Impala是基于Hive的大数据实时分析查询引擎，直接使用Hive的元数据库Metadata,意味着impala元数据都存储在Hive的metastore中。并且impala兼容Hive的sql解析，实现了Hive的SQL语义的子集，功能还在不断的完善中

impalaJDBC4以及41

apache-atlas-2.1.0-impala-hook.tar.gz--基于cdh6.3.1编译完成

impala udf C++版需要，CDH官网不再开放下载。

springboot+mybatis+impala/mysql整合Demo ， 内嵌PageHelper插件已整合，需要根据pom.xml中的备注操作即可使用mysql和PageHelper, impala 不支持PageHelper插件

impala cookbook详解版

springboot集成impala，包含yml文件、impala配置Bean、ImpalaJDBC41-2.6.4.1005.jar和impala在pom.xml中的配置，有问题留言

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

ambari集成impala-3.0.0依赖cdh版本的hadoop-hbase-hive相关jar包，查hive外部表(基于hbase)

该资源是impala的jdbc驱动,是最新版本，需要下载的小伙伴赶快行动起来