ADLS Sink connector

The ADLS Sink connector is a Stateless NiFi dataflow developed by Cloudera that is running in the Kafka connect framework. Learn about the connector, its properties, and configuration.

The ADLS Sink connector fetches messages from Kafka and uploads them to ADLS. The topic this connector receives messages from is determined by the value of the topics property in the configuration. The messages can contain unstructured (character or binary) data or they can be in Avro or JSON format.

If the input is unstructured data, record processing is disabled. In a case like this, multiple messages can be concatenated into a single output file on ADLS using a demarcator (for example, newline for text messages). Merging is optional, large binary data can be forwarded to Azure at a 1:1 ratio, one Kafka message equals a single ADLS file.

If the input is either Avro or JSON, record processing is enabled. In a case like this, the schema of the records can be a predefined schema retrieved from Schema Registry (for both Avro and JSON data), it can be embedded in the Avro data, or inferred from the JSON data. The output can be Avro, JSON or CSV. Multiple records are typically merged into a single output file before uploading to ADLS.

The connector can authenticate to Azure using an Account Key, SAS Token, Service Principal, or a Managed Identity.

Properties and configuration

Configuration is passed to the connector in a JSON file during creation. The properties of the connector can be categorized into three groups. These are as follows:

Common connector properties

These are the properties of the Kafka Connect framework that are accepted by all connectors. For a comprehensive list of these properties, see the Apache Kafka documentation.

Stateless NiFi Sink properties

These are the properties that are specific to the Stateless NiFi Sink connector. All Stateless NiFi Sink connectors share and accept these properties. For a comprehensive list of these properties, see the Stateless NiFi Sink property reference.

Connector/dataflow-specific properties

These properties are unique to this specific connector. Or to be more precise, unique to the dataflow running within the connector. These properties use the following prefix:

parameter.[***CONNECTOR NAME***] Parameters:

For a comprehensive list of these properties, see the ADLS Sink properties reference.

Notes and limitations

Required properties must be assigned a valid value even if they are not used in the particular configuration. If a required property is not used, either leave its default value, or completely remove the property from the configuration JSON.
If a property that has a default value is completely removed from the configuration JSON, the system uses the default value.
Properties not marked as required must be completely removed from the configuration JSON if not set.

Configuration example for fetching unstructured data

In this example, the connector fetches unstructured messages containing single line character data from Kafka. The connector concatenates the messages using newline characters as the demarcator. The files that the connector creates and uploads to ADLS are maximum 10 MB in size. The files are named according to the following pattern: messages_[***UUID***]. The connector authenticates to Azure using an Account Key.

{
 "connector.class": "org.apache.nifi.kafka.connect.StatelessNiFiSinkConnector",
 "meta.smm.predefined.flow.name": "ADLS Sink",
 "meta.smm.predefined.flow.version": "1.0.0",
 "key.converter": "org.apache.kafka.connect.storage.StringConverter",
 "value.converter": "org.apache.kafka.connect.converters.ByteArrayConverter",
 "tasks.max": "1",
 "nexus.url": "https://repository.cloudera.com/artifactory/repo",
 "extensions.directory": "/tmp/nifi-stateless-extensions",
 "working.directory": "/tmp/nifi-stateless-working",
 "failure.ports": "PutAzureDataLakeStorage Failure",
 "topics": "[***KAFKA TOPIC NAME***]",
 "parameter.ADLS Sink Parameters:ADLS Account Name": "[***ACCOUNT NAME***]",
 "parameter.ADLS Sink Parameters:ADLS Account Key": "[***ACCOUNT KEY***]",
 "parameter.ADLS Sink Parameters:ADLS Filesystem Name": "[***FILESYSTEM NAME***]",
 "parameter.ADLS Sink Parameters:ADLS Directory Name": "[***DIRECTORY NAME***]",
 "parameter.ADLS Sink Parameters:Maximum File Size": "10 MB",
 "parameter.ADLS Sink Parameters:Kafka Message Data Format": "Raw",
 "parameter.ADLS Sink Parameters:Output File Demarcator": "\n",
 "parameter.ADLS Sink Parameters:Output Filename Pattern": "messages_${filename.uuid}"
}

The following list collects the properties from the configuration example that must be customized for this use case.

topics: The name of the Kafka topic the connector fetches messages from.
ADLS Account Name: The Storage Account Name to use for authentication to Azure. This is also the target account where the output file is uploaded.
ADLS Account Key: The Storage Account Key to use for authentication to Azure.
ADLS Filesystem Name: The filesystem (or container) in the Storage Account to upload data to.
ADLS Directory Name: The target directory in the filesystem.
Maximum File Size: The maximum size of the output data file. In this example, the maximum size is 10 MB.
Kafka Message Data Format: The format of the messages the connector receives from Kafka. In this example, this property is set to Raw. This means that the connector expects unstructured text or binary data.
Output File Demarcator: Specifies the character sequence for demarcating (delimiting) message boundaries when multiple Kafka messages are ingested into an output file as raw messages. In this example, the property is set to \n (newline). This means that the newline character is used to separate the single line character data of the Kafka messages.
Output Filename Pattern: Specifies the structure of the name of the output file. This property accepts string literals (fixed text) as well as various expressions. In this example, the property is set to messages_${filename.uuid}.
messages_ is a string literal. ${filename.uuid} is an expression that inserts a generated UUID in the filename. As a result, the files are named according to the following pattern: messages_[***UUID***].

Configuration example for fetching JSON data

In this example, the connector fetches messages in JSON format from Kafka. The connector parses the JSON records and converts them to Avro format using the schema inferred from the JSON data. The schema is also embedded in the output file. The connector merges multiple records (all messages that are available for a single execution of the connector) into an Avro file, generates a name for the file using the following pattern data_[***TIMESTAMP***]_[***SEQUENCE***].avro, and uploads the file to ADLS. The connector authenticates to Azure using a Service Principal.

{
 "connector.class": "org.apache.nifi.kafka.connect.StatelessNiFiSinkConnector",
 "meta.smm.predefined.flow.name": "ADLS Sink",
 "meta.smm.predefined.flow.version": "1.0.0",
 "key.converter": "org.apache.kafka.connect.storage.StringConverter",
 "value.converter": "org.apache.kafka.connect.converters.ByteArrayConverter",
 "nexus.url": "https://repository.cloudera.com/artifactory/repo",
 "extensions.directory": "/tmp/nifi-stateless-extensions",
 "working.directory": "/tmp/nifi-stateless-working",
 "failure.ports": "PutAzureDataLakeStorage Failure",
 "topics": "[***KAFKA TOPIC NAME***]",
 "parameter.ADLS Sink Parameters:ADLS Account Name": "[***ACCOUNT NAME***]",
 "parameter.ADLS Sink Parameters:Azure Service Principal Tenant ID": "[***SERVICE PRINCIPAL TENANT ID***]",
 "parameter.ADLS Sink Parameters:Azure Service Principal Client ID": "[***SERVICE PRINCIPAL CLIENT ID***]",
 "parameter.ADLS Sink Parameters:Azure Service Principal Client Secret": "[***SERVICE PRINCIPAL CLIENT SECRET***]",
 "parameter.ADLS Sink Parameters:ADLS Filesystem Name": "[***FILESYSTEM NAME***]",
 "parameter.ADLS Sink Parameters:ADLS Directory Name": "[***DIRECTORY NAME***]",
 "parameter.ADLS Sink Parameters:Kafka Message Data Format": "JSON",
 "parameter.ADLS Sink Parameters:Schema Access Strategy": "Infer Schema",
 "parameter.ADLS Sink Parameters:Schema Write Strategy": "Embed Avro Schema",
 "parameter.ADLS Sink Parameters:Output File Data Format": "Avro",
 "parameter.ADLS Sink Parameters:Output Filename Pattern": "data_${filename.timestamp}_${filename.sequence}.avro",
 "parameter.ADLS Sink Parameters:Output Filename Timestamp Format": "yyyyMMdd_HHmmss_SSS"
}

The following list collects the properties from the configuration example that must be customized for this use case.

topics: The name of the Kafka topic the connector fetches messages from.
ADLS Account Name: The Storage Account Name to use for authentication to Azure. This is also the target account where the output file is uploaded.
Service Principal *: The properties of the Service Principal to use for authentication to Azure.
ADLS Filesystem Name: The filesystem (or container) in the Storage Account to upload data to.
ADLS Directory Name: The target directory in the filesystem.
Kafka Message Data Format: The format of the messages the connector receives from Kafka. In this example, this property is set to JSON. This means that the connector expects JSON data.
Schema Access Strategy: Specifies the strategy used for determining the schema of the Kafka record. In this example, this property is set to Infer Schema, meaning that the schema is determined (inferred) from the JSON data.
Schema Write Strategy: Specifies whether the record schema is written to the output data file. In this example, this property is set to Embed Avro Schema, meaning that the schema is embedded in the output Avro file.
Output File Data Format: Specifies the format of the records written to the output file. In this example, this property is set to Avro, meaning that the output file format is Avro.
Output Filename Pattern: Specifies the structure of the name of the output file. This property accepts string literals (fixed text) as well as various expressions. In this example, the property is set to data_${filename.timestamp}_${filename.sequence}.avro.
data_, the underscore ( _ ), and .avro are string literals. ${filename.timestamp} and ${filename.sequence} are expressions. ${filename.timestamp} inserts the current timestamp in the filename. ${filename.sequence} inserts an incrementing sequence value in the filename. As a result, the files are named according to the following pattern: data_[***TIMESTAMP***]_[***SEQUENCE***].avro.
Output Filename Timestamp Format: Specifies the timestamp format used in the ${filename.timestamp} expression. The expression is used when generating the output filename.