【Flink-Kafka-To-Hive】使用 Flink 实现 Kafka 数据写入 Hive_kakfa+flink+hive

作者：木道寻08 | 2024-07-30 16:14:50

踩

kakfa+flink+hive

【Flink-Kafka-To-Hive】使用 Flink 实现 Kafka 数据写入 Hive

1）导入相关依赖
2）代码实现

需求描述：

1、数据从 Kafka 写入 Hive。

2、相关配置存放于 Mysql 中，通过 Mysql 进行动态读取。

3、此案例中的 Kafka 是进行了 Kerberos 安全认证的，如果不需要自行修改。

4、Flink 集成 Kafka 写入 Hive 需要进行 checkpoint 才能落盘至 HDFS。

5、先在 Hive 中创建表然后动态获取 Hive 的表结构。

6、Kafka 数据为 Json 格式，通过 FlatMap 扁平化处理后，根据表结构封装到 Row 中后完成写入。

7、写入时转换成临时视图模式，利用 Flink-Sql 实现数据写入。

8、本地测试时 Hive 相关文件要放置到 resources 目录下。

9、本地测试时可以编辑 resources.flink_backup_local.yml 通过 ConfigTools.initConf 方法获取配置。

1）导入相关依赖

这里的依赖比较冗余，大家可以根据各自需求做删除或保留。

<?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>example.cn.test</groupId>
    <artifactId>kafka2hive</artifactId>
    <version>1.0.0</version>

    <properties>
        <hbase.version>2.3.3</hbase.version>
        <hadoop.version>3.1.1</hadoop.version>
        <spark.version>3.0.2</spark.version>
        <scala.version>2.12.10</scala.version>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <flink.version>1.14.0</flink.version>
        <scala.binary.version>2.12</scala.binary.version>
        <target.java.version>1.8</target.java.version>
        <maven.compiler.source>${target.java.version}</maven.compiler.source>
        <maven.compiler.target>${target.java.version}</maven.compiler.target>
        <log4j.version>2.17.2</log4j.version>
        <hadoop.version>3.1.2</hadoop.version>
        <hive.version>3.1.2</hive.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>gaei.cn.x5l.bigdata.common</groupId>
            <artifactId>x5l-bigdata-common</artifactId>
            <version>1.1-SNAPSHOT</version>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-core</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-slf4j-impl</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-api</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.flink/flink-dist -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-dist_2.12</artifactId>
            <version>1.14.0-csa1.7.0.0</version>
            <scope>provided</scope>
            <exclusions>
                <exclusion>
                    <groupId>org.slf4j</groupId>
                    <artifactId>slf4j-log4j12</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.jyaml</groupId>
            <artifactId>jyaml</artifactId>
            <version>1.3</version>
        </dependency>
        <dependency>
            <groupId>gaei.cn.x5l</groupId>
            <artifactId>tsp-gb-decode</artifactId>
            <version>1.0.0</version>
            <exclusions>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-core</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-api</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-slf4j-impl</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.44</version>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>gaei.cn.x5l.flink.common</groupId>
            <artifactId>x5l-flink-common</artifactId>
            <version>1.2-SNAPSHOT</version>
            <scope>compile</scope>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-api</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-core</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-api</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-slf4j-impl</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-1.2-api</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <!-- Flink Dependency -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-hive_2.12</artifactId>
            <version>1.14.0</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.flink/flink-shaded-hadoop-3 -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-shaded-hadoop-3</artifactId>
            <version>3.1.1.7.2.8.0-224-9.0</version>
            <scope>provided</scope>
            <exclusions>
                <exclusion>
                    <artifactId>slf4j-log4j12</artifactId>
                    <groupId>org.slf4j</groupId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-core</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-api</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>org.apache.logging.log4j</groupId>
                    <artifactId>log4j-slf4j-impl</artifactId>
                </exclusion>
                <exclusion>
                    <groupId>log4j</groupId>
                    <artifactId>log4j</artifactId>
                </exclusion>
            </exclusions>
        </dependency>
        <dependency>
            <groupId>cn.hutool</groupId>
            <artifactId>hutool-all</artifactId>
            <version>5.8.10</version>
        </dependency>
        <dependency>
            <groupId>com.alibaba.ververica</groupId>
            <artifactId>flink-connector-mysql-cdc</artifactId>
            <version>1.4.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-jdbc_2.11</artifactId>
            <version>1.11.6</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-sql-connector-kafka_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <!-- 基础依赖  开始-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <!-- 基础依赖  结束-->
        <!-- TABLE  开始-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-java-bridge_${scala.binary.version}</artifactId>
            <version>1.14.0</version>
            <scope>provided</scope>
        </dependency>
        <!-- 使用 hive sql时注销，其他时候可以放开 -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-common</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-cep_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <!-- TABLE  结束-->
        <!-- sql  开始-->
        <!-- sql解析 开始 -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-json</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-csv</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <!-- sql解析 结束 -->
        <!-- sql连接 kafka -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-sql-connector-kafka_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <!-- sql  结束-->
        <!-- 检查点 -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-state-processor-api_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>commons-lang</groupId>
            <artifactId>commons-lang</artifactId>
            <version>2.5</version>
            <scope>compile</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-runtime-web_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <!-- 本地监控任务 结束 -->
        <!-- DataStream 开始 -->
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-slf4j-impl</artifactId>
            <version>${log4j.version}</version>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-api</artifactId>
            <version>${log4j.version}</version>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.logging.log4j</groupId>
            <artifactId>log4j-core</artifactId>
            <version>${log4j.version}</version>
            <scope>runtime</scope>
        </dependency>
        <!-- hdfs -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>3.3.1</version>
        </dependency>
        <!-- 重点，容易被忽略的jar -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-auth</artifactId>
            <version>${hadoop.version}</version>
        </dependency>
        <!-- rocksdb_2 -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <!-- 其他 -->
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.1.23</version>
        </dependency>
        <dependency>
            <groupId>org.projectlombok</groupId>
            <artifactId>lombok</artifactId>
            <version>1.16.18</version>
            <scope>provided</scope>
        </dependency>
            <!-- kafka2mongo 离线任务 -->
            <dependency>
                <groupId>org.mongodb</groupId>
                <artifactId>mongodb-driver</artifactId>
                <version>3.12.6</version>
            </dependency>
    </dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-shade-plugin</artifactId>
                <version>3.0.0</version>
                <executions>
                    <execution>
                        <phase>package</phase>
                        <goals>
                            <goal>shade</goal>
                        </goals>
                        <configuration>
                            <createDependencyReducedPom>false</createDependencyReducedPom>
                            <artifactSet>
                                <excludes>
                                    <exclude>org.apache.flink:force-shading</exclude>
                                    <exclude>com.google.code.findbugs:jsr305</exclude>
                                    <exclude>org.slf4j:*</exclude>
                                    <exclude>org.apache.logging.log4j:*</exclude>
                                    <exclude>org.apache.flink:flink-runtime-web_2.11</exclude>
                                </excludes>
                            </artifactSet>
                            <filters>
                                <filter>
                                    <artifact>*:*</artifact>
                                    <excludes>
                                        <exclude>META-INF/*.SF</exclude>
                                        <exclude>META-INF/*.DSA</exclude>
                                        <exclude>META-INF/*.RSA</exclude>
                                    </excludes>
                                </filter>
                            </filters>
                            <transformers>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                    <mainClass>com.owp.flink.kafka.KafkaSourceDemo</mainClass>
                                </transformer>
                                <!-- flink sql 需要  -->
                                <!-- The service transformer is needed to merge META-INF/services files -->
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer"/>
                                <!-- ... -->
                            </transformers>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>

        <pluginManagement>
            <plugins>
                <!-- This improves the out-of-the-box experience in Eclipse by resolving some warnings. -->
                <plugin>
                    <groupId>org.eclipse.m2e</groupId>
                    <artifactId>lifecycle-mapping</artifactId>
                    <version>1.0.0</version>
                    <configuration>
                        <lifecycleMappingMetadata>
                            <pluginExecutions>
                                <pluginExecution>
                                    <pluginExecutionFilter>
                                        <groupId>org.apache.maven.plugins</groupId>
                                        <artifactId>maven-shade-plugin</artifactId>
                                        <versionRange>[3.0.0,)</versionRange>
                                        <goals>
                                            <goal>shade</goal>
                                        </goals>
                                    </pluginExecutionFilter>
                                    <action>
                                        <ignore/>
                                    </action>
                                </pluginExecution>
                                <pluginExecution>
                                    <pluginExecutionFilter>
                                        <groupId>org.apache.maven.plugins</groupId>
                                        <artifactId>maven-compiler-plugin</artifactId>
                                        <versionRange>[3.1,)</versionRange>
                                        <goals>
                                            <goal>testCompile</goal>
                                            <goal>compile</goal>
                                        </goals>
                                    </pluginExecutionFilter>
                                    <action>
                                        <ignore/>
                                    </action>
                                </pluginExecution>
                            </pluginExecutions>
                        </lifecycleMappingMetadata>
                    </configuration>
                </plugin>
            </plugins>
        </pluginManagement>

    </build>
    <repositories>
        <repository>
            <id>cdh.releases.repo</id>
            <url>https://repository.cloudera.com/artifactory/libs-release-local/</url>
            <name>Releases Repository</name>
        </repository>
    </repositories>
</project>
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438

2）代码实现

2.1.resources

2.1.1.appconfig.yml

mysql.url: "jdbc:mysql://1.1.1.1:3306/test?useSSL=false"
mysql.username: "test"
mysql.password: "123456"
mysql.driver: "com.mysql.jdbc.Driver"
1
2
3
4

2.1.2.log4j.properties

log4j.rootLogger=info, stdout
log4j.appender.stdout=org.apache.log4j.ConsoleAppender
log4j.appender.stdout.layout=org.apache.log4j.PatternLayout
log4j.appender.stdout.layout.ConversionPattern=%-4r [%t] %-5p %c %x - %m%n
1
2
3
4

2.1.3.log4j2.xml

<?xml version="1.0" encoding="UTF-8"?>
<configuration monitorInterval="5">
    <Properties>
        <property name="LOG_PATTERN" value="%date{HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n" />
        <property name="LOG_LEVEL" value="ERROR" />
    </Properties>

    <appenders>
        <console name="console" target="SYSTEM_OUT">
            <PatternLayout pattern="${LOG_PATTERN}"/>
            <ThresholdFilter level="${LOG_LEVEL}" onMatch="ACCEPT" onMismatch="DENY"/>
        </console>
        <File name="log" fileName="tmp/log/job.log" append="false">
            <PatternLayout pattern="%d{HH:mm:ss.SSS} %-5level %class{36} %L %M - %msg%xEx%n"/>
        </File>
    </appenders>

    <loggers>
        <root level="${LOG_LEVEL}">
            <appender-ref ref="console"/>
            <appender-ref ref="log"/>
        </root>
    </loggers>
</configuration>
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24

2.1.4.flink_backup_local.yml

hdfs:
  checkPointPath: 'hdfs://nameserver/user/flink/rocksdbcheckpoint'
  checkpointTimeout: 360000
  checkpointing: 300000
  maxConcurrentCheckpoints: 1
  minPauseBetweenCheckpoints: 10000
  restartInterval: 60
  restartStrategy: 3
hive:
  defaultDatabase: 'ods'
  hiveConfDir: 'D:/WorkSpace/bigdata-flink-backup/kafka2hive/src/main/resources/'
  sourceTopic: 'topicA,topicB'
  tableName: 'table_name'
kafka-consumer:
  prop:
    auto.offset.reset: 'earliest'
    bootstrap.servers: 'kfk01:9092,kfk02:9092,kfk03:9092'
    enable.auto.commit: 'false'
    fetch.max.bytes: '52428700'
    group.id: 'test'
    isKerberized: '1'
    keytab: 'D:/keytab/test.keytab'
    krb5Conf: 'D:/keytab/krb5.conf'
    max.poll.interval.ms: '300000'
    max.poll.records: '1000'
    principal: 'test@PRE.TEST.COM'
    security_protocol: 'SASL_PLAINTEXT'
    serviceName: 'kafka'
    session.timeout.ms: '600000'
    useTicketCache: 'false'
  topics: 'topicA,topicB'
kafka-producer:
  defaultTopic: 'kafka2hive_error'
  prop:
    acks: 'all'
    batch.size: '1048576'
    bootstrap.servers: 'kfk01:9092,kfk02:9092,kfk03:9092'
    compression.type: 'lz4'
    key.serializer: 'org.apache.kafka.common.serialization.StringSerializer'
    retries: '3'
    value.serializer: 'org.apache.kafka.common.serialization.StringSerializer'
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41

2.2.utils

2.2.1.DBConn

import java.sql.*;

public class DBConn {


    private static final String driver = "com.mysql.jdbc.Driver";		//mysql驱动
    private static Connection conn = null;

    private static PreparedStatement ps = null;
    private static ResultSet rs = null;
    private static final CallableStatement cs = null;

    /**
     * 连接数据库
     * @return
     */
    public static Connection conn(String url,String username,String password) {
        Connection conn = null;
        try {
            Class.forName(driver);  //加载数据库驱动
            try {
                conn = DriverManager.getConnection(url, username, password);  //连接数据库
            } catch (SQLException e) {
                e.printStackTrace();
            }
        } catch (ClassNotFoundException e) {
            e.printStackTrace();
        }
        return conn;
    }

    /**
     * 关闭数据库链接
     * @return
     */
    public static void close() {
        if(conn != null) {
            try {
                conn.close();  //关闭数据库链接
            } catch (SQLException e) {
                e.printStackTrace();
            }
        }
    }
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45

2.2.2.CommonUtils

@Slf4j
public class CommonUtils {
    public static StreamExecutionEnvironment setCheckpoint(StreamExecutionEnvironment env) throws IOException {
//        ConfigTools.initConf("local");
        Map hdfsMap = (Map) ConfigTools.mapConf.get("hdfs");
        env.enableCheckpointing(((Integer) hdfsMap.get("checkpointing")).longValue(), CheckpointingMode.EXACTLY_ONCE);//这里会造成offset提交的延迟
        env.getCheckpointConfig().setMinPauseBetweenCheckpoints(((Integer) hdfsMap.get("minPauseBetweenCheckpoints")).longValue());
        env.getCheckpointConfig().setCheckpointTimeout(((Integer) hdfsMap.get("checkpointTimeout")).longValue());
        env.getCheckpointConfig().setMaxConcurrentCheckpoints((Integer) hdfsMap.get("maxConcurrentCheckpoints"));
        env.getCheckpointConfig().enableExternalizedCheckpoints(CheckpointConfig.ExternalizedCheckpointCleanup.RETAIN_ON_CANCELLATION);
        env.setRestartStrategy(RestartStrategies.fixedDelayRestart(
                (Integer) hdfsMap.get("restartStrategy"), // 尝试重启的次数，不宜过小，分布式任务很容易出问题（正常情况），建议3-5次
                Time.of(((Integer) hdfsMap.get("restartInterval")).longValue(), TimeUnit.SECONDS) // 延时
        ));
        //设置可容忍的检查点失败数，默认值为0表示不允许容忍任何检查点失败
        env.getCheckpointConfig().setTolerableCheckpointFailureNumber(2);

        //设置状态后端存储方式
        env.setStateBackend(new RocksDBStateBackend((String) hdfsMap.get("checkPointPath"), true));
//        env.setStateBackend(new FsStateBackend((String) hdfsMap.get("checkPointPath"), true));
//        env.setStateBackend(new HashMapStateBackend(());
        return env;
    }

    public static FlinkKafkaConsumer<ConsumerRecord<String, String>> getKafkaConsumer(Map<String, Object> kafkaConf) throws IOException {
        String[] topics = ((String) kafkaConf.get("topics")).split(",");
        log.info("监听的topic: {}", topics);
        Properties properties = new Properties();
        Map<String, String> kafkaProp = (Map<String, String>) kafkaConf.get("prop");
        for (String key : kafkaProp.keySet()) {
            properties.setProperty(key, kafkaProp.get(key).toString());
        }

        if (!StringUtils.isBlank((String) kafkaProp.get("isKerberized")) && "1".equals(kafkaProp.get("isKerberized"))) {
            System.setProperty("java.security.krb5.conf", kafkaProp.get("krb5Conf"));
            properties.put("security.protocol", kafkaProp.get("security_protocol"));
            properties.put("sasl.jaas.config", "com.sun.security.auth.module.Krb5LoginModule required "
                    + "useTicketCache=" + kafkaProp.get("useTicketCache") + " "

                    + "serviceName=\"" + kafkaProp.get("serviceName") + "\" "
                    + "useKeyTab=true "
                    + "keyTab=\"" + kafkaProp.get("keytab").toString() + "\" "
                    + "principal=\"" + kafkaProp.get("principal").toString() + "\";");
        }

        properties.put("key.serializer", "org.apache.flink.kafka.shaded.org.apache.kafka.common.serialization.ByteArrayDeserializer");
        properties.put("value.serializer", "org.apache.flink.kafka.shaded.org.apache.kafka.common.serialization.ByteArrayDeserializer");

        FlinkKafkaConsumer<ConsumerRecord<String, String>> consumerRecordFlinkKafkaConsumer = new FlinkKafkaConsumer<ConsumerRecord<String, String>>(Arrays.asList(topics), new KafkaDeserializationSchema<ConsumerRecord<String, String>>() {
            @Override
            public TypeInformation<ConsumerRecord<String, String>> getProducedType() {
                return TypeInformation.of(new TypeHint<ConsumerRecord<String, String>>() {
                });
            }

            @Override
            public boolean isEndOfStream(ConsumerRecord<String, String> stringStringConsumerRecord) {
                return false;
            }

            @Override
            public ConsumerRecord<String, String> deserialize(ConsumerRecord<byte[], byte[]> record) throws Exception {
                return new ConsumerRecord<String, String>(
                        record.topic(),
                        record.partition(),
                        record.offset(),
                        record.timestamp(),
                        record.timestampType(),
                        record.checksum(),
                        record.serializedKeySize(),
                        record.serializedValueSize(),
                        new String(record.key() == null ? "".getBytes(StandardCharsets.UTF_8) : record.key(), StandardCharsets.UTF_8),
                        new String(record.value() == null ? "{}".getBytes(StandardCharsets.UTF_8) : record.value(), StandardCharsets.UTF_8));
            }
        }, properties);
        return consumerRecordFlinkKafkaConsumer;
    }
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78

2.3.conf

2.3.1.ConfigTools

@Slf4j
public class ConfigTools {

    public static Map<String, Object> mapConf;

    /**
     * 获取对应的配置文件
     *
     * @param option
     */
    public static void initConf(String option) {
        String confFile = "/flink_backup_" + option + ".yml";
        try {
            InputStream dumpFile = ConfigTools.class.getResourceAsStream(confFile);
            mapConf = Yaml.loadType(dumpFile, HashMap.class);
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /**
     * 获取对应的配置文件
     *
     * @param option
     */
    public static void initMySqlConf(String option, Class clazz) {
        String className = clazz.getName();
        String confFile = "/appconfig.yml";
        Map<String, String> mysqlConf;
        try {
            InputStream dumpFile = ConfigTools.class.getResourceAsStream(confFile);
            mysqlConf = Yaml.loadType(dumpFile, HashMap.class);
            String username = mysqlConf.get("mysql.username");
            String password = mysqlConf.get("mysql.password");
            String url = mysqlConf.get("mysql.url");
            Connection conn = DBConn.conn(url, username, password);
            Map<String, Object> config = getConfig(conn, className, option);

            if (config == null || config.size() == 0) {
                log.error("获取配置文件失败");
                return;
            }

            mapConf = config;

        } catch (Exception e) {
            e.printStackTrace();
        }

    }

    private static Map<String, Object> getConfig(Connection conn, String className, String option) throws SQLException {
        PreparedStatement preparedStatement = null;
        try {
            String sql = "select config_context from app_config where app_name = '%s' and config_name = '%s'";
            preparedStatement = conn.prepareStatement(String.format(sql, className, option));

            ResultSet rs = preparedStatement.executeQuery();

            Map<String, String> map = new LinkedHashMap<>();

            String config_context = "";
            while (rs.next()) {
                config_context = rs.getString("config_context");
            }
            System.out.println("配置信息config_context："+config_context);
//            if(StringUtils.isNotBlank(config_context)){
//                System.out.println(JSONObject.toJSONString(JSONObject.parseObject(config_context), SerializerFeature.PrettyFormat));
//            }
            Map<String, Object> mysqlConfMap = JSON.parseObject(config_context, Map.class);
            return mysqlConfMap;
        }finally {
            if (preparedStatement != null) {
                preparedStatement.close();
            }
            if (conn != null) {
                conn.close();
            }
        }
    }

    public static void main(String[] args) {
//        initMySqlConf("local", TboxPeriodBackoutA3K.class);
        initConf("local");
        String s = JSON.toJSONString(mapConf);
        System.out.println(s);
    }
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88

2.4.po

2.4.1.SchemaPo

/**
 * 字段属性对象
 */
@Data
@AllArgsConstructor
@NoArgsConstructor
public class SchemaPo implements Serializable {
    private String signal;
    private String type;
}

1
2
3
4
5
6
7
8
9
10
11

2.5.kafka2hive

2.5.1.Kafka2Hive-ODS

从 Kafka 中获取到的数据不做任何处理直接写入到 Hive 的 ODS 层

public class Kafka2Hive_ODS {

    public static Logger logger = Logger.getLogger(Kafka2Hive_ODS.class);
    
    public static void main(String[] args) throws Exception {
        ConfigTools.initMySqlConf(args[0], AcpBackoutAll_X9E_ORIGINAL.class);
        Map<String, Object> mapConf = ConfigTools.mapConf;
        Map<String, Object> kafkaConsumerConf = (Map<String, Object>) mapConf.get("kafka-consumer");
        Map<String, Object> hiveConf = (Map<String, Object>) mapConf.get("hive");


        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment().disableOperatorChaining();

        CommonUtils.setCheckpoint(env);

        EnvironmentSettings fsSettings = EnvironmentSettings
                .newInstance()
                .useBlinkPlanner()
                .inStreamingMode()
                .build();

        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env, fsSettings);
        StreamStatementSet statementSet = tableEnv.createStatementSet();

        // 使用Hive的sql方言
        tableEnv.getConfig().setSqlDialect(SqlDialect.HIVE);
        //自定义一个名字（没有限制随意取）
        String name = "myhive";
        //这里需要配置hive表中的默认库（不是mysql的hive元数据库）
        String defaultDatabase = "ods";
        //hive-site.xml文件目录
        String hiveConfDir = (String) hiveConf.get("hiveConfDir");
        //创建HiveCatalog
        HiveCatalog hive = new HiveCatalog(name, defaultDatabase, hiveConfDir, "3.1.2");
        //注册HiveCatalog
        tableEnv.registerCatalog("myhive", hive);
        //使用HiveCatalog
        tableEnv.useCatalog("myhive");


//        FlinkKafkaConsumer<String> myConsumer = CommonUtils.getKafkaConsumer();
        FlinkKafkaConsumer<ConsumerRecord<String, String>> myConsumer = CommonUtils.getKafkaConsumer(kafkaConsumerConf);
        DataStream<ConsumerRecord<String, String>> stream = env.addSource(myConsumer);

        String tableName = (String) hiveConf.get("tableName");

        List<FieldSchema> schemas = hive.getHiveTable(new ObjectPath(defaultDatabase, tableName)).getSd().getCols();
        List<FieldSchema> partitionKeys = hive.getHiveTable(new ObjectPath(defaultDatabase, tableName)).getPartitionKeys();
        schemas.addAll(partitionKeys);

        List<SchemaPo> schemaPos = new ArrayList<>();
        List<String> fieldLists = new ArrayList<>();
        List<TypeInformation> typeList = new ArrayList<>();
        for (FieldSchema schema : schemas) {
            SchemaPo schemaPo = new SchemaPo();
            schemaPo.setSignal(schema.getName());
            schemaPo.setType(schema.getType());
            schemaPos.add(schemaPo);
            fieldLists.add(schema.getName());
            String type = schema.getType();
            if (type.equalsIgnoreCase("bigint")) {
                typeList.add(Types.LONG);
            } else {
                typeList.add(Types.STRING);
            }
        }

        String[] fieldNames = fieldLists.toArray(new String[fieldLists.size()]);
        TypeInformation[] types = typeList.toArray(new TypeInformation[typeList.size()]);

        SingleOutputStreamOperator<Row> originalRow = stream.flatMap(new KafkaMsgFormatFunction(schemaPos), new RowTypeInfo(types, fieldNames)).uid("ORIGINAL");

        tableEnv.createTemporaryView("originalRow", originalRow);
        StringBuilder sql = new StringBuilder();
        tableEnv.executeSql("alter table table_name set TBLPROPERTIES ('sink.partition-commit.policy.kind'='metastore')");
        sql.append("insert into `table_name` select ");
        sql.append(" * ");
        sql.append(" from `myhive`.`ods`.originalRow");
        tableEnv.executeSql(sql.toString());
//        env.execute();
    }


    static class KafkaMsgFormatFunction extends RichFlatMapFunction<ConsumerRecord<String,String>, Row> {

        private List<SchemaPo> schemaPos;

        public KafkaMsgFormatFunction(List<SchemaPo> schemaPos) {
            this.schemaPos = schemaPos;
        }

        @Override
        public void open(Configuration parameters) {
        
        }

        @Override
        public void flatMap(ConsumerRecord<String,String> record, Collector<Row> out) {
            String key = null;
            try {
                HashMap<String, Object> infoMap = JSON.parseObject((String) record.value(), HashMap.class);
                
                for (String signalkey : infoMap.keySet()) {
                    resultMap.put(signalkey.toLowerCase(), String.valueOf(infoMap.get(signalkey)));
                }

                Row row = new Row(schemaPos.size());
                for (int i = 0; i < schemaPos.size(); i++) {
                    SchemaPo schemaPo = schemaPos.get(i);
                    String v = resultMap.get(schemaPo.getSignal());
                    if (StringUtils.isBlank(v)) {
                        row.setField(i, null);
                        continue;
                    }
                    if ("bigint".equalsIgnoreCase(schemaPo.getType())) {
                        Long svalue = Long.valueOf(resultMap.get(schemaPo.getSignal()));
                        row.setField(i, svalue);
                    } else {
                        String svalue = resultMap.get(schemaPo.getSignal());
                        row.setField(i, svalue);
                    }
                }
                out.collect(row);
            } catch (Exception e) {
            	e.printStackTrace();
            }
        }
    }
}
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129

声明：本文内容由网友自发贡献，不代表【wpsshop博客】立场，版权归原作者所有，本站不承担相应法律责任。如您发现有侵权的内容，请联系我们。转载请注明出处：https://www.wpsshop.cn/w/木道寻08/article/detail/904459