关于大数据:Flume接入Hive数仓搭建流程

实时流接入数仓，根本在大公司都会有，在 Flume1.8 当前反对taildir source, 其有以下几个特点，而被宽泛应用：

1. 应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. 高牢靠，不会失落数据
4. 不会对跟踪文件有任何解决，不会重命名也不会删除
5. 不反对Windows，不能读二进制文件。反对按行读取文本文件

本文以开源 Flume 流为例，介绍流接入 HDFS , 前面在其下面建设ods 层表面。

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.
# 配置文件滚动形式（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
# 应用本地工夫
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.
# 配置文件滚动形式（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
# 应用本地工夫
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"
# 要想使配置文件失效，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 加上面的参数，否则会报谬误如下：

1.5 应用自定义拦截器解决 Flume Agent 替换本地工夫为日志外面的工夫戳

应用 netcat source → logger sink 来测试

# a1 是 agent 的名称。source、channel、sink 的名称别离为：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 

拦截器次要代码如下：

public class CustomerInterceptor implements Interceptor {private static DateTimeFormatter formatter = DateTimeFormatter.ofPattern("yyyyMMdd");

    @Override
    public void initialize() {}

    @Override
    public Event intercept(Event event) {
        // 取得 body 的内容
        String eventBody = new String(event.getBody(), Charsets.UTF_8);
        // 获取 header 的内容
        Map<String, String> 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 转为工夫日期类型（格局：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<Event> intercept(List<Event> events) {List<Event> 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 

吴邪，小三爷，混迹于后盾，大数据，人工智能畛域的小菜鸟。
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