Hello,
Not sure that it will help, but I would do the following
1. Need to create a case class which matches your json schema.
2. Change the following line:
old:
Dataset<Row> rows_salaries = spark.read().json("/Users/
sreeharsha/Downloads/rows_salaries.json");
new:
Dataset<MyCaseClass> rows_salaries = spark.read().json("/Users/
sreeharsha/Downloads/rows_salaries.json").as[MyCaseClass];
3. Make your code compiling successfully
BR,
Denis
On 29 August 2016 at 12:27, Sree Eedupuganti <s...@inndata.in> wrote:
> Here is the snippet of code :
>
> //The entry point into all functionality in Spark is the SparkSession
> class. To create a basic SparkSession, just use SparkSession.builder():
>
> SparkSession spark = SparkSession.builder().appName("Java Spark SQL
> Example").master("local").getOrCreate();
>
> //With a SparkSession, applications can create DataFrames from an existing
> RDD, from a Hive table, or from Spark data sources.
>
> Dataset<Row> rows_salaries = spark.read().json("/Users/
> sreeharsha/Downloads/rows_salaries.json");
>
> // Register the DataFrame as a SQL temporary view
>
> rows_salaries.createOrReplaceTempView("salaries");
>
> // SQL statements can be run by using the sql methods provided by spark
>
> List<Row> df = spark.sql("select * from salaries").collectAsList();
>
> for(Row r:df){
>
> if(r.get(0)!=null)
>
> System.out.println(r.get(0).toString());
>
>
> }
>
>
> Actaul Output :
>
> WrappedArray(WrappedArray(1, B9B42DE1-E810-4489-9735-B365A47A4012, 1,
> 1467358044, 697390, 1467358044, 697390, null, Aaron,Patricia G,
> Facilities/Office Services II, A03031, OED-Employment Dev (031),
> 1979-10-24T00:00:00, 56705.00, 54135.44))
>
> Expecting Output:
>
> Need elements from the WrappedArray
>
> Below you can find the attachment of .json file
>
>
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>
--
//with Best Regards
--Denis Bolshakov
e-mail: bolshakov.de...@gmail.com
