Cuir in eagar

Comhroinn trí

Copy data from Spark using Azure Data Factory or Synapse Analytics

  • Alt

APPLIES TO: Azure Data Factory Azure Synapse Analytics

Tip

Try out Data Factory in Microsoft Fabric, an all-in-one analytics solution for enterprises. Microsoft Fabric covers everything from data movement to data science, real-time analytics, business intelligence, and reporting. Learn how to start a new trial for free!

This article outlines how to use the Copy Activity in an Azure Data Factory or Synapse Analytics pipeline to copy data from Spark. It builds on the copy activity overview article that presents a general overview of copy activity.

Supported capabilities

This Spark connector is supported for the following capabilities:

Supported capabilities IR
Copy activity (source/-) ① ②
Lookup activity ① ②

① Azure integration runtime ② Self-hosted integration runtime

For a list of data stores that are supported as sources/sinks by the copy activity, see the Supported data stores table.

The service provides a built-in driver to enable connectivity, therefore you don't need to manually install any driver using this connector.

Prerequisites

If your data store is located inside an on-premises network, an Azure virtual network, or Amazon Virtual Private Cloud, you need to configure a self-hosted integration runtime to connect to it.

If your data store is a managed cloud data service, you can use the Azure Integration Runtime. If the access is restricted to IPs that are approved in the firewall rules, you can add Azure Integration Runtime IPs to the allow list.

You can also use the managed virtual network integration runtime feature in Azure Data Factory to access the on-premises network without installing and configuring a self-hosted integration runtime.

For more information about the network security mechanisms and options supported by Data Factory, see Data access strategies.

Getting started

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

Create a linked service to Spark using UI

Use the following steps to create a linked service to Spark in the Azure portal UI.

  1. Browse to the Manage tab in your Azure Data Factory or Synapse workspace and select Linked Services, then click New:

  2. Search for Spark and select the Spark connector.

    Screenshot of the Spark connector.

  3. Configure the service details, test the connection, and create the new linked service.

    Screenshot of linked service configuration for Spark.

Connector configuration details

The following sections provide details about properties that are used to define Data Factory entities specific to Spark connector.

Linked service properties

The following properties are supported for Spark linked service:

Property Description Required
type The type property must be set to: Spark Yes
host IP address or host name of the Spark server Yes
port The TCP port that the Spark server uses to listen for client connections. If you connect to Azure HDInsights, specify port as 443. Yes
serverType The type of Spark server.
Allowed values are: SharkServer, SharkServer2, SparkThriftServer		 No
thriftTransportProtocol The transport protocol to use in the Thrift layer.
Allowed values are: Binary, SASL, HTTP		 No
authenticationType The authentication method used to access the Spark server.
Allowed values are: Anonymous, Username, UsernameAndPassword, WindowsAzureHDInsightService		 Yes
username The user name that you use to access Spark Server. No
password The password corresponding to the user. Mark this field as a SecureString to store it securely, or reference a secret stored in Azure Key Vault. No
httpPath The partial URL corresponding to the Spark server. No
enableSsl Specifies whether the connections to the server are encrypted using TLS. The default value is false. No
trustedCertPath The full path of the .pem file containing trusted CA certificates for verifying the server when connecting over TLS. This property can only be set when using TLS on self-hosted IR. The default value is the cacerts.pem file installed with the IR. No
useSystemTrustStore Specifies whether to use a CA certificate from the system trust store or from a specified PEM file. The default value is false. No
allowHostNameCNMismatch Specifies whether to require a CA-issued TLS/SSL certificate name to match the host name of the server when connecting over TLS. The default value is false. No
allowSelfSignedServerCert Specifies whether to allow self-signed certificates from the server. The default value is false. No
connectVia The Integration Runtime to be used to connect to the data store. Learn more from Prerequisites section. If not specified, it uses the default Azure Integration Runtime. No

Example:

{
    "name": "SparkLinkedService",
    "properties": {
        "type": "Spark",
        "typeProperties": {
            "host" : "<cluster>.azurehdinsight.net",
            "port" : "<port>",
            "authenticationType" : "WindowsAzureHDInsightService",
            "username" : "<username>",
            "password": {
                 "type": "SecureString",
                 "value": "<password>"
            }
        }
    }
}

Dataset properties

For a full list of sections and properties available for defining datasets, see the datasets article. This section provides a list of properties supported by Spark dataset.

To copy data from Spark, set the type property of the dataset to SparkObject. The following properties are supported:

Property Description Required
type The type property of the dataset must be set to: SparkObject Yes
schema Name of the schema. No (if "query" in activity source is specified)
table Name of the table. No (if "query" in activity source is specified)
tableName Name of the table with schema. This property is supported for backward compatibility. Use schema and table for new workload. No (if "query" in activity source is specified)

Example

{
    "name": "SparkDataset",
    "properties": {
        "type": "SparkObject",
        "typeProperties": {},
        "schema": [],
        "linkedServiceName": {
            "referenceName": "<Spark linked service name>",
            "type": "LinkedServiceReference"
        }
    }
}

Copy activity properties

For a full list of sections and properties available for defining activities, see the Pipelines article. This section provides a list of properties supported by Spark source.

Spark as source

To copy data from Spark, set the source type in the copy activity to SparkSource. The following properties are supported in the copy activity source section:

Property Description Required
type The type property of the copy activity source must be set to: SparkSource Yes
query Use the custom SQL query to read data. For example: "SELECT * FROM MyTable". No (if "tableName" in dataset is specified)

Example:

"activities":[
    {
        "name": "CopyFromSpark",
        "type": "Copy",
        "inputs": [
            {
                "referenceName": "<Spark input dataset name>",
                "type": "DatasetReference"
            }
        ],
        "outputs": [
            {
                "referenceName": "<output dataset name>",
                "type": "DatasetReference"
            }
        ],
        "typeProperties": {
            "source": {
                "type": "SparkSource",
                "query": "SELECT * FROM MyTable"
            },
            "sink": {
                "type": "<sink type>"
            }
        }
    }
]

Lookup activity properties

To learn details about the properties, check Lookup activity.

Related content

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