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Releases: marklogic/kafka-marklogic-connector

1.5.0

14 Nov 17:18

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  • Added options for logging incoming record keys and headers after write failures
  • Updated the AWS CloudFormation Quick Start document
  • Added documentation for using the connector with the AWS MSK (Kafka as a Service)

1.4.0

13 Oct 01:40

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  • Support for JSON Schema, ProtoBuf messages.
  • Also support of ID strategies - UUID, JSONPATH,HASH, KAFKA_META_WITH_SLASH, KAFKA_META_HASHED
  • Removing some erroneous comments in the example connect-standalone properties file.
  • Changes for additional Security options
  • Updated build.gradle to new kafka connect and datahub
  • Updated Test Cases.
  • Some forgotten cleanup left over from building the Confluent archive.

1.3.0

18 Aug 16:49

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Support of additional authentication options.
Documentation of how to update the connector for security options. Refer to MarkLogic_Kafka_Connector_v1.3.0.pdf for details.

1.2.1

24 May 19:47

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Fixed erroneous comments in the connect-standalone properties file.

1.2.0

22 Apr 00:57
b15f4c0

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  • Can now run a flow using DHF 5.2.0
  • Updated the AWS quickstart document.
  • Updated AWS-CloudFormation/cloudFormationTemplates/* with newer AMI, added some steps to CloudFormation-QuickStart.md

1.1.0

13 Dec 17:38

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Fixed a bug with handling null, or "tombstone", messages.
Added a feature to permit automatically adding the Kafka topic name as a collection on the documents.
Documented how to use simple SSL to connect to Kafka brokers and/or MarkLogic clusters.
Documented how to use multiple instances of the connector in distributed mode.

1.0.0

22 Oct 01:19

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This version is stable and ready for integration.
It includes:

  • the ability to call a DMSDK transformation on each document.
  • Tested with MarkLogic 10.
  • examples of SSL integration with Kafka and MarkLogic.
  • the ability to generate a Confluent Connector Archive.

0.9.0

31 Aug 19:26
2cbd9c7

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This initial release has all necessary functionality.
It has been tested extensively in AWS and Docker using test clusters and test data producers.