deep api integration makes getting value from your big data easy
深度api集成使你大数据访问更加容易
标签：elasticsearch hadoop es-hadoop
深度api集成使你大数据访问更加容易
Elasticsearch is quickly becoming the de facto search and analytics solution that organizations are using to provide real-time insights into their Hadoop data. Elasticsearch for Hadoop—affectionately known as es-hadoop—is a two-way connector that lets you index data into Elasticsearch and query it in real time. With a native API implementation, fast indexing, and a rich query language, es-hadoop is optimized for performance and efficiency, making it an elegant solution for your big data projects. With support for a wide range of libraries, Elasticsearch helps you to make better use of your data across the entire Hadoop ecosystem.
leave the real-time analytics to us
Gone are the days of waiting hours or more for a batch process to run in order to get insight into your Hadoop data. Elasticsearch provides responses in milliseconds, which can significantly reduce a Hadoop job’s execution time and the cost associated with
it, especially on “rented resources” such as Amazon EMR or EC2.
ask more sophisticated questions
Elasticsearch provides a robust query DSL that lets users to ask sophisticated questions that result in more complete answers, faster.
prepared for when things go awry
Elasticsearch is designed to tolerate hardware failures. Es-hadoop continues communicating with the cluster, even when failures occur.
added efficiency with our native integration
Elasticsearch is natively integrated with Hadoop so there is no gap for the user to bridge. We provide a dedicated Input and Output format for vanilla MapReduce, taps for reading and writing data in Cascading, storages for Pig and Hive, a native Spark Resilient
Distributed Dataset (RDD) for both Java and Scala, and support for Storm’s bolt and spout abstractions so you can access Elasticsearch just as if the data were in HDFS.
enhance your workflow to get the best of both worlds
Get maximum flexibility with the es-hadoop connector by leveraging everything that Hadoop has to offer (via MapReduce, Hive, Pig, Cascading, Spark, and Storm) and combining it with a real-time search and analytics capability of Elasticsearch.
need to grow? just add more nodes.
Elasticsearch can be scaled in the same way as your Hadoop cluster – add more Elasticsearch nodes and the data will be automatically re-balanced.
原文网址：http://www.elasticsearch.com/products/hadoop/
explore your hadoop data and get real-time results
标签：elasticsearch hadoop es-hadoop
原文地址：http://blog.csdn.net/sunflower_cao/article/details/40041203
