Configuration Reference for Google Cloud Dataproc Sink Connector for Confluent Platform

To use this connector, specify the name of the connector class in the connector.class configuration property.

connector.class=io.confluent.connect.gcp.dataproc.DataprocSinkConnector

Connector-specific configuration properties are described below.

Note

These are properties for the self-managed connector. If you are using Confluent Cloud, see Google Cloud Dataproc Sink connector for Confluent Cloud.

GCP

gcp.dataproc.credentials.path

The path to the JSON service key file. Configure exactly one of gcp.dataproc.credentials.path or gcp.dataproc.credentials.json.

  • Type: string

  • Default: “”

  • Importance: high

gcp.dataproc.credentials.json

The contents of the JSON service key file. Configure exactly one of gcp.dataproc.credentials.path and gcp.dataproc.credentials.json.

  • Type: password

  • Default: “”

  • Importance: high

gcp.dataproc.projectId

The GCP project ID that the GCP Dataproc cluster belongs to.

  • Type: string

  • Default: “”

  • Importance: high

gcp.dataproc.region

The region that GCP Dataproc cluster belongs to.

  • Type: string

  • Default: “global”

  • Importance: high

gcp.dataproc.cluster

Name of the GCP Dataproc cluster.

  • Type: string

  • Default: “”

  • Importance: high

Proxy

proxy.host

Proxy Host. This property is meant to be used only if you need to access GCP Dataproc cluster through a proxy.

  • Type: string

  • Default: “”

  • Importance: low

proxy.port

Proxy Port. This property is meant to be used only if you need to access GCP Dataproc cluster through a proxy.

  • Type: int

  • Default: 0

  • Importance: low

proxy.username

Proxy User. This property is meant to be used only if you need to access GCP Dataproc cluster through a proxy.

  • Type: string

  • Default: “”

  • Importance: low

proxy.password

Proxy Password. This property is meant to be used only if you need to access GCP Dataproc cluster through a proxy.

  • Type: password

  • Default: “”

  • Importance: low

HDFS

logs.dir

Top level directory to store the write ahead logs.

  • Type: string

  • Default: logs

  • Importance: high

Security

hdfs.authentication.kerberos

Configuration indicating whether HDFS is using Kerberos for authentication.

  • Type: boolean

  • Default: false

  • Importance: high

  • Dependents: connect.hdfs.principal, connect.hdfs.keytab, hdfs.namenode.principal, kerberos.ticket.renew.period.ms

connect.hdfs.principal

The principal to use when HDFS is using Kerberos to for authentication.

  • Type: string

  • Default: “”

  • Importance: high

connect.hdfs.keytab

The path to the keytab file for the HDFS connector principal. This keytab file should only be readable by the connector user.

  • Type: string

  • Default: “”

  • Importance: high

hdfs.namenode.principal

The principal for HDFS Namenode.

  • Type: string

  • Default: “”

  • Importance: high

kerberos.ticket.renew.period.ms

The period in milliseconds to renew the Kerberos ticket.

  • Type: long

  • Default: 3600000

  • Importance: low

Connector

format.class

The format class to use when writing data to the store. Format classes implement the io.confluent.connect.storage.format.Format interface.

  • Type: class

  • Default: io.confluent.connect.gcp.dataproc.hdfs.avro.AvroFormat

  • Importance: high

These classes are available by default:

  • io.confluent.connect.gcp.dataproc.hdfs.avro.AvroFormat

  • io.confluent.connect.gcp.dataproc.hdfs.json.JsonFormat

  • io.confluent.connect.gcp.dataproc.hdfs.parquet.ParquetFormat

  • io.confluent.connect.gcp.dataproc.hdfs.string.StringFormat

flush.size

Number of records written to store before invoking file commits.

  • Type: int

  • Importance: high

rotate.interval.ms

The time interval in milliseconds to invoke file commits. This configuration ensures that file commits are invoked every configured interval. This configuration is useful when data ingestion rate is low and the connector didn’t write enough messages to commit files. The default value -1 means that this feature is disabled.

  • Type: long

  • Default: -1

  • Importance: high

rotate.schedule.interval.ms

The time interval in milliseconds to periodically invoke file commits. This configuration ensures that file commits are invoked every configured interval. Time of commit will be adjusted to 00:00 of selected timezone. Commit will be performed at scheduled time regardless of previous commit time or number of messages. This configuration is useful when you have to commit your data based on current server time, such as at the beginning of every hour. The default value -1 means that this feature is disabled.

  • Type: long

  • Default: -1

  • Importance: medium

schema.cache.size

The size of the schema cache used in the Avro converter.

  • Type: int

  • Default: 1000

  • Importance: low

retry.backoff.ms

The retry backoff in milliseconds. This config is used to notify Connect to retry delivering a message batch or performing recovery in case of transient exceptions.

  • Type: long

  • Default: 5000

  • Importance: low

shutdown.timeout.ms

Clean shutdown timeout. This makes sure that asynchronous Hive metastore updates are completed during connector shutdown.

  • Type: long

  • Default: 3000

  • Importance: medium

filename.offset.zero.pad.width

Width to zero pad offsets in store’s filenames if offsets are too short to provide fixed-width filenames that can be ordered by simple lexicographic sorting.

  • Type: int

  • Default: 10

  • Valid Values: [0,…]

  • Importance: low

Storage

storage.class

The underlying storage layer.

  • Type: class

  • Default: io.confluent.connect.gcp.dataproc.hdfs.storage.HdfsStorage

  • Importance: high

topics.dir

Top level directory to store the data ingested from Apache Kafka®.

  • Type: string

  • Default: topics

  • Importance: high

store.url

Store’s connection URL, if applicable.

  • Type: string

  • Default: null

  • Importance: high

directory.delim

Directory delimiter pattern.

  • Type: string

  • Default: /

  • Importance: medium

file.delim

File delimiter pattern.

  • Type: string

  • Default: +

  • Importance: medium

Partitioner

partitioner.class

The partitioner to use when writing data to the store. The following partitioners are available:

  • DefaultPartitioner preserves the Kafka partitions.

  • DailyPartitioner partitions data according to date.

  • HourlyPartitioner partitions data according to hour.

  • FieldPartitioner partitions the data to different directories according to the value of the partitioning field specified in partition.field.name.

  • TimeBasedPartitioner partitions data according to ingestion time.

  • Type: class

  • Default: io.confluent.connect.storage.partitioner.DefaultPartitioner

  • Importance: high

  • Dependents: partition.field.name, partition.duration.ms, path.format, locale, timezone

partition.field.name

The name of the partitioning field when FieldPartitioner is used. You can enter multiple partitioning field names using comma-separated names.

  • Type: string

  • Default: “”

  • Importance: medium

partition.duration.ms

The duration of a partition milliseconds used by TimeBasedPartitioner. The default value -1 means TimeBasedPartitioner is not being used.

  • Type: long

  • Default: -1

  • Importance: medium

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 proper directories strings. For example, if you set path.format='year'=YYYY/'month'=MM/'day'=dd/'hour'=HH, the data directories will have the format /year=2015/month=12/day=07/hour=15/.

  • Type: string

  • Default: “”

  • Importance: medium

locale

The locale to use when partitioning with TimeBasedPartitioner, and used to format dates and times. For example, use en-US for US English, en-GB for UK English, or fr-FR for French (in France). These may vary by Java version; see the available locales.

  • Type: string

  • Default: “”

  • Importance: medium

timezone

The timezone to use when partitioning with TimeBasedPartitioner. Used to format and compute dates and times. All timezone IDs must be specified in the long format, such as America/Los_Angeles, America/New_York, and Europe/Paris, or UTC. Alternatively a locale independent, fixed offset, datetime zone can be specified in form [+-]hh:mm. Support for these timezones may vary by Java version. See the available timezones within each locale, such as those within the US English locale.

  • Type: string

  • Default: “”

  • Importance: medium

timestamp.extractor

The extractor that gets the timestamp for records when partitioning with TimeBasedPartitioner. It can be set to Wallclock, Record, or RecordField in order to use one of the built-in timestamp extractors or be given the fully-qualified class name of a user-defined class that extends the TimestampExtractor interface.

  • Type: string

  • Default: Wallclock

  • Importance: medium

timestamp.field

The record field to be used as timestamp by the timestamp extractor.

  • Type: string

  • Default: timestamp

  • Importance: medium

Hive

hive.integration

Configuration indicating whether to integrate with Hive when running the connector.

  • Type: boolean

  • Default: false

  • Importance: high

  • Dependents: hive.metastore.uris, hive.conf.dir, hive.home, hive.database, schema.compatibility

hive.metastore.uris

The Hive metastore URIs. Can be an IP address or fully-qualified domain name and port of the metastore host.

  • Type: string

  • Default: “”

  • Importance: high

hive.conf.dir

Hive configuration directory.

  • Type: string

  • Default: “”

  • Importance: high

hive.home

Hive home directory.

  • Type: string

  • Default: “”

  • Importance: high

hive.database

The database to use when the connector creates tables in Hive.

  • Type: string

  • Default: default

  • Importance: high

Schema

schema.compatibility

The schema compatibility rule to use when the connector is observing schema changes. The supported configurations are NONE, BACKWARD, FORWARD, and FULL.

  • Type: string

  • Default: NONE

  • Importance: high

Confluent Platform license

confluent.topic.bootstrap.servers A list of host/port pairs to use for establishing the initial connection to the Kafka cluster used for licensing. All servers in the cluster will be discovered from the initial connection. This list should be in the form <code>host1:port1,host2:port2,…</code>. Because these servers are just used for the initial connection to discover the full cluster membership that could change dynamically, this list need not contain the full set of servers . You may want to list more than one in case a server is down.

  • Type: list

  • Importance: high

confluent.topic Name of the Kafka topic used for Confluent Platform configuration, including licensing information.

  • Type: string

  • Default: _confluent-command

  • Importance: low

confluent.topic.replication.factor The replication factor for the Kafka topic used for Confluent Platform configuration, including licensing information. This is used only if the topic does not already exist, and the default of 3 is appropriate for production use. If you are using a development environment with less than 3 brokers, you must set this to the number of brokers (typically 1).

  • Type: int

  • Default: 3

  • Importance: low

Confluent license properties

You can put license-related properties in the connector configuration, or starting with Confluent Platform version 6.0, you can put license-related properties in the Connect worker configuration instead of in each connector configuration.

This connector is proprietary and requires a license. The license information is stored in the _confluent-command topic. If the broker requires SSL for connections, you must include the security-related confluent.topic.* properties as described below.

confluent.license

Confluent issues enterprise license keys to each subscriber. The license key is text that you can copy and paste as the value for confluent.license. A trial license allows using the connector for a 30-day trial period. A developer license allows using the connector indefinitely for single-broker development environments.

If you are a subscriber, contact Confluent Support for more information.

  • Type: string

  • Default: “”

  • Valid Values: Confluent Platform license

  • Importance: high

confluent.topic.ssl.truststore.location

The location of the trust store file.

  • Type: string

  • Default: null

  • Importance: high

confluent.topic.ssl.truststore.password

The password for the trust store file. If a password is not set access to the truststore is still available, but integrity checking is disabled.

  • Type: password

  • Default: null

  • Importance: high

confluent.topic.ssl.keystore.location

The location of the key store file. This is optional for client and can be used for two-way authentication for client.

  • Type: string

  • Default: null

  • Importance: high

confluent.topic.ssl.keystore.password

The store password for the key store file. This is optional for client and only needed if ssl.keystore.location is configured.

  • Type: password

  • Default: null

  • Importance: high

confluent.topic.ssl.key.password

The password of the private key in the key store file. This is optional for client.

  • Type: password

  • Default: null

  • Importance: high

confluent.topic.security.protocol

Protocol used to communicate with brokers. Valid values are: PLAINTEXT, SSL, SASL_PLAINTEXT, SASL_SSL.

  • Type: string

  • Default: “PLAINTEXT”

  • Importance: medium

License topic configuration

A Confluent enterprise license is stored in the _confluent-command topic. This topic is created by default and contains the license that corresponds to the license key supplied through the confluent.license property. No public keys are stored in Kafka topics.

The following describes how the default _confluent-command topic is generated under different scenarios:

  • A 30-day trial license is automatically generated for the _confluent command topic if you do not add the confluent.license property or leave this property empty (for example, confluent.license=).

  • Adding a valid license key (for example, confluent.license=<valid-license-key>) adds a valid license in the _confluent-command topic.

Here is an example of the minimal properties for development and testing.

You can change the name of the _confluent-command topic using the confluent.topic property (for instance, if your environment has strict naming conventions). The example below shows this change and the configured Kafka bootstrap server.

confluent.topic=foo_confluent-command
confluent.topic.bootstrap.servers=localhost:9092

The example above shows the minimally required bootstrap server property that you can use for development and testing. For a production environment, you add the normal producer, consumer, and topic configuration properties to the connector properties, prefixed with confluent.topic..

License topic ACLs

The _confluent-command topic contains the license that corresponds to the license key supplied through the confluent.license property. It is created by default. Connectors that access this topic require the following ACLs configured:

  • CREATE and DESCRIBE on the resource cluster, if the connector needs to create the topic.

  • DESCRIBE, READ, and WRITE on the _confluent-command topic.

    Important

    You can also use DESCRIBE and READ without WRITE to restrict access to read-only for license topic ACLs. If a topic exists, the LicenseManager will not try to create the topic.

You can provide access either individually for each principal that will use the license or use a wildcard entry to allow all clients. The following examples show commands that you can use to configure ACLs for the resource cluster and _confluent-command topic.

  1. Set a CREATE and DESCRIBE ACL on the resource cluster:

    kafka-acls --bootstrap-server localhost:9092 --command-config adminclient-configs.conf \
--add --allow-principal User:<principal> \
--operation CREATE --operation DESCRIBE --cluster

  2. Set a DESCRIBE, READ, and WRITE ACL on the _confluent-command topic:

    kafka-acls --bootstrap-server localhost:9092 --command-config adminclient-configs.conf \
--add --allow-principal User:<principal> \
--operation DESCRIBE --operation READ --operation WRITE --topic _confluent-command

Override Default Configuration Properties

You can override the replication factor using confluent.topic.replication.factor. For example, when using a Kafka cluster as a destination with less than three brokers (for development and testing) you should set the confluent.topic.replication.factor property to 1.

You can override producer-specific properties by using the producer.override.* prefix (for source connectors) and consumer-specific properties by using the consumer.override.* prefix (for sink connectors).

You can use the defaults or customize the other properties as well. For example, the confluent.topic.client.id property defaults to the name of the connector with -licensing suffix. You can specify the configuration settings for brokers that require SSL or SASL for client connections using this prefix.

You cannot override the cleanup policy of a topic because the topic always has a single partition and is compacted. Also, do not specify serializers and deserializers using this prefix; they are ignored if added.