, if necessary.
10. Run your model
You can now run your models for the first time by running the below command (see the operation page for more information on operation of the package):
dbt run --selector snowplow_ecommerce