hadoop学习之(MapReduce、Pig、hive)

学习背景:

基于美国民航航班的历年数据(1987年--2008年),开发MapReduce、Pig、hive 应用程序计算其中某一年各个航班的飞行数据(飞行架次、飞行距离);

MapReduce项目:

1.编写MapReduce项目;

hadoop学习之(MapReduce、Pig、hive)_第1张图片

2.将数据文件上传到hadoop;

 3.可以看看有没有上传成功,也可以在eclipse中查看;hadoop学习之(MapReduce、Pig、hive)_第2张图片

 4.启动MapReduce项目,对项目进行配置;

hadoop学习之(MapReduce、Pig、hive)_第3张图片

5.我们可以导出flightweekDist.jar 文件,并将其运行在hadoop上;

 6.可以到自己的输出路径去查看结果了。

是不是很简单[手动狗头]

Pig项目:

1.当然是编写pig脚本了

里面用到的和sql语句都很像,学过数据库的应该问题不大。hadoop学习之(MapReduce、Pig、hive)_第4张图片

解释一下,load 数据后,stream的目的;

有兴趣的小伙伴可以去来了解一下 stream 的用途,有过滤、去重、排序、分组,反正很多,很复杂。那句话的用途就是筛掉原数据中的表头部分。

后面的语句不解释了,不知道的看书。

2.然后我们就可以愉快的执行脚本了; 

hadoop学习之(MapReduce、Pig、hive)_第5张图片

 看到 success 就可以了。

3.直接 hadoop fs -cat 查看结果。

hive项目:

hive就比较有难度了,因为最后还要把结果写入到 mysql 中。

1.上来直接写代码;

很简单,都是jdbc的东西,javaSE大家都搞过。

注意:记得启动hiveserver

hadoop学习之(MapReduce、Pig、hive)_第6张图片

 2.然后就可以跑了,sell中会打印日志信息,会跑一会,可以看看日志,这样就知道程序再跑而不是卡了,哈哈。

hadoop学习之(MapReduce、Pig、hive)_第7张图片

小提示:

如果大家在启动了hiveserver后,还需要用到终端的话,可以ctrl + z 后 输入 bg 就可以挂起了。(大佬教的,哈哈哈);

最麻烦最麻烦的地方终于来了。

使用udf 函数 将 hive 运行结果写入到 mysql 中;(我要是不把函数放出来我会不会被骂)

1.添加 jar 包(hive-contrib-0.9.0-cdh4.1.2.jarmysql-connector-java-5.1.38.jar);

 

2.编写udf函数打包成jar包导出。(大概长这个样子)

hadoop学习之(MapReduce、Pig、hive)_第8张图片

3.打包导出后,就是创建函数了。

注:函数要每次进入都需要创建的,要是经常需要的话,可以把这个写入到配置文件中,具体的我就不会了。

hive>select dboutput('jdbc:mysql://192.168.1.100/hive','hive','mysql','INSERT INTO flightinfodistance(flightnumber,distance) VALUES (?,?)',flightnumber,distance) from flightinfodistance;

这句话比较重要,我们来分析一下哈(从左到右

'dboutput' 是函数名;

'192.168.1.100' 是主机ip;

'hive' 是mysql数据库名:

'hive' 是mysql数据库账号;

mysql是mysql数据库密码;

'flightinfodistance'是mysql数据库名;

(flightnumber,distance)是mysql 数据库字段;

flightnumber,distance 是hive表中字段;

flightinfodistance是hive表名;

执行这句话就行了,可以去自己的mysql数据库中查看一下哈。

---------------------------------------分割线------------------------------------------

今天刚刚知道hive要把数据写到 本地mysql 中,我直接 jj,没办法还得搞啊。

疯狂浏览csdn,发现不行,然后找了我朋友,(一个大佬),然后请教了人家。

得到了一个办法 ----- 用springboot 通过 jdbc 连接 hive,写到本地mysql。

我直呼 tql,tql,tql。

 1.编写实体类

hadoop学习之(MapReduce、Pig、hive)_第9张图片

hadoop学习之(MapReduce、Pig、hive)_第10张图片

2.编写controller类,将数据查询出来放到结果集中,通过service层将数据写入到数据库 

hadoop学习之(MapReduce、Pig、hive)_第11张图片

hadoop学习之(MapReduce、Pig、hive)_第12张图片

4.service层代码

hadoop学习之(MapReduce、Pig、hive)_第13张图片

 5.配置hive 和 spring 

hadoop学习之(MapReduce、Pig、hive)_第14张图片

hadoop学习之(MapReduce、Pig、hive)_第15张图片

6.然后我们就可以愉快的运行了

 我们可以在hiveserver的启动那里看到运行的过程,对了记得数据库提前建表哈

 注:1.记得关掉防火墙

        2.开启hadoop

        3.离开安全模式

        4.启动hiveserver

 这是几个比较常见的问题了(这个代码太多了,我就不放了 [ 狗头 ] )

含泪上代码:

MapReduce;

package com.ssh.flight;

import java.io.BufferedReader;
import java.io.File;
import java.io.FileReader;
import java.io.FileWriter;
import java.io.IOException;
import java.util.ArrayList;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapreduce.Job;
import org.apache.hadoop.mapreduce.Mapper;
import org.apache.hadoop.mapreduce.Reducer;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
import org.apache.hadoop.util.GenericOptionsParser;
import org.mockito.asm.tree.IntInsnNode;

public class FlightWeekDist {

	//
	public static class FlightNumMapper extends
			Mapper {
		private final static IntWritable one = new IntWritable(1);
		private Text dateofWeek = new Text();

		public void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			String[] fields = value.toString().split(",");
			try {
				int year = Integer.parseInt(fields[0]); // filter first raw
			} catch (NumberFormatException e) {
				return;
			}
			dateofWeek.set(fields[3]); // date of week
			context.write(dateofWeek, one);
		}
	}

	//
	public static class FlightMilesMapper extends
			Mapper {
		private IntWritable Miles = new IntWritable();
		private Text FlightNum = new Text();

		public void map(Object key, Text value, Context context)
				throws IOException, InterruptedException {
			String[] fields = value.toString().split(",");
			try {
				int year = Integer.parseInt(fields[0]); // filter first raw
			} catch (NumberFormatException e) {
				return;
			}
			String flight = fields[8] + fields[9];
			FlightNum.set(flight); // class name
			int miles = 0;
			try {
				miles = Integer.parseInt(fields[18]); // filter first raw
			} catch (NumberFormatException e) {
			}
			Miles.set(miles);
			context.write(FlightNum, Miles);
		}
	}

	//
	public static class FlightSumReducer extends
			Reducer {
		private IntWritable result = new IntWritable();

		public void reduce(Text key, Iterable values,
				Context context) throws IOException, InterruptedException {
			int sum = 0;
			for (IntWritable val : values) {
				sum += val.get();
			}
			result.set(sum);
			context.write(key, result);
		}
	}

	//
	private static void removeOutputPath(Configuration conf, String output1,
			String output2) throws IOException {
		FileSystem hdfs = FileSystem.get(conf);
		Path path = new Path(output1);
		hdfs.delete(path, true);

		path = new Path(output2);
		hdfs.delete(path, true);
	}

	//
	private static Job createFlightNumJob(Configuration conf, String input,
			String output) throws IOException {
		Job job = new Job(conf, "Flight Numbers");
		job.setJarByClass(FlightWeekDist.class);

		job.setMapperClass(FlightNumMapper.class);
		job.setCombinerClass(FlightSumReducer.class);
		job.setReducerClass(FlightSumReducer.class);

		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);

		FileInputFormat.addInputPath(job, new Path(input));
		FileOutputFormat.setOutputPath(job, new Path(output));

		return job;
	}

	private static Job createFlightMilesJob(Configuration conf, String input,
			String output) throws IOException {
		Job job = new Job(conf, "Flight Milse");
		job.setJarByClass(FlightWeekDist.class);

		job.setMapperClass(FlightMilesMapper.class);
		job.setCombinerClass(FlightSumReducer.class);
		job.setReducerClass(FlightSumReducer.class);

		job.setOutputKeyClass(Text.class);
		job.setOutputValueClass(IntWritable.class);

		FileInputFormat.addInputPath(job, new Path(input));
		FileOutputFormat.setOutputPath(job, new Path(output));

		return job;
	}

    //此处以后代码,是将结果写入到html文件中的
	public static void transHDFSfile2local(Configuration conf, String src,
			String dst) {
		FileSystem hdfs;
		try {
			hdfs = FileSystem.get(conf);
			Path path_src = new Path(src + "/part-r-00000");
			Path path_dst = new Path(dst);
			hdfs.copyToLocalFile(path_src, path_dst);
			hdfs.close();
			System.out.println("File copy success");
		} catch (IOException e) {
			// TODO Auto-generated catch block
			e.printStackTrace();
			System.out.println("copy failed:" + e.getMessage());
		}
	}

	public static ArrayList readFile(String path) {
		File file = new File(path);
		BufferedReader reader = null;
		ArrayList lines = new ArrayList();
		try {
			reader = new BufferedReader(new FileReader(file));
			String tempString = null;
			int line = 1;
	
			while ((tempString = reader.readLine()) != null) {
				// ines.add(tempString.substring(0,
				// tempString.lastIndexOf('	')));
				// System.out.println(tempString.substring(0,
				// tempString.lastIndexOf('	')));
				// System.out.println(tempString.substring(tempString.lastIndexOf('	')+1));
				lines.add(tempString.substring(0, tempString.lastIndexOf('	')));
				lines.add(tempString.substring(tempString.lastIndexOf('	') + 1));
			}
			reader.close();
		} catch (IOException e) {
			e.printStackTrace();
		} finally {
			if (reader != null) {
				try {
					reader.close();
				} catch (IOException e1) {
				}
			}
		}
		// System.out.println("lines:");
		// for (int i = 0; i < lines.size(); i++) {
		// System.out.println(lines.get(i));
		// }
		return lines;
	}

	public static void writeFile(String path, ArrayList strs) {
		try {
			
			FileWriter writer = new FileWriter(path, true);
			int m = 0;
			for (int i = 0; i < strs.size(); i++) {
				if (m == 0) {
					writer.write("" + '\n');
				}
				writer.write("" + strs.get(i) + "" + '\n');
				m++;
				if (m == 2) {
					writer.write("" + '\n');
					m = 0;
				}
			}
			writer.close();
		} catch (IOException e) {
			e.printStackTrace();
		}
	}

	public static void writeFileFromOtherFile(String from, String dst) {
		try {
			File from_file = new File(from);
			FileWriter writer = new FileWriter(dst, true);
			BufferedReader reader = null;
			reader = new BufferedReader(new FileReader(from_file));
			String tempString = null;
			
			while ((tempString = reader.readLine()) != null) {
				writer.write(tempString+'\n');
			}
			reader.close();
			writer.close();
		} catch (IOException e) {
			e.printStackTrace();
		}
	}

	public static void transTxT2HTML(String txt_src, String html_src) {
		writeFile(html_src, readFile(txt_src));
	}

	//
	public static void main(String[] args) throws Exception {
		// hadoop jar flightcountjar.jar
		// org.hebeu.hadoop.flightdist.FlightWeekDist ./flightcount/1987-all.csv
		// ./flightcount/output1 ./flightcount/output2

		 Configuration conf = new Configuration();
		 String[] otherArgs = new GenericOptionsParser(conf, args)
		 .getRemainingArgs();
		 if (otherArgs.length != 3) {
		 System.err.println("Usage: ScoreAnalysis   ");
		 System.exit(2);
		 }
		 removeOutputPath(conf, otherArgs[1], otherArgs[2]);
		 Job job = createFlightNumJob(conf, otherArgs[0], otherArgs[1]);
		 job.waitForCompletion(true);
		 job = createFlightMilesJob(conf, otherArgs[0], otherArgs[2]);
		 job.waitForCompletion(true);
		 
		 // copy files to local
		 transHDFSfile2local(conf, "/home/hoodoop/flightcount/output1",
		 "/home/hoodoop/flight_data/week_flight.dat");
		 transHDFSfile2local(conf, "/home/hoodoop/flightcount/output2",
		 "/home/hoodoop/flight_data/distance_flight.dat");


		writeFileFromOtherFile("/home/hoodoop/html_format/before.dat", "/home/hoodoop/test.html");
		transTxT2HTML("/home/hoodoop/flight_data/week_flight.dat",
				"/home/hoodoop/test.html");
		writeFileFromOtherFile("/home/hoodoop/html_format/middle.dat", "/home/hoodoop/test.html");
		transTxT2HTML("/home/hoodoop/flight_data/distance_flight.dat",
				"/home/hoodoop/test.html");
		writeFileFromOtherFile("/home/hoodoop/html_format/last.dat", "/home/hoodoop/test.html");
	}

}

 pig;

records = LOAD '1987-all.csv' USING PigStorage(',') AS
(Year:int,Month:int,DayofMonth:int,DayOfWeek:int,DepTime:int,CRSDepTime:int,ArrTime:int,CRSArrTime:int,UniqueCarrier:chararray,FlightNum:chararray,TailNum:int,ActualElapsedTime:int,CRSElapsedTime:int,AirTime:int,ArrDelay:int,DepDelay:int,Origin:chararray,Dest:chararray,Distance:int,TaxiIn:chararray,TaxiOut:chararray,Cancelled:chararray,CancellationCode:chararray,Diverted:chararray,CarrierDelay:chararray,WeatherDelay:chararray,NASDelay:chararray,SecurityDelay:chararray,LateAircraftDelay:chararray);

flight_without_first_row = STREAM records THROUGH `tail -n +2` AS (Year:int,Month:int,DayofMonth:int,DayOfWeek:int,DepTime:int,CRSDepTime:int,ArrTime:int,CRSArrTime:int,UniqueCarrier:chararray,FlightNum:chararray,TailNum:int,ActualElapsedTime:int,CRSElapsedTime:int,AirTime:int,ArrDelay:int,DepDelay:int,Origin:chararray,Dest:chararray,Distance:int,TaxiIn:chararray,TaxiOut:chararray,Cancelled:chararray,CancellationCode:chararray,Diverted:chararray,CarrierDelay:chararray,WeatherDelay:chararray,NASDelay:chararray,SecurityDelay:chararray,LateAircraftDelay:chararray);

rmf week_flight_sort;
week_sorts = Group flight_without_first_row BY DayOfWeek;

week_sort = FOREACH week_sorts GENERATE group,COUNT($1);

STORE week_sort INTO 'week_flight_sort';


rmf flight_distances_statistices;
flight_distances= Group flight_without_first_row BY CONCAT(UniqueCarrier,FlightNum);

flight_distance = FOREACH flight_distances GENERATE group,SUM($1.Distance);

STORE flight_distance INTO 'flight_distances_statistices';

 hive;

package hive;

import java.sql.Connection;

import java.sql.DriverManager;

import java.sql.ResultSet;

import java.sql.Statement;

public class HiveJdbcTest {

    private static final String driverName = "org.apache.hadoop.hive.jdbc.HiveDriver";

    private static final String HOST = "192.168.1.100:10021";

    private static final String URL = "jdbc:hive://" + HOST + "/default";

    public static void main(String[] args) throws Exception {

        Class.forName(driverName);

        Connection conn = DriverManager.getConnection(URL, "", "");

        Statement stmt = conn.createStatement();
 
        String hql = "";

        ResultSet res = null;  

        hql = "insert overwrite table flightinfosort select DayOfWeek,count(*) from FlightInfo1987 group by DayOfWeek ";
        
        stmt.execute(hql);
       
        hql = "insert overwrite table flightinfodistance select concat(UniqueCarrier,FlightNum),sum(Distance) from FlightInfo1987 group by concat(UniqueCarrier,FlightNum)";

        stmt.execute(hql);

        res.close();

        stmt.close();

        conn.close();
    }
}

udf 函数GenericUDFDBOutput; 

package org.apache.Hadoop.hive;


import java.sql.Connection;
import java.sql.DriverManager;
import java.sql.PreparedStatement;
import java.sql.SQLException;

import org.apache.commons.logging.Log;
import org.apache.commons.logging.LogFactory;
import org.apache.hadoop.hive.ql.exec.Description;
import org.apache.hadoop.hive.ql.exec.UDFArgumentTypeException;
import org.apache.hadoop.hive.ql.metadata.HiveException;
import org.apache.hadoop.hive.ql.udf.UDFType;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDF;
import org.apache.hadoop.hive.ql.udf.generic.GenericUDFUtils;
import org.apache.hadoop.hive.serde.Constants;
import org.apache.hadoop.hive.serde2.objectinspector.ObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.PrimitiveObjectInspector;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.PrimitiveObjectInspectorFactory;
import org.apache.hadoop.hive.serde2.objectinspector.primitive.StringObjectInspector;
import org.apache.hadoop.io.IntWritable;

 


/**
* GenericUDFDBOutput is designed to output data directly from Hive to a JDBC
* datastore. This UDF is useful for exporting small to medium summaries that
* have a unique key.
*
* Due to the nature of hadoop, individual mappers, reducers or entire jobs can
* fail. If a failure occurs a mapper or reducer may be retried. This UDF has no
* way of detecting failures or rolling back a transaction. Consequently, you
* should only only use this to export to a table with a unique key. The unique
* key should safeguard against duplicate data.
*
* Use hive's ADD JAR feature to add your JDBC Driver to the distributed cache,
* otherwise GenericUDFDBoutput will fail.
*/
@Description(name = "dboutput",
value = "_FUNC_(jdbcstring,username,password,preparedstatement,[arguments])"
+ " - sends data to a jdbc driver",
extended = "argument 0 is the JDBC connection string\n"
+ "argument 1 is the user name\n"
+ "argument 2 is the password\n"
+ "argument 3 is an SQL query to be used in the PreparedStatement\n"
+ "argument (4-n) The remaining arguments must be primitive and are "
+ "passed to the PreparedStatement object\n")
@UDFType(deterministic = false)
public class GenericUDFDBOutput extends GenericUDF {
private static final Log LOG = LogFactory
.getLog(GenericUDFDBOutput.class.getName());

private transient ObjectInspector[] argumentOI;
private transient Connection connection = null;
private String url;
private String user;
private String pass;
private final IntWritable result = new IntWritable(-1);

/**
* @param arguments
* argument 0 is the JDBC connection string argument 1 is the user
* name argument 2 is the password argument 3 is an SQL query to be
* used in the PreparedStatement argument (4-n) The remaining
* arguments must be primitive and are passed to the
* PreparedStatement object
*/
@Override
public ObjectInspector initialize(ObjectInspector[] arguments)
throws UDFArgumentTypeException {
argumentOI = arguments;

// this should be connection url,username,password,query,column1[,columnn]*
for (int i = 0; i < 4; i++) {
if (arguments[i].getCategory() == ObjectInspector.Category.PRIMITIVE) {
PrimitiveObjectInspector poi = ((PrimitiveObjectInspector) arguments[i]);

if (!(poi.getPrimitiveCategory() == PrimitiveObjectInspector.PrimitiveCategory.STRING)) {
throw new UDFArgumentTypeException(i,
"The argument of function should be \""
+ Constants.STRING_TYPE_NAME + "\", but \""
+ arguments[i].getTypeName() + "\" is found");
}
}
}
for (int i = 4; i < arguments.length; i++) {
if (arguments[i].getCategory() != ObjectInspector.Category.PRIMITIVE) {
throw new UDFArgumentTypeException(i,
"The argument of function should be primative" + ", but \""
+ arguments[i].getTypeName() + "\" is found");
}
}

return PrimitiveObjectInspectorFactory.writableIntObjectInspector;
}

/**
* @return 0 on success -1 on failure
*/
@Override
public Object evaluate(DeferredObject[] arguments) throws HiveException {

url = ((StringObjectInspector) argumentOI[0])
.getPrimitiveJavaObject(arguments[0].get());
user = ((StringObjectInspector) argumentOI[1])
.getPrimitiveJavaObject(arguments[1].get());
pass = ((StringObjectInspector) argumentOI[2])
.getPrimitiveJavaObject(arguments[2].get());

try {
connection = DriverManager.getConnection(url, user, pass);
} catch (SQLException ex) {
LOG.error("Driver loading or connection issue", ex);
result.set(2);
}

if (connection != null) {
try {

PreparedStatement ps = connection
.prepareStatement(((StringObjectInspector) argumentOI[3])
.getPrimitiveJavaObject(arguments[3].get()));
for (int i = 4; i < arguments.length; ++i) {
PrimitiveObjectInspector poi = ((PrimitiveObjectInspector) argumentOI[i]);
ps.setObject(i - 3, poi.getPrimitiveJavaObject(arguments[i].get()));
}
ps.execute();
ps.close();
result.set(0);
} catch (SQLException e) {
LOG.error("Underlying SQL exception", e);
result.set(1);
} finally {
try {
connection.close();
} catch (Exception ex) {
LOG.error("Underlying SQL exception during close", ex);
}
}
}

return result;
}

@Override
public String getDisplayString(String[] children) {
StringBuilder sb = new StringBuilder();
sb.append("dboutput(");
if (children.length > 0) {
sb.append(children[0]);
for (int i = 1; i < children.length; i++) {
sb.append(",");
sb.append(children[i]);
}
}
sb.append(")");
return sb.toString();
}

}

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