Category Archives: CDH

Robust Message Serialization in Apache Kafka Using Apache Avro, Part 2

Categories: Avro CDH How-to Kafka

Implementing a Schema Store

In Part 1, we saw the need for an Apache Avro schema provider but did not implement one. In this part we will implement a schema provider that works with Apache Kafka as storage.

In-Memory SchemaStore

First we can implement an in-memory store for schemas. This is useful to understand the requirements for such a store and as the cache of the Kafka backed store. A SchemaStore has to be quick in looking up VersionedSchema entries.

Read more

Robust Message Serialization in Apache Kafka Using Apache Avro, Part 1

Categories: Avro CDH How-to Kafka

In Apache Kafka, Java applications called producers write structured messages to a Kafka cluster (made up of brokers). Similarly, Java applications called consumers read these messages from the same cluster.  In some organizations, there are different groups in charge of writing and managing the producers and consumers. In such cases, one major pain point can be in the coordination of the agreed upon message format between producers and consumers.

This example demonstrates how to use Apache Avro to serialize records that are produced to Apache Kafka while allowing evolution of schemas and nonsynchronous update of producer and consumer applications.

Read more

Fine Grained Access Control in Cloudera Manager

Categories: CDH Cloudera Manager

One instance of Cloudera Manager (CM) can manage N clusters. In the current Role Based Access Control (RBAC) model, CM users hold privileges and permissions across everything in CM’s purview (including every cluster that CM manages). For example, Read-Only user John is a user who can perform all the actions of Read-Only users on all clusters managed by CM. The “Cluster Admin” user Chris is a cluster administrator of all the clusters managed by CM.

Read more

How-to: Automate Replications with Cloudera Manager API

Categories: CDH Cloud Cloudera Manager

Cloudera Enterprise Backup and Disaster Recovery (BDR) enables you to replicate data across data centers for disaster recovery scenarios. As a lower cost solution to geographical redundancy or as a means to perform an on-premises to cloud migration, BDR can also replicate HDFS and Hive data to and from Amazon S3 or a Microsoft Azure Data Lake Store.

Many customers may require an automated solution for creating, running, and managing replication schedules in order to minimize Recovery Point Objectives (RPOs) for late arriving data or to automate recovery after disaster recovery.

Read more