An open source server that reliably coordinates distributed processes
Apache ZooKeeper provides operational services for a Hadoop cluster. ZooKeeper provides a distributed configuration service, a synchronization service and a naming registry for distributed systems. Distributed applications use Zookeeper to store and mediate updates to important configuration information.
ZooKeeper provides a very simple interface and services. ZooKeeper brings these key benefits:
ZooKeeper allows distributed processes to coordinate with each other through a shared hierarchical name space of data registers, known as znodes. Every znode is identified by a path, with path elements separated by a slash (“/”). Aside from the root, every znode has a parent, and a znode cannot be deleted if it has children.
This is much like a normal file system, but ZooKeeper provides superior reliability through redundant services. A service is replicated over a set of machines and each maintains an in-memory image of the the data tree and transaction logs. Clients connect to a single ZooKeeper server and maintains a TCP connection through which they send requests and receive responses.
This architecture allows ZooKeeper to provide high throughput and availability with low latency, but the size of the database that ZooKeeper can manage is limited by memory.
Introduction Hadoop has always been associated with BigData, yet the perception is it’s only suitable for high latency, high throughput queries. With the contribution of the community, you can use Hadoop interactively for data exploration and visualization. In this tutorial you’ll learn how to analyze large datasets using Apache Hive LLAP on Amazon Web Services […]
A very common request from many customers is to be able to index text in image files; for example, text in scanned PNG files. In this tutorial we are going to walkthrough how to do this with SOLR. Prerequisites Download the Hortonworks Sandbox Complete the Learning the Ropes of the HDP Sandbox tutorial. Step-by-step guide […]
Introduction In this tutorial, you will learn about the different features available in the HDF sandbox. HDF stands for Hortonworks DataFlow. HDF was built to make processing data-in-motion an easier task while also directing the data from source to the destination. You will learn about quick links to access these tools that way when you […]
Introduction JReport is a embedded BI reporting tool can easily extract and visualize data from the Hortonworks Data Platform 2.3 using the Apache Hive JDBC driver. You can then create reports, dashboards, and data analysis, which can be embedded into your own applications. In this tutorial we are going to walkthrough the folllowing steps to […]
The Hortonworks Sandbox is delivered as a Dockerized container with the most common ports already opened and forwarded for you. If you would like to open even more ports, check out this tutorial.
Introduction R is a popular tool for statistics and data analysis. It has rich visualization capabilities and a large collection of libraries that have been developed and maintained by the R developer community. One drawback to R is that it’s designed to run on in-memory data, which makes it unsuitable for large datasets. Spark is […]
Apache Zeppelin on HDP 2.4.2 Author: Vinay Shukla In March 2016 we delivered the second technical preview of Apache Zeppelin, on HDP 2.4. Meanwhile we and the Zeppelin community have continued to add new features to Zeppelin. These features are now available in the final technical preview of Apache Zeppelin. This technical preview works with […]
Welcome to the Hortonworks Sandbox! Look at the attached sections for sandbox documentation.
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