Apache Cassandra is the most widely used open-source NoSQL database management system used to handle large amounts of data across many servers with high availability and no single point of failure. But sometimes, we need to repair the data between the nodes. Cassandra Schedule repair is a process that synchronizes data. When running repairs in large clusters, we need to arrange the repairs. One of the tools is Cassandra Reaper.
But what to do if you don’t have any knowledge about Cassandra reapers. No worries, we are here for you. Ksolves being a pioneer in Apache Cassandra development services brings to you the use of Cassandra Reaper to orchestrate repairs on clusters. Let’s have a look.
Cassandra Repair: What is it and why do we need it?
What is Repair?
Cassandra repair or an anti-entropy operation is crucial for every Cassandra cluster as it synchronizes data between nodes. As we all know, Cassandra data with the latest timestamp always wins the race and that is what repair does. It compares data with associated timestamps.
There are different types of Cassandra repair:
- Incremental Repair (Default)
- Full Repair
Cassandra is designed to be highly available and users can access Cassandra even if one of its nodes is down or unreachable. Users can still read, write, update and delete data. However, when a failed node returns to the Cassandra cluster, it becomes out of sync with the changes that occurred while it was offline and results in data loss.
In some cases, Cassandra automatically repairs the data with Hinted Hand-off and Read-Repair. The problem occurs when the node goes down for a longer period of time, we need to run a manual repair on the clusters. This manual Cassandra repair is anti-entropy repair.
Now when we understand the need for Cassandra repair, let’s hodge towards arranging repair with Cassandra Reaper.
Repair with Cassandra Reaper
Cassandra Reaper is an open-source tool that is meant to schedule repairs of Apache Cassandra clusters. It enhances the node tool repair by the following process-
- Spitting repair jobs into small segments
- Monitor running repairs and pending compactions to handle back-pressure.
- Provide the ability to cancel or pause repairs.
Let’s start how to orchestrate repairs with Cassandra Reaper.
Configure Apache Cassandra
- Firstly runs Cassandra cluster and sets JMX remote access credentials.
- After that, create keyspace, table and then bootstrap some data.
- The keyspace can be repaired with the help of a Reaper.
Configure Cassandra Reaper
- Examine the reaper configuration file and install the reaper.
- Cassandra Reaper can be executed within a docker container.
- It can be executed with either in-memory storage or the Cassandra database.
- To run Reaper with Cassandra backend, we need to create a keyspace on Cassandra.
- Reaper will store all the data like repaired and migrated on the Cassandra table.
- Now we can run the Cassandra Reaper.
Authentication of Cassandra Reaper
- Once you start the Reaper, you can browse the reaper web.
- Authentication activated in the Reaper is by default.
- Specify Cassandra host and JMX port to add any cluster.
- DOCKER_HOST in the mac-os can be replaced with server IP in Linux.
- To create repairs, we need to set a few parameters like cluster name, keyspace name, etc.
- You can refer to advanced settings for options like table name, incremental mode, subrange size, etc.
- After creating a repair, activate it to run. You can even view the progress of the repair segment.
- Cassandra Reaper splits runs into segments.
Reaper has the ability to create and manage Cassandra schedule repair to repair scheduled for a cluster. A single reaper instance can handle multiple data centers.
In a nutshell
In this article, we have discussed that Cassandra clusters must perform repair operations in order to maintain the consistency of the data, and Cassandra Reaper is the most preferred solution for these operations. Now when you know the best solution to Cassandra repair, it’s time to look for the best partner. Ksolves’ Apache Cassandra services are known for their low failure rates. Our 10 years of experience as an Apache Cassandra development company along with 350+ developers are efficient in solving all your Cassandra problems right from development to support.
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