Reworking the deltastreamer tool

- Standardize version of jackson
 - DFSPropertiesConfiguration replaces usage of commons PropertiesConfiguration
 - Remove dependency on ConstructorUtils
 - Throw error if ordering value is not present, during key generation
 - Switch to shade plugin for hoodie-utilities
 - Added support for consumption for Confluent avro kafka serdes
 - Support for Confluent schema registry
 - KafkaSource now deals with skews nicely, by doing round robin allocation of source limit across partitions
 - Added support for BULK_INSERT operations as well
 - Pass in the payload class config properly into HoodieWriteClient
 - Fix documentation based on new usage
 - Adding tests on deltastreamer, sources and all new util classes.

hoodie-spark/src/main/scala/com/uber/hoodie/DefaultSource.scala

@@ -25,10 +25,10 @@ import java.util.{Optional, Properties}
 import com.uber.hoodie.DataSourceReadOptions._
 import com.uber.hoodie.DataSourceWriteOptions._
 import com.uber.hoodie.common.table.{HoodieTableConfig, HoodieTableMetaClient}
+import com.uber.hoodie.common.util.TypedProperties
 import com.uber.hoodie.config.HoodieWriteConfig
 import com.uber.hoodie.exception.HoodieException
 import org.apache.avro.generic.GenericRecord
-import org.apache.commons.configuration.PropertiesConfiguration
 import org.apache.hadoop.fs.Path
 import org.apache.log4j.LogManager
 import org.apache.spark.api.java.JavaSparkContext
@@ -121,10 +121,10 @@ class DefaultSource extends RelationProvider
     mapAsScalaMap(defaultsMap)
   }
 
-  def toPropertiesConfiguration(params: Map[String, String]): PropertiesConfiguration = {
-    val propCfg = new PropertiesConfiguration()
-    params.foreach(kv => propCfg.addProperty(kv._1, kv._2))
-    propCfg
+  def toProperties(params: Map[String, String]): TypedProperties = {
+    val props = new TypedProperties()
+    params.foreach(kv => props.setProperty(kv._1, kv._2))
+    props
   }
 
 
@@ -161,7 +161,7 @@ class DefaultSource extends RelationProvider
     // Convert to RDD[HoodieRecord]
     val keyGenerator = DataSourceUtils.createKeyGenerator(
       parameters(KEYGENERATOR_CLASS_OPT_KEY),
-      toPropertiesConfiguration(parameters)
+      toProperties(parameters)
     )
     val genericRecords: RDD[GenericRecord] = AvroConversionUtils.createRdd(df, structName, nameSpace)
     val hoodieRecords = genericRecords.map(gr => {