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Flink通过将sql 讲 hbase 的数据导入到Mysql中

Flink通过将sql 讲 hbase 的数据导入到Mysql中

作者: wudl | 来源:发表于2021-12-15 00:33 被阅读0次

1. 场景， 将hbase 表中的数据导入到mysql 中

·官网参考·
https://nightlies.apache.org/flink/flink-docs-release-1.12/dev/table/connectors/jdbc.html
https://nightlies.apache.org/flink/flink-docs-release-1.12/dev/table/connectors/hbase.html

2. 需要添加的pom 文件

<?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>org.wudlflink12</groupId>
    <artifactId>wudl-flink-12</artifactId>
    <version>1.0-SNAPSHOT</version>

    <!-- 指定仓库位置，依次为aliyun、apache和cloudera仓库 -->
    <repositories>
        <repository>
            <id>aliyun</id>
            <url>http://maven.aliyun.com/nexus/content/groups/public/</url>
        </repository>
        <repository>
            <id>apache</id>
            <url>https://repository.apache.org/content/repositories/snapshots/</url>
        </repository>
        <repository>
            <id>cloudera</id>
            <url>https://repository.cloudera.com/artifactory/cloudera-repos/</url>
        </repository>

            <repository>
                <id>spring-plugin</id>
                <url>https://repo.spring.io/plugins-release/</url>
            </repository>

    </repositories>

    <properties>
        <encoding>UTF-8</encoding>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <java.version>1.8</java.version>
        <scala.version>2.11</scala.version>
        <flink.version>1.12.0</flink.version>
    </properties>
    <dependencies>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-elasticsearch7_2.11</artifactId>
            <version>1.12.3</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-hbase-2.2_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>


        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-jdbc_2.11</artifactId>
            <version>1.10.3</version>
        </dependency>

        <!--依赖Scala语言-->
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>2.12.11</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.12</artifactId>
            <version>${flink.version}</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-scala_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-scala_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-scala-bridge_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <!-- blink执行计划,1.11+默认的-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-blink_2.12</artifactId>
            <version>${flink.version}</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-common</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-cep_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <!-- flink连接器-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-sql-connector-kafka_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-csv</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-json</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <!-- <dependency>
           <groupId>org.apache.flink</groupId>
           <artifactId>flink-connector-filesystem_2.12</artifactId>
           <version>${flink.version}</version>
       </dependency>-->
        <!--<dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-jdbc_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>-->
        <!--<dependency>
              <groupId>org.apache.flink</groupId>
              <artifactId>flink-parquet_2.12</artifactId>
              <version>${flink.version}</version>
         </dependency>-->
        <!--<dependency>
            <groupId>org.apache.avro</groupId>
            <artifactId>avro</artifactId>
            <version>1.9.2</version>
        </dependency>
        <dependency>
            <groupId>org.apache.parquet</groupId>
            <artifactId>parquet-avro</artifactId>
            <version>1.10.0</version>
        </dependency>-->


        <dependency>
            <groupId>org.apache.bahir</groupId>
            <artifactId>flink-connector-redis_2.11</artifactId>
            <version>1.0</version>
            <exclusions>
                <exclusion>
                    <artifactId>flink-streaming-java_2.11</artifactId>
                    <groupId>org.apache.flink</groupId>
                </exclusion>
                <exclusion>
                    <artifactId>flink-runtime_2.11</artifactId>
                    <groupId>org.apache.flink</groupId>
                </exclusion>
<!--                <exclusion>-->
<!--                    <artifactId>flink-core</artifactId>-->
<!--                    <groupId>org.apache.flink</groupId>-->
<!--                </exclusion>-->
                <exclusion>
                    <artifactId>flink-java</artifactId>
                    <groupId>org.apache.flink</groupId>
                </exclusion>
            </exclusions>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-hive_2.12</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-metastore</artifactId>
            <version>2.1.0</version>
            <exclusions>
                <exclusion>
                    <artifactId>hadoop-hdfs</artifactId>
                    <groupId>org.apache.hadoop</groupId>
                </exclusion>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.apache.hive</groupId>
            <artifactId>hive-exec</artifactId>
            <version>2.1.0</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-shaded-hadoop-2-uber</artifactId>
            <version>2.7.5-10.0</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-log4j12</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>2.1.0</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
                <exclusion>
                    <artifactId>slf4j-log4j12</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.38</version>
            <!--<version>8.0.20</version>-->
        </dependency>

        <!-- 高性能异步组件：Vertx-->
        <dependency>
            <groupId>io.vertx</groupId>
            <artifactId>vertx-core</artifactId>
            <version>3.9.0</version>
        </dependency>
        <dependency>
            <groupId>io.vertx</groupId>
            <artifactId>vertx-jdbc-client</artifactId>
            <version>3.9.0</version>
        </dependency>
        <dependency>
            <groupId>io.vertx</groupId>
            <artifactId>vertx-redis-client</artifactId>
            <version>3.9.0</version>
        </dependency>

        <!-- 日志 -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.7</version>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
            <scope>runtime</scope>
        </dependency>

        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.44</version>
        </dependency>

        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <version>1.18.2</version>
            <scope>provided</scope>
        </dependency>

        <!-- 参考：https://blog.csdn.net/f641385712/article/details/84109098-->
        <!--<dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-collections4</artifactId>
            <version>4.4</version>
        </dependency>-->
        <!--<dependency>
            <groupId>org.apache.thrift</groupId>
            <artifactId>libfb303</artifactId>
            <version>0.9.3</version>
            <type>pom</type>
            <scope>provided</scope>
         </dependency>-->
        <!--<dependency>
           <groupId>com.google.guava</groupId>
           <artifactId>guava</artifactId>
           <version>28.2-jre</version>
       </dependency>-->


        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>3.1.3</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>3.1.3</version>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
                <exclusion>
                    <artifactId>slf4j-log4j12</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
            </exclusions>
        </dependency>

    </dependencies>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.0.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>

</project>

3. 建表

3.1 mysql 建表

需要注意 建表的编码： utf8mb4


CREATE TABLE `wudlHbase` (
  `id` int(11) DEFAULT NULL,
  `name` varchar(64) CHARACTER SET latin1 DEFAULT NULL,
  `address` varchar(64) CHARACTER SET latin1 DEFAULT NULL,
  `age` int(11) DEFAULT NULL
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4
然后给列加编码： 
ALTER TABLE `wudlHbase` MODIFY NAME VARCHAR(64) CHARACTER SET utf8;
ALTER TABLE `wudlHbase` MODIFY id VARCHAR(64) CHARACTER SET utf8;
ALTER TABLE `wudlHbase` MODIFY address VARCHAR(64) CHARACTER SET utf8;
ALTER TABLE `wudlHbase` MODIFY age VARCHAR(64) CHARACTER SET utf8;
ALTER TABLE `wudlHbase` MODIFY NAME VARCHAR(20) CHARACTER SET utf8;

3.2 hbase 表结构

hbase(main):003:0> desc 'wudlHbase'
Table wudlHbase is ENABLED                                                                                                                                                 
wudlHbase                                                                                                                                                                  
COLUMN FAMILIES DESCRIPTION                                                                                                                                                
{NAME => 'cf', VERSIONS => '1', EVICT_BLOCKS_ON_CLOSE => 'false', NEW_VERSION_BEHAVIOR => 'false', KEEP_DELETED_CELLS => 'FALSE', CACHE_DATA_ON_WRITE => 'false', DATA_BLOC
K_ENCODING => 'NONE', TTL => 'FOREVER', MIN_VERSIONS => '0', REPLICATION_SCOPE => '0', BLOOMFILTER => 'ROW', CACHE_INDEX_ON_WRITE => 'false', IN_MEMORY => 'false', CACHE_B
LOOMS_ON_WRITE => 'false', PREFETCH_BLOCKS_ON_OPEN => 'false', COMPRESSION => 'NONE', BLOCKCACHE => 'true', BLOCKSIZE => '65536'}                                          
1 row(s)
Took 0.0686 seconds                                                                                                                                                        
hbase(main):004:0>

表数据

hbase(main):002:0> scan 'wudlHbase'
ROW                                      COLUMN+CELL                                                                                                           
 10000                                   column=cf:address, timestamp=1638633405738, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x810                               
 10000                                   column=cf:age, timestamp=1638633405738, value=10                                                                      
 10000                                   column=cf:name, timestamp=1638633405738, value=hdfs0                                                                  
 10001                                   column=cf:address, timestamp=1638633405741, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x811                               
 10001                                   column=cf:age, timestamp=1638633405741, value=11                                                                      
 10001                                   column=cf:name, timestamp=1638633405741, value=hdfs1                                                                  
 10002                                   column=cf:address, timestamp=1638633405743, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x812                               
 10002                                   column=cf:age, timestamp=1638633405743, value=12                                                                      
 10002                                   column=cf:name, timestamp=1638633405743, value=hdfs2                                                                  
 10003                                   column=cf:address, timestamp=1638633405746, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x813                               
 10003                                   column=cf:age, timestamp=1638633405746, value=13                                                                      
 10003                                   column=cf:name, timestamp=1638633405746, value=hdfs3                                                                  
 10004                                   column=cf:address, timestamp=1638633405748, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x814                               
 10004                                   column=cf:age, timestamp=1638633405748, value=14                                                                      
 10004                                   column=cf:name, timestamp=1638633405748, value=hdfs4                                                                  
 10005                                   column=cf:address, timestamp=1638633405750, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x815                               
 10005                                   column=cf:age, timestamp=1638633405750, value=15                                                                      
 10005                                   column=cf:name, timestamp=1638633405750, value=hdfs5                                                                  
 10006                                   column=cf:address, timestamp=1638633405752, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x816                               
 10006                                   column=cf:age, timestamp=1638633405752, value=16                                                                      
 10006                                   column=cf:name, timestamp=1638633405752, value=hdfs6                                                                  
 10007                                   column=cf:address, timestamp=1638633405753, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x817                               
 10007                                   column=cf:age, timestamp=1638633405753, value=17                                                                      
 10007                                   column=cf:name, timestamp=1638633405753, value=hdfs7                                                                  
 10008                                   column=cf:address, timestamp=1638633405755, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x818                               
 10008                                   column=cf:age, timestamp=1638633405755, value=18                                                                      
 10008                                   column=cf:name, timestamp=1638633405755, value=hdfs8                                                                  
 10009                                   column=cf:address, timestamp=1638633405757, value=\xE5\xB9\xBF\xE4\xB8\x9C\xE7\x9C\x819                               
 10009                                   column=cf:age, timestamp=1638633405757, value=19                                                                      
 10009                                   column=cf:name, timestamp=1638633405757, value=hdfs9                                                                  
10 row(s)
Took 0.1297 seconds

4. 代码实现：

package com.wudl.flink.source;

import com.wudl.flink.bean.HbaseUser;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableResult;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;
import org.apache.flink.util.CloseableIterator;

import java.util.ArrayList;
import java.util.List;
import java.util.function.Consumer;

/**
 * @author ：wudl
 * @date ：Created in 2021-12-14 23:28
 * @description：
 * @modified By：
 * @version: 1.0
 */

public class HbaseSouce {

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

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        TableResult tableResult = tableEnv.executeSql(
                "CREATE TABLE testWudlHbase (" +
                        " rowkey STRING," +
                        " cf ROW<name STRING,address STRING,age STRING>," +
                        " PRIMARY KEY (rowkey) NOT ENFORCED" +
                        " ) WITH (" +
                        " 'connector' = 'hbase-2.2' ," +
                        " 'table-name' = 'wudlHbase' ," +
                        " 'zookeeper.quorum' = '192.168.1.161:2181'" +
                        " )");

        TableResult outPutTable = tableEnv.executeSql("CREATE TABLE  MySqlwudlHbase (" +
                "id INT ," +
                "name STRING ," +
                "address STRING , " +
                "age INT " +
                ") " +
                "WITH (" +
                "'connector' = 'jdbc'," +
                "'url' = 'jdbc:mysql://192.168.1.180:3306/test?useUnicode=true&characterEncoding=UTF-8'," +
                "'table-name' = 'wudlHbase'," +
                " 'username' = 'root'," +
                " 'password' = '123456'" +
                " )");

//        tableEnv.executeSql(" SELECT  cast(rowkey as INT) id, cf.name name ,cf.address address , cast(cf.age as  BIGINT) age FROM testWudlHbase");
        tableEnv.executeSql(" insert into  MySqlwudlHbase SELECT  cast(rowkey as INT) id, cf.name name ,cf.address address , cast(cf.age as  INT) age FROM testWudlHbase");

5. 查看结果

HbaseTo-mysql.png

6. 读取hbase 的数据：

package com.wudl.flink.source;

import com.wudl.flink.bean.HbaseUser;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.table.api.Table;
import org.apache.flink.table.api.TableResult;
import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;
import org.apache.flink.types.Row;
import org.apache.flink.util.CloseableIterator;

import java.util.ArrayList;
import java.util.List;
import java.util.function.Consumer;

/**
 * @author ：wudl
 * @date ：Created in 2021-12-14 23:28
 * @description：
 * @modified By：
 * @version: 1.0
 */

public class HbaseSouce {

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

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);

        TableResult tableResult = tableEnv.executeSql(
                "CREATE TABLE testWudlHbase (" +
                        " rowkey STRING," +
                        " cf ROW<name STRING,address STRING,age STRING>," +
                        " PRIMARY KEY (rowkey) NOT ENFORCED" +
                        " ) WITH (" +
                        " 'connector' = 'hbase-2.2' ," +
                        " 'table-name' = 'wudlHbase' ," +
                        " 'zookeeper.quorum' = '192.168.1.161:2181'" +
                        " )");

        TableResult outPutTable = tableEnv.executeSql("CREATE TABLE  MySqlwudlHbase (" +
                "id INT ," +
                "name STRING ," +
                "address STRING , " +
                "age INT " +
                ") " +
                "WITH (" +
                "'connector' = 'jdbc'," +
                "'url' = 'jdbc:mysql://192.168.1.180:3306/test?useUnicode=true&characterEncoding=UTF-8'," +
                "'table-name' = 'wudlHbase'," +
                " 'username' = 'root'," +
                " 'password' = '123456'" +
                " )");

//        tableEnv.executeSql(" SELECT  cast(rowkey as INT) id, cf.name name ,cf.address address , cast(cf.age as  BIGINT) age FROM testWudlHbase");
//        tableEnv.executeSql(" insert into  MySqlwudlHbase SELECT  cast(rowkey as INT) id, cf.name name ,cf.address address , cast(cf.age as  INT) age FROM testWudlHbase");
        // 相当于 scan
        Table table = tableEnv.sqlQuery("SELECT * FROM testWudlHbase");
        // 查询的结果
        TableResult executeResult = table.execute();
        // 获取查询结果
        CloseableIterator<Row> collect = executeResult.collect();
        // 输出 (执行print或者下面的 Consumer之后，数据就被消费了。两个只能留下一个)
//        executeResult.print();
        List<HbaseUser> hbaseUsers = new ArrayList<>();
        collect.forEachRemaining(new Consumer<Row>() {
            @Override
            public void accept(Row row) {
                String field0 = String.valueOf(row.getField(0));
                String cl = String.valueOf(row.getField(1));
                String[] hUser = cl.split(",");
                hbaseUsers.add(new HbaseUser(hUser[0].toString(),hUser[1].toString()));
            }
        });
        System.out.println("................");

        for(HbaseUser um : hbaseUsers){
            System.out.println(um);
        }
    }
}
hbase 读取数据.png

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