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这篇文章主要讲解了“Flume接入Hive数仓的搭建流程”,文中的讲解内容简单清晰,易于学习与理解,下面请大家跟着小编的思路慢慢深入,一起来研究和学习“Flume接入Hive数仓的搭建流程”吧!
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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:
使用正则表达式匹配目录中的文件名
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
高可靠,不会丢失数据
不会对跟踪文件有任何处理,不会重命名也不会删除
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 MapheaderMap = 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。这里是创新互联,小编将为大家推送更多相关知识点的文章,欢迎关注!