
Explore big data concepts, definitions, and the four v's—velocity, volume, variety, veracity—along with data quality costs and the three data types: structured, semi-structured, and unstructured.
Explore facts about big data, highlighting how mobile devices like smartphones and tablets generate massive daily data streams and illustrate the scale of data across everyday life.
Explore how big data transforms financial services, e-tailing, and government sectors by enabling fraud detection, credit scoring, and personalized recommendations from data collected from smartphones and e-commerce sites.
Identify the module objectives for Apache Ambari, understand its importance, explore use cases, management tools, and installation options.
Explore Apache Ambari features, including cross-platform support from Windows to Mac and pluggable components for extensibility, upgrades, and secure LDAP-based protection; plus failure recovery.
Ambari architecture centers on a central server and per-node agents to automate secure, efficient cluster operations, surface health dashboards, and monitor operational metrics via a PostgreSQL-backed state.
Explore ambari internals and workflow, including how agents report metrics via heartbeat signals, authenticate through providers, and coordinate components for centralized monitoring and access control.
Learn the prerequisites to run Ambari, including online and offline installation paths, internet requirements, and using a local repository or rpm packages for enterprise Linux.
Explore the top five reasons to learn Apache Ambari, the open source tool for provisioning and managing Hadoop clusters. Benefit from a simple web interface, lifecycle management, and extensible blueprints.
Apache Ambari is an open source administration tool deployed on top of Hadoop cluster and responsible for keeping track of running applications and their status. Apache Ambari can be referred to as an open source web-based management tool that manages, monitors and provisions the health of Hadoop clusters.
It provides a highly interactive dashboard which allows the administrators to visualize the progress and status of every application running over the Hadoop cluster.
Its flexible and scalable user-interface allows a range of tools such as Pig, MapReduce, Hive, etc., to be installed on the cluster and administers their performances in a user-friendly fashion. Some of the key features of this technology can be highlighted as:
Instantaneous insight into the health of Hadoop cluster using pre-configured operational metrics
User-friendly configuration providing an easy step-by-step guide for installation
You can install Apache Ambari through the Hortonworks Data Platform
Dependencies and performances monitored by visualizing and analyzing jobs and tasks
Authentication, authorization and auditing by installing Kerberos-based Hadoop clusters
Flexible and adaptive technology fitting perfectly in the enterprise environment.