Creating a Standard Data Flow Spec Reference

A standard Data Flow Spec is the most basic type of Data Flow Spec and is suited to basic use cases where you are performing 1:1 ingestion or loads. It is particularly suited to Bronze Ingestion Use Cases.

Example:

The below demonstrates a standard Data Flow Spec for a Bronze ingestion use case (refer to patterns_streaming_basic_1_to_1 for more information):

{
    "dataFlowId": "crm_1",
    "dataFlowGroup": "crm",
    "dataFlowType": "standard",
    "sourceType": "delta",
    "sourceSystem": "crm",
    "sourceViewName": "v_customer_address",
    "sourceDetails": {
        "database": "source_db",
        "table": "customer_address",
        "cdfEnabled": true,
        "schemaPath": "schemas/customer_address.json"
    },
    "mode": "stream",
    "targetFormat": "delta",
    "targetDetails": {
        "table": "customer_address",
        "tableProperties": {
            "delta.autoOptimize.optimizeWrite": "true",
            "delta.autoOptimize.autoCompact": "true"
        },
        "partitionColumns": ["country_code"],
        "schemaPath": "schemas/customer_address.json"
    },
    "dataQualityExpectationsEnabled": true,
    "quarantineMode": "table",
    "quarantineTargetDetails": {
        "targetFormat": "delta",
        "table": "customer_address_quarantine",
        "tableProperties": {}
    },
    "cdcSettings": {
        "keys": ["address_id"],
        "sequence_by": "updated_timestamp",
        "scd_type": "2",
        "where": "",
        "ignore_null_updates": true,
        "except_column_list": ["updated_timestamp"],
        "apply_as_deletes": "DELETE_FLAG = True"
    }
}

dataFlowId: crm_1
dataFlowGroup: crm
dataFlowType: standard
sourceType: delta
sourceSystem: crm
sourceViewName: v_customer_address
sourceDetails:
  database: source_db
  table: customer_address
  cdfEnabled: true
  schemaPath: schemas/customer_address.json
mode: stream
targetFormat: delta
targetDetails:
  table: customer_address
  tableProperties:
    delta.autoOptimize.optimizeWrite: 'true'
    delta.autoOptimize.autoCompact: 'true'
  partitionColumns:
    - country_code
  schemaPath: schemas/customer_address.json
dataQualityExpectationsEnabled: true
quarantineMode: table
quarantineTargetDetails:
  targetFormat: delta
  table: customer_address_quarantine
  tableProperties: {}
cdcSettings:
  keys:
    - address_id
  sequence_by: updated_timestamp
  scd_type: '2'
  where: ''
  ignore_null_updates: true
  except_column_list:
    - updated_timestamp
  apply_as_deletes: DELETE_FLAG = True

The above dataflow spec sample contains the following core components:

Dataflow metadata configuration

Source configuration

Target configuration

Data quality and quarantine settings

CDC (SCD2) configuration

The following sections detail each of the above components.

Dataflow Metadata Configuration

These properties define the basic identity and type of the dataflow:

Field	Type	Description
dataFlowId	`string`	A unique identifier for the data flow.
dataFlowGroup	`string`	The group to which the data flow belongs, can be the same as dataFlowId if there is no group.
dataFlowType	`string`	The type of data flow. It can be either flow or standard. Supported: [“flow”, “standard”]

Source Configuration

These properties define the source of the data:

Field	Type	Description
sourceSystem (optional)	`string`	The source system name. Value is not used to determine or change any behaviour, required if dataFlowType is standard.
sourceType	`string`	The type of source, required if dataFlowType is standard. Supported: `cloudFiles`, `delta`, `deltaJoin`, `kafka`
sourceViewName	`string`	The name to assign the source view, required if dataFlowType is standard. String Pattern: v_([A-Za-z0-9_]+)
sourceDetails	`object`	See Data Flow Spec - Source Details for more information.

Target Configuration

These properties define where and how the data will be written:

Field	Type	Description
mode	`string`	The mode of the data flow. Supported: `["stream", "batch"]`
targetFormat	`string`	The format of the target data. If the format is delta, additional targetDetails must be provided.
targetDetails	`object`	See Target Details Reference.

Change Data Capture (CDC) Configuration

The cdcSettings and cdcSnapshotSettings enable and pass configuration info to the CDC API’s.

Field	Type	Description
cdcSettings	`object`	See cdcSettings for more information.
cdcSnapshotSettings	`object`	See cdcSnapshotSettings for more information.

cdcSettings

The cdcSettings object contains the following properties:

Parameter	Type	Description
keys	`list`	The column or combination of columns that uniquely identify a row in the source data. This is used to identify which CDC events apply to specific records in the target table.
sequence_by	str	The column name specifying the logical order of CDC events in the source data. Delta Live Tables uses this sequencing to handle change events that arrive out of order.
scd_type	`string`	Whether to store records as SCD type 1 or SCD type 2. Set to `1` for SCD type 1 or 2 for SCD type `2`.
apply_as_deletes	`string`	(optional) Specifies when a CDC event should be treated as a DELETE rather than an upsert.
where	`string`	(optional) Filter the rows by a condition.
ignore_null_updates	`boolean`	(optional) Allow ingesting updates containing a subset of the target columns. When a CDC event matches an existing row and ignore_null_updates is True, columns with a null retain their existing values in the target. This also applies to nested columns with a value of null. When ignore_null_updates is False, existing values are overwritten with null values.
except_column_list	`list`	(optional) A list of columns to exclude from the upsert into the target table.
track_history_column_list track_history_except_column_list	`list`	A subset of output columns to be tracked for history in the target table. Use track_history_column_list to specify the complete list of columns to be tracked. Use track_history_except_column_list to specify the columns to be excluded from tracking.

cdcSnapshotSettings

The cdcSnapshotSettings object contains the following properties:

Parameter	Type	Description
keys	`list`	The column or combination of columns that uniquely identify a row in the source data. This is used to identify which CDC events apply to specific records in the target table.
snapshotType	str	The type of snapshot to process. Set to `periodic` for periodic snapshots or `historical` for historical snapshots (refer to CDC Historical Snapshot Source Configuration for which type to use). Note that `historical` snapshot types are not supported in `flow` data flow types.
scd_type	`string`	Whether to store records as SCD type 1 or SCD type 2. Set to `1` for SCD type 1 or 2 for SCD type `2`.
sourceType	`string`	The type of source to ingest the snapshots from. Set to `file` for file based sources.
source	`object`	The source to ingest the snapshots from. This is required for `historical` snapshot types. See CDC Historical Snapshot Source Configuration for more information.
track_history_column_list	`list`	(optional) A subset of output columns to be tracked for history in the target table. Use this to specify the complete list of columns to be tracked. This cannot be used in conjunction with `track_history_except_column_list`.
track_history_except_column_list	`list`	(optional) A subset of output columns to be excluded from history tracking in the target table. Use this to specify which columns should not be tracked. This cannot be used in conjunction with `track_history_column_list`.

CDC Historical Snapshot Source Configuration

The source object contains the following properties for file based sources:

Parameter

Type

Description

format

string

The format of the source data. E.g. supported formats are table, parquet, csv, json. All formats supported by spark see PySpark Data Sources API.

path

string

The location to load the source data from. This can be a table name or a path to a a file or directory with multiple snapshots. A placeholder {version} can be used in this path which will be substituted with the version value in run time.

versionType

string

The type of versioning to use. Can be either int or datetime.

datetimeFormat

string

(conditional) Required if versionType is datetime. The format of startingVersion datetime value.

microSecondMaskLength

integer

(optional) WARNING: Edge Cases Only! - Specify this if your versionType is datetime and your filename includes microsends, but not the full 6 digits. The number of microsecond digits to included at the end of the datetime value. - The default value is 6.

startingVersion

string or integer

(optional) The version to start processing from.

readerOptions

object

(optional) Additional options to pass to the reader.

schemaPath

string

(optional) The schema path to use for the source data.

selectExp

list

(optional) A list of select expressions to apply to the source data.

filter

string

(optional) A filter expression to apply to the source data. This filter is applied to the dataframe as a WHERE clause when the source is read. A placeholder {version} can be used in this filter expression which will be substituted with the version value in run time.

recursiveFileLookup

boolean

(optional) When set to true, enables recursive directory traversal to find snapshot files. This should be used when snapshots are stored in a nested directory structure such as Hive-style partitioning (e.g., /data/{version}/file.parquet). When set to false (default), only files in the immediate directory are searched. Default: false.

Note

If recursiveFileLookup is set to true, ensure that the path parameter is specified in a way that is compatible with recursive directory traversal. I.e. the {version} placeholder is used in the path and not the filename.

The source object contains the following properties for table based sources:

Parameter

Type

Description

table

string

The table name to load the source data from.

versionColumn

string

The column name to use for versioning.

startingVersion

string or integer

(optional) The version to start processing from.

selectExp

list

(optional) A list of select expressions to apply to the source data.

Data Quality and Quarantine Configuration

These properties control how data quality issues are handled:

Field	Type	Description
dataQualityExpectationsEnabled (optional)	`boolean`	A flag indicating whether data quality expectations are enabled (see Data Quality - Quarantine).
dataQualityExpectationsPath (optional)	`string`	Either a relative path or filename for the expectations file. Note that the framework automatically calculates all relative paths from the appropriate expectations sub-folder, in the Pipeline Bundle. Examples: All expectations files in the `expectations` sub-folder: `.` or `*` A specific expectations file: `my_table_dqe.json`
quarantineMode (optional)	`string`	The mode for handling quarantined data. It can be off, flag, or table. Supported: [“off”, “flag”, “table”]
quarantineTargetDetails (optional)	`object`	Details about the quarantine target, only required if `quarantineMode` is set to `table`. See quarantineTargetDetails section below.

quarantineTargetDetails

The quarantineTargetDetails object contains the following properties:

Parameter	Type	Description
targetFormat	`string`	The format of the quarantine target. Currently, only `delta` is supported. Supported: `["delta"]` Default: `"delta"`
table	`string`	(conditional) The table name, required if `targetFormat` is `delta`.
tableProperties	`object`	(conditional) Additional properties for the table, required if `targetFormat` is `delta`.
path	`string`	(conditional) The path to the table, required if `targetFormat` is `delta`.

Table Migration Configuration

These properties control table migration:

Field	Type	Description
tableMigrationDetails (optional)	`object`	Details about table migration, only required if a table migration is needed. See Table Migration Details section below.

tableMigrationDetails

The tableMigrationDetails object contains the following properties:

Property	Type	Description
enabled	`boolean`	A flag indicating whether table migration is enabled.
catalogType	`string`	The type of catalog, either hms or uc. Supported values: [“hms”, “uc”]
autoStartingVersionsEnabled (optional)	`boolean`	Flag to enable automatic starting version management. When enabled, the system automatically tracks source table versions and manages starting versions for views. Defaults to `true`.
sourceDetails	`object`	Details about the source for migration. See sourceDetails.

sourceDetails

The sourceDetails object can potentially cater to different types of sources but is currently limited to the following:

sourceMigrateDelta

sourceMigrateDelta

The sourceMigrateDelta object contains the following properties:

Field	Type	Description
database	`string`	The database name.
table	`string`	The table name.
selectExp (optional)	`array` (items: `string`)	An array of select expressions.
whereClause (optional)	`array` (items: `string`)	An array of where clauses.
exceptColumns (optional)	`array` (items: `string`)	An array of columns to exclude.