Saving an Apache Spark DataFrame to a HPE Ezmeral Data Fabric Database JSON Table

To save an Apache Spark DataFrame to a HPE Ezmeral Data Fabric Database, invoke the saveToMapRDB method on the DataFrame object (Scala). This returns a DataFrameWriter object, from which you can invoke the saveToMapRDB method. For Java and Python, invoke the saveToMapRDB method on the MapRDBJavaSession object or SparkSession object, respectively.

If a row with the same ID already exists, the savetoMapRDB method updates or overwrites that row. If you want an exception to be thrown in this case, you can use the insertToMapRDB method.

import com.mapr.db.spark.sql._
            
df.write.saveToMapRDB("/tmp/userInfo")
For EEP 4.1.0 and later, you can directly invoke the saveToMapRDB method on the DataFrame object: 
def saveToMapRDB(tableName: String, idFieldPath : String = "_id", createTable: Boolean = false, bulkInsert:Boolean = false): Unit
              
import org.apache.spark.sql.SparkSession
import com.mapr.db.spark.sql._
              
val df = spark.loadFromMapRDB("/tmp/user_profiles")
df.saveToMapRDB(tableName, createTable = true)
For saving a DataFrame (Dataset<Row> ), apply the following method on a MapRDBJavaSession object: 
def saveToMapRDB[T](df: DataFrame[T], tableName: String, idFieldPath: String, createTable: Boolean, bulkInsert: Boolean): Unit 
              
import com.mapr.db.spark.sql.api.java.MapRDBJavaSession;
            
MapRDBJavaSession maprSession = new MapRDBJavaSession(sparkSession);
Dataset<Row> ds = maprSession.loadFromMapRDB("/tmp/user_profiles");

maprSession.saveToMapRDB(ds, "/tmp/userInfo");
For saving a DataFrame, apply the following method on a Dataframe: 
def saveToMapRDB(dataframe, table_name, id_field_path = default_id_field, create_table = False, bulk_insert = False)
              
from pyspark.sql import SparkSession 

df = spark.loadFromMapRDB("/tmp/user_profiles")
            
sparkSession.saveToMapRDB(df, table_name, create_table=True)