Kafka Schema Registry Tips

Yeva Byzek shares 17 tips for managing your Kafka Schema Registry:

Mistake #5: Configuring different names for the schemas topic in different Schema Registry instances

There is a commit log with all the schema information, which gets written to a Kafka topic. All Schema Registry instances should be configured to use the same schemas topic, whose name is set by the configuration parameter kafkastore.topic. This topic is the schema’s source of truth, and the primary instances read the schemas from this topic. The name of this topic defaults to _schemas, but sometimes customers choose to rename it. This has to be the same for all Schema Registry instances, otherwise it may result in different schemas with the same ID.

Read on for sixteen more.

Related Posts

When Not to Use Spark

Ramandeep Kaur gives us several cases when it makes sense not to use Apache Spark: There can be use cases where Spark would be the inevitable choice. Spark considered being an excellent tool for use cases like ETL of a large amount of a dataset, analyzing a large set of data files, Machine learning, and […]

Read More

Hyperparameter Tuning with MLflow

Joseph Bradley shows how you can perform hyperparameter tuning of an MLlib model with MLflow: Apache Spark MLlib users often tune hyperparameters using MLlib’s built-in tools CrossValidator and TrainValidationSplit.  These use grid search to try out a user-specified set of hyperparameter values; see the Spark docs on tuning for more info. Databricks Runtime 5.3 and 5.3 ML and above support […]

Read More

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Categories

May 2019
MTWTFSS
« Apr Jun »
 12345
6789101112
13141516171819
20212223242526
2728293031