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名师互学网 > IT > 前沿技术 > 大数据 > 大数据系统

flink按天分区实时写入hive表问题

flink按天分区实时写入hive表问题

flink按天分区实时写入hive表问题

参考链接:
https://www.cnblogs.com/codetouse/p/12746612.html
https://www.cnblogs.com/kancy/p/13912443.html
https://www.e-learn.cn/content/wangluowenzhang/227836

1.问题:

2022-02-07 17:04:49,196 WARN org.apache.flink.yarn.configuration.YarnLogConfigUtil [] - The configuration directory (’/opt/flink/conf’) already contains a LOG4J config file.If you want to use logback, then please delete or rename the log configuration file.
2022-02-07 17:04:49,391 INFO org.apache.hadoop.yarn.client.api.impl.TimelineReaderClientImpl [] - Initialized TimelineReader URI=http://hadoop11.nb:8198/ws/v2/timeline/, clusterId=yarn-cluster
java.lang.linkageError: ClassCastException: attempting to castjar:file:/data/work/cmbh/project/flinkJob/bigdata-1.0-SNAPSHOT-jar-with-dependencies.jar!/javax/ws/rs/ext/RuntimeDelegate.class to jar:file:/opt/flink/lib/javax.ws.rs-api-2.0.jar!/javax/ws/rs/ext/RuntimeDelegate.class
at javax.ws.rs.ext.RuntimeDelegate.findDelegate(RuntimeDelegate.java:146)
at javax.ws.rs.ext.RuntimeDelegate.getInstance(RuntimeDelegate.java:120)
at javax.ws.rs.core.MediaType.valueOf(MediaType.java:179)
at com.sun.jersey.core.header.MediaTypes.(MediaTypes.java:65)
at com.sun.jersey.core.spi.factory.MessageBodyFactory.initReaders(MessageBodyFactory.java:182)
at com.sun.jersey.core.spi.factory.MessageBodyFactory.initReaders(MessageBodyFactory.java:175)
at com.sun.jersey.core.spi.factory.MessageBodyFactory.init(MessageBodyFactory.java:162)
at com.sun.jersey.api.client.Client.init(Client.java:343)
at com.sun.jersey.api.client.Client.access$000(Client.java:119)
at com.sun.jersey.api.client.Client$1.f(Client.java:192)
at com.sun.jersey.api.client.Client 1. f ( C l i e n t . j a v a : 188 ) a t c o m . s u n . j e r s e y . s p i . i n j e c t . E r r o r s . p r o c e s s W i t h E r r o r s ( E r r o r s . j a v a : 193 ) a t c o m . s u n . j e r s e y . a p i . c l i e n t . C l i e n t . < i n i t > ( C l i e n t . j a v a : 188 ) a t c o m . s u n . j e r s e y . a p i . c l i e n t . C l i e n t . < i n i t > ( C l i e n t . j a v a : 171 ) a t o r g . a p a c h e . h a d o o p . y a r n . c l i e n t . a p i . i m p l . T i m e l i n e C o n n e c t o r . s e r v i c e I n i t ( T i m e l i n e C o n n e c t o r . j a v a : 122 ) a t o r g . a p a c h e . h a d o o p . s e r v i c e . A b s t r a c t S e r v i c e . i n i t ( A b s t r a c t S e r v i c e . j a v a : 164 ) a t o r g . a p a c h e . h a d o o p . s e r v i c e . C o m p o s i t e S e r v i c e . s e r v i c e I n i t ( C o m p o s i t e S e r v i c e . j a v a : 108 ) a t o r g . a p a c h e . h a d o o p . y a r n . c l i e n t . a p i . i m p l . T i m e l i n e R e a d e r C l i e n t I m p l . s e r v i c e I n i t ( T i m e l i n e R e a d e r C l i e n t I m p l . j a v a : 99 ) a t o r g . a p a c h e . h a d o o p . s e r v i c e . A b s t r a c t S e r v i c e . i n i t ( A b s t r a c t S e r v i c e . j a v a : 164 ) a t o r g . a p a c h e . h a d o o p . y a r n . c l i e n t . a p i . i m p l . A H S v 2 C l i e n t I m p l . s e r v i c e I n i t ( A H S v 2 C l i e n t I m p l . j a v a : 63 ) a t o r g . a p a c h e . h a d o o p . s e r v i c e . A b s t r a c t S e r v i c e . i n i t ( A b s t r a c t S e r v i c e . j a v a : 164 ) a t o r g . a p a c h e . h a d o o p . y a r n . c l i e n t . a p i . i m p l . Y a r n C l i e n t I m p l . s e r v i c e I n i t ( Y a r n C l i e n t I m p l . j a v a : 207 ) a t o r g . a p a c h e . h a d o o p . s e r v i c e . A b s t r a c t S e r v i c e . i n i t ( A b s t r a c t S e r v i c e . j a v a : 164 ) a t o r g . a p a c h e . f l i n k . y a r n . Y a r n C l u s t e r C l i e n t F a c t o r y . g e t C l u s t e r D e script o r ( Y a r n C l u s t e r C l i e n t F a c t o r y . j a v a : 82 ) a t o r g . a p a c h e . f l i n k . y a r n . Y a r n C l u s t e r C l i e n t F a c t o r y . c r e a t e C l u s t e r D e script o r ( Y a r n C l u s t e r C l i e n t F a c t o r y . j a v a : 61 ) a t o r g . a p a c h e . f l i n k . y a r n . Y a r n C l u s t e r C l i e n t F a c t o r y . c r e a t e C l u s t e r D e script o r ( Y a r n C l u s t e r C l i e n t F a c t o r y . j a v a : 43 ) a t o r g . a p a c h e . f l i n k . c l i e n t . d e p l o y m e n t . e x e c u t o r s . A b s t r a c t J o b C l u s t e r E x e c u t o r . e x e c u t e ( A b s t r a c t J o b C l u s t e r E x e c u t o r . j a v a : 73 ) a t o r g . a p a c h e . f l i n k . s t r e a m i n g . a p i . e n v i r o n m e n t . S t r e a m E x e c u t i o n E n v i r o n m e n t . e x e c u t e A s y n c ( S t r e a m E x e c u t i o n E n v i r o n m e n t . j a v a : 1957 ) a t o r g . a p a c h e . f l i n k . c l i e n t . p r o g r a m . S t r e a m C o n t e x t E n v i r o n m e n t . e x e c u t e A s y n c ( S t r e a m C o n t e x t E n v i r o n m e n t . j a v a : 137 ) a t o r g . a p a c h e . f l i n k . c l i e n t . p r o g r a m . S t r e a m C o n t e x t E n v i r o n m e n t . e x e c u t e ( S t r e a m C o n t e x t E n v i r o n m e n t . j a v a : 76 ) a t o r g . a p a c h e . f l i n k . s t r e a m i n g . a p i . e n v i r o n m e n t . S t r e a m E x e c u t i o n E n v i r o n m e n t . e x e c u t e ( S t r e a m E x e c u t i o n E n v i r o n m e n t . j a v a : 1834 ) a t o r g . a p a c h e . f l i n k . s t r e a m i n g . a p i . s c a l a . S t r e a m E x e c u t i o n E n v i r o n m e n t . e x e c u t e ( S t r e a m E x e c u t i o n E n v i r o n m e n t . s c a l a : 801 ) a t c o m . l e a d e o n . s e r v i c e . b o s l o g i n d t l 1.f(Client.java:188) at com.sun.jersey.spi.inject.Errors.processWithErrors(Errors.java:193) at com.sun.jersey.api.client.Client.(Client.java:188) at com.sun.jersey.api.client.Client.(Client.java:171) at org.apache.hadoop.yarn.client.api.impl.TimelineConnector.serviceInit(TimelineConnector.java:122) at org.apache.hadoop.service.AbstractService.init(AbstractService.java:164) at org.apache.hadoop.service.CompositeService.serviceInit(CompositeService.java:108) at org.apache.hadoop.yarn.client.api.impl.TimelineReaderClientImpl.serviceInit(TimelineReaderClientImpl.java:99) at org.apache.hadoop.service.AbstractService.init(AbstractService.java:164) at org.apache.hadoop.yarn.client.api.impl.AHSv2ClientImpl.serviceInit(AHSv2ClientImpl.java:63) at org.apache.hadoop.service.AbstractService.init(AbstractService.java:164) at org.apache.hadoop.yarn.client.api.impl.YarnClientImpl.serviceInit(YarnClientImpl.java:207) at org.apache.hadoop.service.AbstractService.init(AbstractService.java:164) at org.apache.flink.yarn.YarnClusterClientFactory.getClusterDescriptor(YarnClusterClientFactory.java:82) at org.apache.flink.yarn.YarnClusterClientFactory.createClusterDescriptor(YarnClusterClientFactory.java:61) at org.apache.flink.yarn.YarnClusterClientFactory.createClusterDescriptor(YarnClusterClientFactory.java:43) at org.apache.flink.client.deployment.executors.AbstractJobClusterExecutor.execute(AbstractJobClusterExecutor.java:73) at org.apache.flink.streaming.api.environment.StreamExecutionEnvironment.executeAsync(StreamExecutionEnvironment.java:1957) at org.apache.flink.client.program.StreamContextEnvironment.executeAsync(StreamContextEnvironment.java:137) at org.apache.flink.client.program.StreamContextEnvironment.execute(StreamContextEnvironment.java:76) at org.apache.flink.streaming.api.environment.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.java:1834) at org.apache.flink.streaming.api.scala.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.scala:801) at com.leadeon.service.bos_login_dtl 1.f(Client.java:188)atcom.sun.jersey.spi.inject.Errors.processWithErrors(Errors.java:193)atcom.sun.jersey.api.client.Client.(Client.java:188)atcom.sun.jersey.api.client.Client.(Client.java:171)atorg.apache.hadoop.yarn.client.api.impl.TimelineConnector.serviceInit(TimelineConnector.java:122)atorg.apache.hadoop.service.AbstractService.init(AbstractService.java:164)atorg.apache.hadoop.service.CompositeService.serviceInit(CompositeService.java:108)atorg.apache.hadoop.yarn.client.api.impl.TimelineReaderClientImpl.serviceInit(TimelineReaderClientImpl.java:99)atorg.apache.hadoop.service.AbstractService.init(AbstractService.java:164)atorg.apache.hadoop.yarn.client.api.impl.AHSv2ClientImpl.serviceInit(AHSv2ClientImpl.java:63)atorg.apache.hadoop.service.AbstractService.init(AbstractService.java:164)atorg.apache.hadoop.yarn.client.api.impl.YarnClientImpl.serviceInit(YarnClientImpl.java:207)atorg.apache.hadoop.service.AbstractService.init(AbstractService.java:164)atorg.apache.flink.yarn.YarnClusterClientFactory.getClusterDescriptor(YarnClusterClientFactory.java:82)atorg.apache.flink.yarn.YarnClusterClientFactory.createClusterDescriptor(YarnClusterClientFactory.java:61)atorg.apache.flink.yarn.YarnClusterClientFactory.createClusterDescriptor(YarnClusterClientFactory.java:43)atorg.apache.flink.client.deployment.executors.AbstractJobClusterExecutor.execute(AbstractJobClusterExecutor.java:73)atorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment.executeAsync(StreamExecutionEnvironment.java:1957)atorg.apache.flink.client.program.StreamContextEnvironment.executeAsync(StreamContextEnvironment.java:137)atorg.apache.flink.client.program.StreamContextEnvironment.execute(StreamContextEnvironment.java:76)atorg.apache.flink.streaming.api.environment.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.java:1834)atorg.apache.flink.streaming.api.scala.StreamExecutionEnvironment.execute(StreamExecutionEnvironment.scala:801)atcom.leadeon.service.bosl​ogind​tl.main(bos_login_dtl.scala:63)
at com.leadeon.service.bos_login_dtl.main(bos_login_dtl.scala)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:498)
at org.apache.flink.client.program.PackagedProgram.callMainMethod(PackagedProgram.java:355)
at org.apache.flink.client.program.PackagedProgram.invokeInteractiveModeForExecution(PackagedProgram.java:222)
at org.apache.flink.client.ClientUtils.executeProgram(ClientUtils.java:114)
at org.apache.flink.client.cli.CliFrontend.executeProgram(CliFrontend.java:812)
at org.apache.flink.client.cli.CliFrontend.run(CliFrontend.java:246)
at org.apache.flink.client.cli.CliFrontend.parseAndRun(CliFrontend.java:1054)
at org.apache.flink.client.cli.CliFrontend.lambda$main$10(CliFrontend.java:1132)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1876)
at org.apache.flink.runtime.security.contexts.HadoopSecurityContext.runSecured(HadoopSecurityContext.java:41)
at org.apache.flink.client.cli.CliFrontend.main(CliFrontend.java:1132)

2.原因:

hadoop-common依赖版本不对

        
            org.apache.hadoop
            hadoop-common

            3.1.1
            provided
        
3.具体实现步骤: 3.1pom.xml文件


    4.0.0

    com.leadeon
    bigdata
    1.0-SNAPSHOT

    jar
    
        1.8
        1.8
        2.11.12
        1.13.3
        2.8.9
        1.7.4
        UTF-8
    

    
        
            org.apache.flink
            flink-streaming-scala_2.11
            ${flink.version}
            provided
        
        
            org.apache.flink
            flink-connector-filesystem_2.11
            1.11.3
        
        
            org.apache.flink
            flink-connector-kafka_2.11
            ${flink.version}
        
        
            org.scala-lang
            scala-library
            2.11.12
            provided
        
        
            org.apache.hadoop
            hadoop-common
            3.1.1
            provided
        

    

    
    
        src/main/scala
        src/test/scala
        
            
                maven-assembly-plugin
                
                    dist
                    true
                    
                        jar-with-dependencies
                    
                
                
                    
                        make-assembly
                        package
                        
                            single
                        
                    
                
            
            
                maven-compiler-plugin
                3.8.1
                
                    1.8
                    1.8
                
            
            
                net.alchim31.maven
                scala-maven-plugin
                3.2.2
                
                    
                        scala-compile-first
                        process-resources
                        
                            compile
                        
                    
                
                
                    ${scala.version}
                    incremental
                    false
                    
                        -unchecked
                        -deprecation
                        -feature
                    
                    
                        -Xms1024m
                        -Xmx1024m
                    
                    
                        -source
                        ${java.version}
                        -target
                        ${java.version}
                        -Xlint:all,-serial,-path
                    
                
            
            
                org.antlr
                antlr4-maven-plugin
                4.7
                
                    
                        antlr
                        
                            antlr4
                        
                        none
                    
                
                
                    src/test/java
                    true
                    true
                
            
        
    



3.2自定义hdfs分区路径

注意:早一天要提早建好分区,要不了分区数据不会进去hive元数据中,数据也查询不出来。
alter table bus_login_dtl_bak2 add if not exists partition(dt=‘20220208’)
location ‘/apps/hive/datahouse/cmbh_real_log/bus_login_dtl/dt=20220208’;

package com.leadeon.utils;

import org.apache.flink.streaming.connectors.fs.Clock;
import org.apache.flink.streaming.connectors.fs.bucketing.basePathBucketer;
import org.apache.hadoop.fs.Path;

import java.io.File;
import java.text.SimpleDateFormat;
import java.util.Date;

public class HdfsbasePathBucketer extends basePathBucketer {
    private static final long serialVersionUID = 1L;
    SimpleDateFormat formatter = new SimpleDateFormat("yyyyMMdd");
    String dateString = formatter.format(new Date().getTime());
    @Override
    public Path getBucketPath(Clock clock, Path basePath, String element) {
        Path path = new Path(basePath + File.separator + "dt=" + dateString);
        return path;
    }

}
3.3flink程序(消费kafka数据到hive)
package com.leadeon.service

import com.typesafe.config.ConfigFactory
import org.apache.flink.api.scala._
import org.apache.flink.streaming.api.TimeCharacteristic
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer
import org.apache.kafka.clients.CommonClientConfigs
import org.apache.kafka.clients.consumer.ConsumerConfig
import java.io.File
import java.text.SimpleDateFormat
import java.util.{Date, Properties}

import com.leadeon.utils.HdfsbasePathBucketer
import org.apache.flink.api.common.serialization.SimpleStringSchema
import org.apache.flink.streaming.connectors.fs.bucketing.BucketingSink

object bos_login_dtl {
  def main(args: Array[String]): Unit = {
    if (args.length != 1) {
      println("usage: set application.conf file path!")
      return
    }
    val Array(brokers, kafkaTopic, group, times,parallelism,  outputHDFS) = getConf(args.head)
    val date = new SimpleDateFormat("yyyyMMdd").format(new Date)

    //1.获取执行器的环境
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    env.enableCheckpointing(5000)
    env.setParallelism(parallelism.toInt)
    env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)

    //2.kafka配置
    val props = new Properties()
    props.setProperty(CommonClientConfigs.BOOTSTRAP_SERVERS_CONFIG,brokers)
    props.setProperty(ConsumerConfig.GROUP_ID_CONFIG, group)
    props.setProperty(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG, "true")
    props.setProperty(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG, "1000")
    props.setProperty(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer")
    props.setProperty(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.StringDeserializer")
    props.setProperty(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "latest")

    //3.设置数据源
    val kafkaDataStream= env.addSource(new FlinkKafkaConsumer[String](kafkaTopic,
      new SimpleStringSchema(), props))

    //4.Storage into hdfs

    val sink = new BucketingSink[String](outputHDFS)
    //    sink.setBucketer(new DateTimeBucketer("yyyyMMdd"))
    sink.setBucketer(new HdfsbasePathBucketer)
    //每个文件最大小限制256M,达到后关闭或创建新文件// 每个文件最大小限制256M,达到后关闭或创建新文件
    sink.setBatchSize(1024 * 1024 * 256L)
    //设定批次滚动时间翻滚间隔30分钟,达到后关闭或创建新文件,和上面的`batchSize`双重检查决定
    sink.setBatchRolloverInterval(times.toLong * 1000L)
    //设定不活动桶时间阈值,超过此值便关闭文件
    sink.setInactiveBucketThreshold(3 * 60 * 1000L)
    //设定检查不活动桶的频率
    sink.setInactiveBucketCheckInterval(30 * 1000L)
    //添加sink 将数据输出到hdfs
//   kafkaDataStream.map(_.replaceAll("\|#\$", "t")).addSink(sink)
    kafkaDataStream.map(new MapOperator).addSink(sink)
    // 打印数据
    kafkaDataStream.print()
    env.execute("login_steaming")


  }

  
  def getConf(path: String): Array[String] = {
    val conf = ConfigFactory.parseFile(new File(path))
    Array(conf.getString("conf.brokers"),
      conf.getString("conf.topics"),
      conf.getString("conf.group"),
      conf.getString("conf.times"),
      conf.getString("conf.parallelism"),
      conf.getString("conf.outputHDFS")
    )
  }
}

import org.apache.flink.api.common.functions.MapFunction

class MapOperator extends MapFunction[String, String] {
  @throws[Exception]
  override def map(line: String): String = { // 转化过程,把字符串转化为大写
    val str = line.replaceAll("\|#\$", "t")
    println("处理后的数据  ************ "+str)
    str
  }
}
3.4启动程序
#!/bin/bash
export HADOOP_CLASSPATH=/usr/hdp/3.1.4.0-315/hadoop
export Hbase_CONF_DIR=/usr/hdp/3.1.4.0-315/hbase/conf
export YARN_CONF_DIR=/usr/hdp/3.1.4.0-315/hadoop-yarn/conf
/opt/flink/bin/flink run -m yarn-cluster -p 4 -yjm 1024m -ytm 4096m -ys 5 -c com.leadeon.service.bos_login_dtl /data/work/cmbh/project/flinkJob/bigdata-1.0-SNAPSHOT-jar-with-dependencies.jar /data/work/cmbh/project/flinkJob/application.conf
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