spark sql怎么连接和使用mysql数据源

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spark sql 可以通过标准的jdbc连接数据库，获得数据源

public class SparkSql {public static SimpleDateFormat sdf = new SimpleDateFormat("_yyyyMMdd_HH_mm_ss");    private static final String appName = "spark sql test";    private static final String master = "spark://192.168.1.21:7077";    private static final String JDBCURL = "jdbc:mysql://192.168.1.18:3306/lng?user=root&password=123456";    public static void main(String[] avgs){        SparkContext context = new SparkContext(master, appName);        SQLContext sqlContext = new SQLContext(context);        // Creates a DataFrame based on a table named "people"        // stored in a MySQL database.        DataFrame df = sqlContext                .read()                .format("jdbc")                .option("url", JDBCURL)                .option("dbtable", "tsys_user")                .load();        // Looks the schema of this DataFrame.        df.printSchema();        // Counts people by age        DataFrame countsByAge = df.groupBy("customStyle").count();        countsByAge.show();        // Saves countsByAge to S3 in the JSON format.        countsByAge.write().format("json").save("hdfs://192.168.1.17:9000/administrator/sql-result" + sdf.format(new Date()));    }}

如果没有包含mysql的驱动程序，需要参考http://stackoverflow.com/questions/34764505/no-suitable-driver-found-for-jdbc-in-spark

1. You might want to assembly you application with your build manager (Maven,SBT) thus you'll not need to add the dependecies in your spark-submit cli. （意思就是把mysql的驱动程序打包到提交到spark的jar包里）

2. You can use the following option in your spark-submit cli :(改成下面，经测试，可行，或者加入export SPARK_CLASSPATH=$SPARK_CLASSPATH:/usr/local/spark-1.6.1-bin-hadoop2.6/conf/driverLib/mysql-connector-java-5.1.36.jar 到conf/spark-env.sh）

   spark-submit --driver-class-path /usr/local/spark-1.6.1-bin-hadoop2.6/conf/driverLib/mysql-connector-java-5.1.36.jar --class com.xxx.SparkSql  /usr/local/spark.jar

   
   

   Explanation : Supposing that you have all your jars in a lib directory in your project root, this will read all the libraries and add them to the application submit.

3. You can also try to configure these 2 variables : spark.driver.extraClassPath and spark.executor.extraClassPath in SPARK_HOME/conf/spark-default.conf file and specify the value of these variables as the path of the jar file. Ensure that the same path exists on workernodes.（经测，不行）

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