2.3.0

• Security: Write maven Descriptors on packaging to avoid incorrect dependencies being identified by security scanner tools. (Fixes CVE-2023-1370).

• Security: Add dependency checking as part of the build process.

AES256 Provider:

• Security: Change AES256 key to PASSWORD type to avoid logging secrets.

AWS Secrets Manager Provider:

• New property : file.write Writes secrets to file on path. Required for Java trust stores, key stores, certs that need to be loaded from file. For ease of use for the secret provider, this is disabled by default.

• New property : secret.default.ttl If no TTL is configured in AWS Secrets Manager, apply a default TTL (in milliseconds).

• New property : aws.endpoint.override Add override for non-standard or compatible AWS endpoints.

• Enhancement : Ensuring secrets are cached within their TTL (same as Vault).

• Enhancement : Upgraded dependencies to use AWS V2 Client.

• Enhancement : Added AWS STS dependency to avoid the requirement of additional libraries for default authentication (eg. EKS).

• Security: Don’t expose secret values in exception messages on JsonParseException.

• New property : secret.type Specify the type of secrets stored in Secret Manager. Defaults to JSON, to enable String secret values to change to STRING.

• Bugfix: enable accessKey and secretKey to remain blank if using DEFAULT auth mode.

Azure Secret Provider:

• Bugfix: Recompute TTL values on each get so the timestamp of reschedule shrinks until TTL is reached.

• Bugfix: Fix so that UTF-8 encodings in Azure are correctly mapped to the UTF8 encoding in the secret provider.

Hashicorp Vault Provider:

• Bugfix: Files will be written to the correct directory.

• New property: app.role.path Support vault approle custom mount path.

• New property: kubernetes.auth.path Support vault custom auth path (with default value to be auth/kubernetes).

• Security: vault-java-driver was no longer maintained, switched to use a community fork io.github.jopenlibs

• Add support for the Vault Database credential engine

1.3.2

Adds support for multiple "from" patterns.

This converts the format.from.pattern field in the following SMTs:

• InsertFieldTimestampHeaders

• InsertRollingFieldTimestampHeaders

• TimestampConverter

into a List (comma separated) so that these SMTs can support multiple (fallback) DateTimeFormatter patterns should multiple timestamps be in use.

Configuration Compatibility

Configurations should be backwards-compatible with previous versions of the SMT, the exception is if commas are used in the format.from.pattern string.

To update the configuration of format.from.pattern ensure you enclose any pattern which contains commas in double quotes.

Old Configuration:

format.from.pattern=yyyy-MM-dd'T'HH:mm:ss,SSS

New Configuration

format.from.pattern="yyyy-MM-dd'T'HH:mm:ss,SSS"

Multiple format.from.pattern can now be configured, each pattern containing a comma can be enclosed in double quotes:

format.from.pattern=yyyyMMddHHmmssSSS,"yyyy-MM-dd'T'HH:mm:ss,SSS"

Configuration Order

When configuring format.from.pattern, the order matters; less granular formats should follow more specific ones to avoid data loss. For example, place yyyy-MM-dd after yyyy-MM-dd'T'HH:mm:ss to ensure detailed timestamp information isn't truncated.

1.3.1

Increase error information for debugging.

1.3.0

Adds support for adding metadata to kafka connect headers (for a source connector).

1.2.1

Workaround for Connect runtime failing with unexplained exception where it looks like the static fields of parent class is not resolved prop.

1.2.0

Adds support for inserting time based headers using a Kafka message payload field.

1.1.2

Fix public visibility of rolling timestamp headers.

1.1.1

Don't make CTOR protected.

1.1.0

Introducing four new Single Message Transforms (SMTs) aimed at simplifying and streamlining the management of system or record timestamps, along with support for rolling windows. These SMTs are designed to significantly reduce the complexity associated with partitioning data in S3/Azure/GCS Sink based on time, offering a more efficient and intuitive approach to data organization. By leveraging these SMTs, users can seamlessly handle timestamp-based partitioning tasks, including optional rolling window functionality, paving the way for smoother data management workflows.

8.1.16

Improvements to the HTTP Sink

1. Queue Limiting: We've set a limit on the queue size per topic to reduce the chances of an Out-of-Memory (OOM) issue. Previously the queue was unbounded and in a scenario where the http calls are slow and the sink gets more records than it clears, it would eventually lead to OOM.

2. Offering Timeout: The offering to the queue now includes a timeout. If there are records to be offered, but the timeout is exceeded, a retriable exception is thrown. Depending on the connector's retry settings, the operation will be attempted again. This helps avoid situations where the sink gets stuck processing a slow or unresponsive batch.

3. Duplicate Record Handling: To prevent the same records from being added to the queue multiple times, we've introduced a Map[TopicPartition, Offset] to track the last processed offset for each topic-partition. This ensures that the sink does not attempt to process the same records repeatedly.

4. Batch Failure Handling: The changes also address a situation where an HTTP call fails due to a specific input, but the batch is not removed from the queue. This could have led to the batch being retried indefinitely, which is now prevented.

8.1.15

HTTP sink ignores null records. Avoids a NPE if custom SMTs send null records to the pipeline

8.1.14

Improvements to the HTTP Sink reporter

8.1.13

8.1.12

Datalake sinks allow an optimisation configuration to avoid rolling the file on schema change. To be used only when the schema changes are backwards compatible

Fixes for the HTTP sink batch.

8.1.11

HTTP sink improvements

HTTP sink improvements

8.1.10

Dependency version upgrades.

Azure Service Bus Source

Fixed timestamp of the messages and some of the fields in the payload to correctly use UTC millis.

8.1.9

Azure Service Bus Source

Changed contentType in the message to be nullable (Optional String).

8.1.8

HTTP Sink

Possible exception fix

Store success/failure response codes in http for the reporter.

8.1.7

HTTP Sink

Fixes possible exception in Reporter code.

8.1.6

HTTP Sink

Fixes and overall stability improvements.

8.1.4

Google Cloud Platform Storage

Remove overriding transport options on GCS client.

8.1.3

HTTP Sink

Bugfix: HTTP Kafka Reporter ClientID is not unique.

8.1.2

HTTP Sink & GCS Sink

Improvements for handing HTTP sink null values & fix for NPE on GCS.

8.1.1

Removal of shading for Avro and Confluent jars.

8.1.0

HTTP Sink

Addition of HTTP reporter functionally to route HTTP success and errors to a configurable topic.

8.0.0

HTTP Sink

Breaking Configuration Change

7.4.5

ElasticSearch (6 and 7)

Http Sink

• Adjust defaultUploadSyncPeriod to make connector more performant by default.

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

• Fix for issue causing sink to fail with NullPointerException due to invalid offset.

7.4.4

Azure Datalake & GCP Storage

Dependency version upgrades

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

• Fixes a gap in the avro/parquet storage where enums where converted from Connect enums to string.

• Adds support for explicit "no partition" specification to kcql, to enable topics to be written in the bucket and prefix without partitioning the data.

  • Syntax Example: INSERT INTO foo SELECT * FROM bar NOPARTITION

7.4.3

All Connectors

Dependency version upgrades

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

This release introduces a new configuration option for three Kafka Connect Sink Connectors—S3, Data Lake, and GCP Storage—allowing users to disable exactly-once semantics. By default, exactly once is enabled, but with this update, users can choose to disable it, opting instead for Kafka Connect’s native at-least-once offset management.

S3 Sink Connector: connect.s3.exactly.once.enable Data Lake Sink Connector: connect.datalake.exactly.once.enable GCP Storage Sink Connector: connect.gcpstorage.exactly.once.enable

Default Value: true

Indexing is enabled by default to maintain exactly-once semantics. This involves creating an .indexes directory at the root of your storage bucket, with subdirectories dedicated to tracking offsets, ensuring that records are not duplicated.

Users can now disable indexing by setting the relevant property to false. When disabled, the connector will utilise Kafka Connect’s built-in offset management, which provides at-least-once semantics instead of exactly-once.

7.4.2

All Connectors

Dependency version upgrades

AWS S3 Source and GCP Storage Source Connectors

File Extension Filtering

Introduced new properties to allow users to filter the files to be processed based on their extensions.

For AWS S3 Source Connector:

• connect.s3.source.extension.excludes: A comma-separated list of file extensions to exclude from the source file search. If this property is not configured, all files are considered.

• connect.s3.source.extension.includes: A comma-separated list of file extensions to include in the source file search. If this property is not configured, all files are considered.

For GCP Storage Source Connector:

• connect.gcpstorage.source.extension.excludes: A comma-separated list of file extensions to exclude from the source file search. If this property is not configured, all files are considered.

• connect.gcpstorage.source.extension.includes: A comma-separated list of file extensions to include in the source file search. If this property is not configured, all files are considered.

These properties provide more control over the files that the AWS S3 Source Connector and GCP Storage Source Connector process, improving efficiency and flexibility.

GCP Storage Source and Sink Connectors

• Increases the default HTTP Retry timeout from 250ms total timeout to 3 minutes as default. The default consumer group max.poll.timeout is 5 minutes, so it’s within the boundaries to avoid a group rebalance.

7.4.1

GCP Storage Connector

Adding retry delay multiplier as a configurable parameter (with default value) to Google Cloud Storage Connector. Main changes revolve around RetryConfig class and its translation to gax HTTP client config.

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

Making indexes directory configurable for both source and sink.

Sinks

Use the below properties to customise the indexes root directory:

• connect.datalake.indexes.name

• connect.gcpstorage.indexes.name

• connect.s3.indexes.name

See connector documentation for more information.

Sources:

• Use the below properties to exclude custom directories from being considered by the source.

• connect.datalake.source.partition.search.excludes

• connect.gcpstorage.source.partition.search.excludes

• connect.s3.source.partition.search.excludes

7.4.0

NEW: Azure Service Bus Sink Connector

• Azure Service Bus Sink Connector.

Other Changes

• Exception / Either Tweaks

• Bump java dependencies (assertJ and azure-core)

• Add logging on flushing

• Fix: Java class java.util.Date support in cloud sink maps

7.3.2

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

• Support added for writing Date, Time and Timestamp data types to AVRO.

7.3.1

GCP Storage Connector

• Invalid Protocol Configuration Fix

7.3.0

NEW: Azure Service Bus Source Connector

NEW: GCP Pub/Sub Source Connector

Data Lake Sinks (AWS, Azure Datalake and GCP Storage)

• To back the topics up the KCQL statement is

When * is used the envelope setting is ignored.

This change allows for the * to be taken into account as a default if the given message topic is not found.

HTTP Sink

Bug fix to ensure that, if specified as part of the template, the Content-Type header is correctly populated.

All Connectors:

• Update of dependencies.

7.2.0

Enhancements

1. Automated Skip for Archived Objects:

• The S3 source now seamlessly bypasses archived objects, including those stored in Glacier and Deep Archive. This enhancement improves efficiency by automatically excluding archived data from processing, avoiding the connector crashing otherwise

1. Enhanced Key Storage in Envelope Mode:

• Changes have been implemented to the stored key when using envelope mode. These modifications lay the groundwork for future functionality, enabling seamless replay of Kafka data stored in data lakes (S3, GCS, Azure Data Lake) from any specified point in time.

7.1.0

Source Line-Start-End Functionality Enhancements

We’ve rolled out enhancements to tackle a common challenge faced by users of the S3 source functionality. Previously, when an external producer abruptly terminated a file without marking the end message, data loss occurred.

To address this, we’ve introduced a new feature: a property entry for KCQL to signal the handling of unterminated messages. Meet the latest addition, read.text.last.end.line.missing. When set to true, this property ensures that in-flight data is still recognized as a message even when EOF is reached but the end line marker is missing.

7.0.0

Data-lakes Sink Connectors

This release brings substantial enhancements to the data-lakes sink connectors, elevating their functionality and flexibility. The focal point of these changes is the adoption of the new KCQL syntax, designed to improve usability and resolve limitations inherent in the previous syntax.

Key Changes

• New KCQL Syntax: The data-lakes sink connectors now embrace the new KCQL syntax, offering users enhanced capabilities while addressing previous syntax constraints.

• Data Lakes Sink Partition Name: This update ensures accurate preservation of partition names by avoiding the scraping of characters like \ and /. Consequently, SMTs can provide partition names as expected, leading to reduced configuration overhead and increased conciseness.

KCQL Keywords Replaced

Several keywords have been replaced with entries in the PROPERTIES section for improved clarity and consistency:

• WITHPARTITIONER: Replaced by PROPERTIES ('partition.include.keys'=true/false). When WITHPARTITIONER KeysAndValue is set to true, the partition keys are included in the partition path. Otherwise, only the partition values are included.

• WITH_FLUSH_SIZE: Replaced by PROPERTIES ('flush.size'=$VALUE).

• WITH_FLUSH_COUNT: Replaced by PROPERTIES ('flush.count'=$VALUE).

• WITH_FLUSH_INTERVAL: Replaced by PROPERTIES ('flush.interval'=$VALUE).

Benefits

The adoption of the new KCQL syntax enhances the flexibility of the data-lakes sink connectors, empowering users to tailor configurations more precisely to their requirements. By transitioning keywords to entries in the PROPERTIES section, potential misconfigurations stemming from keyword order discrepancies are mitigated, ensuring configurations are applied as intended.

Upgrades

Please note that the upgrades to the data-lakes sink connectors are not backward compatible with existing configurations. Users are required to update their configurations to align with the new KCQL syntax and PROPERTIES entries. This upgrade is necessary for any instances of the sink connector (S3, Azure, GCP) set up before version 7.0.0.

To upgrade to the new version, users must follow these steps:

1. Stop the sink connectors.

2. Update the connector to version 7.0.0.

3. Edit the sink connectors’ KCQL setting to translate to the new syntax and PROPERTIES entries.

4. Restart the sink connectors.

6.3.1

This update specifically affects datalake sinks employing the JSON storage format. It serves as a remedy for users who have resorted to a less-than-ideal workaround: employing a Single Message Transform (SMT) to return a Plain Old Java Object (POJO) to the sink. In such cases, instead of utilizing the Connect JsonConverter to seamlessly translate the payload to JSON, reliance is placed solely on Jackson.

However, it’s crucial to note that this adjustment is not indicative of a broader direction for future expansions. This is because relying on such SMT practices does not ensure an agnostic solution for storage formats (such as Avro, Parquet, or JSON).

6.3.0

NEW: HTTP Sink Connector

• HTTP Sink Connector (Beta)

NEW: Azure Event Hubs Source Connector

• Azure Event Hubs Source Connector.

All Connectors:

• Update of dependencies, CVEs addressed.

Please note that the Elasticsearch 6 connector will be deprecated in the next major release.

6.2.0

NEW: GCP Storage Source Connector

AWS Source Connector

• Important: The AWS Source Partition Search properties have changed for consistency of configuration. The properties that have changed for 6.2.0 are:

  • connect.s3.partition.search.interval changes to connect.s3.source.partition.search.interval.

  • connect.s3.partition.search.continuous changes to connect.s3.source.partition.search.continuous.

  • connect.s3.partition.search.recurse.levels changes to connect.s3.source.partition.search.recurse.levels.

• If you use any of these properties, when you upgrade to the new version then your source will halt and the log will display an error message prompting you to adjust these properties. Be sure to update these properties in your configuration to enable the new version to run.

• Dependency upgrade of Hadoop libraries version to mitigate against CVE-2022-25168.

JMS Source and Sink Connector

• Jakarta Dependency Migration: Switch to Jakarta EE dependencies in line with industry standards to ensure evolution under the Eclipse Foundation.

All Connectors:

• There has been some small tidy up of dependencies, restructuring and removal of unused code, and a number of connectors have a slimmer file size without losing any functionality.

• The configuration directory has been removed as these examples are not kept up-to-date. Please see the connector documentation instead.

• Dependency upgrades.

6.1.0

All Connectors:

• In this release, all connectors have been updated to address an issue related to conflicting Antlr jars that may arise in specific environments.

AWS S3 Source:

• Byte Array Support: Resolved an issue where storing the Key/Value as an array of bytes caused compatibility problems due to the connector returning java.nio.ByteBuffer while the Connect framework’s ByteArrayConverter only works with byte[]. This update ensures seamless conversion to byte[] if the key/value is a ByteBuffer.

JMS Sink:

• Fix for NullPointerException: Addressed an issue where the JMS sink connector encountered a NullPointerException when processing a message with a null JMSReplyTo header value.

JMS Source:

• Fix for DataException: Resolved an issue where the JMS source connector encountered a DataException when processing a message with a JMSReplyTo header set to a queue.

AWS S3 Sink/GCP Storage Sink (beta)/Azure Datalake Sink (beta):

• GZIP Support for JSON Writing: Added support for GZIP compression when writing JSON data to AWS S3, GCP Storage, and Azure Datalake sinks.

6.0.2

GCP Storage Sink (beta):

• Improve suppport for handling GCP naming conventions

6.0.1

AWS S3 / Azure Datalake (Beta) / GCP Storage (Beta)

• Removed check preventing nested paths being used in the sink.

• Avoid cast exception in GCP Storage connector when using Credentials mode.

6.0.0

New Connectors introduced in 6.0.0:

• Azure Datalake Sink Connector (Beta)

• GCP Storage Sink Connector (Beta)

Deprecated Connectors removed in 6.0.0:

• Kudu

• Hazelcast

• Hbase

• Hive

• Pulsar

All Connectors:

• Standardising package names. Connector class names and converters will need to be renamed in configuration.

• Some clean up of unused dependencies.

• Introducing cloud-common module to share code between cloud connectors.

• Cloud sinks (AWS S3, Azure Data Lake and GCP Storage) now support BigDecimal and handle nullable keys.

5.0.1

New Connectors introduced in 5.0.1:

• Consumer Group Offsets S3 Sink Connector

AWS S3 Connector - S3 Source & Sink

• Enhancement: BigDecimal Support

Redis Sink Connector

• Bug fix: Redis does not initialise the ErrorHandler

5.0.0

All Connectors

• Test Fixes and E2E Test Clean-up: Improved testing with bug fixes and end-to-end test clean-up.

• Code Optimization: Removed unused code and converted Java code and tests to Scala for enhanced stability and maintainability.

• Ascii Art Loading Fix: Resolved issues related to ASCII art loading.

• Build System Updates: Implemented build system updates and improvements.

• Stream Reactor Integration: Integrated Kafka-connect-query-language inside of Stream Reactor for enhanced compatibility.

• STOREAS Consistency: Ensured consistent handling of backticks with STOREAS.

AWS S3 Connector - S3 Source & Sink

The source and sink has been the focus of this release.

• Full message backup. The S3 sink and source now supports full message backup. This is enabled by adding in the KCQL PROPERTIES('store.envelope'=true)

• Removed Bytes_*** storage format. For those users leveraging them there is a migration information below. Storing raw Kafka message the storage format should be AVRO/PARQUET/JSON(less ideal).

• Introduced support for BYTES storing single message as raw binary. Typically, storing images or videos are the use case for this. This is enabled by adding in the KCQL STOREAS BYTES

• Introduced support for PROPERTIES to drive new settings required to drive the connectors’ behaviour. The KCQL looks like this: INSERT INTO ... SELECT ... FROM ... PROPERTIES(property=key, ...)

Sink

• Enhanced PARTITIONBY Support: expanded support for PARTITIONBY fields, now accommodating fields containing dots. For instance, you can use PARTITIONBY a, `field1.field2` for enhanced partitioning control.

• Advanced Padding Strategy: a more advanced padding strategy configuration. By default, padding is now enforced, significantly improving compatibility with S3 Source.

• Improved Error Messaging: Enhancements have been made to error messaging, providing clearer guidance, especially in scenarios with misaligned topic configurations (#978).

• Commit Logging Refactoring: Refactored and simplified the CommitPolicy for more efficient commit logging (#964).

• Comprehensive Testing: Added additional unit testing around configuration settings, removed redundancy from property names, and enhanced KCQL properties parsing to support Map structures.

• Consolidated Naming Strategies: Merged naming strategies to reduce code complexity and ensure consistency. This effort ensures that both hierarchical and custom partition modes share similar code paths, addressing issues related to padding and the inclusion of keys and values within the partition name.

• Optimized S3 API Calls: Switched from using deleteObjects to deleteObject for S3 API client calls (#957), enhancing performance and efficiency.

• JClouds Removal: The update removes the use of JClouds, streamlining the codebase.

• Legacy Offset Seek Removal: The release eliminates legacy offset seek operations, simplifying the code and enhancing overall efficiency

Source

• Expanded Text Reader Support: new text readers to enhance data processing flexibility, including:

  • Regex-Driven Text Reader: Allows parsing based on regular expressions.

  • Multi-Line Text Reader: Handles multi-line data.

  • Start-End Tag Text Reader: Processes data enclosed by start and end tags, suitable for XML content.

• Improved Parallelization: enhancements enable parallelization based on the number of connector tasks and available data partitions, optimizing data handling.

• Data Consistency: Resolved data loss and duplication issues when the connector is restarted, ensuring reliable data transfer.

• Dynamic Partition Discovery: No more need to restart the connector when new partitions are added; runtime partition discovery streamlines operations.

• Efficient Storage Handling: The connector now ignores the .indexes directory, allowing data storage in an S3 bucket without a prefix.

• Increased Default Records per Poll: the default limit on the number of records returned per poll was changed from 1024 to 10000, improving data retrieval efficiency and throughput.

• Ordered File Processing: Added the ability to process files in date order. This feature is especially useful when S3 files lack lexicographical sorting, and S3 API optimisation cannot be leveraged. Please note that it involves reading and sorting files in memory.

• Parquet INT96 Compatibility: The connector now allows Parquet INT96 to be read as a fixed array, preventing runtime failures.

Kudu and Hive

• The Kudu and Hive connectors are now deprecated and will be removed in a future release.

InfluxDB

• Fixed a memory issue with the InfluxDB writer.

• Upgraded to Influxdb2 client (note: doesn’t yet support Influxdb2 connections).

S3 upgrade notes

Upgrading from 5.0.0 (preview) to 5.0.0

For installations that have been using the preview version of the S3 connector and are upgrading to the release, there are a few important considerations:

Previously, default padding was enabled for both “offset” and “partition” values starting in June.

However, in version 5.0, the decision to apply default padding to the “offset” value only, leaving the " partition" value without padding. This change was made to enhance compatibility with querying in Athena.

If you have been using a build from the master branch since June, your connectors might have been configured with a different default padding setting.

To maintain consistency and ensure your existing connector configuration remains valid, you will need to use KCQL configuration properties to customize the padding fields accordingly.

Upgrading from 4.x to 5.0.0

Starting with version 5.0.0, the following configuration keys have been replaced.

Upgrading from 4.1.* and 4.2.0

In version 4.1, padding options were available but were not enabled by default. At that time, the default padding length, if not specified, was set to 8 characters.

However, starting from version 5.0, padding is now enabled by default, and the default padding length has been increased to 12 characters.

Enabling padding has a notable advantage: it ensures that the files written are fully compatible with the Lenses Stream Reactor S3 Source, enhancing interoperability and data integration.

Sinks created with 4.2.0 and 4.2.1 should retain the padding behaviour, and, therefore should disable padding:

If padding was enabled in 4.1, then the padding length should be specified in the KCQL statement:

Upgrading from 4.x to 5.0.0 only when STOREAS Bytes_*** is used

The Bytes_*** storage format has been removed. If you are using this storage format, you will need to install the 5.0.0-deprecated connector and upgrade the connector instances by changing the class name:

Source Before:

Source After:

Sink Before:

Sink After:

Upgrade a connector configuration

To migrate to the new configuration, please follow the following steps:

• stop all running instances of the S3 connector

• upgrade the connector to 5.0.0

• update the configuration to use the new properties

• resume the stopped connectors

4.2.0

• All

  • Ensure connector version is retained by connectors

  • Lenses branding ASCII art updates

• AWS S3 Sink Connector

  • Improves the error in case the input on BytesFormatWriter is not binary

  • Support for ByteBuffer which may be presented by Connect as bytes

4.1.0

Note From Version 4.10, AWS S3 Connectors will use the AWS Client by default. You can revert to the jClouds version by setting the connect.s3.aws.client property.

• All

  • Scala upgrade to 2.13.10

  • Dependency upgrades

  • Upgrade to Kafka 3.3.0

  • SimpleJsonConverter - Fixes mismatching schema error.

• AWS S3 Sink Connector

  • Add connection pool config

  • Add Short type support

  • Support null values

  • Enabling Compression Codecs for Avro and Parquet

  • Switch to AWS client by default

  • Add option to add a padding when writing files, so that files can be restored in order by the source

  • Enable wildcard syntax to support multiple topics without additional configuration.

• AWS S3 Source Connector

  • Add connection pool config

  • Retain partitions from filename or regex

  • Switch to AWS client by default

• MQTT Source Connector

  • Allow toggling the skipping of MQTT Duplicates

• MQTT Sink Connector

  • Functionality to ensure unique MQTT Client ID is used for MQTT sink

• Elastic6 & Elastic7 Sink Connectors

  • Fixing issue with missing null values

4.0.0

• All

  • Scala 2.13 Upgrade

  • Gradle to SBT Migration

  • Producing multiple artifacts supporting both Kafka 2.8 and Kafka 3.1.

  • Upgrade to newer dependencies to reduce CVE count

  • Switch e2e tests from Java to Scala.

• AWS S3 Sink Connector

  • Optimal seek algorithm

  • Parquet data size flushing fixes.

  • Adding date partitioning capability

  • Adding switch to use official AWS library

  • Add AWS STS dependency to ensure correct operation when assuming roles with a web identity token.

  • Provide better debugging in case of exceptions.

• FTP Source Connector

  • Fixes to slice mode support.

• Hazelcast Sink Connector

  • Upgrade to HazelCast 4.2.4. The configuration model has changed and now uses clusters instead of username and password configuration.

• Hive Sink Connector

  • Update of parquet functionality to ensure operation with Parquet 1.12.2.

  • Support for Hive 3.1.3.

• JMS Connector

  • Enable protobuf support.

• Pulsar

  • Upgrade to Pulsar 2.10 and associated refactor to support new client API.

3.0.1

• All

  • Replace Log4j with Logback to overcome CVE-2021-44228

  • Bringing code from legacy dependencies inside of project

• Cassandra Sink Connector

  • Ensuring the table name is logged on encountering an InvalidQueryException

• HBase Sink Connector

  • Alleviate possible race condition

3.0.0

• All

  • Move to KCQL 2.8.9

  • Change sys.errors to ConnectExceptions

  • Additional testing with TestContainers

  • Licence scan report and status

• AWS S3 Sink Connector

  • S3 Source Offset Fix

  • Fix JSON & Text newline detection when running in certain Docker images

  • Byte handling fixes

  • Partitioning of nested data

  • Error handling and retry logic

  • Handle preCommit with null currentOffsets

  • Remove bucket validation on startup

  • Enabled simpler management of default flush values.

  • Local write mode - build locally, then ship

  • Deprecating old properties, however rewriting them to the new properties to ensure backwards compatibility.

  • Adding the capability to specify properties in yaml configuration

  • Rework exception handling. Refactoring errors to use Either[X,Y] return types where possible instead of throwing exceptions.

  • Ensuring task can be stopped gracefully if it has not been started yet

  • ContextReader testing and refactor

  • Adding a simple state model to the S3Writer to ensure that states and transitions are kept consistent. This can be improved in time.

• AWS S3 Source Connector

  • Change order of match to avoid scala.MatchError

  • S3 Source rewritten to be more efficient and use the natural ordering of S3 keys

  • Region is necessary when using the AWS client

• Cassandra Sink & Source Connectors

  • Add connection and read client timeout

• FTP Connector

  • Support for Secure File Transfer Protocol

• Hive Sink Connector

  • Array Support

  • Kerberos debug flag added

• Influx DB Sink

  • Bump influxdb-java from version 2.9 to 2.29

  • Added array handling support

• MongoDB Sink Connector

  • Nested Fields Support

• Redis Sink Connector

  • Fix Redis Pubsub Writer

  • Add support for json and json with schema

2.1.3

• Move to connect-common 2.0.5 that adds complex type support to KCQL

2.1.2

• AWS S3 Sink Connector

  • Prevent null pointer exception in converters when maps are presented will null values

  • Offset reader optimisation to reduce S3 load

  • Ensuring that commit only occurs after the preconfigured time interval when using WITH_FLUSH_INTERVAL

• AWS S3 Source Connector (New Connector)

• Cassandra Source Connector

  • Add Bucket Timeseries Mode

  • Reduction of logging noise

  • Proper handling of uninitialized connections on task stop()

• Elasticsearch Sink Connector

  • Update default port

• Hive Sink

  • Improve Orc format handling

  • Fixing issues with partitioning by non-string keys

• Hive Source

  • Ensuring newly written files can be read by the hive connector by introduction of a refresh frequency configuration option.

• Redis Sink

  • Correct Redis writer initialisation

2.1.0

• AWS S3 Sink Connector

• Elasticsearch 7 Support

2.0.1

• Hive Source

  • Rename option connect.hive.hive.metastore to connect.hive.metastore

  • Rename option connect.hive.hive.metastore.uris to connect.hive.metastore.uris

• Fix Elastic start up NPE

• Fix to correct batch size extraction from KCQL on Pulsar

2.0.0

• Move to Scala 2.12

• Move to Kafka 2.4.1 and Confluent 5.4

• Deprecated:

  • Druid Sink (not scala 2.12 compatible)

  • Elastic Sink (not scala 2.12 compatible)

  • Elastic5 Sink(not scala 2.12 compatible)

• Redis

  • Add support for Redis Streams

• Cassandra

  • Add support for setting the LoadBalancer policy on the Cassandra Sink

• ReThinkDB

  • Use SSL connection on Rethink initialize tables is ssl set

• FTP Source

  • Respect connect.ftp.max.poll.records when reading slices

• MQTT Source

  • Allow lookup of avro schema files with wildcard subscriptions