Renomear uma tabela ingerida

Aplica-se a : Criação de pipeline baseado em API

Por default, as tabelas de destino criadas pelo pipeline de ingestão gerenciar LakeFlow Connect têm o mesmo nome das tabelas de origem. No entanto, você pode, opcionalmente, renomear uma tabela ingerida. Por exemplo, se você ingerir um objeto em duas tabelas de destino no mesmo esquema, precisará renomear uma das tabelas de destino para diferenciá-las (não há suporte para duplicatas). Se o senhor renomear uma tabela no pipeline, ela se tornará um pipeline somente de API e não será mais possível editar o pipeline na interface do usuário.

Exemplo: Google analítica

Databricks Asset Bundles

YAML

resources:
  pipelines:
    pipeline_ga4:
      name: <pipeline-name>
      catalog: <target-catalog>	# Location of the pipeline event log
      schema: <target-schema> # Location of the pipeline event log
      ingestion_definition:
        connection_name: <connection>
        objects:
	        - table:
              source_url: <project-id>
              source_schema: <property-name>
              destination_catalog: <target-catalog>
              destination_schema: <target-schema>
              destination_table: <custom-target-table-name> # Table rename

Databricks notebook

Google analítica:

Python

pipeline_spec = """
{
  "name": "<pipeline>",
  "ingestion_definition": {
    "connection_name": "<connection>",
    "objects": [
      {
        "table": {
          "source_catalog": "<project-id>",
          "source_schema": "<property-name>",
          "source_table": "<source-table>",
          "destination_catalog": "<target-catalog>",
          "destination_schema": "<target-schema>",
          "destination_table": "<custom-target-table-name>",
        }
      }
    ]
  }
}
"""

Databricks CLI

JSON

{
  "resources": {
    "pipelines": {
      "pipeline_ga4": {
        "name": "<pipeline>",
        "catalog": "<target-catalog>",
        "schema": "<target-schema>",
        "ingestion_definition": {
          "connection_name": "<connection>",
          "objects": [
            {
              "table": {
                "source_url": "<project-id>",
                "source_schema": "<property-name>",
                "destination_catalog": "<destination-catalog>",
                "destination_schema": "<destination-schema>",
                "destination_table": "<custom-destination-table-name>"
              }
            }
          ]
        }
      }
    }
  }
}

Exemplo: Salesforce

Databricks Asset Bundles

YAML

resources:
  pipelines:
    pipeline_sfdc:
      name: <pipeline-name>
      catalog: <target-catalog>	# Location of the pipeline event log
      schema: <target-schema> # Location of the pipeline event log
      ingestion_definition:
        connection_name: <connection>
        objects:
	        - table:
              source_schema: <source-schema>
              source_table: <source-table>
              destination_catalog: <target-catalog>
              destination_schema: <target-schema>
              destination_table: <custom-target-table-name> # Table rename

Databricks notebook

Python

pipeline_spec = """
{
  "name": "<pipeline>",
  "ingestion_definition": {
    "connection_name": "<connection>",
    "objects": [
      {
        "table": {
          "source_catalog": "<source-catalog>",
          "source_schema": "<source-schema>",
          "source_table": "<source-table>",
          "destination_catalog": "<target-catalog>",
          "destination_schema": "<target-schema>",
          "destination_table": "<custom-target-table-name>",
        }
      }
    ]
  }
}
"""

Databricks CLI

JSON

{
  "resources": {
    "pipelines": {
      "pipeline_sfdc": {
        "name": "<pipeline>",
        "catalog": "<target-catalog>",
        "schema": "<target-schema>",
        "ingestion_definition": {
          "connection_name": "<connection>",
          "objects": [
            {
              "table": {
                "source_schema": "<source-schema>",
                "source_table": "<source-table>",
                "destination_catalog": "<destination-catalog>",
                "destination_schema": "<destination-schema>",
                "destination_table": "<custom-destination-table-name>"
              }
            }
          ]
        }
      }
    }
  }
}

Exemplo: Dia de trabalho

Databricks Asset Bundles

YAML

resources:
  pipelines:
    pipeline_workday:
      name: <pipeline>
      catalog: <target-catalog>	# Location of the pipeline event log
      schema: <target-schema> # Location of the pipeline event log
      ingestion_definition:
        connection_name: <connection>
        objects:
	        - report:
              source_url: <report-url>
              destination_catalog: <target-catalog>
              destination_schema: <target-schema>
              destination_table: <custom-target-table-name> # Table rename

Databricks notebook

Python

pipeline_spec = """
{
  "name": "<pipeline>",
  "ingestion_definition": {
    "connection_name": "<connection>",
    "objects": [
      {
        "report": {
          "source_url": "<report-url>",
          "destination_catalog": "<target-catalog>",
          "destination_schema": "<target-schema>",
          "destination_table": "<custom-target-table-name>",
        }
      }
    ]
  }
}
"""

Databricks CLI

JSON

{
  "resources": {
    "pipelines": {
      "pipeline_workday": {
        "name": "<pipeline>",
        "catalog": "<target-catalog>",
        "schema": "<target-schema>",
        "ingestion_definition": {
          "connection_name": "<connection>",
          "objects": [
            {
              "report": {
                "source_url": "<report-url>",
                "destination_catalog": "<destination-catalog>",
                "destination_schema": "<destination-schema>",
                "destination_table": "<custom-destination-table-name>"
              }
            }
          ]
        }
      }
    }
  }
}