flume Interceptor

灰太狼 2022-05-21 02:59 243阅读 0赞

拦截器的介绍与使用

Flume Interceptors

<table> 
 <tbody> 
 <tr> 
 <td style="background:#F4F1BA;">Interceptor类型</td> 
 <td style="background:#F4F1BA;">说明</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Timestamp Interceptor</td> 
 <td style="background:#F4F1BA;">在event的header中添加一个key叫：timestamp,value为当前的时间戳。</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Host Interceptor</td> 
 <td style="background:#F4F1BA;">在event的header中添加一个key叫：host,value为当前机器的hostname或者ip。</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Static Interceptor</td> 
 <td style="background:#F4F1BA;">可以在event的header中添加自定义的key和value。</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">UUID Interceptor</td> 
 <td style="background:#F4F1BA;">用于在每个events header中生成一个UUID字符串，生成的UUID可以在sink中读取并使用</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Morphline Interceptor</td> 
 <td style="background:#F4F1BA;">http://kitesdk.org/docs/current/morphlines/morphlines-reference-guide.html 基本相当于一个ETL 工具</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Search and Replace Interceptor</td> 
 <td style="background:#F4F1BA;">&nbsp;</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Regex Filtering Interceptor</td> 
 <td style="background:#F4F1BA;">通过正则来清洗或包含匹配的events。</td> 
 </tr> 
 <tr> 
 <td style="background:#F4F1BA;">Regex Extractor Interceptor</td> 
 <td style="background:#F4F1BA;">通过正则表达式来在header中添加指定的key,value则为正则匹配的部分。</td> 
 </tr> 
 </tbody> 
</table>

转载：Flume中的拦截器（Interceptor）介绍与使用 https://blog.csdn.net/jek123456/article/details/65633958

以实际配置文件进行说明，自定义了一个拦截器，消费 Kafka topic1 的数据，生产到topic2 中。

#flume 1.8 version
    agentzk.sources = src-1
    agentzk.channels = ch-1
    agentzk.sinks = sink-1
    
    agentzk.sources.src-1.type = org.apache.flume.source.kafka.KafkaSource
    agentzk.sources.src-1.batchSize = 500
    agentzk.sources.src-1.batchDurationMillis = 200
    agentzk.sources.src-1.kafka.topics = flumeSource1
    agentzk.sources.src-1.kafka.bootstrap.servers = 10.120.51.240:21005,10.120.51.143:21005
    agentzk.sources.src-1.kafka.consumer.group.id = flume
    agentzk.sources.src-1.kafka.consumer.timeout.ms = 100
    agentzk.sources.src-1.kafka.enable.auto.commit = false
    agentzk.sources.src-1.kafka.consumer.auto.offset.reset = latest
    agentzk.sources.src-1.kafka.security.protocol  = PLAINTEXT
    agentzk.sources.src-1.channels = ch-1
    
    #多个拦截器按顺序执行，拦截器1用于解决kafka topic 覆盖问题，拦截器2为自定义的
    agentzk.sources.src-1.interceptors=i1 i2
    agentzk.sources.src-1.interceptors.i1.type = static
    agentzk.sources.src-1.interceptors.i1.key = topic
    agentzk.sources.src-1.interceptors.i1.preserveExisting = false
    agentzk.sources.src-1.interceptors.i1.value = flumeSink1
    agentzk.sources.src-1.interceptors.i2.type=com.xxx.bigdata.interceptor.fields.FieldsInterceptor$Builder  
    #fullPair:true 满足所有条件, fullPair:false 满足任一条件
    agentzk.sources.src-1.interceptors.i2.fullPair=false
    #event 分割后,条件i:event[1] == 016; event[1] == 0016
    agentzk.sources.src-1.interceptors.i2.index=1|1
    agentzk.sources.src-1.interceptors.i2.fields=016|0016
    agentzk.sources.src-1.interceptors.i2.splitChar=\\|
    
    agentzk.channels.ch-1.type = memory
    agentzk.channels.ch-1.capacity = 10000
    agentzk.channels.ch-1.transactionCapacity = 1000
    #agentzk.channels.ch-1.byteCapacityBufferPercentage = 50
    #agentzk.channels.ch-1.byteCapacity = 100000
    
    agentzk.sinks.sink-1.type = org.apache.flume.sink.kafka.KafkaSink
    agentzk.sinks.sink-1.kafka.topic = flumeSink1
    agentzk.sinks.sink-1.kafka.producer.acks = 0
    agentzk.sinks.sink-1.kafka.bootstrap.servers = 10.120.51.240:21005,10.120.51.143:21005
    agentzk.sinks.sink-1.kafka.security.protocol = PLAINTEXT
    agentzk.sinks.sink-1.flumeBatchSize = 500
    agentzk.sinks.sink-1.channel = ch-1

拦截器1的作用：解决Flume中同时使用Kafka Source和Kafka Sink的Topic覆盖问题。

参见：[https://blog.csdn.net/u010170616/article/details/80844686][https_blog.csdn.net_u010170616_article_details_80844686]

自定义拦截器，可以参照flume源码里的原生拦截器来写。此处具体逻辑处理涉及到实际业务含义，故不进行赘述。

package com.xxx.bigdata.interceptor.fields;
 
 import java.util.List;
 
 import org.apache.commons.io.Charsets;
 import org.apache.flume.Context;
 import org.apache.flume.Event;
 import org.apache.flume.interceptor.Interceptor;
 import org.slf4j.Logger;
 import org.slf4j.LoggerFactory;
 
 import com.google.common.collect.Lists;
 
 /**
 * 
 *
 * Sample config:
 * 根据 | 分割event,判断 array[index] == fields
 * <code>
 * agent.sources.r1.interceptors = i1
 * agent.sources.r1.interceptors.i1.fullPair = true(false)
 * agent.sources.r1.interceptors.i1.index = 0|2
 * agent.sources.r1.interceptors.i1.fields = 016|1602
 * </code>
 *
 */
 public class FieldsInterceptor implements Interceptor{
 
 	private static final Logger logger = LoggerFactory.getLogger(FieldsInterceptor.class);
 
 //	满足所有条件 or 满足任一条件 
 	private final boolean fullPair;
 	private final String index;
 	private final String fields;
 	private final String splitChar;
 //	满足条件的是否被过滤
 //	private final boolean excludeEvents;
 
 	/**
 	 * Only {@link FieldsInterceptor.Builder} can build me
 	 */
 	private FieldsInterceptor(boolean fullPair, String index, String fields, String splitChar) {
 		this.fullPair = fullPair;
 		this.index = index;
 		this.fields = fields;
 		this.splitChar = splitChar;
 	}
 	
 	@Override
 	public void close() {
 	}
 
 	@Override
 	public void initialize() {
 	}
 
 	@Override
 	public Event intercept(Event event) 
 	{
 		if (index == null || index == "" || fields == null || fields == "")
 		{
 			return null;
 		}
 		
 		String[] indexArray = index.split(splitChar);
 		String[] fieldArray = fields.split(splitChar);
 
 		String body = new String(event.getBody(), Charsets.UTF_8);
 		
 		String[] bodyArray = body.split(splitChar);
 		if (bodyArray.length <= 1)
 		{
 			logger.info("error body : " + body);
 			return null;
 		}
 		
 		// 满足所有条件
 		if (fullPair) 
 		{
 			for (int i = 0; i < indexArray.length; i++) 
 			{
 				if (!bodyArray[Integer.valueOf(indexArray[i])].equals(fieldArray[i]))
 				{
 					return null;
 				}
 			}
 			return event;
 		}
 		else 
 		{
 			for (int i = 0; i < indexArray.length; i++)
 			{
 				if (bodyArray[Integer.valueOf(indexArray[i])].equals(fieldArray[i]))
 				{
 					return event;
 				}
 			}
             return null;
         }
 	}
 
 	@Override
 	public List<Event> intercept(List<Event> events) 
 	{
 	    List<Event> out = Lists.newArrayListWithCapacity(events.size());
     for (Event event : events)
      {
     Event outEvent = intercept(event);
     if (outEvent != null)
      {
     	out.add(outEvent);
     }
     }
     return out;
 	}
 
 	public static class Builder implements Interceptor.Builder
 	{
 		private boolean fullPair;
 		private String index;
 		private String fields;
 		private String splitChar;
 		
 		@Override
 		public void configure(Context context) 
 		{
 			fullPair = context.getBoolean(Constants.FULLPAIR, Constants.DEFAULT_FULLPAIR);
 			index = context.getString(Constants.INDEX);
 			fields = context.getString(Constants.FIELDS);
 			splitChar = context.getString(Constants.SPLIT_CHAR, Constants.DEFAULT_SPLIT_CHAR);
 		}
 
 		@Override
 		public Interceptor build() 
 		{
 			return new FieldsInterceptor(fullPair, index, fields, splitChar);
 		}
 		
 	}
 	
 	public static class Constants 
 	{
 		public static final String SPLIT_CHAR = "splitChar";
 		public static final String DEFAULT_SPLIT_CHAR = "\\|";
 		
 		public static final String FULLPAIR = "fullPair";
 		public static final boolean DEFAULT_FULLPAIR = false;
 		
 		public static final String INDEX = "index";
 		public static final String FIELDS = "fields";
 	}
 	
 }

[https_blog.csdn.net_u010170616_article_details_80844686]: https://blog.csdn.net/u010170616/article/details/80844686