SFTP Sink Connector for Confluent Cloud¶

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

The fully-managed 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.

Note

This Quick Start is for the fully-managed Confluent Cloud connector. If you are installing the connector locally for Confluent Platform, see SFTP Sink Connector for Confluent Platform.
If you require private networking for fully-managed connectors, make sure to set up the proper networking beforehand. For more information, see Manage Networking for Confluent Cloud Connectors.

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 Usage Examples section.

Limitations¶

Be sure to review the following information.

For connector limitations, see SFTP Sink Connector limitations.
If you plan to use one or more Single Message Transforms (SMTs), see SMT Limitations.
If you plan to use Confluent Cloud Schema Registry, see Schema Registry Enabled Environments.

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.
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.

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 topics you want to connect from the Topics list.

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

Enter the SFTP Details:
- SFTP Host: Enter the host address for the SFTP server. For example 192.168.1.231.
- SFTP Port: Enter the SFTP host port to use. If no port number is entered, this defaults to 22.
- Username: Enter the user name that the connector will use to connect to the host.
- Password: Enter the password for the user name entered. A password is not required if a PEM file is used for key based authentication to the host.
- PEM File: If using TLS, upload the PEM file that contains the private key for the SFTP user.
- TLS passphrase: If the private key is encrypted, enter the passphrase to decrypt the private key.
Click Continue.

Note

Configuration properties that are not shown in the Cloud Console use the default values. See Configuration Properties for all property values and descriptions.

Select the Input Kafka record value format (data coming from the Kafka topic): AVRO, JSON_SR (JSON Schema), PROTOBUF, 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).
Select the Output Kafka record value format (data coming from the connector): AVRO or JSON.
Select the Time interval that sets how you want your messages grouped in the file system. For example, if you select Hourly, messages are grouped into folders for each hour data is streamed to the file system.
Enter the Flush size. This value defaults to 1000. The default value can be raised (and lowered, if running a dedicated cluster). Advanced users may define how the connector flushes records to S3 by clicking the following:
Show advanced configurations
- Schema context: Select a schema context to use for this connector, if using a schema-based data format. This property defaults to the Default context, which configures the connector to use the default schema set up for Schema Registry in your Confluent Cloud environment. A schema context allows you to use separate schemas (like schema sub-registries) tied to topics in different Kafka clusters that share the same Schema Registry environment. For example, if you select a non-default context, a Source connector uses only that schema context to register a schema and a Sink connector uses only that schema context to read from. For more information about setting up a schema context, see What are schema contexts and when should you use them?.
- Topic directory (Optional): This is a top-level directory name to use for stored data. Defaults to topics if not used.
- SFTP Working Directory (Optional): Path of the top level directory where the connector should write to. Defaults to /home/${sftp.username}.
- Path format (Optional): This configures the time-based partitioning path created in the file system. The property converts the UNIX timestamp to a date format string. If not used, this property defaults to 'year'=YYYY/'month'=MM/'day'=dd/'hour'=HH if an Hourly Time interval was selected or 'year'=YYYY/'month'=MM/'day'=dd if a Daily Time interval was selected.
Note

The Path format, Topic directory, and Time interval properties can be used to build a directory structure for stored data. For example: You set Time interval to HOURLY, Topics directory 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>.
- Maximum span of record time (in ms) before scheduled rotation (Optional): 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. See Configuration Properties for details about the two optional rotation interval properties.
- Compression Type (Optional): Select a compression type for files. Use deflate, snappy, or bzip2 for AVRO output. Use gzip for JSON output.
- Maximum span of record time (in ms) before rotation (Optional): 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 files starts with the timestamp of the first record inserted in the file.
- Timestamp field name: The record field used for the timestamp, which is used with the time-base partitioner. If not used, this defaults to the timestamp when the Kafka record was produced or stored by the Kafka broker.
- Timezone: Use a valid timezone. Defaults to UTC if not used.
- Locale: Select a locale. Defaults to en.
Auto-restart policy
- Enable Connector Auto-restart: Control the auto-restart behavior of the connector and its task in the event of user-actionable errors. Defaults to true, enabling the connector to automatically restart in case of user-actionable errors. Set this property to false to disable auto-restart for failed connectors. In such cases, you would need to manually restart the connector.
Consumer configuration
- Max poll interval(ms): Set the maximum delay between subsequent consume requests to Kafka. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 300,000 milliseconds (5 minutes).
- Max poll records: Set the maximum number of records to consume from Kafka in a single request. Use this property to improve connector performance in cases when the connector cannot send records to the sink system. The default is 500 records.
Transforms
- Single Message Transforms: To add a new SMT, see Add transforms. For more information about unsupported SMTs, see Unsupported transformations.
Click Continue.

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 Usage Examples section.

Tip

When you launch a connector, a Dead Letter Queue topic is automatically created. See View Connector Dead Letter Queue Errors in Confluent Cloud 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
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Step 2: List the connector configuration properties¶

Enter the following command to show the connector configuration properties:

confluent connect plugin describe <connector-plugin-name>
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The command output shows the required and optional configuration properties.

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",
}
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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 cluster create --config-file <file-name>.json
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For example:

confluent connect cluster create --config-file sftp-sink-config.json
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Example output:

Created connector SftpSinkConnector_0 lcc-do6vzd
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Step 4: Check the connector status.¶

Enter the following command to check the connector status:

confluent connect cluster list
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Example output:

ID           |             Name              | Status  | Type | Trace
+------------+-------------------------------+---------+------+-------+
lcc-do6vzd   | SftpSinkConnector_0           | RUNNING | sink |       |
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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 Usage Examples section.

Tip

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

Configuration Properties¶

Use the following configuration properties with the fully-managed connector. For self-managed connector property definitions and other details, see the connector docs in Self-managed connectors 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

Schema Config¶

schema.context.name

Add a schema context name. A schema context represents an independent scope in Schema Registry. It is a separate sub-schema tied to topics in different Kafka clusters that share the same Schema Registry instance. If not used, the connector uses the default schema configured for Schema Registry in your Confluent Cloud environment.

Type: string
Default: default
Importance: medium

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
Default: JSON
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

Kafka API Key. Required when kafka.auth.mode==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

Secret associated with Kafka API key. Required when kafka.auth.mode==KAFKA_API_KEY.

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.

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). 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
Valid Values: [1000,…] for non-dedicated clusters and [1,…] for dedicated clusters
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

Consumer configuration¶

max.poll.interval.ms

The maximum delay between subsequent consume requests to Kafka. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 300000 milliseconds (5 minutes).

Type: long
Default: 300000 (5 minutes)
Valid Values: [60000,…,1800000] for non-dedicated clusters and [60000,…] for dedicated clusters
Importance: low

max.poll.records

The maximum number of records to consume from Kafka in a single request. This configuration property may be used to improve the performance of the connector, if the connector cannot send records to the sink system. Defaults to 500 records.

Type: long
Default: 500
Valid Values: [1,…,500] for non-dedicated clusters and [1,…] for dedicated clusters
Importance: low

Number of tasks for this connector¶

tasks.max

Maximum number of tasks for the connector.

Type: int
Valid Values: [1,…]
Importance: high

Additional Configs¶

consumer.override.auto.offset.reset

Defines the behavior of the consumer when there is no committed position (which occurs when the group is first initialized) or when an offset is out of range. You can choose either to reset the position to the “earliest” offset or the “latest” offset (the default). You can also select “none” if you would rather set the initial offset yourself and you are willing to handle out of range errors manually. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#auto-offset-reset

Type: string
Importance: low

consumer.override.isolation.level

Controls how to read messages written transactionally. If set to read_committed, consumer.poll() will only return transactional messages which have been committed. If set to read_uncommitted (the default), consumer.poll() will return all messages, even transactional messages which have been aborted. Non-transactional messages will be returned unconditionally in either mode. More details: https://docs.confluent.io/platform/current/installation/configuration/consumer-configs.html#isolation-level

Type: string
Importance: low

header.converter

The converter class for the headers. This is used to serialize and deserialize the headers of the messages.

Type: string
Importance: low

value.converter.allow.optional.map.keys

Allow optional string map key when converting from Connect Schema to Avro Schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.auto.register.schemas

Specify if the Serializer should attempt to register the Schema.

Type: boolean
Importance: low

value.converter.connect.meta.data

Allow the Connect converter to add its metadata to the output schema. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.avro.schema.support

Enable enhanced schema support to preserve package information and Enums. Applicable for Avro Converters.

Type: boolean
Importance: low

value.converter.enhanced.protobuf.schema.support

Enable enhanced schema support to preserve package information. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.flatten.unions

Whether to flatten unions (oneofs). Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.index.for.unions

Whether to generate an index suffix for unions. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.generate.struct.for.nulls

Whether to generate a struct variable for null values. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.int.for.enums

Whether to represent enums as integers. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.latest.compatibility.strict

Verify latest subject version is backward compatible when use.latest.version is true.

Type: boolean
Importance: low

value.converter.object.additional.properties

Whether to allow additional properties for object schemas. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.optional.for.nullables

Whether nullable fields should be specified with an optional label. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.optional.for.proto2

Whether proto2 optionals are supported. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.scrub.invalid.names

Whether to scrub invalid names by replacing invalid characters with valid characters. Applicable for Avro and Protobuf Converters.

Type: boolean
Importance: low

value.converter.use.latest.version

Use latest version of schema in subject for serialization when auto.register.schemas is false.

Type: boolean
Importance: low

value.converter.use.optional.for.nonrequired

Whether to set non-required properties to be optional. Applicable for JSON_SR Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.nullables

Whether nullable fields should use primitive wrapper messages. Applicable for Protobuf Converters.

Type: boolean
Importance: low

value.converter.wrapper.for.raw.primitives

Whether a wrapper message should be interpreted as a raw primitive at root level. Applicable for Protobuf Converters.

Type: boolean
Importance: low

errors.tolerance

Use this property if you would like to configure the connector’s error handling behavior. WARNING: This property should be used with CAUTION for SOURCE CONNECTORS as it may lead to dataloss. If you set this property to ‘all’, the connector will not fail on errant records, but will instead log them (and send to DLQ for Sink Connectors) and continue processing. If you set this property to ‘none’, the connector task will fail on errant records.

Type: string
Default: all
Importance: low

key.converter.key.subject.name.strategy

How to construct the subject name for key schema registration.

Type: string
Default: TopicNameStrategy
Importance: low

value.converter.decimal.format

Specify the JSON/JSON_SR serialization format for Connect DECIMAL logical type values with two allowed literals:

BASE64 to serialize DECIMAL logical types as base64 encoded binary data and

NUMERIC to serialize Connect DECIMAL logical type values in JSON/JSON_SR as a number representing the decimal value.

Type: string
Default: BASE64
Importance: low

value.converter.flatten.singleton.unions

Whether to flatten singleton unions. Applicable for Avro and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.ignore.default.for.nullables

When set to true, this property ensures that the corresponding record in Kafka is NULL, instead of showing the default column value. Applicable for AVRO,PROTOBUF and JSON_SR Converters.

Type: boolean
Default: false
Importance: low

value.converter.reference.subject.name.strategy

Set the subject reference name strategy for value. Valid entries are DefaultReferenceSubjectNameStrategy or QualifiedReferenceSubjectNameStrategy. Note that the subject reference name strategy can be selected only for PROTOBUF format with the default strategy being DefaultReferenceSubjectNameStrategy.

Type: string
Default: DefaultReferenceSubjectNameStrategy
Importance: low

value.converter.replace.null.with.default

Whether to replace fields that have a default value and that are null to the default value. When set to true, the default value is used, otherwise null is used. Applicable for JSON Converter.

Type: boolean
Default: true
Importance: low

value.converter.schemas.enable

Include schemas within each of the serialized values. Input messages must contain schema and payload fields and may not contain additional fields. For plain JSON data, set this to false. Applicable for JSON Converter.

Type: boolean
Default: false
Importance: low

value.converter.value.subject.name.strategy

Determines how to construct the subject name under which the value schema is registered with Schema Registry.

Type: string
Default: TopicNameStrategy
Importance: low

Auto-restart policy¶

auto.restart.on.user.error

Enable connector to automatically restart on user-actionable errors.

Type: boolean
Default: true
Importance: medium

Next Steps¶

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.