Spark Scala：无法导入 sqlContext.implicits._
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Spark Scala : Unable to import sqlContext.implicits._
提问by sudhir
I tried the below code and cannot import sqlContext.implicits._- it throws an error (in the Scala IDE), unable to build the code:
我尝试了以下代码但无法导入sqlContext.implicits._- 它引发错误（在 Scala IDE 中），无法构建代码：
value implicits is not a member of org.apache.spark.sql.SQLContext
隐式值不是 org.apache.spark.sql.SQLContext 的成员
Do I need to add any dependencies in pom.xml?
我需要在 中添加任何依赖项pom.xml吗？
Spark version 1.5.2
Spark 版本 1.5.2
package com.Spark.ConnectToHadoop
import org.apache.spark.SparkConf
import org.apache.spark.SparkConf
import org.apache.spark._
import org.apache.spark.sql._
import org.apache.spark.sql.hive.HiveContext
import org.apache.spark.sql.SQLContext
import org.apache.spark.rdd.RDD
//import groovy.sql.Sql.CreateStatementCommand
//import org.apache.spark.SparkConf
object CountWords {
def main(args:Array[String]){
val objConf = new SparkConf().setAppName("Spark Connection").setMaster("spark://IP:7077")
var sc = new SparkContext(objConf)
val objHiveContext = new HiveContext(sc)
objHiveContext.sql("USE test")
var rdd= objHiveContext.sql("select * from Table1")
val options=Map("path" -> "hdfs://URL/apps/hive/warehouse/test.db/TableName")
//val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val sqlContext = new SQLContext(sc)
import sqlContext.implicits._ //Error
val dataframe = rdd.toDF()
dataframe.write.format("orc").options(options).mode(SaveMode.Overwrite).saveAsTable("TableName")
}
}
My pom.xml file is as follows
我的pom.xml文件如下
<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.Sudhir.Maven1</groupId>
<artifactId>SparkDemo</artifactId>
<version>0.0.1-SNAPSHOT</version>
<packaging>jar</packaging>
<name>SparkDemo</name>
<url>http://maven.apache.org</url>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
</properties>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.10</artifactId>
<version>1.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.0.0</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.10</artifactId>
<version>1.5.2</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>0.9.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-hive_2.10</artifactId>
<version>1.2.1</version>
</dependency>
<dependency>
<groupId>org.apache.hive</groupId>
<artifactId>hive-jdbc</artifactId>
<version>1.2.1</version>
</dependency>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
<scope>test</scope>
</dependency>
</dependencies>
</project>
采纳答案by Niemand
You use an old version of Spark-SQL. Change it to:
您使用旧版本的 Spark-SQL。将其更改为：
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.10</artifactId>
<version>1.5.2</version>
</dependency>
回答by kasi viswanath
first create
首先创建
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
now we have sqlContextw.r.t sc(this will be available automatically when we launch spark-shell)
now,
现在我们有了sqlContextwrt sc（这将在我们启动 spark-shell 时自动可用），
import sqlContext.implicits._
回答by Marsellus Wallace
With the release of Spark 2.0.0 (July 26, 2016) one should now use the following:
随着 Spark 2.0.0（2016 年 7 月 26 日）的发布，现在应该使用以下内容：
import spark.implicits._ // spark = SparkSession.builder().getOrCreate()
https://databricks.com/blog/2016/08/15/how-to-use-sparksession-in-apache-spark-2-0.html
https://databricks.com/blog/2016/08/15/how-to-use-sparksession-in-apache-spark-2-0.html
回答by Arun Goudar
You can also use
你也可以使用
<properties>
<spark.version>2.2.0</spark.version>
</properties>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
