Important
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HDFS 2 Source Connector Configuration Properties¶
To use this connector, specify the name of the connector class in the connector.class
configuration property.
connector.class=io.confluent.connect.hdfs2.Hdfs2SourceConnector
Connector-specific configuration properties are described below.
HDFS2 Parameters¶
store.url
The HDFS connection URL. This configuration has the format of
hdfs://hostname:port
and use to make the connection with HDFS.- Type: string
- Default: null
- Importance: high
hadoop.conf.dir
The Hadoop configuration directory.
- Type: string
- Default: “”
- Importance: high
hdfs.poll.interval.ms
Frequency in milliseconds to poll for new or removed folders. This may result in updated task configurations starting to poll for data in added folders or stopping polling for data in removed folders.
- Type: long
- Default: 300000
- Importance: medium
Security Parameters¶
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
,hadoop.conf.dir
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
connect.hdfs.principal
The principal to use when HDFS is using Kerberos to for authentication.
- 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 Parameters¶
format.class
Class responsible for converting source objects to source records.
- Type: class
- Default:
io.confluent.connect.hdfs2.format.avro.AvroFormat
- Importance: high
You can use following four type of formatter:
io.confluent.connect.hdfs2.format.avro.AvroFormat
io.confluent.connect.hdfs2.format.json.JsonFormat
io.confluent.connect.hdfs2.format.string.StringFormat
io.confluent.connect.hdfs2.format.parquet.ParquetFormat
schema.cache.size
The size of the schema cache used in the Avro converter.
- Type: int
- Default: 50
- Valid Values: [1,…]
- Importance: low
record.batch.max.size
The maximum amount of records to return each time HDFS2 is polled.
- Type: int
- Default: 200
- Valid Values: [1,…]
- Importance: medium
Storage Parameters¶
topics.dir
Top level directory where data was stored to be re-ingested by Kafka.
- Type: string
- Default: topics
- Importance: high
directory.delim
Directory delimiter pattern.
- Type: string
- Default: /
- Importance: medium
behavior.on.error
Sets how the connector handles errors that occur when processing records.
- Type: string
- Default: fail
- Valid Values: Matches:
fail
,ignore
,log
- Importance: medium
Partitioner Parameters¶
partitioner.class
The partitioner to use when reading data to the store.. The following partitioners are available:
io.confluent.connect.storage.partitioner.DefaultPartitioner
io.confluent.connect.storage.partitioner.DailyPartitioner
io.confluent.connect.storage.partitioner.HourlyPartitioner
io.confluent.connect.storage.partitioner.FieldPartitioner
io.confluent.connect.storage.partitioner.TimeBasedPartitioner
- Type: class
- Default: io.confluent.connect.storage.partitioner.DefaultPartitioner
- Importance: high
partition.field.name
The name of the partitioning field when FieldPartitioner is used.
- Type: list
- Default: “”
- Importance: medium
path.format
This configuration that was used to set the format of the data directories when partitioning with a TimeBasedPartitioner. For example, if you set
path.format
to'year'=YYYY/'month'=MM/'day'=dd/'hour'=HH
, then a valid data directories would be:/year=2015/month=12/day=07/hour=15/
.- Type: string
- Default: “”
- Importance: medium
partition.duration.ms
The duration of a partition milliseconds used by
TimeBasedPartitioner
. The default value -1 means that we are not usingTimeBasedPartitioner
.- Type: long
- Default: -1
- Importance: medium
locale
The locale to use when partitioning with
TimeBasedPartitioner
, and used to format dates and times. For example, useen-US
for US English,en-GB
for UK English, orfr-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 asAmerica/Los_Angeles
,America/New_York
, andEurope/Paris
, orUTC
. 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 toWallclock
,Record
orRecordField
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 theTimestampExtractor
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
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
host1:port1,host2:port2,...
. These servers are used only for the initial connection to discover the full cluster membership, which may change dynamically, so this list need not contain the full set of servers. You may want 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 (often 1).
- Type: int
- Default: 3
- Importance: low
Confluent license properties¶
Note
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, please 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.
Note
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 theconfluent.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.
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.
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
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
Overriding 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
confluent.topic.producer.
prefix and consumer-specific properties by using
the confluent.topic.consumer.
prefix.
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.