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社区首页 >专栏 >Hive+Sqoop+Mysql整合

Hive+Sqoop+Mysql整合

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Hongten
发布2019-02-26 12:49:24
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发布2019-02-26 12:49:24
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文章被收录于专栏:HongtenHongten

Hive+Sqoop+Mysql整合

在本文中,LZ随意想到了一个场景:

车,道路,监控,摄像头

即当一辆车在道路上面行驶的时候,道路上面的监控点里面的摄像头就会对车进行数据采集。

我们对采集的数据进行分析,处理,最后把结果保存到mysql数据库中供Web UI显示监控点/摄像头状态。

工作流程如下:

1.数据格式

代码语言:javascript
复制
/**
 * 产生测试数据:
 * 数据format:
 * 记录时间                 车牌号码            车速                     道路编号       监控地点        摄像头编号
 * date_time     vehicle_plate     vehicle_speed    road_id   monitor_id    camera_id
 * 
 * 中间使用'\t'隔开
 * 16/01/2019 10:20:30 SCN89000J 124 10002 20004 40007
 * 
 * 具体说明:
 * 道路编号
 * 10001 - 10100
 * 
 * 监控地点 - 在一条道路上面有2个监控点
 * 20001 - 20200
 * 
 * 摄像头编号 - 在一个监控点上面2个摄像头
 * 40001 - 40400
 * 
 * 道路:      10001                         10002
 * 监控:      20001-20002                   20003-20004
 * 摄像头:  40001-40002-40003-40004       40005-40006-40007-40008
 * 
 * 车速: 1-300。 如果大于260,则为超速行驶
 * 
 * 车牌: SCN89000J
 * 
 * 记录时间: 16/01/2019 10:20:30 
 * 
 */

2.生成测试数据

代码语言:javascript
复制
--编译运行java code
cd /root/vehicle_dir/

vi DataGenerate.java
代码语言:javascript
复制
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import java.io.OutputStreamWriter;
import java.io.PrintWriter;
import java.io.Serializable;
import java.text.SimpleDateFormat;
import java.util.ArrayList;
import java.util.Date;
import java.util.List;
import java.util.Random;
import java.util.concurrent.Callable;
import java.util.concurrent.ExecutionException;
import java.util.concurrent.ExecutorService;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.TimeUnit;

/**
 * 产生测试数据:
 * 数据format:
 * 记录时间                 车牌号码            车速                     道路编号       监控地点        摄像头编号
 * date_time     vehicle_plate     vehicle_speed    road_id   monitor_id    camera_id
 * 
 * 中间使用'\t'隔开
 * 16/01/2019 10:20:30 SCN89000J 124 10002 20004 40007
 * 
 * 具体说明:
 * 道路编号
 * 10001 - 10100
 * 
 * 监控地点 - 在一条道路上面有2个监控点
 * 20001 - 20200
 * 
 * 摄像头编号 - 在一个监控点上面2个摄像头
 * 40001 - 40400
 * 
 * 道路:      10001                         10002
 * 监控:      20001-20002                   20003-20004
 * 摄像头:  40001-40002-40003-40004       40005-40006-40007-40008
 * 
 * 车速: 1-300。 如果大于260,则为超速行驶
 * 
 * 车牌: SCN89000J
 * 
 * 记录时间: 16/01/2019 10:20:30 
 * 
 * @author Hongten
 */
public class DataGenerate {

    Integer[] roadIdArray = new Integer[Common.ROAD_NUM];

    public static void main(String[] args) {
        long begin = System.currentTimeMillis();
        DataGenerate dataGenerate = new DataGenerate();
        dataGenerate.init();
        dataGenerate.generateData();
        long end = System.currentTimeMillis();
        System.out.println("Total: " + (end - begin) + " ms");
    }

    public void init() {
        // create files
        FileUtils.createFile(Common.VEHICLE_LOG);
        FileUtils.createFile(Common.ROAD_MONITOR_CAMERA_RELATIONSHIP);

        generateRoadIds();
    }

    /**
     * 道路: 10001 10002 监控: 20001-20002 20003-20004 摄像头: 40001-40002-40003-40004
     * 40005-40006-40007-40008
     */
    public void generateRoadIds() {
        StringBuilder readMonitorCameraRelationship = new StringBuilder();
        for (int i = 0; i < Common.ROAD_NUM; i++) {
            int roadId = 10000 + (i + 1);// 10001
            roadIdArray[i] = roadId;

            int monitorB = roadId * 2;// 20002
            int monitorA = monitorB - 1;// 20001

            int cameraAB = monitorA * 2;// 40002
            int cameraAA = cameraAB - 1;// 40001

            int cameraBB = monitorB * 2;// 40004
            int cameraBA = cameraBB - 1;// 40003

            // monitorA
            // 10001 20001 40001
            // 10001 20001 40002
            readMonitorCameraRelationship.append(roadId).append(Common.SEPARATOR).append(monitorA).append(Common.SEPARATOR).append(cameraAA).append(Common.LINE_BREAK);
            readMonitorCameraRelationship.append(roadId).append(Common.SEPARATOR).append(monitorA).append(Common.SEPARATOR).append(cameraAB).append(Common.LINE_BREAK);
            // monitorB
            // 10001 20002 40003
            // 10001 20002 40004
            readMonitorCameraRelationship.append(roadId).append(Common.SEPARATOR).append(monitorB).append(Common.SEPARATOR).append(cameraBA).append(Common.LINE_BREAK);
            readMonitorCameraRelationship.append(roadId).append(Common.SEPARATOR).append(monitorB).append(Common.SEPARATOR).append(cameraBB).append(Common.LINE_BREAK);
        }
        saveData(Common.ROAD_MONITOR_CAMERA_RELATIONSHIP, readMonitorCameraRelationship.toString());
    }

    public void saveData(String pathFileName, String newContent) {
        //remove the last '\n'
        newContent = newContent.substring(0, newContent.length() - 1);
        FileUtils.saveFile(pathFileName, newContent);
    }

    public void generateData() {
        //StringBuffer可以保证线程安全
        StringBuffer contentSb = new StringBuffer();
        SimpleDateFormat simpleDateFormat_ddMMyyyy = new SimpleDateFormat(Common.DATE_FORMAT_YYYYMMDD);
        Date today = new Date();
        String date = simpleDateFormat_ddMMyyyy.format(today);
        Random random = new Random();
        
        //异常道路
        List<Integer> errorRoadIdList = new ArrayList<Integer>();
        generateErrorRoadIdList(random, errorRoadIdList);
                
        long begin = System.currentTimeMillis();
        
        //使用多线程
        ExecutorService exec = Executors.newCachedThreadPool();
        for (int i = 0; i < Common.VEHICLE_NUMBER; i++) {
            String vehiclePlate = VehiclePlateGenerateSG.generatePlate();
            //使用Future和Callable组合,可以获取到返回值
            Future<String> result = exec.submit(new GenerateVehicleLog(date, random, errorRoadIdList, vehiclePlate, roadIdArray));
            try {
                contentSb.append(result.get());
                if(i % 100 == 0){
                    System.out.println(i);
                }
                
                if(i != 0 && i % 900 == 0){
                    long end = System.currentTimeMillis();
                    System.out.println(i + " sleeping 1 seconds." + " " + (end - begin)/1000 + " s");
                    //waiting the pre-task to finish.
                    TimeUnit.SECONDS.sleep(1);
                }
            } catch (InterruptedException e) {
                e.printStackTrace();
            } catch (ExecutionException e) {
                e.printStackTrace();
            }
            //System.out.println(contentSb.toString());
        }
        exec.shutdown();
        saveData(Common.VEHICLE_LOG, contentSb.toString());
    }

    private void generateErrorRoadIdList(Random random, List<Integer> errorRoadIdList) {
        for (int x = 0; x < Common.ROAD_ERROR_NUM; x++) {
            if (errorRoadIdList.contains(roadIdArray[random.nextInt(roadIdArray.length)])) {
                generateErrorRoadIdList(random, errorRoadIdList);
            } else {
                errorRoadIdList.add(roadIdArray[random.nextInt(roadIdArray.length)]);
            }
        }
    }
}

class GenerateVehicleLog implements Callable<String>{

    StringBuffer contentSb;
    String date;
    Random random;
    List<Integer> errorRoadIdList;
    String vehiclePlate;
    Integer[] roadIdArray;
    
    public GenerateVehicleLog( String date, Random random, List<Integer> errorRoadIdList, String vehiclePlate, Integer[] roadIdArray){
        this.contentSb = new StringBuffer();
        this.date = date;
        this.random = random;
        this.errorRoadIdList = errorRoadIdList;
        this.vehiclePlate = vehiclePlate;
        this.roadIdArray = roadIdArray;
    }
    
    @Override
    public String call() throws Exception {
        return getVehicleLog(contentSb, date, random, errorRoadIdList, vehiclePlate, roadIdArray);
    }
    
    private String getVehicleLog(StringBuffer contentSb, String date, Random random, List<Integer> errorRoadIdList, String vehiclePlate, Integer[] roadIdArray) {
        // 每一辆车产生记录在100条记录以内
        // 即最多过100个监控点
        // 即最多过50条路
        // 这里可以根据需要调节
        for (int n = 0; n < random.nextInt(Common.ROAD_NUM); n++) {
            int roadId = roadIdArray[random.nextInt(roadIdArray.length)];
            Integer[] monitorIdArray = new Integer[2];
            Integer[] cameraIdArray = new Integer[2];
            boolean isAllError = false;
            int monitorId = 0;
            if (errorRoadIdList.contains(roadId)) {
                // System.out.println("find error road.... " + roadId +
                // " for vehicle : " + vehiclePlate);
                if (roadId % 2 == 0) {
                    // 监控设备全部坏掉
                    isAllError = true;
                } else {
                    // 部分坏掉
                    monitorIdArray[0] = roadId * 2 - 1;
                    monitorIdArray[1] = roadId * 2 - 1;

                    monitorId = monitorIdArray[random.nextInt(monitorIdArray.length)];

                    cameraIdArray[0] = roadId * 4 - 3;
                    cameraIdArray[1] = roadId * 4 - 2;
                }
            } else {
                monitorIdArray[0] = roadId * 2 - 1;
                monitorIdArray[1] = roadId * 2;

                monitorId = monitorIdArray[random.nextInt(monitorIdArray.length)];

                cameraIdArray[0] = monitorId * 2 - 1;
                cameraIdArray[1] = monitorId * 2;
            }

            if (!isAllError) {
                // 16/01/2019 10:20:30 SCN89000J 124 10002 20004 40007
                contentSb.append(date).append(Common.BLANK).append(StringUtils.fulfuill(String.valueOf(random.nextInt(25)))).append(Common.COLON).append(StringUtils.fulfuill(String.valueOf(random.nextInt(61)))).append(Common.COLON).append(StringUtils.fulfuill(String.valueOf(random.nextInt(61)))).append(Common.SEPARATOR);
                contentSb.append(vehiclePlate).append(Common.SEPARATOR);
                contentSb.append((random.nextInt(Common.MAX_SPEED) + 1)).append(Common.SEPARATOR);
                contentSb.append(roadId).append(Common.SEPARATOR);
                contentSb.append(monitorId).append(Common.SEPARATOR);
                contentSb.append(cameraIdArray[random.nextInt(cameraIdArray.length)]).append(Common.LINE_BREAK);
            }
        }
        return contentSb.toString();
    }
}



class FileUtils implements Serializable {

    private static final long serialVersionUID = 1L;

    public static boolean createFile(String pathFileName) {
        try {
            File file = new File(pathFileName);
            if (file.exists()) {
                System.err.println("Find file" + pathFileName + ", system will delete it now!!!");
                file.delete();
            }
            boolean createNewFile = file.createNewFile();
            System.err.println("create file " + pathFileName + " success!");
            return createNewFile;
        } catch (IOException e) {
            e.printStackTrace();
        }
        return false;
    }

    public static void saveFile(String pathFileName, String newContent) {
        FileOutputStream fos = null;
        OutputStreamWriter osw = null;
        PrintWriter pw = null;
        try {
            String content = newContent;
            File file = new File(pathFileName);
            fos = new FileOutputStream(file, true);
            osw = new OutputStreamWriter(fos, Common.CHARSETNAME_UTF_8);
            pw = new PrintWriter(osw);
            pw.write(content);
            pw.close();
            osw.close();
            fos.close();
        } catch (IOException e) {
            e.printStackTrace();
        } finally {
            if (pw != null) {
                pw.close();
            }
            if (osw != null) {
                try {
                    osw.close();
                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
            if (fos != null) {
                try {
                    fos.close();
                } catch (IOException e) {
                    e.printStackTrace();
                }
            }
        }
    }
}

class StringUtils {

    public static String fulfuill(String str) {
        if (str.length() == 1) {
            return Common.ZERO + str;
        }
        return str;
    }
}

/**
 * From wiki:
 * https://en.wikipedia.org/wiki/Vehicle_registration_plates_of_Singapore<br>
 * 
 * A typical vehicle registration number comes in the format "SKV 6201 B":<br>
 * 
 * <li>S – Vehicle class ("S", with some exceptions, stands for a private
 * vehicle since 1984)</li><br>
 * <li>KV – Alphabetical series ("I" and "O" are not used to avoid confusion
 * with "1" and "0")</li><br>
 * <li>6201 – Numerical series</li><br>
 * <li>B – Checksum letter ("F","I", "N", "O", "Q", "V" and "W" are never used
 * as checksum letters; absent on special government vehicle plates and events
 * vehicle plates)</li>
 * 
 */
class VehiclePlateGenerateSG implements Serializable {

    private static final long serialVersionUID = -8006144823705880339L;

    public static Random random = new Random();

    // 主要目的就是使得产生的数字字符不在这个list里面
    // 如果在这个list里面找到,那么需要重新产生
    private static List<String> uniqueList = new ArrayList<String>();

    public static String generatePlate() {
        // System.out.println(ALPHABETICAL_ARRAY[18]);// S
        String alphabeticalSeries = getAlphabeticalStr(Common.ALPHABETICAL_ARRAY, random) + getAlphabeticalStr(Common.ALPHABETICAL_ARRAY, random);
        // System.out.println(alphabeticalSeries);//KV

        String numbericalSeries = getNumericalSeriesStr(random);
        // System.out.println(numbericalSeries);//62010

        String checksumLetter = getChecksumLetterStr(Common.ALPHABETICAL_ARRAY, random);
        // System.out.println(checksumLetter);//B

        String singaporeVehiclePlate = Common.ALPHABETICAL_ARRAY[18] + alphabeticalSeries + numbericalSeries + checksumLetter;
        return singaporeVehiclePlate;
    }

    private static String getAlphabeticalStr(String[] ALPHABETICAL_ARRAY, Random random) {
        String alphabeticalStr = Common.ALPHABETICAL_ARRAY[random.nextInt(Common.ALPHABETICAL_ARRAY.length)];
        // "I", "O"
        if (!(alphabeticalStr.equals(Common.ALPHABETICAL_ARRAY[8]) || alphabeticalStr.equals(Common.ALPHABETICAL_ARRAY[14]))) {
            return alphabeticalStr;
        } else {
            return getAlphabeticalStr(Common.ALPHABETICAL_ARRAY, random);
        }
    }

    private static String getNumericalSeriesStr(Random random) {
        // 为了区别真实的车牌,我们把数字设置为5位
        String numericalStr = random.nextInt(10) + "" + random.nextInt(10) + "" + random.nextInt(10) + "" + random.nextInt(10) + "" + random.nextInt(10);
        if (uniqueList.contains(numericalStr)) {
            // 如果存在,则重新产生
            return getNumericalSeriesStr(random);
        } else {
            uniqueList.add(numericalStr);
            return numericalStr;
        }
    }

    private static String getChecksumLetterStr(String[] ALPHABETICAL_ARRAY, Random random) {
        String checksumLetter = ALPHABETICAL_ARRAY[random.nextInt(ALPHABETICAL_ARRAY.length)];
        // "F","I", "N", "O", "Q", "V" and "W"
        if (!(checksumLetter.equals(Common.ALPHABETICAL_ARRAY[5]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[8]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[13]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[14]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[16]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[21]) || checksumLetter.equals(Common.ALPHABETICAL_ARRAY[22]))) {
            return checksumLetter;
        } else {
            return getChecksumLetterStr(ALPHABETICAL_ARRAY, random);
        }
    }
}

class Common implements Serializable {
    private static final long serialVersionUID = 1L;

    public static String VEHICLE_LOG = "./vehicle_log";
    public static String ROAD_MONITOR_CAMERA_RELATIONSHIP = "./road_monitor_camera_relationship";

    public static final String[] ALPHABETICAL_ARRAY = new String[] { "A", "B", "C", "D", "E", "F", "G", "H", "I", "J", "K", "L", "M", "N", "O", "P", "Q", "R", "S", "T", "U", "V", "W", "X", "Y", "Z" };
    public static final String DATE_FORMAT_YYYYMMDD = "dd/MM/yyyy";
    public static final String CHARSETNAME_UTF_8 = "UTF-8";
    public static final String SEPARATOR = "\t";
    public static final String LINE_BREAK = "\n";
    public static final String BLANK = " ";
    public static final String COLON = ":";
    public static final String ZERO = "0";
    
    //车辆数
    public static final int VEHICLE_NUMBER = 100000;
    //道路数
    public static final int ROAD_NUM = 400;
    public static final int ROAD_ERROR_NUM = 8;
    //最大车速
    public static final int MAX_SPEED = 300;
}

2.1.编译执行

代码语言:javascript
复制
:wq

javac DataGenerate.java
java DataGenerate

--运行完成,会生成下面两个文件
/root/vehicle_dir/vehicle_log
/root/vehicle_dir/road_monitor_camera_relationship

2.2.车辆记录log样本

代码语言:javascript
复制
16/01/2019 14:06:44    SVM35185L    258    10295    20590    41179
16/01/2019 15:56:25    SVM35185L    110    10288    20575    41149
16/01/2019 02:22:29    SVM35185L    28    10109    20217    40436
16/01/2019 24:29:59    SSK43417H    254    10281    20562    41123
16/01/2019 07:36:54    SSK43417H    149    10124    20247    40495
16/01/2019 12:21:30    SSK43417H    196    10211    20421    40843
16/01/2019 12:42:43    SSK43417H    92    10308    20615    41230
16/01/2019 02:57:59    SDV20274X    206    10166    20332    40663
16/01/2019 11:60:17    SDV20274X    191    10372    20744    41488
16/01/2019 00:09:06    SDV20274X    197    10094    20188    40374
16/01/2019 21:18:30    SDV20274X    294    10101    20201    40401
16/01/2019 11:23:38    SDV20274X    74    10163    20325    40652
16/01/2019 04:35:16    SDV20274X    53    10077    20153    40305
16/01/2019 20:56:56    SDV20274X    31    10113    20226    40449
16/01/2019 16:50:11    SEN89218Y    58    10202    20404    40808
16/01/2019 18:34:47    SEN89218Y    113    10042    20083    40168
16/01/2019 02:25:52    SEN89218Y    35    10051    20101    40204
16/01/2019 24:08:52    SEN89218Y    77    10165    20330    40657

2.3.道路-监控-摄像头关系样本

代码语言:javascript
复制
10001    20001    40001
10001    20001    40002
10001    20002    40003
10001    20002    40004
10002    20003    40005
10002    20003    40006
10002    20004    40007
10002    20004    40008
10003    20005    40009
10003    20005    40010
10003    20006    40011
10003    20006    40012
10004    20007    40013
10004    20007    40014
10004    20008    40015
10004    20008    40016

3.在Hive中创建table并且导入数据

代码语言:javascript
复制
-- 创建table,并且把结果数据导入到Hive table里面
cd /root/vehicle_dir/

vi hive_vehicle.sql


--1.drop t_vehicle_log
drop table IF EXISTS t_vehicle_log;

--2.create t_vehicle_log
CREATE TABLE t_vehicle_log(
date_time string ,
vehicle_plate string ,
vehicle_speed int ,
road_id string ,
monitor_id string ,
camera_id string
)ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LINES TERMINATED BY '\n';

--3.load data into t_vehicle_log
load data local inpath '/root/vehicle_dir/vehicle_log' into table t_vehicle_log;

--4.drop t_road_monitor_camera_relationship
drop table IF EXISTS t_road_monitor_camera_relationship;

--5.create t_road_monitor_camera_relationship
CREATE TABLE t_road_monitor_camera_relationship(
road_id string ,
monitor_id string ,
camera_id string
)ROW FORMAT DELIMITED
FIELDS TERMINATED BY '\t'
LINES TERMINATED BY '\n';

--6.load data into t_road_monitor_camera_relationship
load data local inpath '/root/vehicle_dir/road_monitor_camera_relationship' into table t_road_monitor_camera_relationship;

--7.drop t_monitor_camera
drop table IF EXISTS t_monitor_camera;

--8.create t_monitor_camera
create table t_monitor_camera(
monitor_id string ,
cameranum int,
workingcameranum int,
notWorkingCameraNum int
)ROW FORMAT DELIMITED
FIELDS TERMINATED BY '|'
LINES TERMINATED BY '\n';

--9.load data from other table into t_monitor_camera
from (select monitor_id, count(distinct camera_id) cameraNum from t_road_monitor_camera_relationship group by monitor_id) t1 
left outer join 
(select monitor_id, NVL(count(distinct camera_id), 0) workingCameraNum from t_vehicle_log group by monitor_id) t2
on t1.monitor_id=t2.monitor_id
insert into table t_monitor_camera
select t1.monitor_id, t1.cameraNum cameraNum, NVL(t2.workingCameraNum, 0) workingCameraNum,NVL((t1.cameraNum - NVL(t2.workingCameraNum, 0)), 0) notWorkingCameraNum;

4.编写Sqoop配置文件

代码语言:javascript
复制
--配置sqoop:hive数据导入到mysql中
--注意: --export-dir /user/hive/warehouse/t_monitor_camera/ 这里的地址可以在hive中,
--通过desc formatted t_monitor_camera 查看
--Location: hdfs://mycluster/user/hive/warehouse/t_monitor_camera

cd /root/vehicle_dir/

vi hive_to_mysql_for_vehicle

export
--connect
jdbc:mysql://node1:3306/sqoop_db
--username
root
--password
'!QAZ2wsx3edc'
--table
t_hive_to_mysql_for_vehicle
-m
1
--columns
monitor_id,camera_num,working_camera_num,not_working_camera_num
--fields-terminated-by
'|'
--export-dir
/user/hive/warehouse/t_monitor_camera/

:wq

5.在Mysql中创建table

代码语言:javascript
复制
--在mysql里面创建表
mysql -u root -p 
!QAZ2wsx3edc
use sqoop_db;

--如果有则删除
DROP TABLE IF EXISTS t_hive_to_mysql_for_vehicle;

CREATE TABLE t_hive_to_mysql_for_vehicle (monitor_id VARCHAR(5), camera_num INT, working_camera_num INT, not_working_camera_num INT);

6.编写自动化可执行脚本

代码语言:javascript
复制
--编辑可执行脚本
cd /root/vehicle_dir/
vi hive_to_mysql_vehicle.sh

echo 'job begin'

cd /home/hive/bin
./hive -f /root/vehicle_dir/hive_vehicle.sql

echo 'begin to inport to mysql'

sqoop --options-file /root/vehicle_dir/hive_to_mysql_for_vehicle
echo 'done.'

:wq

7.赋予脚本可执行属性

代码语言:javascript
复制
--赋予脚本可执行属性
chmod +x hive_to_mysql_vehicle.sh

8.执行脚本

代码语言:javascript
复制
--执行脚本
./hive_to_mysql_vehicle.sh

9.结果

9.1.执行脚本前,检查mysql table

代码语言:javascript
复制
--执行脚本之前,查询t_hive_to_mysql_for_vehicle
mysql> select * from t_hive_to_mysql_for_vehicle;
Empty set (0.00 sec)

9.2.执行脚本

代码语言:javascript
复制
[root@node1 vehicle_dir]# ./hive_to_mysql_vehicle.sh 
job begin
19/01/16 01:00:53 WARN conf.HiveConf: DEPRECATED: hive.metastore.ds.retry.* no longer has any effect.  Use hive.hmshandler.retry.* instead

Logging initialized using configuration in jar:file:/root/apache-hive-0.13.1-bin/lib/hive-common-0.13.1.jar!/hive-log4j.properties
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/root/hadoop-2.5.1/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/root/apache-hive-0.13.1-bin/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
OK
Time taken: 1.432 seconds
OK
Time taken: 0.306 seconds
Copying data from file:/root/vehicle_dir/vehicle_log
Copying file: file:/root/vehicle_dir/vehicle_log
Loading data to table default.t_vehicle_log
Table default.t_vehicle_log stats: [numFiles=1, numRows=0, totalSize=121817379, rawDataSize=0]
OK
Time taken: 5.958 seconds
OK
Time taken: 0.101 seconds
OK
Time taken: 0.042 seconds
Copying data from file:/root/vehicle_dir/road_monitor_camera_relationship
Copying file: file:/root/vehicle_dir/road_monitor_camera_relationship
Loading data to table default.t_road_monitor_camera_relationship
Table default.t_road_monitor_camera_relationship stats: [numFiles=1, numRows=0, totalSize=28799, rawDataSize=0]
OK
Time taken: 0.637 seconds
OK
Time taken: 0.094 seconds
OK
Time taken: 0.071 seconds
Total jobs = 4
Launching Job 1 out of 4
Number of reduce tasks not specified. Estimated from input data size: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Job = job_1547622676146_0025, Tracking URL = http://node1:8088/proxy/application_1547622676146_0025/
Kill Command = /home/hadoop-2.5/bin/hadoop job  -kill job_1547622676146_0025
Hadoop job information for Stage-1: number of mappers: 1; number of reducers: 1
2019-01-16 01:01:29,337 Stage-1 map = 0%,  reduce = 0%
2019-01-16 01:01:40,583 Stage-1 map = 100%,  reduce = 0%, Cumulative CPU 2.06 sec
2019-01-16 01:02:27,667 Stage-1 map = 100%,  reduce = 100%, Cumulative CPU 4.65 sec
MapReduce Total cumulative CPU time: 4 seconds 650 msec
Ended Job = job_1547622676146_0025
Launching Job 2 out of 4
Number of reduce tasks not specified. Estimated from input data size: 1
In order to change the average load for a reducer (in bytes):
  set hive.exec.reducers.bytes.per.reducer=<number>
In order to limit the maximum number of reducers:
  set hive.exec.reducers.max=<number>
In order to set a constant number of reducers:
  set mapreduce.job.reduces=<number>
Starting Job = job_1547622676146_0026, Tracking URL = http://node1:8088/proxy/application_1547622676146_0026/
Kill Command = /home/hadoop-2.5/bin/hadoop job  -kill job_1547622676146_0026
Hadoop job information for Stage-4: number of mappers: 1; number of reducers: 1
2019-01-16 01:02:43,341 Stage-4 map = 0%,  reduce = 0%
2019-01-16 01:03:01,206 Stage-4 map = 100%,  reduce = 0%, Cumulative CPU 6.99 sec
2019-01-16 01:03:10,440 Stage-4 map = 100%,  reduce = 100%, Cumulative CPU 9.8 sec
MapReduce Total cumulative CPU time: 9 seconds 800 msec
Ended Job = job_1547622676146_0026
Stage-7 is selected by condition resolver.
Stage-2 is filtered out by condition resolver.
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/root/hadoop-2.5.1/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/root/apache-hive-0.13.1-bin/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
19/01/16 01:03:16 WARN conf.Configuration: file:/tmp/root/hive_2019-01-16_01-01-07_044_1858062061865079126-1/-local-10011/jobconf.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.retry.interval;  Ignoring.
19/01/16 01:03:16 WARN conf.Configuration: file:/tmp/root/hive_2019-01-16_01-01-07_044_1858062061865079126-1/-local-10011/jobconf.xml:an attempt to override final parameter: mapreduce.job.end-notification.max.attempts;  Ignoring.
19/01/16 01:03:17 WARN conf.HiveConf: DEPRECATED: hive.metastore.ds.retry.* no longer has any effect.  Use hive.hmshandler.retry.* instead
Execution log at: /tmp/root/root_20190116010101_c2813672-251f-4087-a452-9c26df2565e8.log
2019-01-16 01:03:17    Starting to launch local task to process map join;    maximum memory = 477102080
2019-01-16 01:03:18    Dump the side-table into file: file:/tmp/root/hive_2019-01-16_01-01-07_044_1858062061865079126-1/-local-10004/HashTable-Stage-5/MapJoin-mapfile01--.hashtable
2019-01-16 01:03:18    Uploaded 1 File to: file:/tmp/root/hive_2019-01-16_01-01-07_044_1858062061865079126-1/-local-10004/HashTable-Stage-5/MapJoin-mapfile01--.hashtable (20083 bytes)
2019-01-16 01:03:18    End of local task; Time Taken: 1.033 sec.
Execution completed successfully
MapredLocal task succeeded
Launching Job 4 out of 4
Number of reduce tasks is set to 0 since there's no reduce operator
Starting Job = job_1547622676146_0027, Tracking URL = http://node1:8088/proxy/application_1547622676146_0027/
Kill Command = /home/hadoop-2.5/bin/hadoop job  -kill job_1547622676146_0027
Hadoop job information for Stage-5: number of mappers: 1; number of reducers: 0
2019-01-16 01:03:28,599 Stage-5 map = 0%,  reduce = 0%
2019-01-16 01:03:41,568 Stage-5 map = 100%,  reduce = 0%, Cumulative CPU 1.83 sec
MapReduce Total cumulative CPU time: 1 seconds 830 msec
Ended Job = job_1547622676146_0027
Loading data to table default.t_monitor_camera
Table default.t_monitor_camera stats: [numFiles=1, numRows=800, totalSize=9600, rawDataSize=8800]
MapReduce Jobs Launched: 
Job 0: Map: 1  Reduce: 1   Cumulative CPU: 4.65 sec   HDFS Read: 29057 HDFS Write: 19476 SUCCESS
Job 1: Map: 1  Reduce: 1   Cumulative CPU: 9.8 sec   HDFS Read: 121817595 HDFS Write: 19212 SUCCESS
Job 2: Map: 1   Cumulative CPU: 1.83 sec   HDFS Read: 19834 HDFS Write: 9683 SUCCESS
Total MapReduce CPU Time Spent: 16 seconds 280 msec
OK
_col0    _col1    _col2    _col3
Time taken: 155.84 seconds
begin to inport to mysql
19/01/16 01:03:44 INFO sqoop.Sqoop: Running Sqoop version: 1.4.6
19/01/16 01:03:44 WARN tool.BaseSqoopTool: Setting your password on the command-line is insecure. Consider using -P instead.
19/01/16 01:03:44 INFO manager.MySQLManager: Preparing to use a MySQL streaming resultset.
19/01/16 01:03:44 INFO tool.CodeGenTool: Beginning code generation
19/01/16 01:03:45 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `t_hive_to_mysql_for_vehicle` AS t LIMIT 1
19/01/16 01:03:45 INFO manager.SqlManager: Executing SQL statement: SELECT t.* FROM `t_hive_to_mysql_for_vehicle` AS t LIMIT 1
19/01/16 01:03:45 INFO orm.CompilationManager: HADOOP_MAPRED_HOME is /home/hadoop-2.5
Note: /tmp/sqoop-root/compile/abc965816faa58aeae64d67acf60c1af/t_hive_to_mysql_for_vehicle.java uses or overrides a deprecated API.
Note: Recompile with -Xlint:deprecation for details.
19/01/16 01:03:46 INFO orm.CompilationManager: Writing jar file: /tmp/sqoop-root/compile/abc965816faa58aeae64d67acf60c1af/t_hive_to_mysql_for_vehicle.jar
19/01/16 01:03:46 INFO mapreduce.ExportJobBase: Beginning export of t_hive_to_mysql_for_vehicle
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/root/hadoop-2.5.1/share/hadoop/common/lib/slf4j-log4j12-1.7.5.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/root/hbase-0.98.9-hadoop2/lib/slf4j-log4j12-1.6.4.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.slf4j.impl.Log4jLoggerFactory]
19/01/16 01:03:47 INFO Configuration.deprecation: mapred.jar is deprecated. Instead, use mapreduce.job.jar
19/01/16 01:03:48 INFO Configuration.deprecation: mapred.reduce.tasks.speculative.execution is deprecated. Instead, use mapreduce.reduce.speculative
19/01/16 01:03:48 INFO Configuration.deprecation: mapred.map.tasks.speculative.execution is deprecated. Instead, use mapreduce.map.speculative
19/01/16 01:03:48 INFO Configuration.deprecation: mapred.map.tasks is deprecated. Instead, use mapreduce.job.maps
19/01/16 01:03:48 INFO client.RMProxy: Connecting to ResourceManager at node1/192.168.79.138:8032
19/01/16 01:03:52 INFO input.FileInputFormat: Total input paths to process : 1
19/01/16 01:03:52 INFO input.FileInputFormat: Total input paths to process : 1
19/01/16 01:03:52 INFO mapreduce.JobSubmitter: number of splits:1
19/01/16 01:03:52 INFO Configuration.deprecation: mapred.map.tasks.speculative.execution is deprecated. Instead, use mapreduce.map.speculative
19/01/16 01:03:53 INFO mapreduce.JobSubmitter: Submitting tokens for job: job_1547622676146_0028
19/01/16 01:03:53 INFO impl.YarnClientImpl: Submitted application application_1547622676146_0028
19/01/16 01:03:53 INFO mapreduce.Job: The url to track the job: http://node1:8088/proxy/application_1547622676146_0028/
19/01/16 01:03:53 INFO mapreduce.Job: Running job: job_1547622676146_0028
19/01/16 01:04:01 INFO mapreduce.Job: Job job_1547622676146_0028 running in uber mode : false
19/01/16 01:04:01 INFO mapreduce.Job:  map 0% reduce 0%
19/01/16 01:04:08 INFO mapreduce.Job:  map 100% reduce 0%
19/01/16 01:04:09 INFO mapreduce.Job: Job job_1547622676146_0028 completed successfully
19/01/16 01:04:09 INFO mapreduce.Job: Counters: 30
    File System Counters
        FILE: Number of bytes read=0
        FILE: Number of bytes written=116265
        FILE: Number of read operations=0
        FILE: Number of large read operations=0
        FILE: Number of write operations=0
        HDFS: Number of bytes read=9746
        HDFS: Number of bytes written=0
        HDFS: Number of read operations=4
        HDFS: Number of large read operations=0
        HDFS: Number of write operations=0
    Job Counters 
        Launched map tasks=1
        Rack-local map tasks=1
        Total time spent by all maps in occupied slots (ms)=5229
        Total time spent by all reduces in occupied slots (ms)=0
        Total time spent by all map tasks (ms)=5229
        Total vcore-seconds taken by all map tasks=5229
        Total megabyte-seconds taken by all map tasks=5354496
    Map-Reduce Framework
        Map input records=800
        Map output records=800
        Input split bytes=143
        Spilled Records=0
        Failed Shuffles=0
        Merged Map outputs=0
        GC time elapsed (ms)=29
        CPU time spent (ms)=1150
        Physical memory (bytes) snapshot=184467456
        Virtual memory (bytes) snapshot=902938624
        Total committed heap usage (bytes)=106954752
    File Input Format Counters 
        Bytes Read=0
    File Output Format Counters 
        Bytes Written=0
19/01/16 01:04:09 INFO mapreduce.ExportJobBase: Transferred 9.5176 KB in 21.8085 seconds (446.8896 bytes/sec)
19/01/16 01:04:09 INFO mapreduce.ExportJobBase: Exported 800 records.
done.
[root@node1 vehicle_dir]# mysql -u root -p
Enter password: 
ERROR 1045 (28000): Access denied for user 'root'@'localhost' (using password: YES)
[root@node1 vehicle_dir]# mysql -u root -p
Enter password: 
Welcome to the MySQL monitor.  Commands end with ; or \g.
Your MySQL connection id is 617
Server version: 5.7.24 MySQL Community Server (GPL)

Copyright (c) 2000, 2018, Oracle and/or its affiliates. All rights reserved.

Oracle is a registered trademark of Oracle Corporation and/or its
affiliates. Other names may be trademarks of their respective
owners.

Type 'help;' or '\h' for help. Type '\c' to clear the current input statement.

mysql> use sqoop_db;
Reading table information for completion of table and column names
You can turn off this feature to get a quicker startup with -A

Database changed
mysql> select * from t_hive_to_mysql_for_vehicle;
+------------+------------+--------------------+------------------------+
| monitor_id | camera_num | working_camera_num | not_working_camera_num |
+------------+------------+--------------------+------------------------+
| 20001      |          2 |                  2 |                      0 |
| 20002      |          2 |                  2 |                      0 |
| 20003      |          2 |                  2 |                      0 |
| 20004      |          2 |                  2 |                      0 |
| 20005      |          2 |                  2 |                      0 |
| 20006      |          2 |                  2 |                      0 |
| 20007      |          2 |                  2 |                      0 |
| 20008      |          2 |                  2 |                      0 |
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| 20734      |          2 |                  2 |                      0 |
| 20735      |          2 |                  2 |                      0 |
| 20736      |          2 |                  2 |                      0 |
| 20737      |          2 |                  2 |                      0 |
| 20738      |          2 |                  2 |                      0 |
| 20739      |          2 |                  2 |                      0 |
| 20740      |          2 |                  2 |                      0 |
| 20741      |          2 |                  2 |                      0 |
| 20742      |          2 |                  2 |                      0 |
| 20743      |          2 |                  2 |                      0 |
| 20744      |          2 |                  2 |                      0 |
| 20745      |          2 |                  2 |                      0 |
| 20746      |          2 |                  2 |                      0 |
| 20747      |          2 |                  2 |                      0 |
| 20748      |          2 |                  2 |                      0 |
| 20749      |          2 |                  2 |                      0 |
| 20750      |          2 |                  2 |                      0 |
| 20751      |          2 |                  2 |                      0 |
| 20752      |          2 |                  2 |                      0 |
| 20753      |          2 |                  2 |                      0 |
| 20754      |          2 |                  2 |                      0 |
| 20755      |          2 |                  2 |                      0 |
| 20756      |          2 |                  2 |                      0 |
| 20757      |          2 |                  2 |                      0 |
| 20758      |          2 |                  2 |                      0 |
| 20759      |          2 |                  2 |                      0 |
| 20760      |          2 |                  2 |                      0 |
| 20761      |          2 |                  2 |                      0 |
| 20762      |          2 |                  2 |                      0 |
| 20763      |          2 |                  2 |                      0 |
| 20764      |          2 |                  2 |                      0 |
| 20765      |          2 |                  2 |                      0 |
| 20766      |          2 |                  2 |                      0 |
| 20767      |          2 |                  2 |                      0 |
| 20768      |          2 |                  2 |                      0 |
| 20769      |          2 |                  2 |                      0 |
| 20770      |          2 |                  2 |                      0 |
| 20771      |          2 |                  2 |                      0 |
| 20772      |          2 |                  2 |                      0 |
| 20773      |          2 |                  2 |                      0 |
| 20774      |          2 |                  2 |                      0 |
| 20775      |          2 |                  2 |                      0 |
| 20776      |          2 |                  2 |                      0 |
| 20777      |          2 |                  2 |                      0 |
| 20778      |          2 |                  2 |                      0 |
| 20779      |          2 |                  2 |                      0 |
| 20780      |          2 |                  2 |                      0 |
| 20781      |          2 |                  2 |                      0 |
| 20782      |          2 |                  2 |                      0 |
| 20783      |          2 |                  2 |                      0 |
| 20784      |          2 |                  2 |                      0 |
| 20785      |          2 |                  2 |                      0 |
| 20786      |          2 |                  2 |                      0 |
| 20787      |          2 |                  2 |                      0 |
| 20788      |          2 |                  2 |                      0 |
| 20789      |          2 |                  2 |                      0 |
| 20790      |          2 |                  2 |                      0 |
| 20791      |          2 |                  2 |                      0 |
| 20792      |          2 |                  2 |                      0 |
| 20793      |          2 |                  2 |                      0 |
| 20794      |          2 |                  2 |                      0 |
| 20795      |          2 |                  2 |                      0 |
| 20796      |          2 |                  2 |                      0 |
| 20797      |          2 |                  2 |                      0 |
| 20798      |          2 |                  2 |                      0 |
| 20799      |          2 |                  2 |                      0 |
| 20800      |          2 |                  2 |                      0 |
+------------+------------+--------------------+------------------------+
800 rows in set (0.00 sec)

9.3.异常的监控点/摄像头情况

代码语言:javascript
复制
--异常的监控点/摄像头情况
mysql> select * from t_hive_to_mysql_for_vehicle where not_working_camera_num  > 0;
+------------+------------+--------------------+------------------------+
| monitor_id | camera_num | working_camera_num | not_working_camera_num |
+------------+------------+--------------------+------------------------+
| 20090      |          2 |                  0 |                      2 |
| 20099      |          2 |                  0 |                      2 |
| 20100      |          2 |                  0 |                      2 |
| 20130      |          2 |                  0 |                      2 |
| 20178      |          2 |                  0 |                      2 |
| 20354      |          2 |                  0 |                      2 |
| 20363      |          2 |                  0 |                      2 |
| 20364      |          2 |                  0 |                      2 |
| 20371      |          2 |                  0 |                      2 |
| 20372      |          2 |                  0 |                      2 |
| 20542      |          2 |                  0 |                      2 |
+------------+------------+--------------------+------------------------+
11 rows in set (0.00 sec)

这个时候,就可以从Mysql中查询数据,显示在我们的Web UI中。

 ========================================================

More reading,and english is important.

I'm Hongten

代码语言:javascript
复制
大哥哥大姐姐,觉得有用打赏点哦!你的支持是我最大的动力。谢谢。
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========================================================

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目录
  • Hive+Sqoop+Mysql整合
    • 工作流程如下:
      • 1.数据格式
        • 2.生成测试数据
          • 2.1.编译执行
          • 2.2.车辆记录log样本
          • 2.3.道路-监控-摄像头关系样本
        • 3.在Hive中创建table并且导入数据
          • 4.编写Sqoop配置文件
            • 5.在Mysql中创建table
              • 6.编写自动化可执行脚本
                • 7.赋予脚本可执行属性
                  • 8.执行脚本
                    • 9.结果
                      • 9.1.执行脚本前,检查mysql table
                      • 9.2.执行脚本
                      • 9.3.异常的监控点/摄像头情况
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