Configuration Reference for Databricks Delta Lake Sink for Confluent Platform¶
The following connector configuration properties are used with the Databricks Delta Lake Sink connector for Confluent Platform. For common sink connector configuration properties, see the Kafka Sink Connector Configuration Reference page.
Note
These are properties for the self-managed connector. If you are using Confluent Cloud, see Databricks Delta Lake Sink Connector for Confluent Cloud.
delta.lake.table2partition.map
A map of tables to partition fields in the format of comma-separated tuples (for example,
<table-1>:<partition-1>,<table-2>:<partition-2>,...
)- Type: String
- Importance: Low
- Default value: “”
delta.lake.host.name
The Databricks Delta Lake server hostname.
- Type: String
- Importance: High
delta.lake.http.path
The HTTP path used to connect to the Databricks Delta Lake instance.
- Type: String
- Importance: High
delta.lake.token
The personal access token authenticates the user when connecting to the Databricks Delta Lake instance using JDBC.
- Type: Password
- Importance: High
staging.s3.access.key.id
The AWS access key is used to connect to the S3 staging bucket.
- Type: Password
- Importance: High
staging.s3.secret.access.key
The AWS secret access key is used to connect to the S3 staging bucket.
- Type: Password
- Importance: High
staging.bucket.name
The S3 staging bucket where files get written to from Kafka, and that subsequently get copied into the Databricks Delta Lake table.
- Type: String
- Importance: High
delta.lake.table.format
A format string for the destination table name, which may contain
${topic}
as a placeholder for the originating topic name. For example, to create a table namedkafka-orders
based on a Kafka topic namedorders
, you would enterkafka-${topic}
in this field. Note that you must use the${topic}
placeholder if you have multiple originating topics.- Type: String
- Default value:
${topic}
- Importance: Medium
delta.lake.topic2table.map
Map of topics to tables in the format of comma-separated tuples. For example,
<topic-1>:<table-1>,<topic-2>:<table-2>,...
.- Type: String
- Default value:
${topic}
- Importance: Low
delta.lake.table.auto.create
Whether to automatically create the destination table (based on the record schema) if it does not exist. Defaults to
false
.- Type: String
- Default value: false
- Importance: Medium
delta.lake.tables.location
The underlying location where the data in the Delta Lake table or tables are stored.
- Type: String
- Default value: “”
- Importance: Medium
delta.lake.table2partition.map
Map of tables to partition fields in the format of comma-separated tuples. For example,
<table-1>:<partition-1>,<table-1>:<partition-2>,<table-2>:<partition-3>...
.- Type: String
- Default value: “”
- Importance: Low
flush.interval.ms
The time interval in milliseconds (ms) to periodically invoke file commits. This property ensures the connector invokes file commits at every configured interval. The commit time is adjusted to
00:00
UTC. The commit is performed at the scheduled time, regardless of the last commit time or number of messages. This configuration is useful when you have to commit your data based on current server time, like at the beginning of each hour. The default value used is300,000
ms (5 minutes).- Type: Long
- Default value: 300000
- Importance: Medium
delta.lake.topic2table.map
Map of topics to tables (optional). Create mapping as comma-separated tuples. For example:
<topic-1>:<table-1>,<topic-2>:<table-2>,...
. If you use this property, the connector ignores any string entered fordelta.lake.table.format
.- Type: String
- Default value:
${topic}
- Importance: Low