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
rows_salaries.json (4M)
<http://apache-spark-user-list.1001560.n3.nabble.com/attachment/27615/0/rows_salaries.json>
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