{
  "$result_object_key": {
    "estimated_row_count": 1000,
    "partition": "2025-03-17",
    "schema_differences": [
      {
        "description": "Number of visits of this patient",
        "field": "number_of_visits",
        "field_addition": {},
        "field_type": "INTEGER",
        "field_update": {
          "new_description": "Number of visits of this patient",
          "new_field_type": "STRING",
          "new_repeated": true,
          "new_required": false
        },
        "nested_field_changes": null,
        "repeated": false,
        "required": true
      }
    ],
    "table_name": "healthie_patient_updated",
    "table_schema": [
      {
        "description": "Number of visits of this patient",
        "fields": null,
        "name": "number_of_visits",
        "repeated": false,
        "required": true,
        "type": "INTEGER"
      }
    ]
  }
}

{
  "$result_object_key": {
    "estimated_row_count": "Estimated total number of rows including the data just inserted",
    "partition": "Date partition the data was saved to",
    "schema_differences": {
      "description": "Field description",
      "field": "Field name",
      "field_addition": {},
      "field_type": "Field type",
      "field_update": {
        "new_description": "New description",
        "new_field_type": "New field type",
        "new_repeated": "New value for whether the field is a list",
        "new_required": "New value for whether the field is required"
      },
      "nested_field_changes": null,
      "repeated": "If the field is a list",
      "required": "If the field is required"
    },
    "table_name": "Table name used to save the data",
    "table_schema": {
      "description": "Field description",
      "fields": null,
      "name": "Field name",
      "repeated": "If the field is a list",
      "required": "If the field is required",
      "type": "Field type"
    }
  }
}

{
  "$result_object_key": {
    "estimated_row_count": 1000,
    "partition": "2025-03-17",
    "schema_differences": [
      {
        "description": "Number of visits of this patient",
        "field": "number_of_visits",
        "field_addition": {},
        "field_type": "INTEGER",
        "field_update": {
          "new_description": "Number of visits of this patient",
          "new_field_type": "STRING",
          "new_repeated": true,
          "new_required": false
        },
        "nested_field_changes": null,
        "repeated": false,
        "required": true
      }
    ],
    "table_name": "healthie_patient_updated",
    "table_schema": [
      {
        "description": "Number of visits of this patient",
        "fields": null,
        "name": "number_of_visits",
        "repeated": false,
        "required": true,
        "type": "INTEGER"
      }
    ]
  }
}

{
  "$result_object_key": {
    "estimated_row_count": "Estimated total number of rows including the data just inserted",
    "partition": "Date partition the data was saved to",
    "schema_differences": {
      "description": "Field description",
      "field": "Field name",
      "field_addition": {},
      "field_type": "Field type",
      "field_update": {
        "new_description": "New description",
        "new_field_type": "New field type",
        "new_repeated": "New value for whether the field is a list",
        "new_required": "New value for whether the field is required"
      },
      "nested_field_changes": null,
      "repeated": "If the field is a list",
      "required": "If the field is required"
    },
    "table_name": "Table name used to save the data",
    "table_schema": {
      "description": "Field description",
      "fields": null,
      "name": "Field name",
      "repeated": "If the field is a list",
      "required": "If the field is required",
      "type": "Field type"
    }
  }
}

Getting Started

Automate your healthcare workflows with Google BigQuery integrations and Morf. BigQuery is a cloud-based data warehouse for analyzing and querying large datasets. Save event data from a Morf workflow to a BigQuery table.

Grant Morf access to BigQuery

Create a new dataset. This recommended approach to dataset management ensures Morf only has access to the necessary tables. Follow Google’s instructions on creating a new dataset.
Share your dataset with Morf. Follow Google’s instructions on granting access to a dataset.
- Role: BigQuery Data Editor (roles/bigquery.dataEditor)
- Email: primary-workload-sa@morf-prod-5f7d.iam.gserviceaccount.com

This role should be granted at the dataset level so Morf doesn’t have unneccessary access to other data.

Use Morf’s Save to BigQuery action to store event data directly in BigQuery from a workflow.

Parameters

Hide parameters

string

required

This field maps to the destination API projectID field.

string

required

This field maps to the destination API datasetID field.

string

This field maps to the destination API tableName field.

Map<string,dynamic (any)>

HI ID PII This field maps to the destination API fields field.

bool

This field maps to the destination API additionallyIncludeEventFieldsAtTheTopLevel field.

{
  "$result_object_key": {
    "estimated_row_count": 1000,
    "partition": "2025-03-17",
    "schema_differences": [
      {
        "description": "Number of visits of this patient",
        "field": "number_of_visits",
        "field_addition": {},
        "field_type": "INTEGER",
        "field_update": {
          "new_description": "Number of visits of this patient",
          "new_field_type": "STRING",
          "new_repeated": true,
          "new_required": false
        },
        "nested_field_changes": null,
        "repeated": false,
        "required": true
      }
    ],
    "table_name": "healthie_patient_updated",
    "table_schema": [
      {
        "description": "Number of visits of this patient",
        "fields": null,
        "name": "number_of_visits",
        "repeated": false,
        "required": true,
        "type": "INTEGER"
      }
    ]
  }
}

{
  "$result_object_key": {
    "estimated_row_count": "Estimated total number of rows including the data just inserted",
    "partition": "Date partition the data was saved to",
    "schema_differences": {
      "description": "Field description",
      "field": "Field name",
      "field_addition": {},
      "field_type": "Field type",
      "field_update": {
        "new_description": "New description",
        "new_field_type": "New field type",
        "new_repeated": "New value for whether the field is a list",
        "new_required": "New value for whether the field is required"
      },
      "nested_field_changes": null,
      "repeated": "If the field is a list",
      "required": "If the field is required"
    },
    "table_name": "Table name used to save the data",
    "table_schema": {
      "description": "Field description",
      "fields": null,
      "name": "Field name",
      "repeated": "If the field is a list",
      "required": "If the field is required",
      "type": "Field type"
    }
  }
}

Result Object Field Details

You can use the result of the action’s data as inputs to downstream workflow actions. Each fetch action requires an object name, which nests the action’s result data inside the downstream data context in the workflow. See Passing Data Between Actions for how to set it and reference the result from downstream nodes. Here we demonstrate how to refer to this data using the prefix $result_object_key.

Fetch Action Response Object

Hide fields

values.v1.Date

required

Date partition the data was saved to

CEL

$result_object_key.partition

Example

"2025-03-17"

uint64

required

Estimated total number of rows including the data just inserted

CEL

$result_object_key.estimated_row_count

Example

[]object

required

Description coming soon

CEL

$result_object_key.schema_differences

Example

[
{
"description": "Number of visits of this patient",
"field": "number_of_visits",
"field_addition": {},
"field_type": "INTEGER",
"field_update": {
"new_description": "Number of visits of this patient",
"new_field_type": "STRING",
"new_repeated": true,
"new_required": false
},
"nested_field_changes": null,
"repeated": false,
"required": true
}
]

[]string

required

Mapped array of: Field name

CEL

$result_object_key.schema_differences.map(x, x.field)

Example

[
"number_of_visits"
]

[]string

required

Mapped array of: Field description

CEL

$result_object_key.schema_differences.map(x, x.description)

Example

[
"Number of visits of this patient"
]

google.bigquery.v1.FieldType

required

Mapped array of: Field type

CEL

field_type

Example

google.bigquery.v1.FieldType.STRING
google.bigquery.v1.FieldType.BYTES
google.bigquery.v1.FieldType.INTEGER
google.bigquery.v1.FieldType.FLOAT
google.bigquery.v1.FieldType.BOOLEAN
google.bigquery.v1.FieldType.TIMESTAMP
google.bigquery.v1.FieldType.RECORD
google.bigquery.v1.FieldType.DATE
google.bigquery.v1.FieldType.TIME
google.bigquery.v1.FieldType.DATETIME
google.bigquery.v1.FieldType.NUMERIC
google.bigquery.v1.FieldType.GEOGRAPHY
google.bigquery.v1.FieldType.BIGNUMERIC
google.bigquery.v1.FieldType.INTERVAL
google.bigquery.v1.FieldType.JSON
google.bigquery.v1.FieldType.RANGE

[]bool

required

Mapped array of: If the field is a list

CEL

$result_object_key.schema_differences.map(x, x.repeated)

Example

[
false
]

[]bool

required

Mapped array of: If the field is required

CEL

$result_object_key.schema_differences.map(x, x.required)

Example

[
true
]

[]bool

required

Description coming soon

CEL

$result_object_key.schema_differences.map(x, x.nested_field_changes)

Example

[
[
{
"description": "Number of visits of this patient",
"field": "number_of_visits",
"field_addition": {},
"field_type": "INTEGER",
"field_update": {
  "new_description": "Number of visits of this patient",
  "new_field_type": "STRING",
  "new_repeated": true,
  "new_required": false
},
"nested_field_changes": null,
"repeated": false,
"required": true
}
]
]

[]bool

required

Description coming soon

CEL

$result_object_key.schema_differences.map(x, x.field_addition)

Example

[
{}
]

[]bool

required

Description coming soon

CEL

$result_object_key.schema_differences.map(x, x.field_update)

Example

[
{
"new_description": "Number of visits of this patient",
"new_field_type": "STRING",
"new_repeated": true,
"new_required": false
}
]

google.bigquery.v1.FieldType

New field type

CEL

field_update.new_field_type

Example

google.bigquery.v1.FieldType.STRING
google.bigquery.v1.FieldType.BYTES
google.bigquery.v1.FieldType.INTEGER
google.bigquery.v1.FieldType.FLOAT
google.bigquery.v1.FieldType.BOOLEAN
google.bigquery.v1.FieldType.TIMESTAMP
google.bigquery.v1.FieldType.RECORD
google.bigquery.v1.FieldType.DATE
google.bigquery.v1.FieldType.TIME
google.bigquery.v1.FieldType.DATETIME
google.bigquery.v1.FieldType.NUMERIC
google.bigquery.v1.FieldType.GEOGRAPHY
google.bigquery.v1.FieldType.BIGNUMERIC
google.bigquery.v1.FieldType.INTERVAL
google.bigquery.v1.FieldType.JSON
google.bigquery.v1.FieldType.RANGE

[]object

required

Description coming soon

CEL

$result_object_key.table_schema

Example

[
{
"description": "Number of visits of this patient",
"fields": null,
"name": "number_of_visits",
"repeated": false,
"required": true,
"type": "INTEGER"
}
]

[]string

required

Mapped array of: Field name

CEL

$result_object_key.table_schema.map(x, x.name)

Example

[
"number_of_visits"
]

google.bigquery.v1.FieldType

required

Mapped array of: Field type

CEL

type

Example

google.bigquery.v1.FieldType.STRING
google.bigquery.v1.FieldType.BYTES
google.bigquery.v1.FieldType.INTEGER
google.bigquery.v1.FieldType.FLOAT
google.bigquery.v1.FieldType.BOOLEAN
google.bigquery.v1.FieldType.TIMESTAMP
google.bigquery.v1.FieldType.RECORD
google.bigquery.v1.FieldType.DATE
google.bigquery.v1.FieldType.TIME
google.bigquery.v1.FieldType.DATETIME
google.bigquery.v1.FieldType.NUMERIC
google.bigquery.v1.FieldType.GEOGRAPHY
google.bigquery.v1.FieldType.BIGNUMERIC
google.bigquery.v1.FieldType.INTERVAL
google.bigquery.v1.FieldType.JSON
google.bigquery.v1.FieldType.RANGE

[]bool

required

Mapped array of: If the field is a list

CEL

$result_object_key.table_schema.map(x, x.repeated)

Example

[
false
]

[]bool

required

Mapped array of: If the field is required

CEL

$result_object_key.table_schema.map(x, x.required)

Example

[
true
]

[]string

required

Mapped array of: Field description

CEL

$result_object_key.table_schema.map(x, x.description)

Example

[
"Number of visits of this patient"
]

[]bool

required

Description coming soon

CEL

$result_object_key.table_schema.map(x, x.fields)

Example

[
[
{
"description": "Number of visits of this patient",
"fields": null,
"name": "number_of_visits",
"repeated": false,
"required": true,
"type": "INTEGER"
}
]
]

string

required

Table name used to save the data

CEL

$result_object_key.table_name

Example

"healthie_patient_updated"

Events

Actions

Save To Bigquery

Getting Started

Grant Morf access to BigQuery

Parameters

Result Object Field Details

​Getting Started

​Grant Morf access to BigQuery

​Parameters

​Result Object Field Details

Getting Started

Grant Morf access to BigQuery

Parameters

Result Object Field Details