/*
 *  Copyright (c) 2017 Uber Technologies, Inc. (hoodie-dev-group@uber.com)
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *           http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 *
 */
package com.uber.hoodie

import java.nio.ByteBuffer
import java.sql.{Date, Timestamp}
import java.util

import com.databricks.spark.avro.SchemaConverters
import org.apache.avro.generic.GenericData.Record
import org.apache.avro.generic.GenericRecord
import org.apache.avro.{Schema, SchemaBuilder}
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.types._
import org.apache.spark.sql.{DataFrame, Row}


object AvroConversionUtils {

  def createRdd(df: DataFrame, structName: String, recordNamespace: String): RDD[GenericRecord] = {
    val dataType = df.schema
    df.rdd.mapPartitions { records =>
      if (records.isEmpty) Iterator.empty
      else {
        val convertor = createConverterToAvro(dataType, structName, recordNamespace)
        records.map { x => convertor(x).asInstanceOf[GenericRecord] }
      }
    }
  }

  def createConverterToAvro(dataType: DataType,
                            structName: String,
                            recordNamespace: String): (Any) => Any = {
    dataType match {
      case BinaryType => (item: Any) =>
        item match {
          case null => null
          case bytes: Array[Byte] => ByteBuffer.wrap(bytes)
        }
      case ByteType | ShortType | IntegerType | LongType |
           FloatType | DoubleType | StringType | BooleanType => identity
      case _: DecimalType => (item: Any) => if (item == null) null else item.toString
      case TimestampType => (item: Any) =>
        if (item == null) null else item.asInstanceOf[Timestamp].getTime
      case DateType => (item: Any) =>
        if (item == null) null else item.asInstanceOf[Date].getTime
      case ArrayType(elementType, _) =>
        val elementConverter = createConverterToAvro(elementType, structName, recordNamespace)
        (item: Any) => {
          if (item == null) {
            null
          } else {
            val sourceArray = item.asInstanceOf[Seq[Any]]
            val sourceArraySize = sourceArray.size
            val targetList = new util.ArrayList[Any](sourceArraySize)
            var idx = 0
            while (idx < sourceArraySize) {
              targetList.add(elementConverter(sourceArray(idx)))
              idx += 1
            }
            targetList
          }
        }
      case MapType(StringType, valueType, _) =>
        val valueConverter = createConverterToAvro(valueType, structName, recordNamespace)
        (item: Any) => {
          if (item == null) {
            null
          } else {
            val javaMap = new util.HashMap[String, Any]()
            item.asInstanceOf[Map[String, Any]].foreach { case (key, value) =>
              javaMap.put(key, valueConverter(value))
            }
            javaMap
          }
        }
      case structType: StructType =>
        val builder = SchemaBuilder.record(structName).namespace(recordNamespace)
        val schema: Schema = SchemaConverters.convertStructToAvro(
          structType, builder, recordNamespace)
        val fieldConverters = structType.fields.map(field =>
          createConverterToAvro(field.dataType, field.name, recordNamespace))
        (item: Any) => {
          if (item == null) {
            null
          } else {
            val record = new Record(schema)
            val convertersIterator = fieldConverters.iterator
            val fieldNamesIterator = dataType.asInstanceOf[StructType].fieldNames.iterator
            val rowIterator = item.asInstanceOf[Row].toSeq.iterator

            while (convertersIterator.hasNext) {
              val converter = convertersIterator.next()
              record.put(fieldNamesIterator.next(), converter(rowIterator.next()))
            }
            record
          }
        }
    }
  }

  def convertStructTypeToAvroSchema(structType: StructType,
                                    structName: String,
                                    recordNamespace: String): Schema = {
    val builder = SchemaBuilder.record(structName).namespace(recordNamespace)
    SchemaConverters.convertStructToAvro(structType, builder, recordNamespace)
  }

  def convertAvroSchemaToStructType(avroSchema: Schema): StructType = {
    SchemaConverters.toSqlType(avroSchema).dataType.asInstanceOf[StructType];
  }
}