flink1.11发布以来,很多人就很关心hive仓库实时化。所以自己也试着尝试一下,然而遇到很多环境问题。
1、启动hadoop
2、启动zk、kafka、hive
环境准备好之后,先在本地测试一下,注意:本地跑需要将<dependency>的scop改成compile:
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>test</groupId>
<artifactId>test</artifactId>
<version>1.0-SNAPSHOT</version>
<packaging>jar</packaging>
<name>Flink Quickstart Job</name>
<url>http://www.myorganization.org</url>
<repositories>
<repository>
<id>apache.snapshots</id>
<name>Apache Development Snapshot Repository</name>
<url>https://repository.apache.org/content/repositories/snapshots/</url>
<releases>
<enabled>false</enabled>
</releases>
<snapshots>
<enabled>true</enabled>
</snapshots>
</repository>
</repositories>
<properties>
<scala.bin.version>2.11</scala.bin.version>
<flink.version>1.11.0</flink.version>
<flink-shaded-hadoop.version>2.8.3-10.0</flink-shaded-hadoop.version>
<hive.version>2.3.7</hive.version>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-streaming-scala_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-clients_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-common</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-api-scala-bridge_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-table-planner-blink_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-connector-hive_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-sql-connector-kafka-0.11_${scala.bin.version}</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-json</artifactId>
<version>${flink.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.flink</groupId>
<artifactId>flink-shaded-hadoop-2-uber</artifactId>
<version>${flink-shaded-hadoop.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.apache.hive</groupId>
<artifactId>hive-exec</artifactId>
<version>${hive.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>
<build>
<resources>
<resource>
<directory>src/main/scala</directory>
</resource>
<resource>
<directory>src/main/java</directory>
</resource>
<resource>
<directory>src/main/resources</directory>
</resource>
</resources>
<testResources>
<testResource>
<directory>src/test/java</directory>
</testResource>
</testResources>
<plugins>
<plugin>
<groupId>org.scala-tools</groupId>
<artifactId>maven-scala-plugin</artifactId>
<version>2.15.2</version>
<executions>
<execution>
<id>scala-compile-first</id>
<phase>process-resources</phase>
<goals>
<goal>add-source</goal>
<goal>compile</goal>
</goals>
</execution>
<execution>
<id>scala-test-compile</id>
<phase>process-test-resources</phase>
<goals>
<goal>testCompile</goal>
</goals>
</execution>
</executions>
<configuration>
<scalaVersion>2.11.12</scalaVersion>
<args>
<arg>-target:jvm-1.8</arg>
</args>
</configuration>
</plugin>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.1</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<plugin>
<artifactId>maven-assembly-plugin</artifactId>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
<archive>
<manifest>
</manifest>
</archive>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
代码:
def main(args: Array[String]): Unit = {
val env: StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
env.setStreamTimeCharacteristic(TimeCharacteristic.EventTime)
env.setParallelism(1)
val tableEnvSettings = EnvironmentSettings.newInstance()
.useBlinkPlanner()
.inStreamingMode()
.build()
val tableEnv: StreamTableEnvironment = StreamTableEnvironment.create(env,tableEnvSettings)
tableEnv.getConfig.getConfiguration.set(ExecutionCheckpointingOptions.CHECKPOINTING_MODE, CheckpointingMode.EXACTLY_ONCE)
tableEnv.getConfig.getConfiguration.set(ExecutionCheckpointingOptions.CHECKPOINTING_INTERVAL, Duration.ofSeconds(10))
val catalogName = "my_catalog"
val catalog = new HiveCatalog(
catalogName, // catalog name
"default", // default database
// "D:\\workspace\\idea_work\\flink_test\\src\\main\\resources\\", // Hive config (hive-site.xml) directory
"/usr/local/app/hive-2.3.7/conf", // Hive config (hive-site.xml) directory
"2.3.4" // Hive version
)
tableEnv.registerCatalog(catalogName, catalog)
tableEnv.useCatalog(catalogName)
tableEnv.executeSql("DROP TABLE IF EXISTS kafka_table")
tableEnv.executeSql(
"""
|CREATE TABLE kafka_table (
| user_id STRING,
| order_amount DOUBLE,
| log_ts TIMESTAMP(3),
| WATERMARK FOR log_ts AS log_ts - INTERVAL '5' SECOND
|)WITH (
| 'connector' = 'kafka-0.11',
| 'topic' = 'ods_analytics_test',
| 'properties.bootstrap.servers' = 'xiao100:9092,xiao101:9092,xiao102:9092',
| 'properties.group.id' = 'flink_hive_test',
| 'scan.startup.mode' = 'latest-offset',
| 'format' = 'json',
| 'json.fail-on-missing-field' = 'false',
| 'json.ignore-parse-errors' = 'true'
| )
|""".stripMargin)
tableEnv.getConfig.setSqlDialect(SqlDialect.HIVE)
tableEnv.executeSql("DROP TABLE IF EXISTS hive_table")
tableEnv.executeSql(
"""
|CREATE TABLE hive_table (
| user_id STRING,
| order_amount DOUBLE
| ) PARTITIONED BY (dt STRING, hr STRING) STORED AS parquet TBLPROPERTIES (
| 'partition.time-extractor.timestamp-pattern'='$dt $hr:00:00',
| 'sink.partition-commit.trigger'='partition-time',
| 'sink.partition-commit.delay'='1 min',
| 'sink.partition-commit.policy.kind'='metastore,success-file'
|)
|""".stripMargin)
// tableEnv.getConfig.setSqlDialect(SqlDialect.DEFAULT)
tableEnv.executeSql(
"""
|INSERT INTO TABLE hive_table
| SELECT user_id, order_amount, DATE_FORMAT(log_ts, 'yyyy-MM-dd'), DATE_FORMAT(log_ts, 'HH')
|FROM kafka_table
|""".stripMargin)
}
注意:1.11版本executeSql就已经触发执行了,如果里面用到dataStream了,需要用streamEnv来触发执行
启动成功后输入测试数据:
{"user_id":"a1111","order_amount":11.0,"log_ts":"2020-06-29 12:12:12"}
{"user_id":"a1111","order_amount":11.0,"log_ts":"2020-06-29 12:15:00"}
{"user_id":"a1111","order_amount":11.0,"log_ts":"2020-06-29 12:20:00"}
{"user_id":"a1111","order_amount":11.0,"log_ts":"2020-06-29 12:30:00"}
{"user_id":"a1111","order_amount":13.0,"log_ts":"2020-06-29 12:32:00"}
查看hive仓库:
然后将项目打包,运行到flink集群,需要注意的是,pom中的dependency的scop全都改成provided,然后flink集群的lib目录需要添加几个jar。
执行./bin/flink run -c test.kafka2hive test.jar 运行即可。
注意:如果项目中的flink依赖包在集群的classpath中已经存在的话,可能会报错,所以全都改成provided的了。
Caused by: java.lang.ClassCastException: org.codehaus.janino.CompilerFactory cannot be cast to org.codehaus.commons.compiler.ICompilerFactory
at org.codehaus.commons.compiler.CompilerFactoryFactory.getCompilerFactory(CompilerFactoryFactory.java:129)
at org.codehaus.commons.compiler.CompilerFactoryFactory.getDefaultCompilerFactory(CompilerFactoryFactory.java:79)
at org.apache.calcite.rel.metadata.JaninoRelMetadataProvider.compile(JaninoRelMetadataProvider.java:431)
... 62 more