/*
 *  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.util.concurrent.ConcurrentHashMap

import com.uber.hoodie.DataSourceReadOptions._
import com.uber.hoodie.exception.HoodieException
import org.apache.log4j.LogManager
import org.apache.spark.sql.execution.datasources.DataSource
import org.apache.spark.sql.execution.streaming.Sink
import org.apache.spark.sql.sources._
import org.apache.spark.sql.streaming.OutputMode
import org.apache.spark.sql.types.StructType
import org.apache.spark.sql.{DataFrame, SQLContext, SaveMode}

import scala.collection.JavaConversions._
import scala.collection.mutable

/**
  * Hoodie Spark Datasource, for reading and writing hoodie datasets
  *
  */
class DefaultSource extends RelationProvider
  with SchemaRelationProvider
  with CreatableRelationProvider
  with DataSourceRegister
  with StreamSinkProvider
  with Serializable {

  private val log = LogManager.getLogger(classOf[DefaultSource])

  override def createRelation(sqlContext: SQLContext,
                              parameters: Map[String, String]): BaseRelation = {
    createRelation(sqlContext, parameters, null)
  }

  /**
    * Add default options for unspecified read options keys.
    *
    * @param parameters
    * @return
    */
  def parametersWithReadDefaults(parameters: Map[String, String]): mutable.Map[String, String] = {
    val defaultsMap = new ConcurrentHashMap[String, String](mapAsJavaMap(parameters))
    defaultsMap.putIfAbsent(VIEW_TYPE_OPT_KEY, DEFAULT_VIEW_TYPE_OPT_VAL)
    mapAsScalaMap(defaultsMap)
  }

  override def createRelation(sqlContext: SQLContext,
                              optParams: Map[String, String],
                              schema: StructType): BaseRelation = {
    val parameters = parametersWithReadDefaults(optParams)
    val path = parameters.get("path")
    if (path.isEmpty) {
      throw new HoodieException("'path' must be specified.")
    }

    if (parameters(VIEW_TYPE_OPT_KEY).equals(VIEW_TYPE_REALTIME_OPT_VAL)) {
      throw new HoodieException("Realtime view not supported yet via data source. Please use HiveContext route.")
    }

    if (parameters(VIEW_TYPE_OPT_KEY).equals(VIEW_TYPE_INCREMENTAL_OPT_VAL)) {
      new IncrementalRelation(sqlContext, path.get, optParams, schema)
    } else {
      // this is just effectively RO view only, where `path` can contain a mix of
      // non-hoodie/hoodie path files. set the path filter up
      sqlContext.sparkContext.hadoopConfiguration.setClass(
        "mapreduce.input.pathFilter.class",
        classOf[com.uber.hoodie.hadoop.HoodieROTablePathFilter],
        classOf[org.apache.hadoop.fs.PathFilter]);

      log.info("Constructing hoodie (as parquet) data source with options :" + parameters)
      // simply return as a regular parquet relation
      DataSource.apply(
        sparkSession = sqlContext.sparkSession,
        userSpecifiedSchema = Option(schema),
        className = "parquet",
        options = parameters.toMap)
        .resolveRelation()
    }
  }

  override def createRelation(sqlContext: SQLContext,
                              mode: SaveMode,
                              optParams: Map[String, String],
                              df: DataFrame): BaseRelation = {

    val parameters = HoodieSparkSqlWriter.parametersWithWriteDefaults(optParams).toMap
    HoodieSparkSqlWriter.write(sqlContext, mode, parameters, df)
    createRelation(sqlContext, parameters, df.schema)
  }

  override def createSink(sqlContext: SQLContext,
                          optParams: Map[String, String],
                          partitionColumns: Seq[String],
                          outputMode: OutputMode): Sink = {
    val parameters = HoodieSparkSqlWriter.parametersWithWriteDefaults(optParams).toMap
    new HoodieStreamingSink(
      sqlContext,
      parameters,
      partitionColumns,
      outputMode)
  }

  override def shortName(): String = "hoodie"
}