【发布时间】:2015-07-17 00:30:48
【问题描述】:
我对 Spark 和 Cassandra 都很陌生,需要一些指导。我正在建立一个使用 Spark v1.3.1 和 Cassandra v2.0.14 的 maven 项目。我正在尝试以下操作:
1) 使用以下方法与Oracle DB建立连接进行数据输入;利用 Spark 1.3.0 的新数据帧:http://www.sparkexpert.com/2015/03/28/loading-database-data-into-spark-using-data-sources-api/
2) 使用 spark-cassandra-connector 进行后者之间的连接;在github上找到。
3) 一旦我在 DataFrame 中有数据库数据,我应该能够转换为 JavaRDD 类型并推送到 Cassandra 键空间,如下所示:http://www.datastax.com/dev/blog/accessing-cassandra-from-spark-in-java
4) 简而言之:[Oracle DB][Cassandra]
我遇到的问题是在我的 Java 代码中的 Scala-lib 调用期间(上面的第 1 步);更具体地说,在加载函数调用期间:DataFrame jdbcDF = sqlContext.load(“jdbc”, options);
运行时错误: java.lang.ClassNotFoundException: scala.collection.GenTraversableOnce$class”
尽管在我的 pom.xml 文件中尝试了推荐的 2.10.X Scala 的几个不同版本,但仍出现上述错误。根据我之前的研究,我认为这可能是 Spark-Scala 兼容性问题。我还读到我需要在我的类路径中包含 scala-lib.jar,但我不确定如何使用 maven 执行此操作。对此有任何想法吗?我在下面包含了 pom.xml 和 java 代码:
POM.XML
<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.dev</groupId>
<artifactId>spark-cassandra</artifactId>
<version>0.0.1-SPARK-CASSANDRA</version>
<dependencies>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>1.3.1</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>1.3.1</version>
</dependency>
<dependency>
<groupId>mysql</groupId>
<artifactId>mysql-connector-java</artifactId>
<version>5.1.35</version>
</dependency>
<dependency>
<groupId>com.oracle</groupId>
<artifactId>ojdbc6</artifactId>
<version>11.2.0</version>
</dependency>
<dependency>
<groupId>com.datastax.spark</groupId>
<artifactId>spark-cassandra-connector_2.10</artifactId>
<version>1.0.0-rc4</version>
</dependency>
<dependency>
<groupId>com.datastax.spark</groupId>
<artifactId>spark-cassandra-connector-java_2.10</artifactId>
<version>1.0.0-rc4</version>
</dependency>
<dependency>
<groupId>com.datastax.cassandra</groupId>
<artifactId>cassandra-driver-core</artifactId>
<version>2.1.5</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-streaming_2.10</artifactId>
<version>1.3.1</version>
</dependency>
<dependency>
<groupId>com.dev.cassandra</groupId>
<artifactId>spark-cassandra</artifactId>
<version>1.0</version>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>2.10.3</version>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-compiler</artifactId>
<version>2.10.3</version>
</dependency>
<!--
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-reflect</artifactId>
<version>2.10.0-M1</version>
</dependency>
-->
<!--
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-swing</artifactId>
<version>2.10.0-M1</version>
</dependency>
-->
</dependencies>
<build>
<pluginManagement>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<version>3.1.5</version>
</plugin>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-compiler-plugin</artifactId>
<version>3.3</version>
<configuration>
<source>1.7</source>
<target>1.7</target>
<mainClass>com.dev.cassandra.Main</mainClass>
<cleanupDaemonThreads>false</cleanupDaemonThreads>
<compilerArgument>-Xlint:all</compilerArgument>
<showWarnings>true</showWarnings>
<showDeprecation>true</showDeprecation>
</configuration>
</plugin>
</plugins>
</pluginManagement>
<plugins>
<plugin>
<groupId>net.alchim31.maven</groupId>
<artifactId>scala-maven-plugin</artifactId>
<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>
</plugin>
<!-- Plugin to create a single jar that includes all dependencies
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<version>2.4</version>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
<archive>
<manifest>
<mainClass>com.dev.cassandra.Main</mainClass>
</manifest>
</archive>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
-->
</plugins>
</build>
</project>
JAVA 代码:
package com.dev.cassandra;
import java.io.Serializable;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.sql.*;
import org.apache.spark.*;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.*;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;
import oracle.jdbc.*;
import com.datastax.spark.connector.cql.CassandraConnector;
import static com.datastax.spark.connector.CassandraJavaUtil.*;
public class Main implements Serializable {
private static final org.apache.log4j.Logger LOGGER = org.apache.log4j.Logger.getLogger(Main.class);
private static final String JDBC_DRIVER = "oracle.jdbc.driver.OracleDriver";
private static final String JDBC_USERNAME = "XXXXXO01";
private static final String JDBC_PWD = "XXXXXO01";
private static final String JDBC_CONNECTION_URL =
"jdbc:oracle:thin:" + JDBC_USERNAME + "/" + JDBC_PWD + "@CONNECTION VALUES";
private transient SparkConf conf;
private Main(SparkConf conf) {
this.conf = conf;
}
private void run() {
JavaSparkContext sc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(sc);
generateData(sc);
compute(sc);
showResults(sc);
sc.stop();
}
private void generateData(JavaSparkContext sc) {
SQLContext sqlContext = new org.apache.spark.sql.SQLContext(sc);
System.out.println("AFTER SQL CONTEXT");
//Data source options
Map<String, String> options = new HashMap<>();
options.put("driver", JDBC_DRIVER);
options.put("url", JDBC_CONNECTION_URL);
options.put("dbtable","(SELECT * FROM XXX_SAMPLE_TABLE WHERE ROWNUM <=5)");
CassandraConnector connector = CassandraConnector.apply(sc.getConf());
try{
Class.forName(JDBC_DRIVER);
System.out.println("BEFORE jdbcDF");
//Load JDBC query result as DataFrame
DataFrame jdbcDF = sqlContext.load("jdbc", options);
System.out.println("AFTER jdbcDF");
List<Row> tableRows = jdbcDF.collectAsList();
System.out.println("AFTER tableRows");
for (Row tableRow : tableRows) {
System.out.println();
LOGGER.info(tableRow);
System.out.println();
}
}catch(Exception e){
//Handle errors for Class.forName
e.printStackTrace();
}
}
private void compute(JavaSparkContext sc) {
}
private void showResults(JavaSparkContext sc) {
}
public static void main(String[] args) throws InterruptedException
{
if (args.length != 2) {
System.err.println("Syntax: com.datastax.spark.dev.cassandra <Spark Master URL> <Cassandra contact point>");
System.exit(1);
}
//JavaSparkContext sc = new JavaSparkContext(new SparkConf().setAppName("SparkJdbcDs").setMaster("local[*]"));
SparkConf conf = new SparkConf().setAppName("SparkJdbcDs").setMaster("local[*]");
//SparkConf conf = new SparkConf();
//conf.setAppName("SparkJdbcDs");
//conf.setMaster(args[0]);
//conf.set("spark.cassandra.connection.host", args[1]);
Main app = new Main(conf);
app.run();
}
}
提前致谢!
【问题讨论】:
-
Spark-Cassandra 连接器还不支持 Spark 1.3.x - 请参阅兼容性表:github.com/datastax/spark-cassandra-connector
-
此外,您的 pom.xml 正在请求 Spark JAR 的 Scala 2.11 版本和 Cassandra JAR 的 Scala 2.10 版本。 (基于 Scala 工件 ID 的命名约定,它以您希望为其构建的 Scala 版本结尾。)这些需要(a)彼此一致,(b)与您实际使用的 Scala 版本一致。
-
@SpiroMichaylov - 非常感谢您的推荐;我的错误,就像你提到的那样,是我在 pom.xml 中调用了错误的 Scala 版本(2.11)。在我的 Spark 依赖项中更改为 2.10 版后,它起作用了。谢谢!
-
@maasg - 由于 spark-cassandra-connector 不支持 Spark 1.3.x,但我可能无法使用下面帖子中使用的 DataFrame 概念来发送/转换 DataFrame卡桑德拉正确吗? sparkexpert.com/2015/03/28/…
-
不,唉,你将无法使用 DataFrame,因为它们是在 1.3.0 中引入的。此外,Cassandra 连接器对 Spark SQL 的支持通常早于 Spark 1.2.0 中引入的外部数据源 API,因此即使对 Spark 1.3.0 的支持出现,它也不一定会立即支持博客文章中描述的方法你参考。 (但是,您可以使用Spark SQL support 获得类似的功能——搜索“SQL”。)
标签: java scala maven cassandra apache-spark