Hbase批量导入&批量删除

刺骨的言语ヽ痛彻心扉 2022-02-25 07:36 648阅读 0赞

Hi：

小明：sir，我遇见一个需求，根据42万手机号码段生产全量的手机号。

大牛：what，那岂不是要生成42亿多手机号。

小明：yes，而且还需要每次随机提取一千万条，第二次提取不能包含上一次的手机号。

大牛：shit，good luck。

思考时间……

大牛：管它三七二十一，一个循环跑去吧。然后提取从头开始循环然后依次随机跳过几十条数据。

小明：那得跑多久，人家明天就要。

大牛：那就用Hive的分桶，《Hive权威指南》里不是说分桶最适合采样吗~，然后采用数据放在另外一个Hive表，两个做Join进行去重。

小明：嗯，好像可以呀，大牛就是大牛。不过运营业务人员很懒，想从页面点击个按钮就想直接导出了结果。

大牛：嗯，好吧，那么我们用这个方案，先用Spark/MapReduce生产Hfile文件，一条命令直接怼到Hbase，然后根据RandomRowFilter过滤器进行样本提取，随机因子0.005f，也就是说一千条里面随机提取5个手机号，生产Csv文件流直接怼到他们浏览器上。

小明：哇，这个太棒了，但是怎么实现呢？

大牛：嗯，给我一首歌的时间~

一、CreateHfile：

object CreateHfile {
    
      def main(args: Array[String]): Unit = {
    
        val conf = new SparkConf().setAppName("CreateHfile").setMaster(args(0))
        val sc = new SparkContext(conf)
    
        val hbaseConf = HBaseConfiguration.create()
        //
        val rdd = sc.textFile(args(1))
            .flatMap(v =>{
                    val x = new javaList[String]()
                    for( a <- 1 to 9999){
                            x.add(v + "%04d".format(a))
                    }
                    x.toArray
            })
            .sortBy(v=>v.toString)
            .map(r =>(new ImmutableBytesWritable(Bytes.toBytes(r.toString)),
                new KeyValue(Bytes.toBytes(r.toString), Bytes.toBytes("phoneFamliy"), Bytes.toBytes("phoneCol"), Bytes.toBytes(1))))
    
        rdd.saveAsNewAPIHadoopFile(args(2), classOf[ImmutableBytesWritable],classOf[KeyValue],classOf[HFileOutputFormat2], hbaseConf)
        sc.stop()
    
      }
    
    }

二、生产Hfile，执行命令：

spark-submit --master yarn --class com.dw.spark.CreateHfile /home/hdfs/dp/createPhone.jar yarn hdfs://xxx.xxx.xxx.xxx:8020/user/Phone.txt hdfs://xxx.xxx.xxx.xxx:8020/user/phoneout0401\_cre/

三、创建HBASE表：

create 'dp\_phone\_42yi', \{NAME => 'phoneFamliy', VERSIONS => 5\}

四、怼到HBASE，执行命令：

hbase org.apache.hadoop.hbase.mapreduce.LoadIncrementalHFiles /user/phoneout0401\_cre dp\_phone\_42yi

五、验证奇迹的时候到了：

scan 'dp\_phone\_42yi2',\{LIMIT=>100\}

六、随机提取一千万条：

import com.typesafe.config.Config;
    import com.typesafe.config.ConfigFactory;
    import org.apache.hadoop.conf.Configuration;
    import org.apache.hadoop.hbase.Cell;
    import org.apache.hadoop.hbase.HBaseConfiguration;
    import org.apache.hadoop.hbase.TableName;
    import org.apache.hadoop.hbase.client.*;
    import org.apache.hadoop.hbase.filter.Filter;
    import org.apache.hadoop.hbase.filter.RandomRowFilter;
    import org.apache.hadoop.hbase.util.Bytes;
    
    import java.io.BufferedWriter;
    import java.io.File;
    import java.io.FileWriter;
    import java.io.IOException;
    import java.util.ArrayList;
    import java.util.List;
    
    /**
     * https://blog.csdn.net/u013870094/article/details/80091256
     * Created by geo on 2019/3/29. */
    public class HbaseService {
        private final Config config = ConfigFactory.load().getConfig("main");
        private static Connection conn = null;
    
    
        public HbaseService() {
            Configuration conf = HBaseConfiguration.create();
            conf.set("hbase.zookeeper.quorum", config.getString("hbase_zookeeper_quorum"));
            conf.set("hbase.rootdir", config.getString("hbase_rootdir"));
            try {
                conn = ConnectionFactory.createConnection(conf);
            } catch (IOException e) {
                e.printStackTrace();
            }
        }
    
        /**
         16，RandomRowFilter
         参数小于0时一条查不出大于1值会返回所有，而想取随机行的话有效区间为0~1，值代表取到的几率
         */
        public void RandomRowFilter(String tableName,String output) throws Exception {
            List<String> phoneList = new ArrayList<String>();
            Long nun=0L;
            Table table = conn.getTable(TableName.valueOf(tableName));
            //该构造参数0-1之间,如果为负数全部过滤,大于1全部通过 0.2f表的该行数据20%的概率通过
            Filter filter = new RandomRowFilter(Float.parseFloat(config.getString("random")));
            Scan scan = new Scan();
            scan.setFilter(filter);
            scan.setMaxResultSize(Integer.parseInt(config.getString("maxResultSize")));
            ResultScanner results = table.getScanner(scan);
            for (Result result:results) {
                for (Cell cell : result.rawCells()) {
    //                String f=Bytes.toString(cell.getFamilyArray(),cell.getFamilyOffset(),cell.getFamilyLength());
    //                String col= Bytes.toString(cell.getQualifierArray(),cell.getQualifierOffset(),cell.getQualifierLength()) ;
    //                String v=Bytes.toString(cell.getValueArray(), cell.getValueOffset(), cell.getValueLength());
                    String r=Bytes.toString(cell.getQualifierArray(),cell.getRowOffset(),cell.getRowLength()) ;
    
                    nun++;
                    System.out.println(nun) ;
                    phoneList.add(r);
                }
    
                if(nun >= Integer.parseInt(config.getString("phoneCount"))) break;
                if(phoneList.size() > 10000){
                    writeFileContext(phoneList,output);
                    delPhoneList(table,phoneList);
                    phoneList.clear();
                }
            }
            writeFileContext(phoneList,output);
            delPhoneList(table,phoneList);
            table.close();
            conn.close();
    
            File fileOK = new File(output + "phonelist.txt_OK");
            //如果没有文件就创建
            if (!fileOK.isFile()) {
                fileOK.createNewFile();
            }
        }
    
        private void delPhoneList(Table table,List<String> phoneList)throws Exception{
            List<Delete> deleteList = new ArrayList<Delete>() ;
            for (String phone:phoneList){
                deleteList.add(new Delete(Bytes.toBytes(phone))) ;
            }
            table.delete(deleteList);
        }
        /**
         * 将list按行写入到txt文件中
         * @param strings phonelist
         * @param path 输出路径
         * @throws Exception 异常
         */
        private void writeFileContext(List<String>  strings, String path) throws Exception {
            File file = new File(path + "phonelist.txt");
            //如果没有文件就创建
            if (!file.isFile()) {
                file.createNewFile();
            }
            BufferedWriter writer = new BufferedWriter(new FileWriter(file, true));
            for (String phone:strings){
                writer.write(phone + "\n");
            }
            writer.close();
        }
    }

入口：

public class Application {
    
        public static void main(String[] args)throws Exception {
            HbaseService hbaseService = new HbaseService();
            String tableName = args[0];
            String output = args[1] ;
            hbaseService.RandomRowFilter(tableName,output);
        }
    }

大牛：现在可以了吧？

小明：他们又提了个需求，想从42亿全量手机号里删掉咱们存量的3亿手机号，还得您老来给个方案。

大牛：嗯原理一样，往着看。

DeleteHfile：

import java.util.{ArrayList => javaList}
    
    import org.apache.hadoop.hbase.io.ImmutableBytesWritable
    import org.apache.hadoop.hbase.mapreduce.HFileOutputFormat2
    import org.apache.hadoop.hbase.util.Bytes
    import org.apache.hadoop.hbase.{HBaseConfiguration, KeyValue}
    import org.apache.spark.{SparkConf, SparkContext}
    
    /**
     * Created by geo on 2019/3/27. */
    object DeleteHfile {
    
      def main(args: Array[String]): Unit = {
    
        val conf = new SparkConf().setAppName("CreateHfile").setMaster(args(0))
        val sc = new SparkContext(conf)
    
        val hbaseConf = HBaseConfiguration.create()
        //
        val rdd = sc.textFile(args(1))
            .flatMap(v =>{
                    val x = new javaList[String]()
                    for( a <- 1 to 9999){
                            x.add(v + "%04d".format(a))
                    }
                    x.toArray
            })
            .sortBy(v=>v.toString)
            .map(r =>(new ImmutableBytesWritable(Bytes.toBytes(r.toString)),
                new KeyValue(Bytes.toBytes(r.toString), Bytes.toBytes("phoneFamliy"), Bytes.toBytes("phoneCol"), System.currentTimeMillis(),KeyValue.Type.DeleteColumn)))
    
        rdd.saveAsNewAPIHadoopFile(args(2), classOf[ImmutableBytesWritable],classOf[KeyValue],classOf[HFileOutputFormat2], hbaseConf)
        sc.stop()
    
      }
    
    }

大牛：然后和上面一样，怼到HBASE里面就行。

小明：得了您内，弱弱地问一句，能把pom文件贴出来吗？

大牛：嗯、可以，但是你要根据自己的spark和scala版本找响应的jar啊，如果有jar包冲突，就maven看一下jar依赖，快捷键ctrl+alt+shift+u，find一下就知道了。

pom

<?xml version="1.0" encoding="UTF-8"?>
    <project xmlns="http://maven.apache.org/POM/4.0.0"
             xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
             xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
        <modelVersion>4.0.0</modelVersion>
    
        <groupId>geo.bigdata</groupId>
        <artifactId>dw</artifactId>
        <version>1.0-SNAPSHOT</version>
    
        <properties>
            <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
            <scala.version>2.10.5</scala.version>
            <spark.version>1.6.3</spark.version>
        </properties>
    
        <dependencies>
            <dependency>
                <groupId>org.apache.hadoop</groupId>
                <artifactId>hadoop-common</artifactId>
                <version>2.6.5</version>
                <exclusions>
                    <exclusion>
                        <groupId>javax.servlet</groupId>
                        <artifactId>servlet-api</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet.jsp</groupId>
                        <artifactId>jsp-api</artifactId>
                    </exclusion>
                </exclusions>
            </dependency>
            <dependency>
                <groupId>org.apache.hbase</groupId>
                <artifactId>hbase-server</artifactId>
                <version>1.1.2</version>
                
                <exclusions>
                    <exclusion>
                        <groupId>commons-logging</groupId>
                        <artifactId>commons-logging</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>log4j</groupId>
                        <artifactId>log4j</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet</groupId>
                        <artifactId>servlet-api</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet.jsp</groupId>
                        <artifactId>jsp-api</artifactId>
                    </exclusion>
    
                </exclusions>
            </dependency>
    
            <dependency>
                <groupId>org.apache.hbase</groupId>
                <artifactId>hbase-client</artifactId>
                <version>1.4.8</version>
                
                <exclusions>
                    <exclusion>
                        <groupId>commons-logging</groupId>
                        <artifactId>commons-logging</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>log4j</groupId>
                        <artifactId>log4j</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet</groupId>
                        <artifactId>servlet-api</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet.jsp</groupId>
                        <artifactId>jsp-api</artifactId>
                    </exclusion>
                </exclusions>
            </dependency>
            
            <dependency>
                <groupId>org.apache.spark</groupId>
                <artifactId>spark-core_2.10</artifactId>
                <version>${spark.version}</version>
                
                <exclusions>
                    <exclusion>
                        <artifactId>slf4j-log4j12</artifactId>
                        <groupId>org.slf4j</groupId>
                    </exclusion>
                    <exclusion>
                        <artifactId>slf4j-api</artifactId>
                        <groupId>org.slf4j</groupId>
                    </exclusion>
                    <exclusion>
                        <groupId>javax.servlet</groupId>
                        <artifactId>servlet-api</artifactId>
                    </exclusion>
                    <exclusion>
                        <groupId>org.eclipse.jetty.orbit</groupId>
                        <artifactId>javax.servlet</artifactId>
                    </exclusion>
                </exclusions>
            </dependency>
            <dependency>
            <groupId>javax.servlet</groupId>
            <artifactId>javax.servlet-api</artifactId>
            <version>3.0.1</version>
            </dependency>
            
            
            <dependency>
                <groupId>org.scala-lang</groupId>
                <artifactId>scala-library</artifactId>
                <version>${scala.version}</version>
            </dependency>
    
            <dependency>
                <groupId>com.thoughtworks.paranamer</groupId>
                <artifactId>paranamer</artifactId>
                <version>2.8</version>
            </dependency>
        </dependencies>
        <build>
            <plugins>
                <plugin>
                    <groupId>net.alchim31.maven</groupId>
                    <artifactId>scala-maven-plugin</artifactId>
                    <version>3.2.2</version>
                    <executions>
                        <execution>
                            <id>eclipse-add-source</id>
                            <goals>
                                <goal>add-source</goal>
                            </goals>
                        </execution>
                        <execution>
                            <id>scala-compile-first</id>
                            <phase>process-resources</phase>
                            <goals>
                                <goal>compile</goal>
                            </goals>
                        </execution>
                        <execution>
                            <id>scala-test-compile-first</id>
                            <phase>process-test-resources</phase>
                            <goals>
                                <goal>testCompile</goal>
                            </goals>
                        </execution>
                    </executions>
                    <configuration>
                        <scalaVersion>${scala.version}</scalaVersion>
                        <args>
                            <arg>-unchecked</arg>
                            <arg>-deprecation</arg>
                            <arg>-feature</arg>
                        </args>
                    </configuration>
                </plugin>
                <plugin>
                    <artifactId>maven-assembly-plugin</artifactId>
                    <configuration>
                        <appendAssemblyId>false</appendAssemblyId>
                        <descriptorRefs>
                            <descriptorRef>jar-with-dependencies</descriptorRef>
                        </descriptorRefs>
                        <archive>
                            <manifest>
                                
                                <mainClass>com.geotmt.dw.spark.CreateHfile</mainClass>
                            </manifest>
                        </archive>
                    </configuration>
                    <executions>
                        <execution>
                            <id>make-assembly</id>
                            <phase>package</phase>
                            <goals>
                                <goal>assembly</goal>
                            </goals>
                        </execution>
                    </executions>
                </plugin>
                
                <plugin>
                    <groupId>org.apache.maven.plugins</groupId>
                    
                    <artifactId>maven-compiler-plugin</artifactId>
                    <version>3.3</version>
                    <configuration>
                        <source>1.7</source>
                        <target>1.7</target>
                        
                        <encoding>utf-8</encoding>
                    </configuration>
                </plugin>
            </plugins>
        </build>
    </project>

pom