Revert "Define public API for spark integration module" for missing JIRA number.

This reverts commit 58b6d9759e.

hbase-common/src/main/java/org/apache/hadoop/hbase/HBaseInterfaceAudience.java

@@ -35,8 +35,6 @@ public final class HBaseInterfaceAudience {
   public static final String COPROC = "Coprocesssor";
   public static final String REPLICATION = "Replication";
   public static final String PHOENIX = "Phoenix";
-  public static final String SPARK = "Spark";
-
   /**
    * Denotes class names that appear in user facing configuration files.
    */

hbase-spark/src/main/java/org/apache/hadoop/hbase/spark/SparkSQLPushDownFilter.java

@@ -20,7 +20,6 @@ package org.apache.hadoop.hbase.spark;
 import org.apache.commons.logging.Log;
 import org.apache.commons.logging.LogFactory;
 import org.apache.hadoop.hbase.Cell;
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.exceptions.DeserializationException;
 import org.apache.hadoop.hbase.filter.FilterBase;
 import org.apache.hadoop.hbase.spark.datasources.BytesEncoder;
@@ -44,7 +43,6 @@ import com.google.protobuf.ByteString;
  * by SparkSQL so that we have make the filters at the region server level
  * and avoid sending the data back to the client to be filtered.
  */
-@InterfaceAudience.Private
 public class SparkSQLPushDownFilter extends FilterBase{
   protected static final Log log = LogFactory.getLog(SparkSQLPushDownFilter.class);
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/BulkLoadPartitioner.scala

@@ -20,8 +20,6 @@ package org.apache.hadoop.hbase.spark
 import java.util
 import java.util.Comparator
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.util.Bytes
 import org.apache.spark.Partitioner
 
@@ -31,8 +29,6 @@ import org.apache.spark.Partitioner
  *
  * @param startKeys   The start keys for the given table
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class BulkLoadPartitioner(startKeys:Array[Array[Byte]])
   extends Partitioner {
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/ByteArrayComparable.scala

@@ -19,12 +19,8 @@
 
 package org.apache.hadoop.hbase.spark
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.util.Bytes
 
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class ByteArrayComparable(val bytes:Array[Byte], val offset:Int = 0, var length:Int = -1)
   extends Comparable[ByteArrayComparable] {
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/ByteArrayWrapper.scala

@@ -18,8 +18,6 @@ package org.apache.hadoop.hbase.spark
 
 import java.io.Serializable
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.util.Bytes
 
 /**
@@ -28,8 +26,6 @@ import org.apache.hadoop.hbase.util.Bytes
  *
  * @param value The Byte Array value
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class ByteArrayWrapper (var value:Array[Byte])
   extends Comparable[ByteArrayWrapper] with Serializable {
   override def compareTo(valueOther: ByteArrayWrapper): Int = {

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/ColumnFamilyQualifierMapKeyWrapper.scala

@@ -17,8 +17,6 @@
 
 package org.apache.hadoop.hbase.spark
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.util.Bytes
 
 /**
@@ -32,8 +30,6 @@ import org.apache.hadoop.hbase.util.Bytes
  * @param qualifierOffSet    Offset of qualifier value in the array
  * @param qualifierLength    Length of the qualifier value with in the array
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class ColumnFamilyQualifierMapKeyWrapper(val columnFamily:Array[Byte],
                                          val columnFamilyOffSet:Int,
                                          val columnFamilyLength:Int,

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/DefaultSource.scala

@@ -20,7 +20,6 @@ package org.apache.hadoop.hbase.spark
 import java.util
 import java.util.concurrent.ConcurrentLinkedQueue
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.client._
 import org.apache.hadoop.hbase.io.ImmutableBytesWritable
 import org.apache.hadoop.hbase.mapred.TableOutputFormat
@@ -46,9 +45,6 @@ import scala.collection.mutable
  * DefaultSource for integration with Spark's dataframe datasources.
  * This class will produce a relationProvider based on input given to it from spark
  *
- * This class needs to stay in the current package 'org.apache.hadoop.hbase.spark'
- * for Spark to match the hbase data source name.
- *
  * In all this DefaultSource support the following datasource functionality
  * - Scan range pruning through filter push down logic based on rowKeys
  * - Filter push down logic on HBase Cells
@@ -56,7 +52,6 @@ import scala.collection.mutable
  * - Type conversions of basic SQL types.  All conversions will be
  *   Through the HBase Bytes object commands.
  */
-@InterfaceAudience.Private
 class DefaultSource extends RelationProvider  with CreatableRelationProvider with Logging {
   /**
    * Is given input from SparkSQL to construct a BaseRelation
@@ -90,7 +85,6 @@ class DefaultSource extends RelationProvider  with CreatableRelationProvider wit
   *
   * @param sqlContext              SparkSQL context
  */
-@InterfaceAudience.Private
 case class HBaseRelation (
     @transient parameters: Map[String, String],
     userSpecifiedSchema: Option[StructType]
@@ -575,7 +569,6 @@ case class HBaseRelation (
  * @param lowerBound          Lower bound of scan
  * @param isLowerBoundEqualTo Include lower bound value in the results
  */
-@InterfaceAudience.Private
 class ScanRange(var upperBound:Array[Byte], var isUpperBoundEqualTo:Boolean,
                 var lowerBound:Array[Byte], var isLowerBoundEqualTo:Boolean)
   extends Serializable {
@@ -729,7 +722,6 @@ class ScanRange(var upperBound:Array[Byte], var isUpperBoundEqualTo:Boolean,
  * @param currentPoint the initial point when the filter is created
  * @param currentRange the initial scanRange when the filter is created
  */
-@InterfaceAudience.Private
 class ColumnFilter (currentPoint:Array[Byte] = null,
                      currentRange:ScanRange = null,
                      var points:mutable.MutableList[Array[Byte]] =
@@ -859,7 +851,6 @@ class ColumnFilter (currentPoint:Array[Byte] = null,
  * Also contains merge commends that will consolidate the filters
  * per column name
  */
-@InterfaceAudience.Private
 class ColumnFilterCollection {
   val columnFilterMap = new mutable.HashMap[String, ColumnFilter]
 
@@ -925,7 +916,6 @@ class ColumnFilterCollection {
  * Status object to store static functions but also to hold last executed
  * information that can be used for unit testing.
  */
-@InterfaceAudience.Private
 object DefaultSourceStaticUtils {
 
   val rawInteger = new RawInteger
@@ -1068,7 +1058,6 @@ object DefaultSourceStaticUtils {
  * @param currentPoint the initial point when the filter is created
  * @param currentRange the initial scanRange when the filter is created
  */
-@InterfaceAudience.Private
 class RowKeyFilter (currentPoint:Array[Byte] = null,
                     currentRange:ScanRange =
                     new ScanRange(null, true, new Array[Byte](0), true),
@@ -1219,6 +1208,7 @@ class RowKeyFilter (currentPoint:Array[Byte] = null,
   }
 }
 
-@InterfaceAudience.Private
+
+
 class ExecutionRuleForUnitTesting(val rowKeyFilter: RowKeyFilter,
                                   val dynamicLogicExpression: DynamicLogicExpression)

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/DynamicLogicExpression.scala

@@ -19,7 +19,6 @@ package org.apache.hadoop.hbase.spark
 
 import java.util
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.spark.datasources.{BytesEncoder, JavaBytesEncoder}
 import org.apache.hadoop.hbase.spark.datasources.JavaBytesEncoder.JavaBytesEncoder
 import org.apache.hadoop.hbase.util.Bytes
@@ -34,7 +33,6 @@ import org.apache.spark.sql.types._
  * A logic tree can be written out as a string and reconstructed from that string
  *
  */
-@InterfaceAudience.Private
 trait DynamicLogicExpression {
   def execute(columnToCurrentRowValueMap: util.HashMap[String, ByteArrayComparable],
               valueFromQueryValueArray:Array[Array[Byte]]): Boolean
@@ -55,7 +53,6 @@ trait DynamicLogicExpression {
   }
 }
 
-@InterfaceAudience.Private
 trait CompareTrait {
   self: DynamicLogicExpression =>
   def columnName: String
@@ -71,7 +68,6 @@ trait CompareTrait {
   }
 }
 
-@InterfaceAudience.Private
 class AndLogicExpression (val leftExpression:DynamicLogicExpression,
                            val rightExpression:DynamicLogicExpression)
   extends DynamicLogicExpression{
@@ -91,7 +87,6 @@ class AndLogicExpression (val leftExpression:DynamicLogicExpression,
   }
 }
 
-@InterfaceAudience.Private
 class OrLogicExpression (val leftExpression:DynamicLogicExpression,
                           val rightExpression:DynamicLogicExpression)
   extends DynamicLogicExpression{
@@ -110,7 +105,6 @@ class OrLogicExpression (val leftExpression:DynamicLogicExpression,
   }
 }
 
-@InterfaceAudience.Private
 class EqualLogicExpression (val columnName:String,
                             val valueFromQueryIndex:Int,
                             val isNot:Boolean) extends DynamicLogicExpression{
@@ -131,7 +125,6 @@ class EqualLogicExpression (val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class IsNullLogicExpression (val columnName:String,
                              val isNot:Boolean) extends DynamicLogicExpression{
   override def execute(columnToCurrentRowValueMap:
@@ -147,7 +140,6 @@ class IsNullLogicExpression (val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class GreaterThanLogicExpression (override val columnName:String,
                                   override val valueFromQueryIndex:Int)
   extends DynamicLogicExpression with CompareTrait{
@@ -157,7 +149,6 @@ class GreaterThanLogicExpression (override val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class GreaterThanOrEqualLogicExpression (override val columnName:String,
                                          override val valueFromQueryIndex:Int)
   extends DynamicLogicExpression with CompareTrait{
@@ -167,7 +158,6 @@ class GreaterThanOrEqualLogicExpression (override val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class LessThanLogicExpression (override val columnName:String,
                                override val valueFromQueryIndex:Int)
   extends DynamicLogicExpression with CompareTrait {
@@ -177,7 +167,6 @@ class LessThanLogicExpression (override val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class LessThanOrEqualLogicExpression (val columnName:String,
                                       val valueFromQueryIndex:Int)
   extends DynamicLogicExpression with CompareTrait{
@@ -187,7 +176,6 @@ class LessThanOrEqualLogicExpression (val columnName:String,
   }
 }
 
-@InterfaceAudience.Private
 class PassThroughLogicExpression() extends DynamicLogicExpression {
   override def execute(columnToCurrentRowValueMap:
                        util.HashMap[String, ByteArrayComparable],
@@ -202,7 +190,6 @@ class PassThroughLogicExpression() extends DynamicLogicExpression {
   }
 }
 
-@InterfaceAudience.Private
 object DynamicLogicExpressionBuilder {
   def build(expressionString: String, encoder: BytesEncoder): DynamicLogicExpression = {
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/FamiliesQualifiersValues.scala

@@ -18,15 +18,10 @@ package org.apache.hadoop.hbase.spark
 
 import java.util
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
-
 /**
  * This object is a clean way to store and sort all cells that will be bulk
  * loaded into a single row
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class FamiliesQualifiersValues extends Serializable {
   //Tree maps are used because we need the results to
   // be sorted when we read them

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/FamilyHFileWriteOptions.scala

@@ -19,9 +19,6 @@ package org.apache.hadoop.hbase.spark
 
 import java.io.Serializable
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
-
 /**
  * This object will hold optional data for how a given column family's
  * writer will work
@@ -32,8 +29,6 @@ import org.apache.hadoop.hbase.classification.InterfaceStability;
  * @param dataBlockEncoding String to define the data block encoding to be used
  *                          in the HFile
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class FamilyHFileWriteOptions( val compression:String,
                                val bloomType: String,
                                val blockSize: Int,

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseContext.scala

@@ -22,8 +22,6 @@ import java.util
 import java.util.UUID
 import javax.management.openmbean.KeyAlreadyExistsException
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.fs.HFileSystem
 import org.apache.hadoop.hbase._
 import org.apache.hadoop.hbase.io.compress.Compression
@@ -60,8 +58,6 @@ import scala.collection.mutable
   * of disseminating the configuration information
   * to the working and managing the life cycle of Connections.
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class HBaseContext(@transient sc: SparkContext,
                    @transient val config: Configuration,
                    val tmpHdfsConfgFile: String = null)

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseDStreamFunctions.scala

@@ -17,8 +17,6 @@
 package org.apache.hadoop.hbase.spark
 
 import org.apache.hadoop.hbase.TableName
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.client._
 import org.apache.hadoop.hbase.io.ImmutableBytesWritable
 import org.apache.spark.streaming.dstream.DStream
@@ -29,8 +27,6 @@ import scala.reflect.ClassTag
  * HBaseDStreamFunctions contains a set of implicit functions that can be
  * applied to a Spark DStream so that we can easily interact with HBase
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 object HBaseDStreamFunctions {
 
   /**

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/HBaseRDDFunctions.scala

@@ -20,8 +20,6 @@ package org.apache.hadoop.hbase.spark
 import java.util
 
 import org.apache.hadoop.hbase.{HConstants, TableName}
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.client._
 import org.apache.hadoop.hbase.io.ImmutableBytesWritable
 import org.apache.spark.rdd.RDD
@@ -32,8 +30,6 @@ import scala.reflect.ClassTag
  * HBaseRDDFunctions contains a set of implicit functions that can be
  * applied to a Spark RDD so that we can easily interact with HBase
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 object HBaseRDDFunctions
 {
 

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/JavaHBaseContext.scala

@@ -19,8 +19,6 @@ package org.apache.hadoop.hbase.spark
 
 import org.apache.hadoop.conf.Configuration
 import org.apache.hadoop.hbase.TableName
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.client.{Connection, Delete, Get, Put, Result, Scan}
 import org.apache.hadoop.hbase.io.ImmutableBytesWritable
 import org.apache.spark.api.java.{JavaRDD, JavaSparkContext}
@@ -38,8 +36,6 @@ import scala.reflect.ClassTag
  * @param jsc    This is the JavaSparkContext that we will wrap
  * @param config This is the config information to out HBase cluster
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class JavaHBaseContext(@transient jsc: JavaSparkContext,
                        @transient config: Configuration) extends Serializable {
   val hbaseContext = new HBaseContext(jsc.sc, config)

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/KeyFamilyQualifier.scala

@@ -19,8 +19,6 @@ package org.apache.hadoop.hbase.spark
 
 import java.io.Serializable
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.util.Bytes
 
 /**
@@ -32,8 +30,6 @@ import org.apache.hadoop.hbase.util.Bytes
  * @param family    Record ColumnFamily
  * @param qualifier Cell Qualifier
  */
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class KeyFamilyQualifier(val rowKey:Array[Byte], val family:Array[Byte], val qualifier:Array[Byte])
   extends Comparable[KeyFamilyQualifier] with Serializable {
   override def compareTo(o: KeyFamilyQualifier): Int = {

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/NewHBaseRDD.scala

@@ -18,14 +18,10 @@
 package org.apache.hadoop.hbase.spark
 
 import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.mapreduce.InputFormat
 import org.apache.spark.rdd.NewHadoopRDD
 import org.apache.spark.{InterruptibleIterator, Partition, SparkContext, TaskContext}
 
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 class NewHBaseRDD[K,V](@transient sc : SparkContext,
                        @transient inputFormatClass: Class[_ <: InputFormat[K, V]],
                        @transient keyClass: Class[K],

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/Bound.scala

@@ -17,7 +17,6 @@
 
 package org.apache.hadoop.hbase.spark.datasources
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.spark.hbase._
 
 /**
@@ -26,14 +25,9 @@ import org.apache.hadoop.hbase.spark.hbase._
  * @param b The byte array of the bound
  * @param inc inclusive or not.
  */
-@InterfaceAudience.Private
 case class Bound(b: Array[Byte], inc: Boolean)
 // The non-overlapping ranges we need to scan, if lower is equal to upper, it is a get request
-
-@InterfaceAudience.Private
 case class Range(lower: Option[Bound], upper: Option[Bound])
-
-@InterfaceAudience.Private
 object Range {
   def apply(region: HBaseRegion): Range = {
     Range(region.start.map(Bound(_, true)), if (region.end.get.size == 0) {
@@ -44,7 +38,6 @@ object Range {
   }
 }
 
-@InterfaceAudience.Private
 object Ranges {
   // We assume that
   // 1. r.lower.inc is true, and r.upper.inc is false
@@ -94,7 +87,6 @@ object Ranges {
   }
 }
 
-@InterfaceAudience.Private
 object Points {
   def and(r: Range, ps: Seq[Array[Byte]]): Seq[Array[Byte]] = {
     ps.flatMap { p =>

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/HBaseResources.scala

@@ -17,7 +17,6 @@
 
 package org.apache.hadoop.hbase.spark.datasources
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.TableName
 import org.apache.hadoop.hbase.client._
 import org.apache.hadoop.hbase.spark.{HBaseConnectionKey, SmartConnection,
@@ -29,12 +28,10 @@ import scala.language.implicitConversions
 
 // User has to invoke release explicitly to release the resource,
 // and potentially parent resources
-@InterfaceAudience.Private
 trait Resource {
   def release(): Unit
 }
 
-@InterfaceAudience.Private
 case class ScanResource(tbr: TableResource, rs: ResultScanner) extends Resource {
   def release() {
     rs.close()
@@ -42,14 +39,12 @@ case class ScanResource(tbr: TableResource, rs: ResultScanner) extends Resource
   }
 }
 
-@InterfaceAudience.Private
 case class GetResource(tbr: TableResource, rs: Array[Result]) extends Resource {
   def release() {
     tbr.release()
   }
 }
 
-@InterfaceAudience.Private
 trait ReferencedResource {
   var count: Int = 0
   def init(): Unit
@@ -89,7 +84,6 @@ trait ReferencedResource {
   }
 }
 
-@InterfaceAudience.Private
 case class TableResource(relation: HBaseRelation) extends ReferencedResource {
   var connection: SmartConnection = _
   var table: Table = _
@@ -119,7 +113,6 @@ case class TableResource(relation: HBaseRelation) extends ReferencedResource {
   }
 }
 
-@InterfaceAudience.Private
 case class RegionResource(relation: HBaseRelation) extends ReferencedResource {
   var connection: SmartConnection = _
   var rl: RegionLocator = _
@@ -151,7 +144,6 @@ case class RegionResource(relation: HBaseRelation) extends ReferencedResource {
   }
 }
 
-@InterfaceAudience.Private
 object HBaseResources{
   implicit def ScanResToScan(sr: ScanResource): ResultScanner = {
     sr.rs

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/HBaseSparkConf.scala

@@ -17,11 +17,6 @@
 
 package org.apache.hadoop.hbase.spark.datasources
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
-
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 object HBaseSparkConf{
   // This is the hbase configuration. User can either set them in SparkConf, which
   // will take effect globally, or configure it per table, which will overwrite the value

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/HBaseTableScanRDD.scala

@@ -19,7 +19,6 @@ package org.apache.hadoop.hbase.spark.datasources
 
 import java.util.ArrayList
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.client._
 import org.apache.hadoop.hbase.spark._
 import org.apache.hadoop.hbase.spark.hbase._
@@ -31,7 +30,6 @@ import org.apache.spark.rdd.RDD
 
 import scala.collection.mutable
 
-@InterfaceAudience.Private
 class HBaseTableScanRDD(relation: HBaseRelation,
                        val hbaseContext: HBaseContext,
                        @transient val filter: Option[SparkSQLPushDownFilter] = None,

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/JavaBytesEncoder.scala

@@ -17,9 +17,6 @@
 
 package org.apache.hadoop.hbase.spark.datasources
 
-import org.apache.hadoop.hbase.HBaseInterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.spark.datasources.JavaBytesEncoder.JavaBytesEncoder
 import org.apache.hadoop.hbase.util.Bytes
 import org.apache.spark.Logging
@@ -32,8 +29,6 @@ import org.apache.spark.sql.types._
   * @param low: the lower bound of the range.
   * @param upper: the upper bound of the range.
   */
-@InterfaceAudience.LimitedPrivate(Array(HBaseInterfaceAudience.SPARK))
-@InterfaceStability.Evolving
 case class BoundRange(low: Array[Byte],upper: Array[Byte])
 
 /**
@@ -45,8 +40,6 @@ case class BoundRange(low: Array[Byte],upper: Array[Byte])
   * @param greater: the set of ranges for GreaterThan/GreaterThanOrEqualTo
   * @param value: the byte array of the original value
   */
-@InterfaceAudience.LimitedPrivate(Array(HBaseInterfaceAudience.SPARK))
-@InterfaceStability.Evolving
 case class BoundRanges(less: Array[BoundRange], greater: Array[BoundRange], value: Array[Byte])
 
 /**
@@ -54,8 +47,6 @@ case class BoundRanges(less: Array[BoundRange], greater: Array[BoundRange], valu
   * encode is used for serializing the data type to byte array and the filter is
   * used to filter out the unnecessary records.
   */
-@InterfaceAudience.LimitedPrivate(Array(HBaseInterfaceAudience.SPARK))
-@InterfaceStability.Evolving
 trait BytesEncoder {
   def encode(dt: DataType, value: Any): Array[Byte]
 
@@ -92,8 +83,6 @@ trait BytesEncoder {
   def ranges(in: Any): Option[BoundRanges]
 }
 
-@InterfaceAudience.LimitedPrivate(Array(HBaseInterfaceAudience.SPARK))
-@InterfaceStability.Evolving
 object JavaBytesEncoder extends Enumeration with Logging{
   type JavaBytesEncoder = Value
   val Greater, GreaterEqual, Less, LessEqual, Equal, Unknown = Value

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/NaiveEncoder.scala

@@ -16,7 +16,6 @@ package org.apache.hadoop.hbase.spark.datasources
  * limitations under the License.
  */
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.spark.datasources.JavaBytesEncoder.JavaBytesEncoder
 import org.apache.hadoop.hbase.spark.hbase._
 import org.apache.hadoop.hbase.util.Bytes
@@ -32,7 +31,6 @@ import org.apache.spark.unsafe.types.UTF8String
   * can work correctly, which is done by wrapping the type into the first byte
   * of the serialized array.
   */
-@InterfaceAudience.Private
 class NaiveEncoder extends BytesEncoder with Logging{
   var code = 0
   def nextCode: Byte = {

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/SchemaConverters.scala

@@ -30,7 +30,6 @@ import org.apache.avro.SchemaBuilder.FieldDefault
 import org.apache.avro.SchemaBuilder.RecordBuilder
 import org.apache.avro.io._
 import org.apache.commons.io.output.ByteArrayOutputStream
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 import org.apache.hadoop.hbase.util.Bytes
 
 import scala.collection.JavaConversions._
@@ -44,10 +43,8 @@ import org.apache.spark.sql.types._
 
 import scala.collection.immutable.Map
 
-@InterfaceAudience.Private
-abstract class AvroException(msg: String) extends Exception(msg)
 
-@InterfaceAudience.Private
+abstract class AvroException(msg: String) extends Exception(msg)
 case class SchemaConversionException(msg: String) extends AvroException(msg)
 
 /***
@@ -58,7 +55,6 @@ case class SchemaConversionException(msg: String) extends AvroException(msg)
   * 3. convertTypeToAvro: This function constructs converter function for a given sparkSQL
   *    datatype. This is used in writing Avro records out to disk
   */
-@InterfaceAudience.Private
 object SchemaConverters {
 
   case class SchemaType(dataType: DataType, nullable: Boolean)
@@ -397,7 +393,7 @@ object SchemaConverters {
   }
 }
 
-@InterfaceAudience.Private
+
 object AvroSerdes {
   // We only handle top level is record or primary type now
   def serialize(input: Any, schema: Schema): Array[Byte]= {

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/SerDes.scala

@@ -28,15 +28,14 @@ import org.apache.avro.generic.{GenericDatumReader, GenericDatumWriter, GenericR
 import org.apache.avro.io._
 import org.apache.commons.io.output.ByteArrayOutputStream
 import org.apache.hadoop.hbase.util.Bytes
+import org.apache.hadoop.hbase.util.Bytes
 import org.apache.spark.sql.types._
 
-// TODO: This is not really used in code.
 trait SerDes {
   def serialize(value: Any): Array[Byte]
   def deserialize(bytes: Array[Byte], start: Int, end: Int): Any
 }
 
-// TODO: This is not really used in code.
 class DoubleSerDes extends SerDes {
   override def serialize(value: Any): Array[Byte] = Bytes.toBytes(value.asInstanceOf[Double])
   override def deserialize(bytes: Array[Byte], start: Int, end: Int): Any = {

hbase-spark/src/main/scala/org/apache/hadoop/hbase/spark/datasources/SerializableConfiguration.scala

@@ -20,11 +20,9 @@ package org.apache.hadoop.hbase.spark.datasources
 import java.io.{IOException, ObjectInputStream, ObjectOutputStream}
 
 import org.apache.hadoop.conf.Configuration
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
 
 import scala.util.control.NonFatal
 
-@InterfaceAudience.Private
 class SerializableConfiguration(@transient var value: Configuration) extends Serializable {
   private def writeObject(out: ObjectOutputStream): Unit = tryOrIOException {
     out.defaultWriteObject()

hbase-spark/src/main/scala/org/apache/spark/sql/datasources/hbase/DataTypeParserWrapper.scala

@@ -21,7 +21,6 @@ import org.apache.spark.sql.catalyst.SqlLexical
 import org.apache.spark.sql.catalyst.util.DataTypeParser
 import org.apache.spark.sql.types.DataType
 
-// TODO:  Only used in test suite.
 object DataTypeParserWrapper {
   lazy val dataTypeParser = new DataTypeParser {
     override val lexical = new SqlLexical

hbase-spark/src/main/scala/org/apache/spark/sql/datasources/hbase/HBaseTableCatalog.scala

@@ -18,8 +18,6 @@
 package org.apache.spark.sql.datasources.hbase
 
 import org.apache.avro.Schema
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-import org.apache.hadoop.hbase.classification.InterfaceStability;
 import org.apache.hadoop.hbase.spark.SchemaConverters
 import org.apache.hadoop.hbase.spark.datasources._
 import org.apache.hadoop.hbase.spark.hbase._
@@ -34,7 +32,6 @@ import scala.collection.mutable
 // Due the access issue defined in spark, we have to locate the file in this package.
 // The definition of each column cell, which may be composite type
 // TODO: add avro support
-@InterfaceAudience.Private
 case class Field(
     colName: String,
     cf: String,
@@ -115,7 +112,6 @@ case class Field(
 
 // The row key definition, with each key refer to the col defined in Field, e.g.,
 // key1:key2:key3
-@InterfaceAudience.Private
 case class RowKey(k: String) {
   val keys = k.split(":")
   var fields: Seq[Field] = _
@@ -131,7 +127,6 @@ case class RowKey(k: String) {
   }
 }
 // The map between the column presented to Spark and the HBase field
-@InterfaceAudience.Private
 case class SchemaMap(map: mutable.HashMap[String, Field]) {
   def toFields = map.map { case (name, field) =>
     StructField(name, field.dt)
@@ -144,7 +139,6 @@ case class SchemaMap(map: mutable.HashMap[String, Field]) {
 
 
 // The definition of HBase and Relation relation schema
-@InterfaceAudience.Private
 case class HBaseTableCatalog(
      namespace: String,
      name: String,
@@ -209,8 +203,6 @@ case class HBaseTableCatalog(
   initRowKey
 }
 
-@InterfaceAudience.Public
-@InterfaceStability.Evolving
 object HBaseTableCatalog {
   // If defined and larger than 3, a new table will be created with the nubmer of region specified.
   val newTable = "newtable"
@@ -294,7 +286,6 @@ object HBaseTableCatalog {
                       |}""".stripMargin
    */
   @deprecated("Please use new json format to define HBaseCatalog")
-  // TODO: There is no need to deprecate since this is the first release.
   def convert(parameters: Map[String, String]): Map[String, String] = {
     val tableName = parameters.get(TABLE_KEY).getOrElse(null)
     // if the hbase.table is not defined, we assume it is json format already.
@@ -328,7 +319,6 @@ object HBaseTableCatalog {
     * @param schemaMappingString The schema mapping string from the SparkSQL map
     * @return                    A map of definitions keyed by the SparkSQL column name
     */
-  @InterfaceAudience.Private
   def generateSchemaMappingMap(schemaMappingString:String):
   java.util.HashMap[String, SchemaQualifierDefinition] = {
     println(schemaMappingString)
@@ -372,7 +362,6 @@ object HBaseTableCatalog {
   * @param columnFamily HBase column family
   * @param qualifier    HBase qualifier name
   */
-@InterfaceAudience.Private
 case class SchemaQualifierDefinition(columnName:String,
     colType:String,
     columnFamily:String,

hbase-spark/src/main/scala/org/apache/spark/sql/datasources/hbase/Utils.scala

@@ -24,9 +24,6 @@ import org.apache.spark.sql.execution.SparkSqlSerializer
 import org.apache.spark.sql.types._
 import org.apache.spark.unsafe.types.UTF8String
 
-import org.apache.hadoop.hbase.classification.InterfaceAudience;
-
-@InterfaceAudience.Private
 object Utils {