本TTP为大数据及其常用组件的基本介绍（hdfs hive hbase kafka spark kudu impala kylin streamsets）仅供参考。

压缩文件包含 ：kudu执行文件、kudu-master、kudu-tserver，直接在原来的旧集群，替换这三个文件就可以升级使用

kudu构建近实时分析系统.pdf.

因liunx安装kudu需要6个包，但是下载速度很慢，为此提供，kudu所需的6个rpm包，供大家快速下载。

kudu1.9的rpm安装包，包含以下六个资源： kudu-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm kudu-client0-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm kudu-client-devel-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm kudu-debuginfo-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm kudu-master-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm kudu-tserver-1.9.0+cdh6.2.1-1425774.el6.x86_64.rpm

压缩文件包含 ：kudu执行文件、kudu-master、kudu-tserver，直接在原来的旧集群，替换这三个文件就可以升级使用。

Utilize this practical and easy-to-follow guide to modernize traditional enterprise data warehouse and business intelligence environments with next-generation big data technologies. Next-Generation Big Data takes a holistic approach, covering the most important aspects of modern enterprise big data. The book covers not only the main technology stack but also the next-generation tools and applications used for big data warehousing, data warehouse optimization, real-time and batch data ingestion and processing, real-time data visualization, big data governance, data wrangling, big data cloud deployments, and distributed in-memory big data computing. Finally, the book has an extensive and detailed coverage of big data case studies from Navistar, Cerner, British Telecom, Shopzilla, Thomson Reuters, and Mastercard. What You’ll Learn Install Apache Kudu, Impala, and Spark to modernize enterprise data warehouse and business intelligence environments, complete with real-world, easy-to-follow examples, and practical advice Integrate HBase, Solr, Oracle, SQL Server, MySQL, Flume, Kafka, HDFS, and Amazon S3 with Apache Kudu, Impala, and Spark Use StreamSets, Talend, Pentaho, and CDAP for real-time and batch data ingestion and processing Utilize Trifacta, Alteryx, and Datameer for data wrangling and interactive data processing Turbocharge Spark with Alluxio, a distributed in-memory storage platform Deploy big data in the cloud using Cloudera Director Perform real-time data visualization and time series analysis using Zoomdata, Apache Kudu, Impala, and Spark Understand enterprise big data topics such as big data governance, metadata management, data lineage, impact analysis, and policy enforcement, and how to use Cloudera Navigator to perform common data governance tasks Implement big data use cases such as big data warehousing, data warehouse optimization, Internet of Things, real-time data ingestion and analytics, complex event processing, and scalable predictive

python -kudu 需要的 rpm 安装包

kudu-1.7.0+cdh5.16.1 6个RPM

该文档是根据真实项目，搭建的一套OGG实时同步oracle数据到kafka集群，文档主要介绍OGG的安装和进程配置。文档最后附带整个数据处理的流程图。