Status

Current state: "Under Discussion"

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Please keep the discussion on the mailing list rather than commenting on the wiki (wiki discussions get unwieldy fast).

Motivation

There are several places in Connect during which failures may occur. Any failure to deserialize, convert, process, or read/write a record in Kafka Connect can cause a task to fail. Although some errors can be addressed with SMTs or custom converters that check for malformed data, in general it is difficult to ensure correct and valid data or to tell Connect to skip problematic records.

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Several new behaviors for handling and reporting errors are introduced, and all must be configured in the individual connector configurations.

Retry on Failure

Retry the failed operation a configurable number of times, with backoff between each retry. The number of retries and backoff can be configured using the following new properties:

Task Tolerance Limits

Tolerate up to a configurable number of failures in a task. If the task fails to successfully perform an operation on a record within tolerance limit, the record is skipped. Once the tolerance limit (overall or rate) is reached, the task will fail. Tolerance limits can be configured using the following new properties:

Log Error Context

The error context and processing information can be logged along with the standard application logs using the following configuration properties:

Produce Error Context to a Dead Letter Queue (Kafka Topic)

Produce a message which contains the processing context and error information to a Kafka topic. By default, the worker properties will be used to locate the Kafka cluster. This can be overridden using the errors.dlq.producer.* configs as shown below:

Metrics

The following new metrics will monitor the number of failures, and the behavior of the response handler. Specifically, the following set of counters:

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Proposed Changes

A connector consists of multiple stages. For source connectors, Connect retrieves the records from the connector, applies zero or more transformations, uses the converters to serialize each record’s key, value, and headers, and finally writes each record to Kafka. For sink connectors, Connect reads the topic(s), uses the converters to deserialize each record’s key, value, and headers, and for each record applies zero or more transformations and delivers the records to the sink connector. In this proposal, we will specifically deal with the following failure scenarios which can occur during these stages:

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While logging the error context, it might be worthwhile to take precautions to hide sensitive content. For example, some of the configs might contain sensitive information such as usernames or passwords. To prevent logging critical information, we provide configuration options to disable logging the messages (errors.dlq.include.messages) and/or configs (errors.dlq.include.configs).

Example 1: Fail Fast

To maintain backward compatibility, by default a Connector task will fail immediately upon an error or exception. This reflects the same behavior as earlier releases, ensuring that existing installations work the same way. Although it is not necessary to add extra configuration properties, the following properties may be added to a connector configuration to achieve this older behavior:

# disable retries on failure
errors.retries.limit=0

# do not log the error and their contexts
errors.log.enable=false

# do not record errors in a dead letter queue topic
errors.dlq.enable=false

# Fail on first failure
errors.tolerance.limit=0

Example 2: Record and Skip

The following configuration shows how to setup error handling with multiple retries, logging both to the application logs and a Kafka topic with infinite tolerance:

# retry at most 100 times waiting up to 5 minutes between consecutive failures
errors.retries.limit=100
errors.retries.delay.max.ms=300000

# log error context with application logs, but do not include configs and messages
errors.log.enable=true
errors.log.include.configs=false
errors.log.include.messages=false

# produce error context into the Kafka topic
errors.dlq.enable=true
errors.dlq.topic.name=my-connector-errors
errors.dlq.topic.partitions=25
errors.dlq.topic.replication.factor=3
errors.dlq.include.configs=true
errors.dlq.include.messages=true

# Tolerance all errors.
errors.tolerance.limit=-1
errors.tolerance.rate.limit=-1
errors.tolerance.rate.duration.ms=60000

Example 3: Record to separate Kafka cluster

In the previous example, errors are recorded in the log and in a separate "dead letter queue" (DLQ) Kafka topic in the same broker cluster that Connect is using for its internal topics. It is possible to record the errors in a DLQ on a separate Kafka cluster by defining extra errors.dlq.producer.* configuration properties. Here is the same set of connector configuration properties as in Example 2, except with the additional errors.dlq.producer.* properties:

# retry up to 100 times waiting up to 5 minutes between consecutive failures
errors.retries.limit=100
errors.retries.delay.max.ms=300000

# log error context with log4j appender, but do not include configs and messages
errors.log.enable=true
errors.log.include.configs=false
errors.log.include.messages=false

# produce error context into a secure Kafka topic
errors.dlq.enable=true
errors.dlq.topic.name=my-connector-errors
errors.dlq.topic.partitions=25
errors.dlq.topic.replication.factor=3
errors.dlq.include.configs=true
errors.dlq.include.messages=true
errors.dlq.producer.bootstrap.servers=secure-broker:9093
errors.dlq.producer.acks = 0
errors.dlq.producer.security.protocol=SSL
errors.dlq.producer.ssl.truststore.location=/var/private/ssl/kafka.client.truststore.jks
errors.dlq.producer.ssl.truststore.password=test1234
errors.dlq.producer.ssl.keystore.location=/var/private/ssl/kafka.client.keystore.jks
errors.dlq.producer.ssl.keystore.password=test1234
errors.dlq.producer.ssl.key.password=test1234

# Tolerance all errors.
errors.tolerance.limit=-1
errors.tolerance.rate.limit=-1
errors.tolerance.rate.duration.ms=60000

Compatibility, Deprecation, and Migration Plan

The current behavior in Connect is to kill the task on the first error in any stage. As mentioned above, this will remain the default behavior if connector configurations are not changed.

Rejected Alternatives

Correcting records in the handler: the handler will not be responsible for providing corrected records. For sink records, the user can correct records and write the corrected records back to the origin Kafka topics using the dead letter queue mentioned above. For source records, the user can analyze the error messages and fix the data at the source.

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