示例实现beam用java编程，监听kafka的testmsg主题，然后将收取到的单词，按5秒做一次统计。结果输出到outputmessage 的kafka主题，同时同步到elasticSearch。

kafka需要运行

启动：
cd /root/kafuka/kafka_2.12-0.11.0.0

 nohup bin/zookeeper-server-start.sh config/zookeeper.properties &

 nohup bin/kafka-server-start.sh config/server.properties &

 创建topic：

 bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic testmsg

  bin/kafka-topics.sh --list --zookeeper localhost:2181

生产者producer

  bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test

消费者consumer

 bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic test --from-beginning

elasticSearch

创建索引Put http://192.168.11.100:9200/myindex?pretty

查看所有索引： http://192.168.11.100:9200/_cat/indices?v

获取内容Get http://192.168.11.100:9200/myindex/_search?q=*&pretty

http://192.168.11.100:9200/myindex/_search?q=*&sort=_id:desc&pretty

用mvn自动生成项目代码：

windows在powershell中运行：

 mvn archetype:generate `

 -D archetypeGroupId=org.apache.beam `

 -D archetypeArtifactId=beam-sdks-java-maven-archetypes-examples `

 -D archetypeVersion=2.8.0 `

 -D groupId=org.example `

 -D artifactId=word-count-beam `

 -D version="0.1" `

 -D package=org.apache.beam.examples `

 -D interactiveMode=false

其他参考beam官方文档： <https://beam.apache.org/get-started/quickstart-java/>

替换pom.xml

<?xml version="1.0" encoding="UTF-8"?>

<!--

    Licensed to the Apache Software Foundation (ASF) under one or more

    contributor license agreements.  See the NOTICE file distributed with

    this work for additional information regarding copyright ownership.

    The ASF licenses this file to You under the Apache License, Version 2.0

    (the "License"); you may not use this file except in compliance with

    the License.  You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

    Unless required by applicable law or agreed to in writing, software

    distributed under the License is distributed on an "AS IS" BASIS,

    WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

    See the License for the specific language governing permissions and

    limitations under the License.

-->

<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.example</groupId>

  <artifactId>word-count-beam</artifactId>

  <version>0.1</version>

  <packaging>jar</packaging>

  <properties>

    <beam.version>2.8.0</beam.version>

    <bigquery.version>v2-rev402-1.24.1</bigquery.version>

    <google-clients.version>1.24.1</google-clients.version>

    <guava.version>20.0</guava.version>

    <hamcrest.version>1.3</hamcrest.version>

    <jackson.version>2.9.5</jackson.version>

    <joda.version>2.4</joda.version>

    <junit.version>4.12</junit.version>

    <maven-compiler-plugin.version>3.7.0</maven-compiler-plugin.version>

    <maven-exec-plugin.version>1.6.0</maven-exec-plugin.version>

    <maven-jar-plugin.version>3.0.2</maven-jar-plugin.version>

    <maven-shade-plugin.version>3.1.0</maven-shade-plugin.version>

    <mockito.version>1.10.19</mockito.version>

    <pubsub.version>v1-rev399-1.24.1</pubsub.version>

    <slf4j.version>1.7.25</slf4j.version>

    <spark.version>2.3.2</spark.version>

    <hadoop.version>2.7.3</hadoop.version>

    <maven-surefire-plugin.version>2.21.0</maven-surefire-plugin.version>

    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>

  </properties>

  <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>

  <build>

    <plugins>

      <plugin>

        <groupId>org.apache.maven.plugins</groupId>

        <artifactId>maven-compiler-plugin</artifactId>

        <version>${maven-compiler-plugin.version}</version>

        <configuration>

          <source>1.8</source>

          <target>1.8</target>

        </configuration>

      </plugin>

      <plugin>

        <groupId>org.apache.maven.plugins</groupId>

        <artifactId>maven-surefire-plugin</artifactId>

        <version>${maven-surefire-plugin.version}</version>

        <configuration>

          <parallel>all</parallel>

          <threadCount>4</threadCount>

          <redirectTestOutputToFile>true</redirectTestOutputToFile>

        </configuration>

        <dependencies>

          <dependency>

            <groupId>org.apache.maven.surefire</groupId>

            <artifactId>surefire-junit47</artifactId>

            <version>${maven-surefire-plugin.version}</version>

          </dependency>

        </dependencies>

      </plugin>

      <!-- Ensure that the Maven jar plugin runs before the Maven

        shade plugin by listing the plugin higher within the file. -->

      <plugin>

        <groupId>org.apache.maven.plugins</groupId>

        <artifactId>maven-jar-plugin</artifactId>

        <version>${maven-jar-plugin.version}</version>

      </plugin>

      <!--

        Configures `mvn package` to produce a bundled jar ("fat jar") for runners

        that require this for job submission to a cluster.

      -->

      <plugin>

        <groupId>org.apache.maven.plugins</groupId>

        <artifactId>maven-shade-plugin</artifactId>

        <version>${maven-shade-plugin.version}</version>

        <executions>

          <execution>

            <phase>package</phase>

            <goals>

              <goal>shade</goal>

            </goals>

            <configuration>

              <finalName>${project.artifactId}-bundled-${project.version}</finalName>

              <filters>

                <filter>

                  <artifact>*:*</artifact>

                  <excludes>

                    <exclude>META-INF/LICENSE</exclude>

                    <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.ServicesResourceTransformer"/>

              </transformers>

            </configuration>

          </execution>

        </executions>

      </plugin>

    </plugins>

    <pluginManagement>

      <plugins>

        <plugin>

          <groupId>org.codehaus.mojo</groupId>

          <artifactId>exec-maven-plugin</artifactId>

          <version>${maven-exec-plugin.version}</version>

          <configuration>

            <cleanupDaemonThreads>false</cleanupDaemonThreads>

          </configuration>

        </plugin>

      </plugins>

    </pluginManagement>

  </build>

  <profiles>

    <profile>

      <id>direct-runner</id>

      <activation>

        <activeByDefault>true</activeByDefault>

      </activation>

      <!-- Makes the DirectRunner available when running a pipeline. -->

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-direct-java</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

      </dependencies>

    </profile>

    <profile>

      <id>apex-runner</id>

      <!-- Makes the ApexRunner available when running a pipeline. -->

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-apex</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

        <!--

          Apex depends on httpclient version 4.3.6, project has a transitive dependency to httpclient 4.0.1 from

          google-http-client. Apex dependency version being specified explicitly so that it gets picked up. This

          can be removed when the project no longer has a dependency on a different httpclient version.

        -->

        <dependency>

          <groupId>org.apache.httpcomponents</groupId>

          <artifactId>httpclient</artifactId>

          <version>4.3.6</version>

          <scope>runtime</scope>

          <exclusions>

            <exclusion>

              <groupId>commons-codec</groupId>

              <artifactId>commons-codec</artifactId>

            </exclusion>

          </exclusions>

        </dependency>

        <!--

          Apex 3.6 is built against YARN 2.6. Version in the fat jar has to match

          what's on the cluster, hence we need to repeat the Apex Hadoop dependencies here.

        -->

        <dependency>

          <groupId>org.apache.hadoop</groupId>

          <artifactId>hadoop-yarn-client</artifactId>

          <version>${hadoop.version}</version>

          <scope>runtime</scope>

        </dependency>

        <dependency>

          <groupId>org.apache.hadoop</groupId>

          <artifactId>hadoop-common</artifactId>

          <version>${hadoop.version}</version>

          <scope>runtime</scope>

        </dependency>

      </dependencies>

    </profile>

    <profile>

      <id>dataflow-runner</id>

      <!-- Makes the DataflowRunner available when running a pipeline. -->

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-google-cloud-dataflow-java</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

      </dependencies>

    </profile>

    <profile>

      <id>flink-runner</id>

      <!-- Makes the FlinkRunner available when running a pipeline. -->

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-flink_2.11</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

      </dependencies>

    </profile>

    <profile>

      <id>spark-runner</id>

      <!-- Makes the SparkRunner available when running a pipeline. Additionally,

           overrides some Spark dependencies to Beam-compatible versions. -->

      <properties>

        <netty.version>4.1.17.Final</netty.version>

      </properties>

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-spark</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-sdks-java-io-hadoop-file-system</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

        <dependency>

          <groupId>org.apache.spark</groupId>

          <artifactId>spark-streaming_2.11</artifactId>

          <version>${spark.version}</version>

          <scope>runtime</scope>

          <exclusions>

            <exclusion>

              <groupId>org.slf4j</groupId>

              <artifactId>jul-to-slf4j</artifactId>

            </exclusion>

          </exclusions>

        </dependency>

        <dependency>

          <groupId>com.fasterxml.jackson.module</groupId>

          <artifactId>jackson-module-scala_2.11</artifactId>

          <version>${jackson.version}</version>

          <scope>runtime</scope>

        </dependency>

        <!-- [BEAM-3519] GCP IO exposes netty on its API surface, causing conflicts with runners -->

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-sdks-java-io-google-cloud-platform</artifactId>

          <version>${beam.version}</version>

          <exclusions>

            <exclusion>

              <groupId>io.grpc</groupId>

              <artifactId>grpc-netty</artifactId>

            </exclusion>

            <exclusion>

              <groupId>io.netty</groupId>

              <artifactId>netty-handler</artifactId>

            </exclusion>

          </exclusions>

        </dependency>

      </dependencies>

    </profile>

    <profile>

      <id>gearpump-runner</id>

      <dependencies>

        <dependency>

          <groupId>org.apache.beam</groupId>

          <artifactId>beam-runners-gearpump</artifactId>

          <version>${beam.version}</version>

          <scope>runtime</scope>

        </dependency>

      </dependencies>

    </profile>

  </profiles>

  <dependencies>

    <!-- Adds a dependency on the Beam SDK. -->

    <dependency>

      <groupId>org.apache.beam</groupId>

      <artifactId>beam-sdks-java-core</artifactId>

      <version>${beam.version}</version>

    </dependency>

    <!-- Adds a dependency on the Beam Google Cloud Platform IO module. -->

    <dependency>

      <groupId>org.apache.beam</groupId>

      <artifactId>beam-sdks-java-io-google-cloud-platform</artifactId>

      <version>${beam.version}</version>

    </dependency>

    <!-- Dependencies below this line are specific dependencies needed by the examples code. -->

    <dependency>

      <groupId>com.google.api-client</groupId>

      <artifactId>google-api-client</artifactId>

      <version>${google-clients.version}</version>

      <exclusions>

        <!-- Exclude an old version of guava that is being pulled

             in by a transitive dependency of google-api-client -->

        <exclusion>

          <groupId>com.google.guava</groupId>

          <artifactId>guava-jdk5</artifactId>

        </exclusion>

      </exclusions>

    </dependency>

    <dependency>

      <groupId>com.google.apis</groupId>

      <artifactId>google-api-services-bigquery</artifactId>

      <version>${bigquery.version}</version>

      <exclusions>

        <!-- Exclude an old version of guava that is being pulled

             in by a transitive dependency of google-api-client -->

        <exclusion>

          <groupId>com.google.guava</groupId>

          <artifactId>guava-jdk5</artifactId>

        </exclusion>

      </exclusions>

    </dependency>

    <dependency>

      <groupId>com.google.http-client</groupId>

      <artifactId>google-http-client</artifactId>

      <version>${google-clients.version}</version>

      <exclusions>

        <!-- Exclude an old version of guava that is being pulled

             in by a transitive dependency of google-api-client -->

        <exclusion>

          <groupId>com.google.guava</groupId>

          <artifactId>guava-jdk5</artifactId>

        </exclusion>

      </exclusions>

    </dependency>

    <dependency>

      <groupId>com.google.apis</groupId>

      <artifactId>google-api-services-pubsub</artifactId>

      <version>${pubsub.version}</version>

      <exclusions>

        <!-- Exclude an old version of guava that is being pulled

             in by a transitive dependency of google-api-client -->

        <exclusion>

          <groupId>com.google.guava</groupId>

          <artifactId>guava-jdk5</artifactId>

        </exclusion>

      </exclusions>

    </dependency>

    <dependency>

      <groupId>joda-time</groupId>

      <artifactId>joda-time</artifactId>

      <version>${joda.version}</version>

    </dependency>

    <dependency>

      <groupId>com.google.guava</groupId>

      <artifactId>guava</artifactId>

      <version>${guava.version}</version>

    </dependency>

    <!-- Add slf4j API frontend binding with JUL backend -->

    <dependency>

      <groupId>org.slf4j</groupId>

      <artifactId>slf4j-api</artifactId>

      <version>${slf4j.version}</version>

    </dependency>

    <dependency>

      <groupId>org.slf4j</groupId>

      <artifactId>slf4j-jdk14</artifactId>

      <version>${slf4j.version}</version>

      <!-- When loaded at runtime this will wire up slf4j to the JUL backend -->

      <scope>runtime</scope>

    </dependency>

    <!-- Hamcrest and JUnit are required dependencies of PAssert,

         which is used in the main code of DebuggingWordCount example. -->

    <dependency>

      <groupId>org.hamcrest</groupId>

      <artifactId>hamcrest-core</artifactId>

      <version>${hamcrest.version}</version>

    </dependency>

    <dependency>

      <groupId>org.hamcrest</groupId>

      <artifactId>hamcrest-library</artifactId>

      <version>${hamcrest.version}</version>

    </dependency>

    <dependency>

      <groupId>junit</groupId>

      <artifactId>junit</artifactId>

      <version>${junit.version}</version>

    </dependency>

    <!-- The DirectRunner is needed for unit tests. -->

    <dependency>

      <groupId>org.apache.beam</groupId>

      <artifactId>beam-runners-direct-java</artifactId>

      <version>${beam.version}</version>

      <scope>test</scope>

    </dependency>

    <dependency>

      <groupId>org.mockito</groupId>

      <artifactId>mockito-core</artifactId>

      <version>${mockito.version}</version>

      <scope>test</scope>

    </dependency>

    <!-- kafka -->

    <dependency>

        <groupId>org.apache.beam</groupId>

        <artifactId>beam-sdks-java-io-kafka</artifactId>

        <version>${beam.version}</version>

    </dependency>

    <dependency>

        <groupId>org.apache.kafka</groupId>

        <artifactId>kafka-clients</artifactId>

        <version>0.11.0.0</version>

    </dependency>

    <!-- kafka -->

    <dependency>

        <groupId>org.apache.beam</groupId>

        <artifactId>beam-sdks-java-io-elasticsearch</artifactId>

        <version>${beam.version}</version>

    </dependency>

  </dependencies>

</project>

将如下代码加入java目录 src/main/java/org.apache.beam.examples

/*

 * Licensed to the Apache Software Foundation (ASF) under one

 * or more contributor license agreements.  See the NOTICE file

 * distributed with this work for additional information

 * regarding copyright ownership.  The ASF licenses this file

 * to you under the Apache License, Version 2.0 (the

 * "License"); you may not use this file except in compliance

 * with the License.  You may obtain a copy of the License at

 *

 *     http://www.apache.org/licenses/LICENSE-2.0

 *

 * Unless required by applicable law or agreed to in writing, software

 * distributed under the License is distributed on an "AS IS" BASIS,

 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.

 * See the License for the specific language governing permissions and

 * limitations under the License.

 */

package org.apache.beam.examples;

import org.apache.beam.sdk.Pipeline;

import org.apache.beam.sdk.io.elasticsearch.ElasticsearchIO;

import org.apache.beam.sdk.io.kafka.KafkaIO;

import org.apache.beam.sdk.io.kafka.KafkaRecord;

import org.apache.beam.sdk.options.Default;

import org.apache.beam.sdk.options.Description;

import org.apache.beam.sdk.options.PipelineOptions;

import org.apache.beam.sdk.options.PipelineOptionsFactory;

import org.apache.beam.sdk.options.Validation.Required;

import org.apache.beam.sdk.transforms.Count;

import org.apache.beam.sdk.transforms.DoFn;

import org.apache.beam.sdk.transforms.MapElements;

import org.apache.beam.sdk.transforms.ParDo;

import org.apache.beam.sdk.transforms.SimpleFunction;

import org.apache.beam.sdk.transforms.windowing.FixedWindows;

import org.apache.beam.sdk.transforms.windowing.Window;

import org.apache.beam.sdk.values.KV;

import org.apache.beam.sdk.values.PCollection;

import org.apache.kafka.common.serialization.StringDeserializer;

import org.apache.kafka.common.serialization.StringSerializer;

import org.joda.time.Duration;

import org.slf4j.Logger;

import org.slf4j.LoggerFactory;

import com.google.common.collect.ImmutableMap;

//import org.apache.beam.runners.flink.FlinkRunner;

public class KafkaSample {

    public static void main(String[] args) {

        String hosts = "211.100.75.227:9092";// 192.168.1.110:11092,192.168.1.119:11092,192.168.1.120:11092

        String sourceTopic = "testmsg";

        // 创建管道工厂

        WordCountOptions options = PipelineOptionsFactory.fromArgs(args).withValidation().as(WordCountOptions.class);

        // 设置相关管道

        Pipeline pipeline = Pipeline.create(options);

        // 这里 kV 后说明 kafka 中的 key 和 value 均为 String 类型

        PCollection<KafkaRecord<String, String>> lines = pipeline.apply(KafkaIO.<String,

        String> read().withBootstrapServers(hosts)// 必需设置 kafka的服务器地址和端口

                .withTopic(sourceTopic)// 必需设置要读取的 kafka 的 topic 名称

                .withKeyDeserializer(StringDeserializer.class)// 必需序列化 key

                .withValueDeserializer(StringDeserializer.class)

                // 必需序列化 value

                .updateConsumerProperties(ImmutableMap.<String, Object> of("auto.offset.reset", "latest")));// 这个属性

                                                                                                            // kafka

                                                                                                            // 最常见的.earliest

        // 为输出的消息类型。或者进行处理后返回的消息类型

        PCollection<String> kafkadata = lines.apply("Remove Kafka Metadata", ParDo.of(new DoFn<KafkaRecord<String, String>, String>() {

            private static final long serialVersionUID = 1L;

            @ProcessElement

            public void processElement(ProcessContext ctx) {

                System.out.println("get from topic：" + ctx.element().getKV());

                ctx.output(ctx.element().getKV().getValue());// 对kafka收到的消息处理

            }

        }));

        PCollection<String> windowedEvents = kafkadata.apply(Window.<String> into(FixedWindows.of(Duration.standardSeconds(5))));

        PCollection<KV<String, Long>> wordcount = windowedEvents.apply(Count.<String> perElement()); // 统计每一个

                                                                                                        // kafka

                                                                                                        // 消息的

                                                                                                        // Count

        PCollection<String> wordtj = wordcount.apply("ConcatResultKVs", MapElements.via( // 拼接最后的格式化输出（Key

                                                                                            // 为

                                                                                            // Word，Value

                                                                                            // 为

                                                                                            // Count）

                new SimpleFunction<KV<String, Long>, String>() {

                    private static final long serialVersionUID = 1L;

                    @Override

                    public String apply(KV<String, Long> input) {

                        System.out.println("key=" + input.getKey());

                        System.out.println("value=" + input.getValue());

                        String ret = " {\"" + input.getKey() + "\":\"" + input.getValue() + "\"}";

                        System.out.println(ret);

                        return ret;

                    }

                }));

        /* sink to kafka*/

        wordtj.apply(KafkaIO.<Void, String> write().withBootstrapServers(hosts)// 设置写会

                // kafka

                // 的集群配置地址

                .withTopic("outputmessage")// 设置返回 kafka 的消息主题

                // .withKeySerializer(StringSerializer.class)// 这里不用设置了，因为上面

                // Void

                .withValueSerializer(StringSerializer.class)

                // Dataflow runner and Spark 兼容， Flink 对 kafka0.11 才支持。我的版本是

                // 0.10 不兼容

                // .withEOS(20, "eos-sink-group-id")

                .values() // 只需要在此写入默认的 key 就行了，默认为 null 值

        ); // 输出结果

        /* sink to elasticsearch */

        String[] addresses = { "http://192.168.11.100:9200" };

        wordtj.apply(ElasticsearchIO.write().withConnectionConfiguration(ElasticsearchIO.ConnectionConfiguration.create(addresses, "myindex", "testdoc")));

        pipeline.run().waitUntilFinish();

    }

    public interface WordCountOptions extends PipelineOptions {

        /**

         * By default, this example reads from a public dataset containing the

         * text of King Lear. Set this option to choose a different input file

         * or glob.

         */

        @Description("Path of the file to read from")

        @Default.String("gs://apache-beam-samples/shakespeare/kinglear.txt")

        String getInputFile();

        void setInputFile(String value);

        /** Set this required option to specify where to write the output. */

        @Description("Path of the file to write to")

        @Required

        String getOutput();

        void setOutput(String value);

    }

    private static final Logger logger = LoggerFactory.getLogger(KafkaSample.class);

    /**

     * Options supported by {@link WordCount}.

     *

     * <p>

     * Concept #4: Defining your own configuration options. Here, you can add

     * your own arguments to be processed by the command-line parser, and

     * specify default values for them. You can then access the options values

     * in your pipeline code.

     *

     * <p>

     * Inherits standard configuration options.

     */

    public interface KFOptions extends PipelineOptions {

        /**

         * By default, this example reads from a public dataset containing the

         * text of King Lear. Set this option to choose a different input file

         * or glob.

         */

        @Description("Path of the file to read from")

        @Default.String("211.100.75.227:9092")

        String getBrokers();

        void setBrokers(String value);

    }

}

修改里面kafka地址，elasticSearch地址。大功告成，可以执行了！

beam平台直接运行：

Direct-Local runner

mvn compile exec:java -D exec.mainClass=org.apache.beam.examples.KafkaSample `

 -D exec.args="--inputFile=pom.xml --output=counts" -P direct-runner

自启动Flink local平台上运行：

 mvn compile exec:java -D exec.mainClass=org.apache.beam.examples.KafkaSample `

  -D exec.args="--runner=FlinkRunner --inputFile=pom.xml --output=counts" -P flink-runner

打包放入已经运行的flink local平台上运行：

mvn package -Pflink-runner

这样可以打包后，上传到flink，指定启动类：

--runner=FlinkRunner --inputFile=C:\path\to\quickstart\pom.xml --output=C:\tmp\counts  --filesToStage=.\target\word-count-beam-bundled-0.1.jar

org.apache.beam.examples.KafkaSample

遇到的问题：

1，kafka收到的json，普通的可以导入elasticSearch。比如

{

“field":"value",

"filed1:"value"

}

但是如果字串里面带有冒号等字符，会报错，后来发现写在一行可以通过。比如

{"mytime": "2018-12-13T06:44:41.460Z","carColor":"blue"}

可能和elasticSearch的_bulk批量插入有关。

用beam实现连接kafka和elasticSearch示例 在flink平台运行的更多相关文章

  1. 使用Akka、Kafka和ElasticSearch等构建分析引擎 -- good

    本文翻译自Building Analytics Engine Using Akka, Kafka & ElasticSearch,已获得原作者Satendra Kumar和网站授权. 在这篇文 ...

  2. Flink SQL结合Kafka、Elasticsearch、Kibana实时分析电商用户行为

    body { margin: 0 auto; font: 13px / 1 Helvetica, Arial, sans-serif; color: rgba(68, 68, 68, 1); padd ...

  3. 一个非常标准的Java连接Oracle数据库的示例代码

    最基本的Oracle数据库连接代码(只针对Oracle11g): 1.右键项目->构建路径->配置构建路径,选择第三项“库”,然后点击“添加外部Jar”,选择“D:\Oracle\app\ ...

  4. Java连接Oracle数据库的示例代码

    最基本的Oracle数据库连接代码(只针对Oracle11g): 1.右键项目->构建路径 ->配置构建路径,选择第三项“库”,然后点击“添加外部Jar”,选择 “D:\Oracle\ap ...

  5. 一个非常标准的连接Mysql数据库的示例代码

    一.About Mysql 1.Mysql 优点 体积小.速度快.开放源码.免费 一般中小型网站的开发都选择 MySQL ,最流行的关系型数据库 LAMP / LNMP Linux作为操作系统 Apa ...

  6. 物联网架构成长之路(8)-EMQ-Hook了解、连接Kafka发送消息

    1. 前言 按照我自己设计的物联网框架,对于MQTT集群中的所有消息,是要持久化到磁盘的,这里采用一个消息队列中间件Kafka作为数据缓冲,缓冲结果存到数据仓库中,以供后续作为数据分析.由于MQTT集 ...

  7. java实现Kafka的消费者示例

    使用java实现Kafka的消费者 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 3 ...

  8. SpringBoot 连接kafka ssl 报 CertificateException: No subject alternative names present 异常解决

    当使用较新版本SpringBoot时,对应的 kafka-client 版本也比较新,如果使用了 2.x 以上的 kafka-client ,并且配置了 kafka ssl 连接方式时,可能会报如下异 ...

  9. Java连接简单使用ElasticSearch

    目录 1. 添加依赖 2. 代码,无账号密码 3. 代码,有账号密码,并且是https方式 4. 参考文章 1. 添加依赖 <!-- https://mvnrepository.com/arti ...

随机推荐

  1. 测者的性能测试手册：快速安装LoadRunner Linux上的Generator

    安装和初始化 安装包 上传Linux.zip(LoadRunner Generator for Linux.zip,后台回复loadrunner获取下载地址),然后通过如下命令: unzip Linu ...

  2. 自己手写一个SpringMVC 框架

    一.了解SpringMVC运行流程及九大组件 1.SpringMVC 的运行流程   · 用户发送请求至前端控制器DispatcherServlet · DispatcherServlet收到请求调用 ...

  3. Spring MVC 响应视图（六）

    完整的项目案例: springmvc.zip 目录 实例 除了依赖spring-webmvc还需要依赖jackson-databind(用于转换json数据格式) <dependency> ...

  4. 【公众号系列】SAP HANA 平台的优势

    公众号:SAP Technical 本文作者:matinal 原文出处:http://www.cnblogs.com/SAPmatinal/ 原文链接:[公众号系列]SAP HANA 平台的优势   ...

  5. 企业业务数据处理用“work”还是“MQ”

    近期公司在做架构梳理已经项目架构方向,不知不觉就引起了使用“work”跑数据还是用“MQ”进行跑数据的争论! 对于争论这件事在各行各业都有,其实我觉得针对“争论”这个词的根源在于一件事情有很多解决方案 ...

  6. nmap比较详细的使用方法

    nmap 信息收集工具 -sP 192.168.1.0/24  区域网内存活主机扫描  -O 192.168.1.1    获取操作系统 nmap -sS -sV baidu.com    -sS 使 ...

  7. redis Lua学习与坑

    1.在写lua脚本往redis中添加zadd 有序集合的时候一直报 "value is not a valid float"的错误,经过查询相关资料,最后发现,是顺序写反了. 相关 ...

  8. kernel笔记——中断

    cpu与磁盘.网卡.键盘等外围设备(相对于cpu和内存而言)交互时,cpu下发I/O请求到这些设备后,相对cpu的处理能力而言,磁盘.网卡等设备需要较长时间完成请求处理. 那么在请求发出到处理完成这段 ...

  9. loadrunner关联及web_reg_save_param方法浅析

    一.什么是关联 关联(correlation):脚本回放过程中,客户端发出请求,通过关联函数所定义的左右边界值(也就是关联规则),在服务器所响应的内容中查找,得到相应的值,已变量的形式替换录制时的静态 ...

  10. Zookeeper集群为什么要是单数

    (原) 在zookeeper集群中,会有三种角色,leader. follower. observer分别对应着总统.议员.观察者. 半数以上投票通过:可以这样理解.客户端的增删改操作无论访问到了哪台 ...