Copy data to or from Azure Data Lake Storage Gen1 using Azure Data Factory

APPLIES TO: Azure Data Factory Azure Synapse Analytics (Preview)

This article outlines how to copy data to and from Azure Data Lake Storage Gen1. To learn about Azure Data Factory, read the introductory article.

Supported capabilities

This Azure Data Lake Storage Gen1 connector is supported for the following activities:

Specifically, with this connector you can:

  • Copy files by using one of the following methods of authentication: service principal or managed identities for Azure resources.
  • Copy files as is or parse or generate files with the supported file formats and compression codecs.
  • Preserve ACLs when copying into Azure Data Lake Storage Gen2.

Important

If you copy data by using the self-hosted integration runtime, configure the corporate firewall to allow outbound traffic to <ADLS account name>.azuredatalakestore.net and login.microsoftonline.com/<tenant>/oauth2/token on port 443. The latter is the Azure Security Token Service that the integration runtime needs to communicate with to get the access token.

Get started

Tip

For a walk-through of how to use the Azure Data Lake Store connector, see Load data into Azure Data Lake Store.

To perform the Copy activity with a pipeline, you can use one of the following tools or SDKs:

The following sections provide information about properties that are used to define Data Factory entities specific to Azure Data Lake Store.

Linked service properties

The following properties are supported for the Azure Data Lake Store linked service:

Property Description Required
type The type property must be set to AzureDataLakeStore. Yes
dataLakeStoreUri Information about the Azure Data Lake Store account. This information takes one of the following formats: https://[accountname].azuredatalakestore.net/webhdfs/v1 or adl://[accountname].azuredatalakestore.net/. Yes
subscriptionId The Azure subscription ID to which the Data Lake Store account belongs. Required for sink
resourceGroupName The Azure resource group name to which the Data Lake Store account belongs. Required for sink
connectVia The integration runtime to be used to connect to the data store. You can use the Azure integration runtime or a self-hosted integration runtime if your data store is located in a private network. If this property isn't specified, the default Azure integration runtime is used. No

Use service principal authentication

To use service principal authentication, follow these steps.

  1. Register an application entity in Azure Active Directory and grant it access to Data Lake Store. For detailed steps, see Service-to-service authentication. Make note of the following values, which you use to define the linked service:

    • Application ID
    • Application key
    • Tenant ID
  2. Grant the service principal proper permission. See examples on how permission works in Data Lake Storage Gen1 from Access control in Azure Data Lake Storage Gen1.

    • As source: In Data explorer > Access, grant at least Execute permission for ALL upstream folders including the root, along with Read permission for the files to copy. You can choose to add to This folder and all children for recursive, and add as an access permission and a default permission entry. There's no requirement on account-level access control (IAM).
    • As sink: In Data explorer > Access, grant at least Execute permission for ALL upstream folders including the root, along with Write permission for the sink folder. You can choose to add to This folder and all children for recursive, and add as an access permission and a default permission entry.

The following properties are supported:

Property Description Required
servicePrincipalId Specify the application's client ID. Yes
servicePrincipalKey Specify the application's key. Mark this field as a SecureString to store it securely in Data Factory, or reference a secret stored in Azure Key Vault. Yes
tenant Specify the tenant information, such as domain name or tenant ID, under which your application resides. You can retrieve it by hovering the mouse in the upper-right corner of the Azure portal. Yes
azureCloudType For service principal authentication, specify the type of Azure cloud environment to which your Azure Active Directory application is registered.
Allowed values are AzurePublic, AzureChina, AzureUsGovernment, and AzureGermany. By default, the data factory's cloud environment is used.
No

Example:

{
    "name": "AzureDataLakeStoreLinkedService",
    "properties": {
        "type": "AzureDataLakeStore",
        "typeProperties": {
            "dataLakeStoreUri": "https://<accountname>.azuredatalakestore.net/webhdfs/v1",
            "servicePrincipalId": "<service principal id>",
            "servicePrincipalKey": {
                "type": "SecureString",
                "value": "<service principal key>"
            },
            "tenant": "<tenant info, e.g. microsoft.onmicrosoft.com>",
            "subscriptionId": "<subscription of ADLS>",
            "resourceGroupName": "<resource group of ADLS>"
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

Use managed identities for Azure resources authentication

A data factory can be associated with a managed identity for Azure resources, which represents this specific data factory. You can directly use this managed identity for Data Lake Store authentication, similar to using your own service principal. It allows this designated factory to access and copy data to or from Data Lake Store.

To use managed identities for Azure resources authentication, follow these steps.

  1. Retrieve the data factory managed identity information by copying the value of the "Service Identity Application ID" generated along with your factory.

  2. Grant the managed identity access to Data Lake Store. See examples on how permission works in Data Lake Storage Gen1 from Access control in Azure Data Lake Storage Gen1.

    • As source: In Data explorer > Access, grant at least Execute permission for ALL upstream folders including the root, along with Read permission for the files to copy. You can choose to add to This folder and all children for recursive, and add as an access permission and a default permission entry. There's no requirement on account-level access control (IAM).
    • As sink: In Data explorer > Access, grant at least Execute permission for ALL upstream folders including the root, along with Write permission for the sink folder. You can choose to add to This folder and all children for recursive, and add as an access permission and a default permission entry.

In Azure Data Factory, you don't need to specify any properties besides the general Data Lake Store information in the linked service.

Example:

{
    "name": "AzureDataLakeStoreLinkedService",
    "properties": {
        "type": "AzureDataLakeStore",
        "typeProperties": {
            "dataLakeStoreUri": "https://<accountname>.azuredatalakestore.net/webhdfs/v1",
            "subscriptionId": "<subscription of ADLS>",
            "resourceGroupName": "<resource group of ADLS>"
        },
        "connectVia": {
            "referenceName": "<name of Integration Runtime>",
            "type": "IntegrationRuntimeReference"
        }
    }
}

Dataset properties

For a full list of sections and properties available for defining datasets, see the Datasets article.

Azure Data Factory supports the following file formats. Refer to each article for format-based settings.

The following properties are supported for Azure Data Lake Store Gen1 under location settings in the format-based dataset:

Property Description Required
type The type property under location in the dataset must be set to AzureDataLakeStoreLocation. Yes
folderPath The path to a folder. If you want to use a wildcard to filter folders, skip this setting and specify it in activity source settings. No
fileName The file name under the given folderPath. If you want to use a wildcard to filter files, skip this setting and specify it in activity source settings. No

Example:

{
    "name": "DelimitedTextDataset",
    "properties": {
        "type": "DelimitedText",
        "linkedServiceName": {
            "referenceName": "<ADLS Gen1 linked service name>",
            "type": "LinkedServiceReference"
        },
        "schema": [ < physical schema, optional, auto retrieved during authoring > ],
        "typeProperties": {
            "location": {
                "type": "AzureDataLakeStoreLocation",
                "folderPath": "root/folder/subfolder"
            },
            "columnDelimiter": ",",
            "quoteChar": "\"",
            "firstRowAsHeader": true,
            "compressionCodec": "gzip"
        }
    }
}

Copy activity properties

For a full list of sections and properties available for defining activities, see Pipelines. This section provides a list of properties supported by Azure Data Lake Store source and sink.

Azure Data Lake Store as source

Azure Data Factory supports the following file formats. Refer to each article for format-based settings.

The following properties are supported for Azure Data Lake Store Gen1 under storeSettings settings in the format-based copy source:

Property Description Required
type The type property under storeSettings must be set to AzureDataLakeStoreReadSettings. Yes
Locate the files to copy:
OPTION 1: static path
Copy from the given folder/file path specified in the dataset. If you want to copy all files from a folder, additionally specify wildcardFileName as *.
OPTION 2: name range
- listAfter
Retrieve the folders/files whose name is after this value alphabetically (exclusive). It utilizes the service-side filter for ADLS Gen1, which provides better performance than a wildcard filter.
Data factory applies this filter to the path defined in dataset, and only one entity level is supported. See more examples in Name range filter examples.
No
OPTION 2: name range
- listBefore
Retrieve the folders/files whose name is before this value alphabetically (inclusive). It utilizes the service-side filter for ADLS Gen1, which provides better performance than a wildcard filter.
Data factory applies this filter to the path defined in dataset, and only one entity level is supported. See more examples in Name range filter examples.
No
OPTION 3: wildcard
- wildcardFolderPath
The folder path with wildcard characters to filter source folders.
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.
See more examples in Folder and file filter examples.
No
OPTION 3: wildcard
- wildcardFileName
The file name with wildcard characters under the given folderPath/wildcardFolderPath to filter source files.
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. See more examples in Folder and file filter examples.
Yes
OPTION 4: a list of files
- fileListPath
Indicates to copy a given file set. Point to a text file that includes a list of files you want to copy, one file per line, which is the relative path to the path configured in the dataset.
When using this option, do not specify file name in dataset. See more examples in File list examples.
No
Additional settings:
recursive Indicates whether the data is read recursively from the subfolders or only from the specified folder. 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.
Allowed values are true (default) and false.
This property doesn't apply when you configure fileListPath.
No
deleteFilesAfterCompletion Indicates whether the binary files will be deleted from source store after successfully moving to the destination store. The file deletion is per file, so when copy activity fails, you will see some files have already been copied to the destination and deleted from source, while others are still remaining on source store.
This property is only valid in binary files copy scenario. The default value: false.
No
modifiedDatetimeStart Files filter based on the attribute: Last Modified.
The files will be selected if their last modified time is within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. The time is applied to UTC time zone in the format of "2018-12-01T05:00:00Z".
The properties can be NULL, which means no file attribute filter will be applied to the dataset. 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. 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.
This property doesn't apply when you configure fileListPath.
No
modifiedDatetimeEnd Same as above. No
enablePartitionDiscovery For files that are partitioned, specify whether to parse the partitions from the file path and add them as additional source columns.
Allowed values are false (default) and true.
No
partitionRootPath When partition discovery is enabled, specify the absolute root path in order to read partitioned folders as data columns.

If it is not specified, by default,
- When you use file path in dataset or list of files on source, partition root path is the path configured in dataset.
- When you use wildcard folder filter, partition root path is the sub-path before the first wildcard.

For example, assuming you configure the path in dataset as "root/folder/year=2020/month=08/day=27":
- If you specify partition root path as "root/folder/year=2020", copy activity will generate two more columns month and day with value "08" and "27" respectively, in addition to the columns inside the files.
- If partition root path is not specified, no extra column will be generated.
No
maxConcurrentConnections The number of connections to connect to storage store concurrently. Specify only when you want to limit the concurrent connection to the data store. No

Example:

"activities":[
    {
        "name": "CopyFromADLSGen1",
        "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": "AzureDataLakeStoreReadSettings",
                    "recursive": true,
                    "wildcardFolderPath": "myfolder*A",
                    "wildcardFileName": "*.csv"
                }
            },
            "sink": {
                "type": "<sink type>"
            }
        }
    }
]

Azure Data Lake Store as sink

Azure Data Factory supports the following file formats. Refer to each article for format-based settings.

The following properties are supported for Azure Data Lake Store Gen1 under storeSettings settings in the format-based copy sink:

Property Description Required
type The type property under storeSettings must be set to AzureDataLakeStoreWriteSettings. Yes
copyBehavior Defines the copy behavior when the source is files from a file-based data store.

Allowed values are:
- PreserveHierarchy (default): Preserves the file hierarchy in the target folder. The relative path of the source file to the source folder is identical to the relative path of the target file to the target folder.
- FlattenHierarchy: All files from the source folder are in the first level of the target folder. The target files have autogenerated names.
- MergeFiles: Merges all files from the source folder to one file. If the file name is specified, the merged file name is the specified name. Otherwise, it's an autogenerated file name.
No
expiryDateTime Specifies the expiry time of the written files. The time is applied to the UTC time in the format of "2020-03-01T08:00:00Z". By default it is NULL, which means the written files are never expired. No
maxConcurrentConnections The number of connections to connect to the data store concurrently. Specify only when you want to limit the concurrent connection to the data store. No

Example:

"activities":[
    {
        "name": "CopyToADLSGen1",
        "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": "AzureDataLakeStoreWriteSettings",
                    "copyBehavior": "PreserveHierarchy"
                }
            }
        }
    }
]

Name range filter examples

This section describes the resulting behavior of name range filters.

Sample source structure ADF configuration Result
root
    a
        file.csv
    ax
        file2.csv
    ax.csv
    b
        file3.csv
    bx.csv
    c
        file4.csv
    cx.csv
In dataset:
- Folder path: root

In copy activity source:
- List after: a
- List before: b
Then the following files will be copied:

root
    ax
        file2.csv
    ax.csv
    b
        file3.csv

Folder and file filter examples

This section describes the resulting behavior of the folder path and file name with wildcard filters.

folderPath fileName recursive Source folder structure and filter result (files in bold are retrieved)
Folder* (Empty, use default) false FolderA
    File1.csv
    File2.json
    Subfolder1
        File3.csv
        File4.json
        File5.csv
AnotherFolderB
    File6.csv
Folder* (Empty, use default) true FolderA
    File1.csv
    File2.json
    Subfolder1
        File3.csv
        File4.json
        File5.csv
AnotherFolderB
    File6.csv
Folder* *.csv false FolderA
    File1.csv
    File2.json
    Subfolder1
        File3.csv
        File4.json
        File5.csv
AnotherFolderB
    File6.csv
Folder* *.csv true FolderA
    File1.csv
    File2.json
    Subfolder1
        File3.csv
        File4.json
        File5.csv
AnotherFolderB
    File6.csv

File list examples

This section describes the resulting behavior of using file list path in copy activity source.

Assuming you have the following source folder structure and want to copy the files in bold:

Sample source structure Content in FileListToCopy.txt ADF configuration
root
    FolderA
        File1.csv
        File2.json
        Subfolder1
            File3.csv
            File4.json
            File5.csv
    Metadata
        FileListToCopy.txt
File1.csv
Subfolder1/File3.csv
Subfolder1/File5.csv
In dataset:
- Folder path: root/FolderA

In copy activity source:
- File list path: root/Metadata/FileListToCopy.txt

The file list path points to a text file in the same data store that includes a list of files you want to copy, one file per line with the relative path to the path configured in the dataset.

Examples of behavior of the copy operation

This section describes the resulting behavior of the copy operation for different combinations of recursive and copyBehavior values.

recursive copyBehavior Source folder structure Resulting target
true preserveHierarchy Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the same structure as the source:

Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5.
true flattenHierarchy Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the following structure:

Folder1
    autogenerated name for File1
    autogenerated name for File2
    autogenerated name for File3
    autogenerated name for File4
    autogenerated name for File5
true mergeFiles Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the following structure:

Folder1
    File1 + File2 + File3 + File4 + File5 contents are merged into one file, with an autogenerated file name.
false preserveHierarchy Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the following structure:

Folder1
    File1
    File2

Subfolder1 with File3, File4, and File5 aren't picked up.
false flattenHierarchy Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the following structure:

Folder1
    autogenerated name for File1
    autogenerated name for File2

Subfolder1 with File3, File4, and File5 aren't picked up.
false mergeFiles Folder1
    File1
    File2
    Subfolder1
        File3
        File4
        File5
The target Folder1 is created with the following structure:

Folder1
    File1 + File2 contents are merged into one file with autogenerated file name. autogenerated name for File1

Subfolder1 with File3, File4, and File5 aren't picked up.

Preserve ACLs to Data Lake Storage Gen2

Tip

To copy data from Azure Data Lake Storage Gen1 into Gen2 in general, see Copy data from Azure Data Lake Storage Gen1 to Gen2 with Azure Data Factory for a walk-through and best practices.

If you want to replicate the access control lists (ACLs) along with data files when you upgrade from Data Lake Storage Gen1 to Data Lake Storage Gen2, see Preserve ACLs from Data Lake Storage Gen1.

Mapping data flow properties

When you're transforming data in mapping data flows, you can read and write files from Azure Data Lake Storage Gen1 in the following formats:

Format-specific settings are located in the documentation for that format. For more information, see Source transformation in mapping data flow and Sink transformation in mapping data flow.

Source transformation

In the source transformation, you can read from a container, folder, or individual file in Azure Data Lake Storage Gen1. The Source options tab lets you manage how the files get read.

Source options

Wildcard path: Using a wildcard pattern will instruct ADF to loop through each matching folder and file in a single Source transformation. This is an effective way to process multiple files within a single flow. Add multiple wildcard matching patterns with the + sign that appears when hovering over your existing wildcard pattern.

From your source container, choose a series of files that match a pattern. Only container can be specified in the dataset. Your wildcard path must therefore also include your folder path from the root folder.

Wildcard examples:

  • * Represents any set of characters

  • ** Represents recursive directory nesting

  • ? Replaces one character

  • [] Matches one of more characters in the brackets

  • /data/sales/**/*.csv Gets all csv files under /data/sales

  • /data/sales/20??/**/ Gets all files in the 20th century

  • /data/sales/*/*/*.csv Gets csv files two levels under /data/sales

  • /data/sales/2004/*/12/[XY]1?.csv Gets all csv files in 2004 in December starting with X or Y prefixed by a two-digit number

Partition Root Path: If you have partitioned folders in your file source with a key=value format (for example, year=2019), then you can assign the top level of that partition folder tree to a column name in your data flow data stream.

First, set a wildcard to include all paths that are the partitioned folders plus the leaf files that you wish to read.

Partition source file settings

Use the Partition Root Path setting to define what the top level of the folder structure is. When you view the contents of your data via a data preview, you'll see that ADF will add the resolved partitions found in each of your folder levels.

Partition root path

List of files: This is a file set. Create a text file that includes a list of relative path files to process. Point to this text file.

Column to store file name: Store the name of the source file in a column in your data. Enter a new column name here to store the file name string.

After completion: Choose to do nothing with the source file after the data flow runs, delete the source file, or move the source file. The paths for the move are relative.

To move source files to another location post-processing, first select "Move" for file operation. Then, set the "from" directory. If you're not using any wildcards for your path, then the "from" setting will be the same folder as your source folder.

If you have a source path with wildcard, your syntax will look like this below:

/data/sales/20??/**/*.csv

You can specify "from" as

/data/sales

And "to" as

/backup/priorSales

In this case, all files that were sourced under /data/sales are moved to /backup/priorSales.

Note

File operations run only when you start the data flow from a pipeline run (a pipeline debug or execution run) that uses the Execute Data Flow activity in a pipeline. File operations do not run in Data Flow debug mode.

Filter by last modified: You can filter which files you process by specifying a date range of when they were last modified. All date-times are in UTC.

Sink properties

In the sink transformation, you can write to either a container or folder in Azure Data Lake Storage Gen1. the Settings tab lets you manage how the files get written.

sink options

Clear the folder: Determines whether or not the destination folder gets cleared before the data is written.

File name option: Determines how the destination files are named in the destination folder. The file name options are:

  • Default: Allow Spark to name files based on PART defaults.
  • Pattern: Enter a pattern that enumerates your output files per partition. For example, loans[n].csv will create loans1.csv, loans2.csv, and so on.
  • Per partition: Enter one file name per partition.
  • As data in column: Set the output file to the value of a column. The path is relative to the dataset container, not the destination folder. If you have a folder path in your dataset, it will be overridden.
  • Output to a single file: Combine the partitioned output files into a single named file. The path is relative to the dataset folder. Please be aware that te merge operation can possibly fail based upon node size. This option is not recommended for large datasets.

Quote all: Determines whether to enclose all values in quotes

Lookup activity properties

To learn details about the properties, check Lookup activity.

GetMetadata activity properties

To learn details about the properties, check GetMetadata activity

Delete activity properties

To learn details about the properties, check Delete activity

Legacy models

Note

The following models are still supported as-is for backward compatibility. 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.

Legacy dataset model

Property Description Required
type The type property of the dataset must be set to AzureDataLakeStoreFile. Yes
folderPath Path to the folder in Data Lake Store. If not specified, it points to the root.

Wildcard filter is supported. Allowed wildcards are * (matches zero or more characters) and ? (matches zero or single character). Use ^ to escape if your actual folder name has a wildcard or this escape char inside.

For example: rootfolder/subfolder/. See more examples in Folder and file filter examples.
No
fileName Name or wildcard filter for the files under the specified "folderPath". If you don't specify a value for this property, the dataset points to all files in the folder.

For filter, the wildcards allowed are * (matches zero or more characters) and ? (matches zero or single character).
- Example 1: "fileName": "*.csv"
- Example 2: "fileName": "???20180427.txt"
Use ^ to escape if your actual file name has a wildcard or this escape char inside.

When fileName isn't specified for an output dataset and preserveHierarchy isn't specified in the activity sink, the copy activity automatically generates the file name with the following pattern: "Data.[activity run ID GUID].[GUID if FlattenHierarchy].[format if configured].[compression if configured]", for example, "Data.0a405f8a-93ff-4c6f-b3be-f69616f1df7a.txt.gz". If you copy from a tabular source by using a table name instead of a query, the name pattern is "[table name].[format].[compression if configured]", for example, "MyTable.csv".
No
modifiedDatetimeStart Files filter based on the attribute Last Modified. The files are selected if their last modified time is within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. The time is applied to the UTC time zone in the format of "2018-12-01T05:00:00Z".

The overall performance of data movement is affected by enabling this setting when you want to do file filter with huge amounts of files.

The properties can be NULL, which means no file attribute filter is applied to the dataset. When modifiedDatetimeStart has a datetime value but modifiedDatetimeEnd is NULL, it means the files whose last modified attribute is greater than or equal to the datetime value are selected. When modifiedDatetimeEnd has a datetime value but modifiedDatetimeStart is NULL, it means the files whose last modified attribute is less than the datetime value are selected.
No
modifiedDatetimeEnd Files filter based on the attribute Last Modified. The files are selected if their last modified time is within the time range between modifiedDatetimeStart and modifiedDatetimeEnd. The time is applied to the UTC time zone in the format of "2018-12-01T05:00:00Z".

The overall performance of data movement is affected by enabling this setting when you want to do file filter with huge amounts of files.

The properties can be NULL, which means no file attribute filter is applied to the dataset. When modifiedDatetimeStart has a datetime value but modifiedDatetimeEnd is NULL, it means the files whose last modified attribute is greater than or equal to the datetime value are selected. When modifiedDatetimeEnd has a datetime value but modifiedDatetimeStart is NULL, it means the files whose last modified attribute is less than the datetime value are selected.
No
format If you want to copy files as is between file-based stores (binary copy), skip the format section in both input and output dataset definitions.

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. Set the type property under format to one of these values. For more information, see the Text format, JSON format, Avro format, Orc format, and Parquet format sections.
No (only for binary copy scenario)
compression Specify the type and level of compression for the data. For more information, see Supported file formats and compression codecs.
Supported types are GZip, Deflate, BZip2, and ZipDeflate.
Supported levels are Optimal and Fastest.
No

Tip

To copy all files under a folder, specify folderPath only.
To copy a single file with a particular name, specify folderPath with a folder part and fileName with a file name.
To copy a subset of files under a folder, specify folderPath with a folder part and fileName with a wildcard filter.

Example:

{
    "name": "ADLSDataset",
    "properties": {
        "type": "AzureDataLakeStoreFile",
        "linkedServiceName":{
            "referenceName": "<ADLS linked service name>",
            "type": "LinkedServiceReference"
        },
        "typeProperties": {
            "folderPath": "datalake/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"
            }
        }
    }
}

Legacy copy activity source model

Property Description Required
type The type property of the copy activity source must be set to AzureDataLakeStoreSource. Yes
recursive Indicates whether the data is read recursively from the subfolders or only from the specified folder. 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. Allowed values are true (default) and false. No
maxConcurrentConnections The number of connections to connect to the data store concurrently. Specify only when you want to limit the concurrent connection to the data store. No

Example:

"activities":[
    {
        "name": "CopyFromADLSGen1",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<ADLS Gen1 input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "AzureDataLakeStoreSource",
                "recursive": true
            },
            "sink": {
                "type": "<sink type>"
            }
        }
    }
]

Legacy copy activity sink model

Property Description Required
type The type property of the copy activity sink must be set to AzureDataLakeStoreSink. Yes
copyBehavior Defines the copy behavior when the source is files from a file-based data store.

Allowed values are:
- PreserveHierarchy (default): Preserves the file hierarchy in the target folder. The relative path of the source file to the source folder is identical to the relative path of the target file to the target folder.
- FlattenHierarchy: All files from the source folder are in the first level of the target folder. The target files have autogenerated names.
- MergeFiles: Merges all files from the source folder to one file. If the file name is specified, the merged file name is the specified name. Otherwise, the file name is autogenerated.
No
maxConcurrentConnections The number of connections to connect to the data store concurrently. Specify only when you want to limit the concurrent connection to the data store. No

Example:

"activities":[
    {
        "name": "CopyToADLSGen1",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<ADLS Gen1 output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "<source type>"
            },
            "sink": {
                "type": "AzureDataLakeStoreSink",
                "copyBehavior": "PreserveHierarchy"
            }
        }
    }
]

Next steps

For a list of data stores supported as sources and sinks by the copy activity in Azure Data Factory, see supported data stores.