Edata base, a secondary development project based on spark packaging, is introduced

Introduce

edata-base Is based on Spark Big data secondary development library , It encapsulates the Spark And other commonly used intermediate methods , Make based on Spark The development of is simpler .
Source warehouse address ：https://gitee.com/alan-sword/edata-base

Project introduction

edata-base Medium POM

edata-base Specifies the Spark API With other middleware API Version of , Customize Spark The project can quote itself ,edata-base-component This parent project is referenced .

<?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>com.edata.bigdata</groupId>
    <artifactId>edata-base</artifactId>
    <packaging>pom</packaging>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <java.version>1.8</java.version>
        <scala.version>2.11</scala.version>
        <scala.binary.version>2.11</scala.binary.version>
        <spark.version>2.4.3</spark.version>
        <hadoop.version>3.1.2</hadoop.version>
        <posgresql.version>42.1.1</posgresql.version>
        <nebula.version>2.6.1</nebula.version>
        <flink.version>1.14.3</flink.version>
        <zookeeper.version>3.6.1</zookeeper.version>
    </properties>

    <modules>
        <module>edata-base-component</module>
        <module>edata-bigdata-test</module>
    </modules>

    <dependencies>


        <!--Postgresql-->
        <dependency>
            <groupId>org.postgresql</groupId>
            <artifactId>postgresql</artifactId>
            <version>42.3.1</version>
        </dependency>

        <!--mongodb-->
        <dependency>
            <groupId>org.mongodb.spark</groupId>
            <artifactId>mongo-spark-connector_${scala.version}</artifactId>
            <version>2.4.3</version>
        </dependency>

        <!--Spark-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-hive_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mllib_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>

        <!--ZooKeeper-->
        <dependency>
            <groupId>org.apache.zookeeper</groupId>
            <artifactId>zookeeper</artifactId>
            <version>${zookeeper.version}</version>
        </dependency>
    </dependencies>
    <build>
<!-- <sourceDirectory>src/main/scala</sourceDirectory>-->
<!-- <testSourceDirectory>src/test/scala</testSourceDirectory>-->
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>${java.version}</source>
                    <target>${java.version}</target>
                    <encoding>UTF-8</encoding>
                    <showWarnings>true</showWarnings>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.scala-tools</groupId>
                <artifactId>maven-scala-plugin</artifactId>
                <version>2.15.2</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
<!-- <plugin>-->
<!-- <groupId>org.apache.maven.plugins</groupId>-->
<!-- <artifactId>maven-surefire-plugin</artifactId>-->
<!-- <version>2.19</version>-->
<!-- <configuration>-->
<!-- <skip>true</skip>-->
<!-- </configuration>-->
<!-- </plugin>-->
        </plugins>
    </build>
</project>

edata-base-component Use in custom projects

We can first take a general look at the custom project edata-base-test How to use edata-base-component Of , First of all POM file

<?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">

    <parent>
        <artifactId>edata-base</artifactId>
        <groupId>com.edata.bigdata</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>edata-bigdata-test</artifactId>
    <modelVersion>4.0.0</modelVersion>

    <dependencies>
        <dependency>
            <groupId>com.edata.bigdata</groupId>
            <artifactId>edata-base-component</artifactId>
            <version>1.0-SNAPSHOT</version>
        </dependency>
    </dependencies>
</project>

As shown above ,edata-base-test Refer to the edata-base-component My bag . You can use related libraries as shown below .

package com.edata.bigdata.viewmain
import com.edata.bigdata.bean.MyClass
import com.edata.bigdata.mongo.{
    SparkMongoConnector, SparkMongoImpl}
object testing {
    
  def main(args: Array[String]): Unit = {
    
    // Create a connector 
    val connector:SparkMongoConnector = new SparkMongoConnector()
    connector.appname="SparkMongoTesting"
    connector.master = "local[*]"
    connector.ipport = "192.168.36.141:27017"
    connector.database = "spark"
    connector.collection = "collection"
    connector.username = "admin"
    connector.password = "123456"
    //connector.uri = "mongodb://admin:[email protected]:27017/spark.collection?authSource=admin"
    // establish Spark-mongo Data interaction examples , Assign connector 
    val smi = new SparkMongoImpl[MyClass]
    smi.connector = connector
    val data = smi.find()
    data.first()
    smi.save(data)
  }
}

Custom projects are in use edata-base-component when , Only two steps are needed
（1） establish Spark Connector with other middleware （connector） example .
（2） establish Spark Interface with other intermediate instances , During the creation process, the user-defined case class（ The code above is MyClass）, And assign the connector instance to the interface instance .

edata-base-component The module division of

As shown in the figure below

edata-base-component according to Spark Different partition modules in interaction with mainstream middleware , for example hdfs,mongodb,postgresql etc. , There are also some tool classes , And for customization case class Reflection conversion . Make based on edata-base-component Developed Spark The program can automatically User defined case class convert to DataFrame Medium Schema.

The use of Engineering

take edata-base-component The project is packaged into Jar, And quote in your own custom project ,POM The documents are as follows

<?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">
    <parent>
        <artifactId>edata-base</artifactId>
        <groupId>com.edata.bigdata</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <artifactId>edata-bigdata-test</artifactId>
    <modelVersion>4.0.0</modelVersion>
    <dependencies>
        <dependency>
            <groupId>com.edata.bigdata</groupId>
            <artifactId>edata-base-component</artifactId>
            <version>1.0-SNAPSHOT</version>
        </dependency>
    </dependencies>
</project>

Overall , Can be based on edata-base-component The code of is divided into two parts , Create a connector , as well as call API.

    val connector:KafkaComsumeConnector = new KafkaComsumeConnector()
    connector.appname = "SparkKafkaComsumerTesting"
    connector.master = "local[*]"
    connector.bootstraps = "localhost:9092"
    connector.topic = "topicA"
    connector.group_id = "direct"

    val ski = new SparkKafkaImpl[String,String]
    ski.comsumeConnector = connector
    ski.createDirectStream()

    ski.stream.foreachRDD(rdd=>{
    
      rdd.foreach(println)
      val kvRDD = rdd.map(record=>(record.key,record.value))
      kvRDD.foreach(println)
    })
    ski.start()