📈Data Application Sync

As your organization's shared data model is constantly evolving, Euno helps ensure that these changes are reflected in your BI tool. The data application sync automation is designed to ensure that your BI application reflects the most up-to-date shared data model of your organization.

How the Data Application Sync Works

Euno supports the automated synchronization of data model revisions, facilitating seamless updates from the dbt manifest to LookML files. Here’s how it works:

  1. New revision: When a change is detected in the dbt manifest, Euno generates LookML files based on the updated manifest/catalog. Euno can either sync all models or be configured for a selective sync, in which models are synced based on a tag. The sync process is triggered by changes in the dbt manifest. If no changes are detected, no sync is triggered.

  2. Branch checkout: Euno checks out the selected LookML repository and branch configured in the data application sync configuration

  3. PR/Commit: Euno generates a PR/commit, depending on the configurations

What Fields are Supported in the Data Application Sync?

Columns

Euno supports syncing all dbt columns in the model to dimensions in LookML. The dimension data type will be dependent on the dialect used in your DW (see Dialect Conversion Charts). For time dimensions, Euno automatically syncs these columns as a dimension_group of type; time, in LookML.

dimension_group: dimension_group_name {
  type: time
  sql: SQL expression ;;  
  timeframes: [raw, time, hour_of_day, date, day_of_the_week, week,  
              month, quarter, year]
  datatype: # field type conversion - dependent on dialect
  convert_tz: yes
}

Metrics

Euno supports automatically syncing dbt metrics to Looker, if the metric is built from a single semantic model. Meaning; the measures or metrics used to create the metric is from the same semantic model, and are of type:

  • Simple

  • Ratio

  • Derived

If the metric includes a filter, Euno will sync an additional dimension specifically for the filter that will hold the filter's logic within the 'sql' parameter of that dimension. The dimension will be of type 'yesno', with the parameter 'hidden' set to 'yes', tagged with 'euno-generated-filter-dimension', and named '<measure_name>_euno_generated_filter_dim' , which can be overridden by placing the macro key; under the meta section of the metric. Inside the measure, under the 'filter' parameter, it will reference this field with the dimension as the key and 'yes' as the value. Essentially, this means that if the data matches the logic in the filter, the metric will be applied to the data.

Note: These filters will only be generated for simple metrics and will specifically apply to dbt filter templates utilizing entities, dimensions, or time dimensions within the identical semantic model. Metrics filtered by other metrics are not currently supported.

Below is an example of how the Data Application Sync syncs a metric with a filter (simple_metric) in LookML.

dbt Metric with Filterdbt Metric Synced to LookML with Filter
semantic_models:
  - name: users
    model: ref('users')
    entities:
      - type: primary
        name: pe
        description: This is a delphi auto-generated primary entity (Change according to desired primary entity)
    defaults:
      agg_time_dimension: time_dim
    dimensions:
      - name: time_dim
        type: time
        type_params:
          time_granularity: day
  measures:
      - name: simple_measure
        label: simple_measure
        agg: sum
        expr: 1
metrics:
  - name: simple_metric
    label: simple_metric
    type: simple
    type_params:
      measure: simple_measure
    filter: |
      {{ TimeDimension('pe__time_dim', 'day') }} IS NULL

  dimension: simple_metric_euno_generated_filter_dim {
    type: yesno
    hidden: yes
    sql: DATE_TRUNC('day', ${TABLE}.time_dim) IS NULL ;;
    tags: ["euno-generated-filter-dimension"]
  }

  measure: simple_metric {
    type: sum
    sql: 1 ;;
    filters: [simple_metric_euno_generated_filter_dim: "TRUE"]
  }

    type: yesno
    sql: metric_time__day IS NOT NULL ;;
  }

Euno also supports syncing filters using our built-in macro 'getdelphi.io/lookml_filters'. As described below, the above macro key should be placed in the metric's meta, with the value being a list containing the 'filter_field' as the key and the 'filter_value' as the value inside the list. If the metric includes both a filter, and the above macro, the macro will override the filter within the metric. 

getdelphi.io/lookml_filters: '[["filter_field", "filter_value"]]'

Limitations of the Data Application Sync

Euno does not support syncing the following dbt metrics:

  • Cross model metric, a metric that is built from metrics across multiple semantic models

  • Cumulative metrics

  • Conversion metrics

  • Metrics which include an offset window

Formatting Fields in the Data Application Sync

Users can utilize Euno’s built-in macros using field meta to sync specific formatting like labels and value_format to LookML. See Customizing Generated LookML by Specifying Meta Fields.

Configuring the Data Application Sync

To leverage one of Euno's distinctive features, syncing your dbt changes back to your BI application, it is necessary to configure the specific data application for syncing with your dbt project.

Configuring Target Repository

From the project Configuration screen, users can link a specific branch in the project to a particular LookML file by clicking the "Sync to Data Application" button next to the branch. Clicking this button opens a dialogue box prompting you to input the target repository information. First, select the Git hosting option, GitHub or GitLab, and follow the input requirements detailed below.

Setting up this data sync ensures that with each new build from the selected job, Euno will automatically trigger a data application sync.

Configuring GitHub LookML Repository

  • Repository: The repository where the LookML files are found for the data sync.

  • Branch: The branch that will be used to push changes.

  • Directory: The target directory for the LookML files generated by Euno. By default, Euno generates a new directory: /dbt_sync.

  • SQL dialect: Users must select the SQL dialect to be written in LookML (e.g., which DW your Looker instance is connected to). By default, Snowflake is the selected dialect. Currently, the additional supported dialects that can be selected are Spark, Databricks, and Presto.

  • Selective sync: Adding a tag in the selective sync input will instruct the system to only sync models with the specified tag. Multiple tags can be input.

  • Users need to specify whether they want the sync to be automatically committed to a branch (selected by default) or have Euno create a pull request.

Configuring GitLab LookML Repository

  • Project ID: The project ID where the LookML files are found for the data sync.

  • Project token: The project token for the project where the LookML files are found. If a group-level token has been defined in the GitLab integration, this field is optional.

  • Branch: The branch that will be used to push changes.

  • Directory: The target directory for the LookML files generated by Euno. By default, Euno generates a new directory: /dbt_sync.

  • SQL dialect: Users must select the SQL dialect to be written in LookML (e.g., which DW your Looker instance is connected to). By default, Snowflake is the selected dialect. Currently, the additional supported dialects that can be selected are Spark, Databricks, and Presto.

  • Selective sync: Adding a tag in the selective sync input will instruct the system to only sync models with the specified tag. Multiple tags can be input.

  • Users need to specify whether they want the sync to be automatically committed to a branch (selected by default) or have Euno create a pull request.

Configuring LookML Repository Outside Euno

If there is an error pushing to the dbt repository due to permissions, or if you prefer to set up the configuration for the data application sync outside Euno, simply copy the configuration file from the "Preview changes" dialogue box and add a new file called project_configuration.yaml under a new directory called .delphi in your git repo, which houses the dbt project you are configuring the sync with.

This file can be easily updated at any time in your preferred code editor. However, it is important to note that the target_repo and target_branch need to exist; otherwise, the sync will fail as Euno will not automatically create anything except for the file directory where the files from the sync are added.

Customizing LookML Structure for Auto-code Generation

Euno uses Jinja2 templates to generate the LookML files from a given dbt manifest and catalog.

Out-of-the-box, every model that is selected by the tags (or all models, if no tags are specified), will automatically generate a single view file in the target directory. Users can customize the behavior by either specifying meta fields in the model or the column, or by overriding the default Euno Jinja2 macros.

Customizing Generated LookML by Specifying Meta Fields

Node Meta Fields

Meta keyDescriptionDefault

getdelphi.io/lookml_filename

Full path of the resulting view file Note: This will override lookml_directory, lookml_filename_prefix, and lookml_filename_suffix

./<model name>.view.lkml (The filepath needs to include the suffix for the file format)

getdelphi.io/lookml_directory or euno.ai/lookml_directory

Adds the file to a sub-directory within the directory configured in the data application sync setup (see configuring target repository)

No sub-diorectory by default

getdelphi.io/lookml_filename_prefix or euno.ai/lookml_filename_prefix

Adds a prefix to the view's file name (e.g. prefix_model-name.view.lkml) Note: This can be used in tandem with euno.ai/lookml_filename_suffix and euno.ai/lookml_directory, but not euno.ai/lookml_filename, which will override this value.

No filename prefix by default

getdelphi.io/lookml_filename_suffix or euno.ai/lookml_filename_suffix

Adds a suffix to the view's file name (e.g. model-name_suffix.view.lkml) Note: This can be used in tandem with euno.ai/lookml_filename_prefix and euno.ai/lookml_directory, but not euno.ai/lookml_filename, which will override this value.

No filename suffix by default

getdelphi.io/lookml_sql_table_schema

Schema to use for the table

Schema specified in the manifest file

getdelphi.io/lookml_sql_table_name

Name of the table

Table name specified in the manifest file

euno.ai/lookml_view_name or getdelphi.io/lookml_view_name

Name of the view

Model name

euno.ai/lookml_view_name_prefix

Adds a prefix to the default view name (e.g. prefix_model-name) Note: This can be used in tandem with euno.ai/lookml_view_name_suffix, but not euno.ai/lookml_view_name, which will override this value.

No view name prefix by default

euno.ai/lookml_view_name_suffix

Adds a suffix to the default view name (e.g. model-name_suffix) Note: This can be used in tandem with euno.ai/lookml_view_name_prefix, but not euno.ai/lookml_view_name, which will override this value.

No view name suffix by default

getdelphi.io/lookml_sync_timeframes or euno.ai/lookml_sync_timeframes

Only relevant for time dimensions. Overrides ALL the default timeframes within the view for a timestamp or date column. This is a comma separated list of time grains. Note: If this key is used at both the model and column level, the more specific option, the column, will override.

raw, time, hour_of_day, date, day_of_week, week, month, quarter, year

getdelphi.io/lookml_sync_convert_tz or euno.ai/lookml_sync_convert_tz

Only relevant for time dimensions. Overrides the default for converting by timezone in ALL the time and date dimensions in the view. Note: If this key is used at both the model and column level, the more specific option, the column, will override.

The default is set to yes.

Column Meta Fields

By default, Delphi will generate a single dimension clause for each column and a single measure for each dbt metric (MetricFlow).

Please note that only simple metrics and ratios are currently supported for dbt Metrics. In addition, we do not support metrics across multiple dbt models.

Meta field/Config key/TagDescriptionDefault

getdelphi.io/lookml_label

Overrides lookml label for the field

No label

getdelphi.io/lookml_view_label

Overrides the lookml view the field is placed

getdelphi.io/lookml_group_label

Overrides the field in lookml group_label

No group label

getdelphi.io/lookml_hidden

Overrides the field in lookml hidden

Not hidden

getdelphi.io/lookml_value_format

Overrides the field in lookml value_format

No value format

getdelphi.io/lookml_value_format_name

Overrides the field in lookml value_format_name

No value format name

getdelphi.io/lookml_extra

For this specific key we expect users to insert a string with a lookml compliment fragment to be placed under the dimension or measure. For example "can_filter: yes"

No extra fields

getdelphi.io/lookml_tags

Overrides fields tags in the lookml file

Use the tags from the metric or column

getdelphi.io/lookml_sync_sql

Overrides the sql used for this dimension, or measure

For dimension - ${TABLE}.<column name> For measure:

  • Simple - "expr" attribute of underlying measure in dbt

  • Ratio - ${measure}/${measure}

getdelphi.io/lookml_sync_dimension_name

Only relevant for dimensions. Overrides the name of the dimension

Column name used

getdelphi.io/lookml_sync_measure_name

Only relevant for measures. Overrides the name of the measure

Measure name used

getdelphi.io/lookml_primary_key

Only relevant for dimension. Overrides the primary key of the dimension

The primary key of the column, if it exists

getdelphi.io/skip_lookml_sync

Set this tag to skip this column/metric

The column/metric is included in the sync

getdelphi.io/lookml_sync_timeframes or euno.ai/lookml_sync_timeframes

Only relevant for time dimensions. Overrides the default timeframes for a timestamp or date column. This is a comma separated list of time grains.

raw, time, hour_of_day, date, day_of_week, week, month, quarter, year

getdelphi.io/lookml_sync_convert_tz or euno.ai/lookml_sync_convert_tz

Only relevant for time dimensions. Overrides the default for converting by timezone.

The default is set to yes.

getdelphi.io/lookml_filters

Only relevant for measures. Overrides the filter of the measure.

No filter

To configure any of the above options:

  • For columns - Insert the meta key & and overriding value underneath the column in the YML file the model is found.

  • For metrics - Insert the config key and overriding value in metric's YML file underneath the config key.

Customizing Generated LookML by Overriding Built-in Macros[

Euno will process any file in the dbt’s repository, under the directory .delphi/lookml_sync/macros/ as a Jinja2 template, and override any build-in macros found in those files.

Note: The macro overrides are taken from the head of a branch, while the sync is triggered by a dbt build. This means that if a macro is changed or removed, and a build or revision occurs in between these changes, the macro override changes might not take effect until the next build or revision occurs.

Deploying LookML Changes Made in GitHub to Looker

Euno syncs to LookML any changes introduced to dbt, by utilizing the GitHub integration to commit changes directly to the LookML repository in GitHub. However, Looker does not automatically pull these changes from GitHub and deploy them to the production environment.

You have the option to deploy changes to the project's production environment in Looker either manually for every commit or by setting up automatic pushes from the master branch.

Note: This step is crucial to ensure a successful sync with Looker.

Manually

To manually deploy the changes from a branch to the Looker’s production environment, follow the following steps from within Looker:

  • Enter “development mode”

  • Go to “Develop”, and pick the Looker project

  • Go to “Git Actions”

  • Click “Pull from…” and pick “Pull from remote”

  • Once the operation is done, click “Deploy to Production”

Automatically

Users can take advantage of Looker’s built-in Advanced deploy mode capability so that changes would automatically be deployed using either a webhook, API endpoint or manually using the deployment manager.

For Looker configurations involving GitHub, we can recommend configuring a webhook so that commits into the master branch would be automatically applied in Looker.

For more detailed instructions see Google’s instructions.

PreviousAutomationsNextData Application Workflows

Last updated