kudu中的flume sink代码路径: https://github.com/apache/kudu/tree/master/java/kudu-flume-sink kudu-flume-sink默认使用的producer是 org.apache.kudu.flume.sink.SimpleKuduOperationsProducer public List<Operation> getOperations(Event event) throws FlumeException { try…
flume sink核心类结构 1 核心接口Sink org.apache.flume.Sink /** * <p>Requests the sink to attempt to consume data from attached channel</p> * <p><strong>Note</strong>: This method should be consuming from the channel * within the bounds…
应用一:kafka数据同步到kudu 1 准备kafka topic # bin/kafka-topics.sh --zookeeper $zk:2181/kafka -create --topic test_sync --partitions 2 --replication-factor 2 WARNING: Due to limitations in metric names, topics with a period ('.') or underscore ('_') could coll…
核心枚举 public enum ServerState { LOOKING, FOLLOWING, LEADING, OBSERVING; } zookeeper服务器状态:刚启动LOOKING,follower是FOLLOWING,leader是LEADING,observer是OBSERVING: public enum LearnerType { PARTICIPANT, OBSERVER; } 简单来说,zookeeper启动的核心类是QuorumPeerMain,启动之后会加载配置,…
相关文章: 大数据系列之Kafka安装 大数据系列之Flume--几种不同的Sources 大数据系列之Flume+HDFS 关于Flume 的 一些核心概念: 组件名称     功能介绍 Agent代理 使用JVM 运行Flume.每台机器运行一个agent,但是可以在一个agent中包含多个sources和sinks. Client客户端 生产数据,运行在一个独立的线程. Source源 从Client收集数据,传递给Channel. Sink接收器 从Channel收集数据,进行相关操作,…
对文件进行词频统计,是一个大数据领域的hello word级别的应用,来看下实现有多简单: 1 Linux单机处理 egrep -o "\b[[:alpha:]]+\b" test_word.log|sort|uniq -c|sort -rn|head -10 2 Spark分布式处理(Scala) val sparkConf = new SparkConf() val sc = new SparkContext(sparkConf) sc.textFile("test_wo…
impala2.12 官方:http://impala.apache.org/ 一 简介 Apache Impala is the open source, native analytic database for Apache Hadoop. Impala is shipped by Cloudera, MapR, Oracle, and Amazon. impala是hadoop上的开源分析性数据库:C++和java语言开发: Do BI-style Queries on Hadoop Im…
tpc 官方:http://www.tpc.org/ 一 简介 The TPC is a non-profit corporation founded to define transaction processing and database benchmarks and to disseminate objective, verifiable TPC performance data to the industry. TPC(The Transaction Processing Perform…
一 简介 Shuffle,简而言之,就是对数据进行重新分区,其中会涉及大量的网络io和磁盘io,为什么需要shuffle,以词频统计reduceByKey过程为例, serverA:partition1: (hello, 1), (word, 1)serverB:partition2: (hello, 2) shuffle之后: serverA:partition1: (hello, 1), (hello, 2)serverB:partition2: (word, 1) 最后才能得到结果: (h…
一 简介 spark核心是RDD,官方文档地址:https://spark.apache.org/docs/latest/rdd-programming-guide.html#resilient-distributed-datasets-rdds官方描述如下:重点是可容错,可并行处理 Spark revolves around the concept of a resilient distributed dataset (RDD), which is a fault-tolerant colle…