使用 Azure 数据工厂在 Azure Blob 存储中复制和转换数据Copy and transform data in Azure Blob storage by using Azure Data Factory

适用于: 是 Azure 数据工厂是 Azure Synapse Analytics(预览版)APPLIES TO: yesAzure Data Factory yesAzure Synapse Analytics (Preview)

本文概述如何使用 Azure 数据工厂中的复制活动从/向 Azure Blob 存储复制数据。This article outlines how to use Copy Activity in Azure Data Factory to copy data from and to Azure Blob storage. 若要了解 Azure 数据工厂,请阅读介绍性文章To learn about Azure Data Factory, read the introductory article.

Tip

对于数据湖或数据仓库迁移方案,请从使用 Azure 数据工厂将数据从数据湖或数据仓库迁移到 Azure 了解更多信息。For data lake or data warehouse migration scenario, learn more from Use Azure Data Factory to migrate data from your data lake or data warehouse to Azure.

支持的功能Supported capabilities

以下活动支持此 Azure Blob 连接器:This Azure Blob connector is supported for the following activities:

对于复制活动,此 Blob 存储连接器支持:For Copy activity, this Blob storage connector supports:

  • 向/从常规用途的 Azure 存储帐户和热/冷 Blob 存储复制 Blob。Copying blobs to and from general-purpose Azure storage accounts and hot/cool blob storage.
  • 使用帐户密钥身份验证、服务共享访问签名身份验证、服务主体身份验证或 Azure 资源的托管标识身份验证复制 Blob。Copying blobs by using account key, service shared access signature, service principal or managed identities for Azure resources authentications.
  • 从块、追加或页 Blob 中复制 Blob,并将数据仅复制到块 Blob。Copying blobs from block, append, or page blobs and copying data to only block blobs.
  • 按原样复制 Blob,或者使用支持的文件格式和压缩编解码器分析或生成 Blob。Copying blobs as is or parsing or generating blobs with supported file formats and compression codecs.
  • 在复制期间保留文件元数据Preserve file metadata during copy.

Important

如果在 Azure 存储防火墙设置上启用了“允许信任的 Microsoft 服务访问此存储帐户” 选项,并且要使用 Azure 集成运行时连接到 Blob 存储,则必须使用托管标识身份验证If you enable the Allow trusted Microsoft services to access this storage account option on Azure Storage firewall settings and want to use Azure integration runtime to connect to your Blob Storage, you must use managed identity authentication.

入门Get started

可以通过以下工具或 SDK 之一结合使用复制活动和管道。You can use one of the following tools or SDKs to use the copy activity with a pipeline. 选择链接,查看分步说明:Select a link for step-by-step instructions:

对于特定于 Blob 存储的数据工厂实体,以下部分提供了有关用于定义这些实体的属性的详细信息。The following sections provide details about properties that are used to define Data Factory entities specific to Blob storage.

链接服务属性Linked service properties

Azure Blob 连接器支持以下身份验证类型,有关详细信息,请参阅相应的部分:Azure Blob connector support the following authentication types, refer to the corresponding section on details:

Note

使用 PolyBase 将数据载入 SQL 数据仓库时,如果源或暂存 Blob 存储配置了虚拟网络终结点,则必须按照 PolyBase 的要求使用托管标识身份验证,并使用版本 3.18 或更高版本的自承载集成运行时。When using PolyBase to load data into SQL Data Warehouse, if your source or staging Blob storage is configured with Virtual Network endpoint, you must use managed identity authentication as required by PolyBase, and use Self-hosted Integration Runtime with version 3.18 or above. 请参阅托管标识身份验证部分,其中介绍了更多配置先决条件。See the managed identity authentication section with more configuration prerequisites.

Note

HDInsights 活动仅支持 Azure Blob 存储帐户密钥身份验证。HDInsights activities only support Azure Blob storage account key authentication.

帐户密钥身份验证Account key authentication

若要使用存储帐户密钥身份验证,需支持以下属性:To use storage account key authentication, the following properties are supported:

属性Property 说明Description 必需Required
typetype type 属性必须设置为 AzureBlobStorage(建议)或 AzureStorage(参阅下面的注释)。The type property must be set to AzureBlobStorage (suggested) or AzureStorage (see notes below). Yes
connectionStringconnectionString 为 connectionString 属性指定连接到存储所需的信息。Specify the information needed to connect to Storage for the connectionString property.
还可以将帐户密钥放在 Azure 密钥保管库中,并从连接字符串中拉取 accountKey 配置。You can also put account key in Azure Key Vault and pull the accountKey configuration out of the connection string. 有关更多详细信息,请参阅以下示例和在 Azure 密钥保管库中存储凭据一文。Refer to the following samples and Store credentials in Azure Key Vault article with more details.
Yes
connectViaconnectVia 用于连接到数据存储的集成运行时The integration runtime to be used to connect to the data store. 如果数据存储位于专用网络,则可以使用 Azure 集成运行时或自承载集成运行时。You can use Azure Integration Runtime or Self-hosted Integration Runtime (if your data store is in a private network). 如果未指定,则使用默认 Azure Integration Runtime。If not specified, it uses the default Azure Integration Runtime. No

Note

使用帐户密钥身份验证时,不支持辅助 Blob 服务终结点。Secondary Blob Service Endpoint is not supported when using account key authentication. 可以使用其他身份验证类型。You can use other authentication types.

Note

如果使用的是“AzureStorage”类型链接服务,它仍然按原样受支持,但建议今后使用此新的“AzureBlobStorage”链接服务类型。If you were using "AzureStorage" type linked service, it is still supported as-is, while you are suggested to use this new "AzureBlobStorage" linked service type going forward.

示例:Example:

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {
            "connectionString": "DefaultEndpointsProtocol=https;AccountName=<accountname>;AccountKey=<accountkey>;EndpointSuffix=core.chinacloudapi.cn"
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

示例:在 Azure 密钥保管库中存储帐户密钥Example: store account key in Azure Key Vault

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {
            "connectionString": "DefaultEndpointsProtocol=https;AccountName=<accountname>;EndpointSuffix=core.chinacloudapi.cn",
            "accountKey": { 
                "type": "AzureKeyVaultSecret", 
                "store": { 
                    "referenceName": "<Azure Key Vault linked service name>", 
                    "type": "LinkedServiceReference" 
                }, 
                "secretName": "<secretName>" 
            }
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }            
    }
}

共享访问签名身份验证Shared access signature authentication

共享访问签名对存储帐户中的资源提供委托访问。A shared access signature provides delegated access to resources in your storage account. 使用共享访问签名可以在指定的时间内授予客户端对存储帐户中对象的有限访问权限。You can use a shared access signature to grant a client limited permissions to objects in your storage account for a specified time. 无需共享帐户访问密钥。You don't have to share your account access keys. 共享访问签名是一个 URI,在其查询参数中包含对存储资源已验证访问所需的所有信息。The shared access signature is a URI that encompasses in its query parameters all the information necessary for authenticated access to a storage resource. 若要使用共享访问签名访问存储资源,客户端只需将共享访问签名传入到相应的构造函数或方法。To access storage resources with the shared access signature, the client only needs to pass in the shared access signature to the appropriate constructor or method. 有关共享访问签名的详细信息,请参阅共享访问签名:了解共享访问签名模型For more information about shared access signatures, see Shared access signatures: Understand the shared access signature model.

Note

若要使用共享访问签名身份验证,需支持以下属性:To use shared access signature authentication, the following properties are supported:

属性Property 说明Description 必需Required
typetype type 属性必须设置为 AzureBlobStorage(建议)或 AzureStorage(参阅下面的注释)。The type property must be set to AzureBlobStorage (suggested) or AzureStorage (see notes below). Yes
sasUrisasUri 指定存储资源(例如 Blob/容器)的共享访问签名 URI。Specify the shared access signature URI to the Storage resources such as blob/container.
将此字段标记为 SecureString,以便安全地将其存储在数据工厂中。Mark this field as a SecureString to store it securely in Data Factory. 还可以将 SAS 令牌放在 Azure 密钥保管库中,以利用自动轮换以及删除令牌部分。You can also put SAS token in Azure Key Vault to leverage auto rotation and remove the token portion. 有关更多详细信息,请参阅以下示例和在 Azure 密钥保管库中存储凭据一文。Refer to the following samples and Store credentials in Azure Key Vault article with more details.
Yes
connectViaconnectVia 用于连接到数据存储的集成运行时The integration runtime to be used to connect to the data store. 如果数据存储位于专用网络,则可以使用 Azure 集成运行时或自承载集成运行时。You can use the Azure Integration Runtime or the Self-hosted Integration Runtime (if your data store is located in a private network). 如果未指定,则使用默认 Azure Integration Runtime。If not specified, it uses the default Azure Integration Runtime. No

Note

如果使用的是“AzureStorage”类型链接服务,它仍然按原样受支持,但建议今后使用此新的“AzureBlobStorage”链接服务类型。If you were using "AzureStorage" type linked service, it is still supported as-is, while you are suggested to use this new "AzureBlobStorage" linked service type going forward.

示例:Example:

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {
            "sasUri": {
                "type": "SecureString",
                "value": "<SAS URI of the Azure Storage resource e.g. https://<container>.blob.core.chinacloudapi.cn/?sv=<storage version>&amp;st=<start time>&amp;se=<expire time>&amp;sr=<resource>&amp;sp=<permissions>&amp;sip=<ip range>&amp;spr=<protocol>&amp;sig=<signature>>"
            }
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

示例:在 Azure 密钥保管库中存储帐户密钥Example: store account key in Azure Key Vault

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {
            "sasUri": {
                "type": "SecureString",
                "value": "<SAS URI of the Azure Storage resource without token e.g. https://<container>.blob.core.chinacloudapi.cn/>"
            },
            "sasToken": { 
                "type": "AzureKeyVaultSecret", 
                "store": { 
                    "referenceName": "<Azure Key Vault linked service name>", 
                    "type": "LinkedServiceReference" 
                }, 
                "secretName": "<secretName>" 
            }
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

在创建共享访问签名 URI 时,请注意以下几点:When you create a shared access signature URI, consider the following points:

  • 根据链接服务(读取、写入、读/写)在数据工厂中的用法,设置针对对象的适当读/写权限。Set appropriate read/write permissions on objects based on how the linked service (read, write, read/write) is used in your data factory.
  • 根据需要设置“到期时间” 。Set Expiry time appropriately. 确保存储对象的访问权限不会在管道的活动期限内过期。Make sure that the access to Storage objects doesn't expire within the active period of the pipeline.
  • 应该根据需要在正确的容器/Blob 中创建 URI。The URI should be created at the right container/blob based on the need. 数据工厂可以使用 Blob 的共享访问签名 URI 访问该特定 Blob。A shared access signature URI to a blob allows Data Factory to access that particular blob. 数据工厂可以使用 Blob 存储容器的共享访问签名 URI 迭代该容器中的 Blob。A shared access signature URI to a Blob storage container allows Data Factory to iterate through blobs in that container. 以后若要提供更多/更少对象的访问权限或需要更新共享访问签名 URI,请记得使用新 URI 更新链接服务。To provide access to more or fewer objects later, or to update the shared access signature URI, remember to update the linked service with the new URI.

服务主体身份验证Service principal authentication

有关 Azure 存储服务主体身份验证的一般信息,请参阅使用 Azure Active Directory 对 Azure 存储访问进行身份验证For Azure Storage service principal authentication in general, refer to Authenticate access to Azure Storage using Azure Active Directory.

若要使用服务主体身份验证,请执行以下步骤:To use service principal authentication, follow these steps:

  1. 遵循将应用程序注册到 Azure AD 租户,在 Azure Active Directory (Azure AD) 中注册一个应用程序实体。Register an application entity in Azure Active Directory (Azure AD) by following Register your application with an Azure AD tenant. 记下下面的值,这些值用于定义链接服务:Make note of the following values, which you use to define the linked service:

    • 应用程序 IDApplication ID
    • 应用程序密钥Application key
    • 租户 IDTenant ID
  2. 授予服务主体在 Azure Blob 存储中的适当权限。Grant the service principal proper permission in Azure Blob storage. 如需了解角色的更多详情,请参阅使用 RBAC 管理对 Azure 存储数据的访问权限Refer to Manage access rights to Azure Storage data with RBAC with more details on the roles.

    • 作为源 ,在访问控制 (IAM) 中,至少授予“存储 Blob 数据读取者” 角色。As source, in Access control (IAM), grant at least Storage Blob Data Reader role.
    • 对于接收器,请在访问控制 (IAM) 中,至少授予“存储 Blob 数据参与者”角色。 As sink, in Access control (IAM), grant at least Storage Blob Data Contributor role.

Azure Blob 存储链接服务支持以下属性:These properties are supported for an Azure Blob storage linked service:

属性Property 说明Description 必需Required
typetype type 属性必须设置为 AzureBlobStorageThe type property must be set to AzureBlobStorage. Yes
serviceEndpointserviceEndpoint 使用 https://<accountName>.blob.core.chinacloudapi.cn/ 模式指定 Azure Blob 存储服务终结点。Specify the Azure Blob storage service endpoint with the pattern of https://<accountName>.blob.core.chinacloudapi.cn/. Yes
servicePrincipalIdservicePrincipalId 指定应用程序的客户端 ID。Specify the application's client ID. Yes
servicePrincipalKeyservicePrincipalKey 指定应用程序的密钥。Specify the application's key. 将此字段标记为 SecureString 以安全地将其存储在数据工厂中或引用存储在 Azure Key Vault 中的机密Mark this field as a SecureString to store it securely in Data Factory, or reference a secret stored in Azure Key Vault. Yes
tenanttenant 指定应用程序的租户信息(域名或租户 ID)。Specify the tenant information (domain name or tenant ID) under which your application resides. 将鼠标悬停在 Azure 门户右上角进行检索。Retrieve it by hovering the mouse in the top-right corner of the Azure portal. Yes
connectViaconnectVia 用于连接到数据存储的集成运行时The integration runtime to be used to connect to the data store. 如果数据存储位于专用网络,则可以使用 Azure 集成运行时或自承载集成运行时。You can use Azure Integration Runtime or Self-hosted Integration Runtime (if your data store is in a private network). 如果未指定,则使用默认 Azure Integration Runtime。If not specified, it uses the default Azure Integration Runtime. No

Note

服务主体身份验证仅受“AzureBlobStorage”类型链接服务的支持,而不受以前的“AzureStorage”类型链接服务的支持。Service principal authentication is only supported by "AzureBlobStorage" type linked service but not previous "AzureStorage" type linked service.

示例:Example:

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {            
            "serviceEndpoint": "https://<accountName>.blob.core.chinacloudapi.cn/",
            "servicePrincipalId": "<service principal id>",
            "servicePrincipalKey": {
                "type": "SecureString",
                "value": "<service principal key>"
            },
            "tenant": "<tenant info, e.g. microsoft.partner.onmschina.cn>" 
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

Azure 资源的托管标识身份验证Managed identities for Azure resources authentication

可将数据工厂与代表此特定数据工厂的 Azure 资源托管标识相关联。A data factory can be associated with a managed identity for Azure resources, which represents this specific data factory. 可以像使用自己的服务主体一样,直接使用此托管标识进行 Blob 存储身份验证。You can directly use this managed identity for Blob storage authentication similar to using your own service principal. 此指定工厂可通过此方法访问以及从/向 Blob 存储复制数据。It allows this designated factory to access and copy data from/to your Blob storage.

有关 Azure 存储身份验证的一般信息,请参阅使用 Azure Active Directory 对 Azure 存储访问进行身份验证Refer to Authenticate access to Azure Storage using Azure Active Directory for Azure Storage authentication in general. 若要使用 Azure 资源的托管标识身份验证,请执行以下步骤:To use managed identities for Azure resources authentication, follow these steps:

  1. 通过复制与工厂一起生成的托管标识对象 ID 的值,检索数据工厂托管标识信息Retrieve data factory managed identity information by copying the value of managed identity object ID generated along with your factory.

  2. 授予托管标识在 Azure Blob 存储中的适当权限。Grant the managed identity proper permission in Azure Blob storage. 如需了解角色的更多详情,请参阅使用 RBAC 管理对 Azure 存储数据的访问权限Refer to Manage access rights to Azure Storage data with RBAC with more details on the roles.

    • 作为源 ,在访问控制 (IAM) 中,至少授予“存储 Blob 数据读取者” 角色。As source, in Access control (IAM), grant at least Storage Blob Data Reader role.
    • 对于接收器,请在访问控制 (IAM) 中,至少授予“存储 Blob 数据参与者”角色。 As sink, in Access control (IAM), grant at least Storage Blob Data Contributor role.

Important

如果使用 PolyBase 将 Blob(作为源或暂存)中的数据载入 SQL 数据仓库,则在对 Blob 使用托管标识身份验证时,请确保还按照此指南中的步骤 1 和步骤 2 完成以下任务:1) 向 Azure Active Directory (Azure AD) 注册 SQL 数据库服务器,2) 将存储 Blob 数据参与者角色分配给 SQL 数据库服务器;其余的任务由数据工厂处理。If you use PolyBase to load data from Blob (as source or as staging) into SQL Data Warehouse, when using managed identity authentication for Blob, make sure you also follow steps 1 and 2 in this guidance to 1) register your SQL Database server with Azure Active Directory (Azure AD) and 2) assign the Storage Blob Data Contributor role to your SQL Database server; the rest are handled by Data Factory. 如果 Blob 存储配置了 Azure 虚拟网络终结点,要使用 PolyBase 从其中加载数据,必须使用 PolyBase 所需的托管标识身份验证。If your Blob storage is configured with an Azure Virtual Network endpoint, to use PolyBase to load data from it, you must use managed identity authentication as required by PolyBase.

Azure Blob 存储链接服务支持以下属性:These properties are supported for an Azure Blob storage linked service:

属性Property 说明Description 必需Required
typetype type 属性必须设置为 AzureBlobStorageThe type property must be set to AzureBlobStorage. Yes
serviceEndpointserviceEndpoint 使用 https://<accountName>.blob.core.chinacloudapi.cn/ 模式指定 Azure Blob 存储服务终结点。Specify the Azure Blob storage service endpoint with the pattern of https://<accountName>.blob.core.chinacloudapi.cn/. Yes
connectViaconnectVia 用于连接到数据存储的集成运行时The integration runtime to be used to connect to the data store. 如果数据存储位于专用网络,则可以使用 Azure 集成运行时或自承载集成运行时。You can use Azure Integration Runtime or Self-hosted Integration Runtime (if your data store is in a private network). 如果未指定,则使用默认 Azure Integration Runtime。If not specified, it uses the default Azure Integration Runtime. No

Note

Azure 资源的托管标识身份验证仅受“AzureBlobStorage”类型链接服务支持,而不受以前的“AzureStorage”类型链接服务支持。Managed identities for Azure resources authentication is only supported by "AzureBlobStorage" type linked service but not previous "AzureStorage" type linked service.

示例:Example:

{
    "name": "AzureBlobStorageLinkedService",
    "properties": {
        "type": "AzureBlobStorage",
        "typeProperties": {            
            "serviceEndpoint": "https://<accountName>.blob.core.chinacloudapi.cn/"
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

数据集属性Dataset properties

有关可用于定义数据集的各部分和属性的完整列表,请参阅数据集一文。For a full list of sections and properties available for defining datasets, see the Datasets article.

Azure 数据工厂支持以下文件格式。Azure Data Factory support the following file formats. 请参阅每一篇关于基于格式的设置的文章。Refer to each article on format-based settings.

基于格式的数据集中 location 设置下的 Azure Blob 支持以下属性:The following properties are supported for Azure Blob under location settings in format-based dataset:

属性Property 说明Description 必需Required
typetype 数据集中位置的 type 属性必须设置为 AzureBlobStorageLocation 。The type property of the location in dataset must be set to AzureBlobStorageLocation. Yes
containercontainer Blob 容器。The blob container. Yes
folderPathfolderPath 给定容器下的文件夹路径。The path to folder under the given container. 如果要使用通配符筛选文件夹,请跳过此设置并在活动源设置中指定。If you want to use wildcard to filter folder, skip this setting and specify in activity source settings. No
fileNamefileName 给定容器 + folderPath 下的文件名。The file name under the given container + folderPath. 如果要使用通配符筛选文件,请跳过此设置并在活动源设置中指定。If you want to use wildcard to filter files, skip this setting and specify in activity source settings. No

示例:Example:

{
    "name": "DelimitedTextDataset",
    "properties": {
        "type": "DelimitedText",
        "linkedServiceName": {
            "referenceName": "<Azure Blob Storage linked service name>",
            "type": "LinkedServiceReference"
        },
        "schema": [ < physical schema, optional, auto retrieved during authoring > ],
        "typeProperties": {
            "location": {
                "type": "AzureBlobStorageLocation",
                "container": "containername",
                "folderPath": "folder/subfolder"
            },
            "columnDelimiter": ",",
            "quoteChar": "\"",
            "firstRowAsHeader": true,
            "compressionCodec": "gzip"
        }
    }
}

复制活动属性Copy activity properties

有关可用于定义活动的各部分和属性的完整列表,请参阅管道一文。For a full list of sections and properties available for defining activities, see the Pipelines article. 本部分提供 Blob 存储源和接收器支持的属性列表。This section provides a list of properties supported by the Blob storage source and sink.

将 Blob 存储用作源类型Blob storage as a source type

Azure 数据工厂支持以下文件格式。Azure Data Factory support the following file formats. 请参阅每一篇关于基于格式的设置的文章。Refer to each article on format-based settings.

基于格式的复制源中 storeSettings 设置下的 Azure Blob 支持以下属性:The following properties are supported for Azure Blob under storeSettings settings in format-based copy source:

属性Property 说明Description 必需Required
typetype storeSettings 下的 type 属性必须设置为 AzureBlobStorageReadSettingsThe type property under storeSettings must be set to AzureBlobStorageReadSettings. Yes
recursiverecursive 指示是要从子文件夹中以递归方式读取数据,还是只从指定的文件夹中读取数据。Indicates whether the data is read recursively from the subfolders or only from the specified folder. 请注意,当 recursive 设置为 true 且接收器是基于文件的存储时,将不会在接收器上复制或创建空的文件夹或子文件夹。Note that when recursive is set to true and the sink is a file-based store, an empty folder or subfolder isn't copied or created at the sink. 允许的值为 true(默认值)和 falseAllowed values are true (default) and false. No
前缀prefix 在数据集中配置的给定容器下的 blob 名称的前缀,用于筛选源 blob。Prefix for the blob name under the given container configured in dataset to filter source blobs. 将选中名称以此前缀开头的 Blob。Blobs whose name starts with this prefix are selected.
仅当未指定 wildcardFolderPathwildcardFileName 属性时适用。Applies only when wildcardFolderPath and wildcardFileName properties are not specified.
No
wildcardFolderPathwildcardFolderPath 数据集中配置的给定容器下包含通配符的文件夹路径,用于筛选源文件夹。The folder path with wildcard characters under the given container configured in dataset to filter source folders.
允许的通配符为:*(匹配零个或更多个字符)和 ?(匹配零个或单个字符);如果实际文件夹名称中包含通配符或此转义字符,请使用 ^ 进行转义。Allowed wildcards are: * (matches zero or more characters) and ? (matches zero or single character); use ^ to escape if your actual folder name has wildcard or this escape char inside.
请参阅文件夹和文件筛选器示例中的更多示例。See more examples in Folder and file filter examples.
No
wildcardFileNamewildcardFileName 给定的容器 + folderPath/wildcardFolderPath 下带有通配符的文件名,用于筛选源文件。The file name with wildcard characters under the given container + folderPath/wildcardFolderPath to filter source files.
允许的通配符为:*(匹配零个或更多个字符)和 ?(匹配零个或单个字符);如果实际文件夹名称中包含通配符或此转义字符,请使用 ^ 进行转义。Allowed wildcards are: * (matches zero or more characters) and ? (matches zero or single character); use ^ to escape if your actual folder name has wildcard or this escape char inside. 请参阅文件夹和文件筛选器示例中的更多示例。See more examples in Folder and file filter examples.
如果数据集中未指定 fileName,则为“是”Yes if fileName is not specified in dataset
modifiedDatetimeStartmodifiedDatetimeStart 基于属性“上次修改时间”的文件筛选器。Files filter based on the attribute: Last Modified. 如果文件的上次修改时间在 modifiedDatetimeStartmodifiedDatetimeEnd 之间的时间范围内,则将选中这些文件。The files will be selected if their last modified time are within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. 该时间应用于 UTC 时区,格式为“2018-12-01T05:00:00Z”。The time is applied to UTC time zone in the format of "2018-12-01T05:00:00Z".
属性可以为 NULL,这意味着不向数据集应用任何文件特性筛选器。The properties can be NULL which mean no file attribute filter will be applied to the dataset. 如果 modifiedDatetimeStart 具有日期/时间值,但 modifiedDatetimeEnd 为 NULL,则意味着将选中“上次修改时间”属性大于或等于该日期/时间值的文件。When modifiedDatetimeStart has datetime value but modifiedDatetimeEnd is NULL, it means the files whose last modified attribute is greater than or equal with the datetime value will be selected. 如果 modifiedDatetimeEnd 具有日期/时间值,但 modifiedDatetimeStart 为 NULL,则意味着将选中“上次修改时间”属性小于该日期/时间值的文件。When modifiedDatetimeEnd has datetime value but modifiedDatetimeStart is NULL, it means the files whose last modified attribute is less than the datetime value will be selected.
No
modifiedDatetimeEndmodifiedDatetimeEnd 同上。Same as above. No
maxConcurrentConnectionsmaxConcurrentConnections 可以同时连接到存储库的连接数。The number of the connections to connect to storage store concurrently. 仅在要限制与数据存储的并发连接时指定。Specify only when you want to limit the concurrent connection to the data store. No

Note

对于 Parquet/带分隔符的文本格式,仍然按原样支持下一部分中提到的 BlobSource 类型复制活动源,以实现向后兼容性。For Parquet/delimited text format, BlobSource type copy activity source mentioned in next section is still supported as-is for backward compatibility. 建议你继续使用此新模型,并且 ADF 创作 UI 已切换为生成这些新类型。You are suggested to use this new model going forward, and the ADF authoring UI has switched to generating these new types.

示例:Example:

"activities":[
    {
        "name": "CopyFromBlob",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<Delimited text input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "DelimitedTextSource",
                "formatSettings":{
                    "type": "DelimitedTextReadSettings",
                    "skipLineCount": 10
                },
                "storeSettings":{
                    "type": "AzureBlobStorageReadSettings",
                    "recursive": true,
                    "wildcardFolderPath": "myfolder*A",
                    "wildcardFileName": "*.csv"
                }
            },
            "sink": {
                "type": "<sink type>"
            }
        }
    }
]

用作接收器类型的 Blob 存储Blob storage as a sink type

Azure 数据工厂支持以下文件格式。Azure Data Factory support the following file formats. 请参阅每一篇关于基于格式的设置的文章。Refer to each article on format-based settings.

基于格式的复制接收器中 storeSettings 设置下的 Azure Blob 支持以下属性:The following properties are supported for Azure Blob under storeSettings settings in format-based copy sink:

属性Property 说明Description 必需Required
typetype storeSettings 下的 type 属性必须设置为 AzureBlobStorageWriteSettingsThe type property under storeSettings must be set to AzureBlobStorageWriteSettings. Yes
copyBehaviorcopyBehavior 定义以基于文件的数据存储中的文件为源时的复制行为。Defines the copy behavior when the source is files from a file-based data store.

允许值包括:Allowed values are:
- PreserveHierarchy(默认):将文件层次结构保留到目标文件夹中。- PreserveHierarchy (default): Preserves the file hierarchy in the target folder. 从源文件到源文件夹的相对路径与从目标文件到目标文件夹的相对路径相同。The relative path of source file to source folder is identical to the relative path of target file to target folder.
- FlattenHierarchy:源文件夹中的所有文件都位于目标文件夹的第一级中。- FlattenHierarchy: All files from the source folder are in the first level of the target folder. 目标文件具有自动生成的名称。The target files have autogenerated names.
- MergeFiles:将源文件夹中的所有文件合并到一个文件中。- MergeFiles: Merges all files from the source folder to one file. 如果指定了文件名或 Blob 名称,则合并文件的名称为指定名称。If the file or blob name is specified, the merged file name is the specified name. 否则,它是自动生成的文件名。Otherwise, it's an autogenerated file name.
No
blockSizeInMBblockSizeInMB 指定用于将数据写入块 blob 的块大小(以 MB 为单位)。Specify the block size in MB used to write data to block blobs. 详细了解块 BlobLearn more about Block Blobs.
允许值为 4 到 100 MBAllowed value is between 4 and 100 MB.
默认情况下,ADF 会根据源存储类型和数据自动确定块大小。By default, ADF automatically determine the block size based on your source store type and data. 对于以非二进制格式复制到 Blob,默认块大小为 100 MB,这样,最多可达 4.95 TB 的数据便可以容纳它。For non-binary copy into Blob, the default block size is 100 MB so as to fit in at most 4.95 TB data. 当数据不大时,它可能并非最优,特别是当你在网络状况不佳的情况下使用自承载集成运行时的时候,这会导致操作超时或性能问题。It may be not optimal when your data is not large, especially when you use Self-hosted Integration Runtime with poor network resulting in operation timeout or performance issue. 可以显式指定块大小,同时确保 blockSizeInMB*50000 足以存储数据,否则复制活动运行将失败。You can explicitly specify a block size, while ensure blockSizeInMB*50000 is big enough to store the data, otherwise copy activity run will fail.
No
maxConcurrentConnectionsmaxConcurrentConnections 可以同时连接到存储库的连接数。The number of the connections to connect to storage store concurrently. 仅在要限制与数据存储的并发连接时指定。Specify only when you want to limit the concurrent connection to the data store. No

示例:Example:

"activities":[
    {
        "name": "CopyFromBlob",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<Parquet output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "<source type>"
            },
            "sink": {
                "type": "ParquetSink",
                "storeSettings":{
                    "type": "AzureBlobStorageWriteSettings",
                    "copyBehavior": "PreserveHierarchy"
                }
            }
        }
    }
]

文件夹和文件筛选器示例Folder and file filter examples

本部分介绍使用通配符筛选器生成文件夹路径和文件名的行为。This section describes the resulting behavior of the folder path and file name with wildcard filters.

folderPathfolderPath fileNamefileName recursiverecursive 源文件夹结构和筛选器结果(用粗体表示的文件已检索)Source folder structure and filter result (files in bold are retrieved)
container/Folder* (为空,使用默认值)(empty, use default) falsefalse containercontainer
    FolderA    FolderA
        File1.csv        File1.csv
        File2.json        File2.json
        Subfolder1        Subfolder1
            File3.csv            File3.csv
            File4.json            File4.json
            File5.csv            File5.csv
    AnotherFolderB    AnotherFolderB
        File6.csv        File6.csv
container/Folder* (为空,使用默认值)(empty, use default) truetrue containercontainer
    FolderA    FolderA
        File1.csv        File1.csv
        File2.json        File2.json
        Subfolder1        Subfolder1
            File3.csv            File3.csv
            File4.json            File4.json
            File5.csv            File5.csv
    AnotherFolderB    AnotherFolderB
        File6.csv        File6.csv
container/Folder* *.csv falsefalse containercontainer
    FolderA    FolderA
        File1.csv        File1.csv
        File2.json        File2.json
        Subfolder1        Subfolder1
            File3.csv            File3.csv
            File4.json            File4.json
            File5.csv            File5.csv
    AnotherFolderB    AnotherFolderB
        File6.csv        File6.csv
container/Folder* *.csv truetrue containercontainer
    FolderA    FolderA
        File1.csv        File1.csv
        File2.json        File2.json
        Subfolder1        Subfolder1
            File3.csv            File3.csv
            File4.json            File4.json
            File5.csv            File5.csv
    AnotherFolderB    AnotherFolderB
        File6.csv        File6.csv

一些 recursive 和 copyBehavior 示例Some recursive and copyBehavior examples

本节介绍了将 recursive 和 copyBehavior 值进行不同组合所产生的复制操作行为。This section describes the resulting behavior of the Copy operation for different combinations of recursive and copyBehavior values.

recursiverecursive copyBehaviorcopyBehavior 源文件夹结构Source folder structure 生成目标Resulting target
truetrue preserveHierarchypreserveHierarchy Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用与源相同的结构创建目标文件夹 Folder1:The target folder Folder1 is created with the same structure as the source:

Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
truetrue flattenHierarchyflattenHierarchy Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用以下结构创建目标 Folder1:The target Folder1 is created with the following structure:

Folder1Folder1
    File1 的自动生成的名称    autogenerated name for File1
    File2 的自动生成的名称    autogenerated name for File2
    File3 的自动生成的名称    autogenerated name for File3
    File4 的自动生成的名称    autogenerated name for File4
    File5 的自动生成的名称    autogenerated name for File5
truetrue mergeFilesmergeFiles Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用以下结构创建目标 Folder1:The target Folder1 is created with the following structure:

Folder1Folder1
    File1 + File2 + File3 + File4 + File5 的内容将合并到一个文件中,且自动生成文件名。    File1 + File2 + File3 + File4 + File5 contents are merged into one file with an autogenerated file name.
falsefalse preserveHierarchypreserveHierarchy Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用以下结构创建目标文件夹 Folder1:The target folder Folder1 is created with the following structure:

Folder1Folder1
    File1    File1
    File2    File2

不会选取带有 File3、File4 和 File5 的 Subfolder1。Subfolder1 with File3, File4, and File5 is not picked up.
falsefalse flattenHierarchyflattenHierarchy Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用以下结构创建目标文件夹 Folder1:The target folder Folder1 is created with the following structure:

Folder1Folder1
    File1 的自动生成的名称    autogenerated name for File1
    File2 的自动生成的名称    autogenerated name for File2

不会选取带有 File3、File4 和 File5 的 Subfolder1。Subfolder1 with File3, File4, and File5 is not picked up.
falsefalse mergeFilesmergeFiles Folder1Folder1
    File1    File1
    File2    File2
    Subfolder1    Subfolder1
        File3        File3
        File4        File4
        File5        File5
使用以下结构创建目标文件夹 Folder1The target folder Folder1 is created with the following structure

Folder1Folder1
    File1 + File2 的内容将合并到一个文件中,且自动生成文件名。    File1 + File2 contents are merged into one file with an autogenerated file name. File1 的自动生成的名称autogenerated name for File1

不会选取带有 File3、File4 和 File5 的 Subfolder1。Subfolder1 with File3, File4, and File5 is not picked up.

在复制期间保留元数据Preserve metadata during copy

将文件从 Amazon S3/Azure Blob/Azure Data Lake Storage Gen2 复制到 Azure Data Lake Storage Gen2/Azure Blob 时,可以选择保留文件元数据和数据。When you copy files from Amazon S3/Azure Blob/Azure Data Lake Storage Gen2 to Azure Data Lake Storage Gen2/Azure Blob, you can choose to preserve the file metadata along with data. 保留元数据中了解更多信息。Learn more from Preserve metadata.

查找活动属性Lookup activity properties

若要了解有关属性的详细信息,请查看 Lookup 活动To learn details about the properties, check Lookup activity.

GetMetadata 活动属性GetMetadata activity properties

若要了解有关属性的详细信息,请查看 GetMetadata 活动To learn details about the properties, check GetMetadata activity

Delete 活动属性Delete activity properties

若要了解有关属性的详细信息,请查看 Delete 活动To learn details about the properties, check Delete activity

旧模型Legacy models

Note

仍按原样支持以下模型,以实现向后兼容性。The following models are still supported as-is for backward compatibility. 建议你以后使用前面部分中提到的新模型,ADF 创作 UI 已经切换到生成新模型。You are suggested to use the new model mentioned in above sections going forward, and the ADF authoring UI has switched to generating the new model.

旧数据集模型Legacy dataset model

属性Property 说明Description 必需Required
typetype 数据集的 type 属性必须设置为 AzureBlobThe type property of the dataset must be set to AzureBlob. Yes
folderPathfolderPath 到 Blob 存储中的容器和文件夹的路径。Path to the container and folder in the blob storage.

不包含容器名称的路径支持通配符筛选器。Wildcard filter is supported for the path excluding container name. 允许的通配符为:*(匹配零个或更多个字符)和 ?(匹配零个或单个字符);如果实际文件夹名称中包含通配符或此转义字符,请使用 ^ 进行转义。Allowed wildcards are: * (matches zero or more characters) and ? (matches zero or single character); use ^ to escape if your actual folder name has wildcard or this escape char inside.

示例:“myblobcontainer/myblobfolder/”,请参阅文件夹和文件筛选器示例中的更多示例。Examples: myblobcontainer/myblobfolder/, see more examples in Folder and file filter examples.
对于复制/查找活动,为“是”;对于 GetMetadata 活动,为“否”Yes for Copy/Lookup activity, No for GetMetadata activity
fileNamefileName 指定的“folderPath”下 blob 的名称或通配符筛选器 。Name or wildcard filter for the blob(s) under the specified "folderPath". 如果没有为此属性指定任何值,则数据集会指向文件夹中的所有 Blob。If you don't specify a value for this property, the dataset points to all blobs in the folder.

对于筛选器,允许的通配符为:*(匹配零个或更多字符)和 ?(匹配零个或单个字符)。For filter, allowed wildcards are: * (matches zero or more characters) and ? (matches zero or single character).
- 示例 1:"fileName": "*.csv"- Example 1: "fileName": "*.csv"
- 示例 2:"fileName": "???20180427.txt"- Example 2: "fileName": "???20180427.txt"
如果实际文件名内具有通配符或此转义符,请使用 ^ 进行转义。Use ^ to escape if your actual file name has wildcard or this escape char inside.

如果没有为输出数据集指定 fileName,并且没有在活动接收器中指定 preserveHierarchy,则复制活动会自动生成采用以下模式的 Blob 名称:“Data.[activity run ID GUID].[GUID if FlattenHierarchy].[format if configured].[compression if configured] ”,例如“Data.0a405f8a-93ff-4c6f-b3be-f69616f1df7a.txt.gz ”;如果使用表名称而不是查询从表格源进行复制,则名称模式为“[table name].[format].[compression if configured]”,例如“MyTable.csv”。When fileName isn't specified for an output dataset and preserveHierarchy isn't specified in the activity sink, the copy activity automatically generates the blob name with the following pattern: "Data.[activity run ID GUID].[GUID if FlattenHierarchy].[format if configured].[compression if configured]", e.g. "Data.0a405f8a-93ff-4c6f-b3be-f69616f1df7a.txt.gz"; if you copy from tabular source using table name instead of query, the name pattern is "[table name].[format].[compression if configured]", e.g. "MyTable.csv".
No
modifiedDatetimeStartmodifiedDatetimeStart 基于属性“上次修改时间”的文件筛选器。Files filter based on the attribute: Last Modified. 如果文件的上次修改时间在 modifiedDatetimeStartmodifiedDatetimeEnd 之间的时间范围内,则将选中这些文件。The files will be selected if their last modified time are within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. 该时间应用于 UTC 时区,格式为“2018-12-01T05:00:00Z”。The time is applied to UTC time zone in the format of "2018-12-01T05:00:00Z".

请注意,当你要从大量文件中进行文件筛选时,启用此设置将影响数据移动的整体性能。Be aware the overall performance of data movement will be impacted by enabling this setting when you want to do file filter from huge amounts of files.

属性可以为 NULL,这意味着不向数据集应用任何文件属性筛选器。The properties can be NULL that mean no file attribute filter will be applied to the dataset. 如果 modifiedDatetimeStart 具有日期/时间值,但 modifiedDatetimeEnd 为 NULL,则意味着将选中“上次修改时间”属性大于或等于该日期/时间值的文件。When modifiedDatetimeStart has datetime value but modifiedDatetimeEnd is NULL, it means the files whose last modified attribute is greater than or equal with the datetime value will be selected. 如果 modifiedDatetimeEnd 具有日期/时间值,但 modifiedDatetimeStart 为 NULL,则意味着将选中“上次修改时间”属性小于该日期/时间值的文件。When modifiedDatetimeEnd has datetime value but modifiedDatetimeStart is NULL, it means the files whose last modified attribute is less than the datetime value will be selected.
No
modifiedDatetimeEndmodifiedDatetimeEnd 基于属性“上次修改时间”的文件筛选器。Files filter based on the attribute: Last Modified. 如果文件的上次修改时间在 modifiedDatetimeStartmodifiedDatetimeEnd 之间的时间范围内,则将选中这些文件。The files will be selected if their last modified time are within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. 该时间应用于 UTC 时区,格式为“2018-12-01T05:00:00Z”。The time is applied to UTC time zone in the format of "2018-12-01T05:00:00Z".

请注意,当你要从大量文件中进行文件筛选时,启用此设置将影响数据移动的整体性能。Be aware the overall performance of data movement will be impacted by enabling this setting when you want to do file filter from huge amounts of files.

属性可以为 NULL,这意味着不向数据集应用任何文件属性筛选器。The properties can be NULL that mean no file attribute filter will be applied to the dataset. 如果 modifiedDatetimeStart 具有日期/时间值,但 modifiedDatetimeEnd 为 NULL,则意味着将选中“上次修改时间”属性大于或等于该日期/时间值的文件。When modifiedDatetimeStart has datetime value but modifiedDatetimeEnd is NULL, it means the files whose last modified attribute is greater than or equal with the datetime value will be selected. 如果 modifiedDatetimeEnd 具有日期/时间值,但 modifiedDatetimeStart 为 NULL,则意味着将选中“上次修改时间”属性小于该日期/时间值的文件。When modifiedDatetimeEnd has datetime value but modifiedDatetimeStart is NULL, it means the files whose last modified attribute is less than the datetime value will be selected.
No
formatformat 若要在基于文件的存储之间按原样复制文件(二进制副本),可以在输入和输出数据集定义中跳过格式节。If you want to copy files as is between file-based stores (binary copy), skip the format section in both the input and output dataset definitions.

若要分析或生成具有特定格式的文件,以下是受支持的文件格式类型:TextFormat、JsonFormat、AvroFormat、OrcFormat 和 ParquetFormat 。If you want to parse or generate files with a specific format, the following file format types are supported: TextFormat, JsonFormat, AvroFormat, OrcFormat, and ParquetFormat. 请将 format 中的 type 属性设置为上述值之一。Set the type property under format to one of these values. 有关详细信息,请参阅文本格式JSON 格式Avro 格式Orc 格式Parquet 格式部分。For more information, see the Text format, JSON format, Avro format, Orc format, and Parquet format sections.
否(仅适用于二进制复制方案)No (only for binary copy scenario)
compressioncompression 指定数据的压缩类型和级别。Specify the type and level of compression for the data. 有关详细信息,请参阅受支持的文件格式和压缩编解码器For more information, see Supported file formats and compression codecs.
支持的类型为 GZipDeflateBZip2ZipDeflateSupported types are GZip, Deflate, BZip2, and ZipDeflate.
支持的级别为“最佳” 和“最快” 。Supported levels are Optimal and Fastest.
No

Tip

如需复制文件夹下的所有 blob,请仅指定 folderPath。To copy all blobs under a folder, specify folderPath only.
如需复制具有给定名称的单个 blob,请指定文件夹部分的 folderPath 和文件名部分的 fileName 。To copy a single blob with a given name, specify folderPath with folder part and fileName with file name.
如需复制文件夹下的一部分 blob,请指定文件夹部分的 folderPath 和通配符筛选器部分的 fileName 。To copy a subset of blobs under a folder, specify folderPath with folder part and fileName with wildcard filter.

示例:Example:

{
    "name": "AzureBlobDataset",
    "properties": {
        "type": "AzureBlob",
        "linkedServiceName": {
            "referenceName": "<Azure Blob storage linked service name>",
            "type": "LinkedServiceReference"
        },
        "typeProperties": {
            "folderPath": "mycontainer/myfolder",
            "fileName": "*",
            "modifiedDatetimeStart": "2018-12-01T05:00:00Z",
            "modifiedDatetimeEnd": "2018-12-01T06:00:00Z",
            "format": {
                "type": "TextFormat",
                "columnDelimiter": ",",
                "rowDelimiter": "\n"
            },
            "compression": {
                "type": "GZip",
                "level": "Optimal"
            }
        }
    }
}

旧复制活动源模型Legacy copy activity source model

属性Property 说明Description 必需Required
typetype 复制活动源的 type 属性必须设置为 BlobSourceThe type property of the copy activity source must be set to BlobSource. Yes
recursiverecursive 指示是要从子文件夹中以递归方式读取数据,还是只从指定的文件夹中读取数据。Indicates whether the data is read recursively from the subfolders or only from the specified folder. 请注意,当 recursive 设置为 true 且接收器是基于文件的存储时,将不会在接收器上复制或创建空的文件夹或子文件夹。Note that when recursive is set to true and the sink is a file-based store, an empty folder or subfolder isn't copied or created at the sink.
允许的值为 true(默认值)和 falseAllowed values are true (default) and false.
No
maxConcurrentConnectionsmaxConcurrentConnections 可以同时连接到存储库的连接数。The number of the connections to connect to storage store concurrently. 仅在要限制与数据存储的并发连接时指定。Specify only when you want to limit the concurrent connection to the data store. No

示例:Example:

"activities":[
    {
        "name": "CopyFromBlob",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<Azure Blob input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "BlobSource",
                "recursive": true
            },
            "sink": {
                "type": "<sink type>"
            }
        }
    }
]

旧复制活动接收器模型Legacy copy activity sink model

属性Property 说明Description 必需Required
typetype 复制活动接收器的 type 属性必须设置为 BlobSinkThe type property of the copy activity sink must be set to BlobSink. Yes
copyBehaviorcopyBehavior 定义以基于文件的数据存储中的文件为源时的复制行为。Defines the copy behavior when the source is files from a file-based data store.

允许值包括:Allowed values are:
- PreserveHierarchy(默认):将文件层次结构保留到目标文件夹中。- PreserveHierarchy (default): Preserves the file hierarchy in the target folder. 从源文件到源文件夹的相对路径与从目标文件到目标文件夹的相对路径相同。The relative path of source file to source folder is identical to the relative path of target file to target folder.
- FlattenHierarchy:源文件夹中的所有文件都位于目标文件夹的第一级中。- FlattenHierarchy: All files from the source folder are in the first level of the target folder. 目标文件具有自动生成的名称。The target files have autogenerated names.
- MergeFiles:将源文件夹中的所有文件合并到一个文件中。- MergeFiles: Merges all files from the source folder to one file. 如果指定了文件名或 Blob 名称,则合并文件的名称为指定名称。If the file or blob name is specified, the merged file name is the specified name. 否则,它是自动生成的文件名。Otherwise, it's an autogenerated file name.
No
maxConcurrentConnectionsmaxConcurrentConnections 可以同时连接到存储库的连接数。The number of the connections to connect to storage store concurrently. 仅在要限制与数据存储的并发连接时指定。Specify only when you want to limit the concurrent connection to the data store. No

示例:Example:

"activities":[
    {
        "name": "CopyToBlob",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<Azure Blob output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "<source type>"
            },
            "sink": {
                "type": "BlobSink",
                "copyBehavior": "PreserveHierarchy"
            }
        }
    }
]

后续步骤Next steps

有关数据工厂中复制活动支持作为源和接收器的数据存储的列表,请参阅支持的数据存储For a list of data stores supported as sources and sinks by the copy activity in Data Factory, see Supported data stores.