Strom 与mysql整合+与hdfs整合

Storm 与mysql整合

代码目录结构如下：

DataSpout

package com.gec.demo.stormToMysql;

import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;

import java.util.Map;
import java.util.Random;

public class DataSpout extends BaseRichSpout {
    private  static  String[] words=new String[]{
        "hadoop","yarn","mapreduce"
    };
    private  static  int  _id=0;
    private  SpoutOutputCollector collector;
    @Override
    public void open(Map map, TopologyContext topologyContext, SpoutOutputCollector spoutOutputCollector) {
        this.collector=spoutOutputCollector;
    }

    @Override
    public void nextTuple() {
        this.collector.emit(new Values(_id++,words[new Random().nextInt(words.length)]));
    }

    @Override
    public void declareOutputFields(OutputFieldsDeclarer outputFieldsDeclarer) {
        outputFieldsDeclarer.declare(new Fields("_id","word"));
    }
}

JdbcInsertBoltMain

package com.gec.demo.stormToMysql;

import com.google.common.collect.Maps;
import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.generated.AlreadyAliveException;
import org.apache.storm.generated.AuthorizationException;
import org.apache.storm.generated.InvalidTopologyException;
import org.apache.storm.jdbc.bolt.JdbcInsertBolt;
import org.apache.storm.jdbc.common.ConnectionProvider;
import org.apache.storm.jdbc.common.HikariCPConnectionProvider;
import org.apache.storm.jdbc.mapper.JdbcMapper;
import org.apache.storm.jdbc.mapper.SimpleJdbcMapper;
import org.apache.storm.topology.TopologyBuilder;

import java.util.Map;

public class JdbcInsertBoltMain {
    public static void main(String[] args) throws InvalidTopologyException, AuthorizationException, AlreadyAliveException {
        Map hikariConfigMap = Maps.newHashMap();
        hikariConfigMap.put("dataSourceClassName","com.mysql.jdbc.jdbc2.optional.MysqlDataSource");
        hikariConfigMap.put("dataSource.url", "jdbc:mysql://hadoop-001:3306/storm_db");
        hikariConfigMap.put("dataSource.user","root");
        hikariConfigMap.put("dataSource.password","123456");
        ConnectionProvider connectionProvider = new HikariCPConnectionProvider(hikariConfigMap);
        String tableName="t_word";
        JdbcMapper simpleJdbcMapper=new SimpleJdbcMapper(tableName,connectionProvider);
        JdbcInsertBolt userPersistanceBolt = new JdbcInsertBolt(connectionProvider, simpleJdbcMapper)
                .withInsertQuery("insert into t_word values (?,?)")
                .withQueryTimeoutSecs(30);


        TopologyBuilder builder = new TopologyBuilder();
        builder.setSpout("dataspout",new DataSpout());
        //添加我们storm与jdbc整合的bolt
        builder.setBolt("userPersistanceBolt" ,userPersistanceBolt).localOrShuffleGrouping("dataspout");

        Config config = new Config();
        if(null  != args && args.length >0){
            StormSubmitter.submitTopology(args[0],config,builder.createTopology());
        }else{
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology("JdbcInsertBoltMain",config,builder.createTopology());
        }
    }
}

效果图如下：

Storm 与hdfs整合

代码目录结构如下：

DataSpout

package com.gec.demo.stormtohdfs;

import org.apache.storm.spout.SpoutOutputCollector;
import org.apache.storm.task.TopologyContext;
import org.apache.storm.topology.OutputFieldsDeclarer;
import org.apache.storm.topology.base.BaseRichSpout;
import org.apache.storm.tuple.Fields;
import org.apache.storm.tuple.Values;

import java.util.Map;
import java.util.Random;

public class DataSpout extends BaseRichSpout {
    private SpoutOutputCollector collector;
    private static String datas[]=new String[]{
            "hello","world","java","hadoop"
    };


    @Override
    public void open(Map conf, TopologyContext context, SpoutOutputCollector collector) {

        this.collector=collector;

    }

    /*
     * 循环调用
     * */
    @Override
    public void nextTuple() {

        //生成此数据
        String data=datas[new Random().nextInt(datas.length)];
        //发送数据到下游组件
        collector.emit(new Values(data));

    }

    /**
     * 此方法是对发送数据进行声明
     * */
    @Override
    public void declareOutputFields(OutputFieldsDeclarer declarer) {

        declarer.declare(new Fields("word"));

    }
}

StromHdfsMain

package com.gec.demo.stormtohdfs;

import org.apache.storm.Config;
import org.apache.storm.LocalCluster;
import org.apache.storm.StormSubmitter;
import org.apache.storm.generated.AlreadyAliveException;
import org.apache.storm.generated.AuthorizationException;
import org.apache.storm.generated.InvalidTopologyException;
import org.apache.storm.hdfs.bolt.HdfsBolt;
import org.apache.storm.hdfs.bolt.format.DefaultFileNameFormat;
import org.apache.storm.hdfs.bolt.format.DelimitedRecordFormat;
import org.apache.storm.hdfs.bolt.format.FileNameFormat;
import org.apache.storm.hdfs.bolt.format.RecordFormat;
import org.apache.storm.hdfs.bolt.rotation.FileRotationPolicy;
import org.apache.storm.hdfs.bolt.rotation.FileSizeRotationPolicy;
import org.apache.storm.hdfs.bolt.sync.CountSyncPolicy;
import org.apache.storm.hdfs.bolt.sync.SyncPolicy;
import org.apache.storm.topology.TopologyBuilder;
import org.apache.storm.tuple.Tuple;

public class StromHdfsMain {
    public static void main(String[] args) throws InvalidTopologyException, AuthorizationException, AlreadyAliveException {
       // use "|" instead of ","  for field delimiter
        RecordFormat format=new DelimitedRecordFormat()
                .withFieldDelimiter("|");
        /**
         * 文件的控制策略，使用两种方式，第一种：数据条数的多少
         * 第二种：文件的内容大小
         */
        // sync the filesystem after every 1k tuples
        SyncPolicy syncPolicy=new CountSyncPolicy(1000);
        //rotate files when they reach 5 MB
        FileRotationPolicy rotationPolicy=new FileSizeRotationPolicy(5.0f, FileSizeRotationPolicy.Units.MB) ;
        FileNameFormat fileNameFormat=new DefaultFileNameFormat()
                .withPath("/stormToHdfs/");
        HdfsBolt hdfsBolt=new HdfsBolt()
                .withFsUrl("hdfs://hadoop-001:9000")
                .withFileNameFormat(fileNameFormat)
                .withRecordFormat(format)
                .withRotationPolicy(rotationPolicy)
                .withSyncPolicy(syncPolicy);
        TopologyBuilder topologyBuilder=new TopologyBuilder();
        topologyBuilder.setSpout("dataSpout",new DataSpout());
        topologyBuilder.setBolt("hdfsBolt",hdfsBolt).localOrShuffleGrouping("dataSpout");
        Config config  = new Config();
        if(args !=null && args.length >0){
            StormSubmitter.submitTopology(args[0],config,topologyBuilder.createTopology());
        }else{
            LocalCluster cluster = new LocalCluster();
            cluster.submitTopology("stormToHdfs",config,topologyBuilder.createTopology());

        }
    }
}

效果图如下：

Strom 与mysql整合+与hdfs整合

原文：https://www.cnblogs.com/Transkai/p/10909090.html