……

1.首先将集群的这3个文件hive-site.xml,core-size.xml,hdfs-site.xml放到资源文件里(必须,否则报错)

2.代码方面。下面几个测试都可以运行。

  1)test03.java

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import org.apache.spark.sql.SparkSession;
import java.text.ParseException;

public class test03 {
    public static void main(String[] args) throws ParseException {
        SparkSession spark = SparkSession
                .builder()
                .appName("Java Spark Hive Example")
                .master("local[*]")
              //.config("spark.sql.warehouse.dir", "/user/hive/warehouse")
                .config("hadoop.home.dir", "/user/hive/warehouse")
                .enableHiveSupport()
                .getOrCreate();
        spark.sql("SELECT * FROM mt1").show();
    }
}
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 2)Hive03.scala

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import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql.hive.HiveContext

object Hive03 {
  def main(args: Array[String]): Unit = {
    val conf = new SparkConf().setAppName("test").setMaster("local[2]")
    val sc = new SparkContext(conf)
    val sqlContext = new HiveContext(sc)
    sqlContext.table("mt1") // 库名.表名 的格式
      .registerTempTable("person")  // 注册成临时表
    sqlContext.sql(
      """
        | select *
        |   from person
        |  limit 10
      """.stripMargin).show()
    sc.stop()
  }
}
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 3) SparkHiveText.scala

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import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.{SparkConf, SparkContext}
object SparkHiveText {
  def main(args: Array[String]) {
    val conf=new SparkConf().setMaster("local").setAppName("SparkHiveText")
    val sc=new SparkContext(conf)
    val hc=new HiveContext(sc)
    hc.sql("select * from mt1").show()
    sc.stop()
  }
}
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运行时会出现类似这个错误 :出现错误(null) entry in command string: null chmod 0700

    解决办法:

https://github.com/SweetInk/hadoop-common-2.7.1-bin中下载hadoop.dll,并拷贝到c:\windows\system32目录中。

运行结果:

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<?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>
    <properties>
        <spark.version>2.2.1</spark.version>
        <scala.version>2.11</scala.version>
    </properties>


    <dependencies>

        <dependency>
            <groupId>org.codehaus.jettison</groupId>
            <artifactId>jettison</artifactId>
            <version>1.3.4</version>
        </dependency>

        <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-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-sql-kafka-0-10_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mllib_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <!--自己1-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>2.2.1</version>
            <scope>provided</scope>
        </dependency>
        <!-- https://mvnrepository.com/artifact/com.sparkjava/spark-core -->
        <dependency>
            <groupId>com.sparkjava</groupId>
            <artifactId>spark-core</artifactId>
            <version>2.2</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-repl -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-repl_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
   
      <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch-spark-20_2.11</artifactId>
            <version>5.6.3</version>
        </dependency>
        <!--自己2-->
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.41</version>
        </dependency>

        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-lang3</artifactId>
            <version>3.4</version>
        </dependency>

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>
        <!-- simple logg facade for java(slf4-api.jar)日志接口 和 log4j具体日志系统之间的适配器 -->

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.12</version>
        </dependency>


        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.12</version>
        </dependency>
        <!--     -->
        <!-- https://mvnrepository.com/artifact/com.101tec/zkclient -->
        <dependency>
            <groupId>com.101tec</groupId>
            <artifactId>zkclient</artifactId>
            <version>0.10</version>
        </dependency>


    </dependencies>

    <build>
        <plugins>

            <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>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.6.0</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>2.19</version>
                <configuration>
                    <skip>true</skip>
                </configuration>
            </plugin>

        </plugins>
    </build>
</project>
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pom.xml

--------------------------------------------------------------------------------------------------------------------------------------------------------------------------

spark读取的结果并写到hive里

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import org.apache.spark.sql.{SaveMode, SparkSession}

object Hive05 {
  def main(args: Array[String]): Unit = {

    val spark = SparkSession
      .builder().master("local[*]")
      .appName("wer")
      //.config("spark.sql.warehouse.dir", "/user/hive/warehouse") //这行可有可无
      .enableHiveSupport()
      .getOrCreate()
    val df = spark.table("mt1").createOrReplaceTempView("person") //自己hive的表,person是创建的临时视图
       // 注册成临时表
   val tt= spark.sql(" select BUS_NO,CITY_NO,INS_TIME from person")
    tt.show();
    tt.write.mode(SaveMode.Overwrite).saveAsTable("test05")

  }
}
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 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------

遇到问题。hive on spark有很多问题。例如scala和spark兼容问题等等

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import org.apache.spark.sql.SparkSession;
import java.text.ParseException;

public class test03 {
    public static void main(String[] args) throws ParseException {
System.setProperty(
"hadoop.home.dir", "C:\\hadoop-common-2.2.0"); SparkSession spark = SparkSession .builder() .appName("Java Spark Hive Example") .master("local[*]") //.config("spark.sql.warehouse.dir", "/user/hive/warehouse") // .config("hadoop.home.dir", "/user/hive/warehouse") .enableHiveSupport() .getOrCreate(); spark.sql("SELECT * FROM mt1").show(); } }
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 上面是我在网上下载的。下载地址https://github.com/srccodes/hadoop-common-2.2.0-bin

参考博客:https://blog.csdn.net/woshixuye/article/details/53461975

2.还有scala版本不要使用2.12.X。我使用的是maven的2.11 

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<?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>
    <properties>
        <spark.version>2.2.1</spark.version>
        <scala.version>2.11</scala.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>1.2.4</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-protocol</artifactId>
            <version>1.2.4</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-common</artifactId>
            <version>1.2.4</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>1.2.4</version>
        </dependency>
        <!---->
        <dependency>
            <groupId>org.codehaus.jettison</groupId>
            <artifactId>jettison</artifactId>
            <version>1.3.4</version>
        </dependency>


        <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-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-sql-kafka-0-10_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-mllib_${scala.version}</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <!--自己1-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-streaming -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>2.2.1</version>
            <scope>provided</scope>
        </dependency>
        <!-- https://mvnrepository.com/artifact/com.sparkjava/spark-core -->
        <dependency>
            <groupId>com.sparkjava</groupId>
            <artifactId>spark-core</artifactId>
            <version>2.2</version>
        </dependency>
        <!-- https://mvnrepository.com/artifact/org.apache.spark/spark-repl -->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-repl_2.11</artifactId>
            <version>2.2.1</version>
        </dependency>

        <dependency>
            <groupId>org.elasticsearch</groupId>
            <artifactId>elasticsearch-spark-20_2.11</artifactId>
            <version>5.6.3</version>
        </dependency>
        <!--自己2-->
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.17</version>
        </dependency>

        <dependency>
            <groupId>org.apache.commons</groupId>
            <artifactId>commons-lang3</artifactId>
            <version>3.4</version>
        </dependency>

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>
      <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.12</version>
        </dependency>


        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.12</version>
        </dependency>
        <!--     -->
        <!-- https://mvnrepository.com/artifact/com.101tec/zkclient -->
        <dependency>
            <groupId>com.101tec</groupId>
            <artifactId>zkclient</artifactId>
            <version>0.10</version>
        </dependency>
    </dependencies>
    <build>
        <plugins>

            <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>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.6.0</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>2.19</version>
                <configuration>
                    <skip>true</skip>
                </configuration>
            </plugin>

        </plugins>
    </build>
</project>
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*hive设置使用spark 的计算模型

// 使用Hive On Spark非常简单
// 只要用set hive.execution.engine命令设置Hive的执行引擎为spark即可
// 默认是mr
set hive.execution.engine=spark;
// 这里,是完全可以将其设置为Spark Master的URL地址的
set spark.master=spark://192.168.1.107:7077

 

 posted on 2020-09-08 17:29  大码王  阅读(2273)  评论(0编辑  收藏  举报
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