Howdy friends! In this blog post, I show how Kudu, a new random-access datastore, can be made to function as a more flexible queueing system with nearly as high throughput as Kafka. One of the more exciting recent developments in data processing is t…

Apache Kudu是由Cloudera开源的存储引擎,可以同时提供低延迟的随机读写和高效的数据分析能力.Kudu支持水平扩展,使用Raft协议进行一致性保证,并且与Cloudera Impala和Apache Spark等当前流行的大数据查询和分析工具结 合紧密.本文将为您介绍Kudu的一些基本概念和架构以及在企业中的应用,使您对Kudu有一个较为全面的了解. 比较有意思的是,同为Cloudera公司开源的另一款产品Impala,是另一种非洲的羚羊,叫做“黑斑羚”,也叫“高角羚”.不知道Cl…

After the GA of Apache Kudu in Cloudera CDH 5.10, we take a look at the Apache Spark on Kudu integration, share code snippets, and explain how to get up and running quickly, as Kudu is already a first-class citizen in Spark’s ecosystem. As the Apache…

A new addition to the open source Apache Hadoop ecosystem, Apache Kudu completes Hadoop's storage layer to enable fast analytics on fast data. 开源Apache Hadoop生态系统的新成员,Apache Kudu完善了Hadoop的存储层,以实现对快速数据的快速分析. Kudu 是 Cloudera 开源的结构化数据的开源存储引擎,是 Apache Ha…

不多说,直接上干货! http://kudu.apache.org/docs/kudu_impala_integration.html http://blog.csdn.net/lovebyz/article/details/77372907…

不多说,直接上干货! http://kudu.apache.org/docs/configuration.html…

kudu 1.7 官方:https://kudu.apache.org/ 一 简介 kudu有很多概念,有分布式文件系统(HDFS),有一致性算法(Zookeeper),有Table(Hive Table),有Tablet(Hive Table Partition),有列式存储(Parquet),有顺序和随机读取(HBase),所以看起来kudu是一个轻量级的 HDFS + Zookeeper + Hive + Parquet + HBase,除此之外,kudu还有自己的特点,快速写入+读取,使…

What Is Apache Hadoop? The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing. Hadoop项目是为了开发可靠.可伸缩的分布式计算的开源软件. The Apache Hadoop software library is a framework that allows for the distributed processi…

What Is Apache Hadoop? Getting Started Download Hadoop Who Uses Hadoop? News 15 October, 2013: release 2.2.0 available 25 August, 2013: release 2.1.0-beta available 27 December, 2011: release 1.0.0 available March 2011 - Apache Hadoop takes top prize…

Kudu的背景 Hadoop中有很多组件,为了实现复杂的功能通常都是使用混合架构, Hbase:实现快速插入和修改,对大量的小规模查询也很迅速 HDFS/Parquet + Impala/Hive:对超大的数据集进行查询分析,对于这类场景, Parquet这种列式存储文件格式具有极大的优势. HDFS/Parquet + Hbase:这种混合架构需要每隔一段时间将数据从hbase导出成Parquet文件,然后用impala来实现复杂的查询分析 以上的架构没办法把复杂的实时查询集成在Hbase上…