SFTP Sink Connector for Confluent Cloud

Note

This is a Quick Start for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see SFTP Sink Connector for Confluent Platform.

You can use the managed SFTP Sink connector for Confluent Cloud to export data from Apache Kafka® topics to files in an SFTP directory.

The SFTP Sink connector periodically polls data from Kafka and writes this data to SFTP files. A time-based partitioner is used to split the data of every Kafka partition into chunks. Each chunk of data is represented as a file. The file name encodes the topic, the Kafka partition, and the start offset of this data chunk. The size of each data chunk is determined by the number of records written and by schema compatibility.

Features

The SFTP Sink connector supports the following features:

  • Exactly once delivery: Records that are exported using a deterministic partitioner are delivered with exactly-once semantics.
  • Partitioner: The connector supports the TimeBasedPartitioner class based on the Kafka class TimeStamp. Time-based partitioning options are daily or hourly.
  • Supports multiple tasks: The connector supports running one or more tasks. More tasks may improve performance.
  • Supported data formats: The connector supports Avro, JSON Schema (JSON-SR), Protobuf, JSON (schemaless), and Bytes input data formats. The connector supports Avro and JSON output formats. Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON Schema, or Protobuf).

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Limitations

Be sure to review the following information.

Quick Start

Use this quick start to get up and running with the Confluent Cloud SFTP Sink connector. The quick start provides the basics of selecting the connector and configuring it to stream events to an SFTP directory.

Prerequisites
  • Authorized access to a Confluent Cloud cluster on Amazon Web Services (AWS), Microsoft Azure (Azure), or Google Cloud Platform (GCP).
  • The Confluent CLI installed and configured for the cluster. See Install the Confluent CLI.
  • Access to an SFTP host.
  • Schema Registry must be enabled to use a Schema Registry-based format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
  • At least one source Kafka topic must exist in your Confluent Cloud cluster before creating the sink connector.

Using the Confluent Cloud Console

Step 1: Launch your Confluent Cloud cluster.

See the Quick Start for Confluent Cloud for installation instructions.

Step 2: Add a connector.

In the left navigation menu, click Connectors. If you already have connectors in your cluster, click + Add connector.

Step 3: Select your connector.

Click the SFTP Sink connector card.

SFTP Sink Connector Card

Step 4: Enter the connector details.

Note

  • Ensure you have all your prerequisites completed.
  • An asterisk ( * ) designates a required entry.

At the Add SFTP Sink Connector screen, complete the following:

If you’ve already populated your Kafka topics, select the topic(s) you want to connect from the Topics list.

To create a new topic, click +Add new topic.

Step 5: Check for files.

Verify that records are being produced on the SFTP host.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

Using the Confluent CLI

To set up and run the connector using the Confluent CLI, complete the following steps.

Note

Make sure you have all your prerequisites completed.

Step 1: List the available connectors.

Enter the following command to list available connectors:

confluent connect plugin list

Step 2: Show the required connector configuration properties.

Enter the following command to show the required connector properties:

confluent connect plugin describe <connector-catalog-name>

For example:

confluent connect plugin describe SftpSink

Example output:

Following are the required configs:
connector.class: SftpSink
topics
input.data.format
name
kafka.api.key
kafka.api.secret
sftp.host
sftp.username
output.data.format
time.interval
rotate.schedule.interval.ms
rotate.interval.ms
tasks.max

Step 3: Create the connector configuration file.

Create a JSON file that contains the connector configuration properties. The following example shows the required connector properties.

{
  "connector.class": "SftpSink",
  "topics": "orders",
  "input.data.format": "JSON",
  "name": "SftpSinkConnector_0",
  "kafka.api.key": "****************",
  "kafka.api.secret": "*********************************",
  "sftp.host": "192.168.1.231",
  "sftp.username": "connect-user",
  "sftp.password:": "****************",
  "output.data.format": "JSON",
  "time.interval": "HOURLY",
  "rotate.schedule.interval.ms": "",
  "rotate.interval.ms": "",
  "tasks.max": "1",
}

Note the following property definitions:

  • "connector.class": Identifies the connector plugin name.
  • "topics": Enter the topic name or a comma-separated list of topic names.
  • "input.data.format": Sets (data coming from the Kafka topic): AVRO, PROTOBUF, JSON_SR (JSON Schema), JSON (schemaless), or BYTES. A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
  • "name": Sets a name for your new connector.
  • "kafka.api.key" and "kafka.api.secret": These credentials are either the cluster API key and secret or the service account API key and secret.
  • "sftp.host": Enter the host address for the SFTP server. For example 192.168.1.231. Note that the port defaults to 22. To change this, add the property "sftp.port".
  • "sftp.username": Enter the user name that the connector will use to connect to the host.
  • "output.data.format": Enter AVRO or JSON (schemaless). A valid schema must be available in Schema Registry to use a schema-based message format (for example, Avro, JSON_SR (JSON Schema), or Protobuf).
  • "time.interval": Sets how you want your messages grouped in the file system. Options are HOURLY or DAILY.
  • "rotate.schedule.interval.ms" and "rotate.interval.ms": See the Configuration Properties for the property descriptions.
  • "tasks.max": Enter the maximum number of tasks for the connector to use. More tasks may improve performance.

Note

The properties path.format, topics.dir, and time.interval properties can be used to build a directory structure for stored data. For example, you set time.interval to HOURLY, topics.dir to json_logs/hourly, and path.format` to ``'dt'=YYYY-MM-dd/'hr'=HH. The result is the directory structure: filesystem://store-name/json_logs/hourly/<Topic-Name>/dt=2020-02-06/hr=09/<files>. See the Configuration Properties for property values and definitions.

Single Message Transforms: See the Single Message Transforms (SMT) documentation for details about adding SMTs using the CLI.

See Configuration Properties for all property values and descriptions.

Step 3: Load the properties file and create the connector.

Enter the following command to load the configuration and start the connector:

confluent connect create --config <file-name>.json

For example:

confluent connect create --config sftp-sink-config.json

Example output:

Created connector SftpSinkConnector_0 lcc-do6vzd

Step 4: Check the connector status.

Enter the following command to check the connector status:

confluent connect list

Example output:

ID           |             Name              | Status  | Type | Trace
+------------+-------------------------------+---------+------+-------+
lcc-do6vzd   | SftpSinkConnector_0           | RUNNING | sink |       |

Step 5: Check for files.

Verify that records are being produced on the SFTP host.

For more information and examples to use with the Confluent Cloud API for Connect, see the Confluent Cloud API for Connect section.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See Confluent Cloud Dead Letter Queue for details.

Configuration Properties

Use the following configuration properties with this connector.

Note

These are properties for the managed cloud connector. If you are installing the connector locally for Confluent Platform, see SFTP Sink Connector for Confluent Platform.

Which topics do you want to get data from?

topics

Identifies the topic name or a comma-separated list of topic names.

  • Type: list
  • Importance: high

Input messages

input.data.format

Sets the input Kafka record value format. Valid entries are AVRO, JSON_SR, PROTOBUF, JSON or BYTES. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO, JSON_SR, and PROTOBUF.

  • Type: string
  • Importance: high

How should we connect to your data?

name

Sets a name for your connector.

  • Type: string
  • Valid Values: A string at most 64 characters long
  • Importance: high

Kafka Cluster credentials

kafka.auth.mode

Kafka Authentication mode. It can be one of KAFKA_API_KEY or SERVICE_ACCOUNT. It defaults to KAFKA_API_KEY mode.

  • Type: string
  • Default: KAFKA_API_KEY
  • Valid Values: KAFKA_API_KEY, SERVICE_ACCOUNT
  • Importance: high
kafka.api.key
  • Type: password
  • Importance: high
kafka.service.account.id

The Service Account that will be used to generate the API keys to communicate with Kafka Cluster.

  • Type: string
  • Importance: high
kafka.api.secret
  • Type: password
  • Importance: high

SFTP Details

sftp.host

Host address of the SFTP server.

  • Type: string
  • Importance: high
sftp.port

Port number of the SFTP server.

  • Type: int
  • Default: 22
  • Importance: medium
sftp.username

Username for the SFTP connection.

  • Type: string
  • Importance: high
sftp.password

Password for the SFTP connection (not required if using TLS).

  • Type: password
  • Importance: high
tls.pemfile

PEM file to be used for authentication via TLS.

  • Type: password
  • Importance: high
tls.passphrase

Passphrase that will be used to decrypt the private key if the given private key is encrypted.

  • Type: password
  • Importance: high
sftp.working.dir

Path of the top level directory where the connector should write to (defaults to /home/${sftp.username}).

  • Type: string
  • Default: /home/${sftp.username}
  • Importance: medium

Output messages

output.data.format

Set the output message format for values. Valid entries are AVRO, JSON. Note that you need to have Confluent Cloud Schema Registry configured if using a schema-based message format like AVRO. Note that the output message format defaults to the value in the Input Message Format field. If either PROTOBUF or JSON_SR is selected as the input message format, you should select one explicitly. If no value for this property is provided, the value specified for the ‘input.data.format’ property is used.

  • Type: string
  • Importance: high

Organize my data by…

topics.dir

Top-level directory where ingested data is stored.

  • Type: string
  • Default: topics
  • Importance: high
path.format

This configuration is used to set the format of the data directories when partitioning with TimeBasedPartitioner. The format set in this configuration converts the Unix timestamp to a valid directory string. To organize files like this example, filesystem://store-name/json_logs/daily/<Topic-Name>/dt=2020-02-06/hr=09/<files>, use the properties: topics.dir=json_logs/daily, path.format=’dt’=YYYY-MM-dd/’hr’=HH, and time.interval=HOURLY.

  • Type: string
  • Default: ‘year’=YYYY/’month’=MM/’day’=dd/’hour’=HH
  • Importance: high
time.interval

Partitioning interval of data, according to the time ingested to storage.

  • Type: string
  • Importance: high
rotate.schedule.interval.ms

Scheduled rotation uses rotate.schedule.interval.ms to close the file and upload to storage on a regular basis using the current time, rather than the record time. Setting rotate.schedule.interval.ms is nondeterministic and will invalidate exactly-once guarantees. Minimum value is 600000ms (10 minutes).

  • Type: int
  • Default: -1
  • Importance: medium
rotate.interval.ms

The connector’s rotation interval specifies the maximum timespan (in milliseconds) a file can remain open and ready for additional records. In other words, when using rotate.interval.ms, the timestamp for each file starts with the timestamp of the first record inserted in the file. The connector closes and uploads a file to the blob store when the next record’s timestamp does not fit into the file’s rotate.interval time span from the first record’s timestamp. If the connector has no more records to process, the connector may keep the file open until the connector can process another record (which can be a long time). Minimum value is 600000ms (10 minutes). If no value for this property is provided, the value specified for the ‘time.interval’ property is used.

  • Type: int
  • Importance: high
flush.size

Number of records written to storage before invoking file commits.

  • Type: int
  • Default: 1000
  • Importance: high
timestamp.field

Sets the field that contains the timestamp used for the TimeBasedPartitioner

  • Type: string
  • Default: “”
  • Importance: high
timezone

Sets the timezone used by the TimeBasedPartitioner.

  • Type: string
  • Default: UTC
  • Importance: high
locale

Sets the locale to use with TimeBasedPartitioner.

  • Type: string
  • Default: en
  • Importance: high
compression.codec

Compression type for files. ‘deflate’, ‘snappy’ and ‘bzip2’ can be used when the output format is AVRO; ‘gzip’ can be used when the output format is JSON.

  • Type: string
  • Importance: high
value.converter.connect.meta.data

Toggle for enabling/disabling connect converter to add its meta data to the output schema or not.

  • Type: boolean
  • Default: true
  • Importance: medium

Number of tasks for this connector

tasks.max
  • Type: int
  • Valid Values: [1,…]
  • Importance: high

Next Steps

See also

For an example that shows fully-managed Confluent Cloud connectors in action with Confluent Cloud ksqlDB, see the Cloud ETL Demo. This example also shows how to use Confluent CLI to manage your resources in Confluent Cloud.

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