【Spark SQL】-データを読み、簡単な照会を行う

    : people.json
   :
{"name":"Michael", "age":12}
{"name":"Andy", "age":30}
{"name":"Justin", "age":19}
{"name":"kafak", "age":19}

 SparkConf conf = new SparkConf()
                .setMaster("local")
                .setAppName("SqlDemo02");
        JavaSparkContext sc = new JavaSparkContext(conf);
        //                        
        sc.setLogLevel("WARN");

        SparkSession spark = SparkSession
                .builder()
                .appName("Java Spark SQL basic example")
                .config("spark.some.config.option", "some-value")
                .getOrCreate();

        /*             appname           */

        DSL(spark);
        System.out.println("*************************************");
        SQL(spark);

        //         !
        spark.stop();
        sc.stop();

 private static void DSL(SparkSession spark) {

        /**
         * 1.    ,           Dataset    
         * 2.        : json , csv ,         , txt   ....
         * 3.      resources   
         * 4.        json("people.json")     
         */
        Dataset df = spark.read().json("SparkSql/src/main/resources/people.json");

        // 1.       
        df.show();
        /**
         * +---+-------+
         * |age|   name|
         * +---+-------+
         * | 12|Michael|
         * | 30|   Andy|
         * | 19| Justin|
         * | 19|  kafak|
         * +---+-------+
         */


        // 2.       
        df.printSchema();
        /**
         *  root
         *  |-- age: long (nullable = true)
         *  |-- name: string (nullable = true)
         */

        // 3.   :     Select   1 ,   2 from people
        /**
         * select("  1" , "  2")
         */
        df.select("age").show();
        /**
         * |age|
         * +---+
         * | 12|
         * | 30|
         * | 19|
         * | 19|
         * +---+
         */

        /**
         * select(Column  1 , Column  2)
         *      : Col                    
         *     : import static org.apache.spark.sql.functions.col;
         *    Col         ,                   .   
         *      functions.col
         *
         * Col(  ) ->    Column   
         * Column                   
         * plus(int n)            n    
         * gt(int n)       n    
         *   
         */
        df.select(col("name"), col("age").plus(1)).show();
        /**
         * +-------+---------+
         * |   name|(age + 1)|
         * +-------+---------+
         * |Michael|       13|
         * |   Andy|       31|
         * | Justin|       20|
         * |  kafak|       20|
         * +-------+---------+
         */

        // 4.     
        /**
         * ->       21      
         * ->          21      col("age").lt(21)
         *   ,          : filter("age > 21")
         *        : age   name          age  int, name String
         *   "age > 21"         ,       "name > 21"      
         *            ,     
         */
        df.filter(col("age").gt(21)).show();
        /**
         * +---+----+
         * |age|name|
         * +---+----+
         * | 30|Andy|
         * +---+----+
         */

        // 5.    
        /**
         *    : groupBy("age").show()       ,                 select("age").show()
         * ->              ,        Count        
         * ->              max()             
         * ->  df.groupBy(col("age")).max().show();
         */
        df.groupBy(col("age")).count().show();
        /**
         * +---+-----+
         * |age|count|
         * +---+-----+
         * | 19|    2|
         * | 12|    1|
         * | 30|    1|
         * +---+-----+
         */

    }

 //   SQL      
    private static void SQL(SparkSession spark) throws AnalysisException {

        //     
        Dataset df = spark.read().json("SparkSql/src/main/resources/people.json");

        // 1.       
        /**
         *    ! :              
         * createOrReplaceTempView :
         * ->                   ,                SparkSession        SaprkSession.stop
         *    SparkSession   ,            ,         SparkSesion           createGlobalTempView
         * createGlobalTempView :         ,   Spark                 ,       SparkSession  
         */
        // 1.       
        df.createOrReplaceTempView("people");

        // 2.       
        Dataset sqlDF_01 = spark.sql("SELECT * FROM people");
        sqlDF_01.show();

        // 3.          
        df.createGlobalTempView("people");
        //       :           ,              global_temp.      
        //                             global_temp    .            
        Dataset sqlDF_02 = spark.sql("SELECT * FROM global_temp.people");
        sqlDF_02.show();

        // 1.        
        /**
         *         ,      SparkContext   (?)               ,      ,          
         *      ,           SparkSession ,   SparkContext     
         */
        SparkSession sparkSession = spark.newSession();
        //       
        Dataset sqlDF_03 = spark.sql("SELECT * FROM global_temp.people");
        Dataset sqlDF_04 = spark.sql("SELECT * FROM people");
        sqlDF_03.show();
        sqlDF_04.show();
    }