Flume接入Hive数仓的搭建流程

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实时流接入数仓，基本在大公司都会有，在Flume1.8以后支持taildir source, 其有以下几个特点，而被广泛使用：

1. 使用正则表达式匹配目录中的文件名

2. 监控的文件中，一旦有数据写入，Flume就会将信息写入到指定的Sink

3. 高可靠，不会丢失数据

4. 不会对跟踪文件有任何处理，不会重命名也不会删除

5. 不支持Windows，不能读二进制文件。支持按行读取文本文件

本文以开源Flume流为例，介绍流接入HDFS ,后面在其上面建立ods层外表。

1.1 taildir source配置

a1.sources.r1.type = TAILDIR a1.sources.r1.positionFile = /opt/hoult/servers/conf/startlog_position.json a1.sources.r1.filegroups = f1 a1.sources.r1.filegroups.f1 =/opt/hoult/servers/logs/start/.*log

1.2 hdfs sink 配置

a1.sinks.k1.type = hdfs a1.sinks.k1.hdfs.path = /user/data/logs/start/logs/start/%Y-%m-%d/ a1.sinks.k1.hdfs.filePrefix = startlog. # 配置文件滚动方式（文件大小32M） a1.sinks.k1.hdfs.rollSize = 33554432 a1.sinks.k1.hdfs.rollCount = 0 a1.sinks.k1.hdfs.rollInterval = 0 a1.sinks.k1.hdfs.idleTimeout = 0 a1.sinks.k1.hdfs.minBlockReplicas = 1 # 向hdfs上刷新的event的个数 a1.sinks.k1.hdfs.batchSize = 100 # 使用本地时间 a1.sinks.k1.hdfs.useLocalTimeStamp = true

1.3 Agent的配置

a1.sources = r1 a1.sinks = k1 a1.channels = c1 # taildir source a1.sources.r1.type = TAILDIR a1.sources.r1.positionFile = /opt/hoult/servers/conf/startlog_position.json a1.sources.r1.filegroups = f1 a1.sources.r1.filegroups.f1 = /user/data/logs/start/.*log # memorychannel a1.channels.c1.type = memory a1.channels.c1.capacity = 100000 a1.channels.c1.transactionCapacity = 2000 # hdfs sink a1.sinks.k1.type = hdfs a1.sinks.k1.hdfs.path = /opt/hoult/servers/logs/start/%Y-%m-%d/ a1.sinks.k1.hdfs.filePrefix = startlog. # 配置文件滚动方式（文件大小32M） a1.sinks.k1.hdfs.rollSize = 33554432 a1.sinks.k1.hdfs.rollCount = 0 a1.sinks.k1.hdfs.rollInterval = 0 a1.sinks.k1.hdfs.idleTimeout = 0 a1.sinks.k1.hdfs.minBlockReplicas = 1 # 向hdfs上刷新的event的个数 a1.sinks.k1.hdfs.batchSize = 1000 # 使用本地时间 a1.sinks.k1.hdfs.useLocalTimeStamp = true # Bind the source and sink to the channel a1.sources.r1.channels = c1 a1.sinks.k1.channel = c1

/opt/hoult/servers/conf/flume-log2hdfs.conf

1.4 启动

flume-ng agent --conf-file /opt/hoult/servers/conf/flume-log2hdfs.conf -name a1 -Dflume.roog.logger=INFO,console  export JAVA_OPTS="-Xms4000m -Xmx4000m -Dcom.sun.management.jmxremote" # 要想使配置文件生效，还要在命令行中指定配置文件目录 flume-ng agent --conf /opt/hoult/servers/flume-1.9.0/conf --conf-file /opt/hoult/servers/conf/flume-log2hdfs.conf -name a1 -Dflume.roog.logger=INFO,console

要$FLUME_HOME/conf/flume-env.sh加下面的参数，否则会报错误如下：

1.5 使用自定义拦截器解决Flume Agent替换本地时间为日志里面的时间戳

使用netcat source → logger sink来测试

# a1是agent的名称。source、channel、sink的名称分别为：r1 c1 k1 a1.sources = r1 a1.channels = c1 a1.sinks = k1 # source a1.sources.r1.type = netcat a1.sources.r1.bind = linux121 a1.sources.r1.port = 9999 a1.sources.r1.interceptors = i1 a1.sources.r1.interceptors.i1.type = com.hoult.flume.CustomerInterceptor$Builder # channel a1.channels.c1.type = memory a1.channels.c1.capacity = 10000 a1.channels.c1.transactionCapacity = 100 # sink a1.sinks.k1.type = logger # source、channel、sink之间的关系 a1.sources.r1.channels = c1 a1.sinks.k1.channel = c1

拦截器主要代码如下：

public class CustomerInterceptor implements Interceptor {     private static DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyyMMdd");      @Override     public void initialize() {      }      @Override     public Event intercept(Event event) {         // 获得body的内容         String eventBody = new String(event.getBody(), Charsets.UTF_8);         // 获取header的内容         Map headerMap = event.getHeaders();         final String[] bodyArr = eventBody.split("\\s+");         try {             String jsonStr = bodyArr[6];             if (Strings.isNullOrEmpty(jsonStr)) {                 return null;             }             // 将 string 转成 json 对象             JSONObject jsonObject = JSON.parseObject(jsonStr);             String timestampStr = jsonObject.getString("time");             //将timestamp 转为时间日期类型（格式 ：yyyyMMdd)             long timeStamp = Long.valueOf(timestampStr);             String date = formatter.format(LocalDateTime.ofInstant(Instant.ofEpochMilli(timeStamp), ZoneId.systemDefault()));             headerMap.put("logtime", date);             event.setHeaders(headerMap);         } catch (Exception e) {             headerMap.put("logtime", "unknown");             event.setHeaders(headerMap);         }         return event;      }      @Override     public List intercept(List events) {         List out = new ArrayList<>();         for (Event event : events) {             Event outEvent = intercept(event);             if (outEvent != null) {                 out.add(outEvent);             }         }         return out;     }      @Override     public void close() {      }      public static class Builder implements Interceptor.Builder {         @Override         public Interceptor build() {             return new CustomerInterceptor();         }          @Override         public void configure(Context context) {         }     }

启动

flume-ng agent --conf /opt/hoult/servers/flume-1.9.0/conf --conf-file /opt/hoult/servers/conf/flume-test.conf -name a1 -Dflume.roog.logger=INFO,console ## 测试 telnet linux121 9999

感谢各位的阅读，以上就是"Flume接入Hive数仓的搭建流程"的内容了，经过本文的学习后，相信大家对Flume接入Hive数仓的搭建流程这一问题有了更深刻的体会，具体使用情况还需要大家实践验证。这里是，小编将为大家推送更多相关知识点的文章，欢迎关注！