HDFS follows a master-slave architecture where every cluster in the HDFS is composed of a single NameNode (master) and multiple DataNodes (slave). There are two main categories of HDFS metrics: Monitoring key HDFS metrics is important because it helps you to: monitor the capacity of the DFS, monitor the space available, track the status of blocks, and optimize the storage of your data.
The HDFS is scalable and can support thousands of nodes. Whenever the HDFS receives data it breaks it down into blocks and sends it to multiple nodes. HDFS MetricsĪpache Hadoop Distributed File System (HDFS) is a distributed file system with a NameNode and DataNode architecture. HDFS metrics (NameNode metrics and DataNode metrics)īelow, we’re going to break each of these metric types down, explaining what they are and providing a brief guide for how you can monitor them.When monitoring the status of clusters, there are four main categories of metrics you need to be aware of: Hadoop’s architecture may be resilient to system failures, but it still needs maintenance to prevent jobs from being disrupted. Like any computing resource, Hadoop clusters need to be monitored to ensure that they keep performing at their best.
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How to Monitor Hadoop: Metrics You Need to Keep Track of to Monitor Hadoop Clusters It divides data processing between multiple nodes, which manages the datasets more efficiently than a single device could. Hadoop was designed to break down data management workloads over a cluster of computers.
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Dynatrace – Application performance management software with Hadoop monitoring with NameNode/DataNode metrics, dashboards, analytics, custom alerts, and more.Īpache Hadoop is an open-source software framework that can process and distribute large data sets across multiple clusters of computers.LogicMonitor – Infrastructure monitoring software with a HadoopPackage, REST API, alerts, reports, dashboards, and more.Datadog – Cloud monitoring software with a customizable Hadoop dashboard, integrations, alerts, and more.Here is our list of the best Hadoop monitoring tools: However, like all pieces of infrastructure, it needs to be monitored. In an era where enterprises are looking to leverage the power of big data, Apache Hadoop has become a key tool for storing and processing large datasets efficiently.
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