Accessing MapR Database in Zeppelin Using the MapR Database Binary Connector

import org.apache.spark.sql.{DataFrame, SQLContext}
import org.apache.spark.{SparkContext, SparkConf}
import org.apache.spark.sql.datasources.hbase.HBaseTableCatalog
case class HBaseRecordClass(
  col0: String,
  col1: Boolean,
  col2: Double,
  col3: Float,
  col4: Int,
  col5: Long,
  col6: Short,
  col7: String,
  col8: Byte)
object HBaseRecord {
  def apply(i:Int): HBaseRecordClass = {
    val s = "row" + "%03d".format(i)
    new HBaseRecordClass(s,
      i % 2 == 0,
      i.toDouble,
      i.toFloat,
      i,
      i.toLong,
      i.toShort,
      s"String$i extra",
      i.toByte)
  }
}
val tableName = "/user/mapruser1/test1" 
val cat = s"""{
          |"table":{"namespace":"default", "name":"$tableName"},
          |"rowkey":"key",
          |"columns":{
            |"col0":{"cf":"rowkey", "col":"key", "type":"string"},
            |"col1":{"cf":"cf1", "col":"col1", "type":"boolean"},
            |"col2":{"cf":"cf2", "col":"col2", "type":"double"},
            |"col3":{"cf":"cf3", "col":"col3", "type":"float"},
            |"col4":{"cf":"cf4", "col":"col4", "type":"int"},
            |"col5":{"cf":"cf5", "col":"col5", "type":"bigint"},
            |"col6":{"cf":"cf6", "col":"col6", "type":"smallint"},
            |"col7":{"cf":"cf7", "col":"col7", "type":"string"},
            |"col8":{"cf":"cf8", "col":"col8", "type":"tinyint"}
            |}
          |}""".stripMargin
val sqlContext = new SQLContext(sc)
import sqlContext.implicits._

def withCatalog(cat: String): DataFrame = {
  sqlContext
    .read
    .options(Map(HBaseTableCatalog.tableCatalog->cat))
    .format("org.apache.hadoop.hbase.spark")
    .load()
}
val data = (0 to 255).map { i =>
  HBaseRecord(i)
}
sc.parallelize(data).toDF.write.options(
  Map(HBaseTableCatalog.tableCatalog -> cat, HBaseTableCatalog.newTable -> "5")).format("org.apache.hadoop.hbase.spark").save()
val df = withCatalog(cat)
df.show