org.apache.phoenix.spark.PhoenixRecordWritable.scala Maven / Gradle / Ivy

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/*
   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 org.apache.phoenix.spark

import java.sql.{PreparedStatement, ResultSet}

import org.apache.hadoop.mapreduce.lib.db.DBWritable
import org.apache.phoenix.jdbc.PhoenixResultSet
import org.apache.phoenix.schema.{PTableKey, PTableType}
import org.apache.phoenix.schema.types._
import org.apache.phoenix.util.{ColumnInfo, PhoenixRuntime, SchemaUtil}
import org.joda.time.DateTime

import scala.collection.{immutable, mutable}


class PhoenixRecordWritable(columnMetaDataList: List[ColumnInfo]) extends DBWritable {
  val upsertValues = mutable.ArrayBuffer[Any]()
  val resultMap = mutable.Map[String, AnyRef]()

  def result : immutable.Map[String, AnyRef] = {
    resultMap.toMap
  }

  override def write(statement: PreparedStatement): Unit = {
    // Make sure we at least line up in size
    if(upsertValues.length != columnMetaDataList.length) {
      throw new UnsupportedOperationException(
        s"Upsert values ($upsertValues) do not match the specified columns (columnMetaDataList)"
      )
    }

    // Correlate each value (v) to a column type (c) and an index (i)
    upsertValues.zip(columnMetaDataList).zipWithIndex.foreach {
      case ((v, c), i) => {
        if (v != null) {

          // Both Java and Joda dates used to work in 4.2.3, but now they must be java.sql.Date
          // Can override any other types here as needed
          val (finalObj, finalType) = v match {
            case dt: DateTime => (new java.sql.Date(dt.getMillis), PDate.INSTANCE)
            case d: java.util.Date => (new java.sql.Date(d.getTime), PDate.INSTANCE)
            case _ => (v, c.getPDataType)
          }


          // Helper method to create an SQL array for a specific PDatatype, and set it on the statement
          def setArrayInStatement(obj: Array[AnyRef]): Unit = {
            // Create a java.sql.Array, need to lookup the base sql type name
            val sqlArray = statement.getConnection.createArrayOf(
              PDataType.arrayBaseType(finalType).getSqlTypeName,
              obj
            )
            statement.setArray(i + 1, sqlArray)
          }

          // Determine whether to save as an array or object
          (finalObj, finalType) match {
            case (obj: Array[AnyRef], _) => setArrayInStatement(obj)
            case (obj: mutable.ArrayBuffer[AnyVal], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]).toArray)
            case (obj: mutable.ArrayBuffer[AnyRef], _) => setArrayInStatement(obj.toArray)
            case (obj: mutable.WrappedArray[AnyVal], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]).toArray)
            case (obj: mutable.WrappedArray[AnyRef], _) => setArrayInStatement(obj.toArray)
            case (obj: Array[Int], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case (obj: Array[Long], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case (obj: Array[Char], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case (obj: Array[Short], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case (obj: Array[Float], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case (obj: Array[Double], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            // PVarbinary and PBinary come in as Array[Byte] but they're SQL objects
            case (obj: Array[Byte], _ : PVarbinary) => statement.setObject(i + 1, obj)
            case (obj: Array[Byte], _ : PBinary) => statement.setObject(i + 1, obj)
            // Otherwise set as array type
            case (obj: Array[Byte], _) => setArrayInStatement(obj.map(_.asInstanceOf[AnyRef]))
            case _ => statement.setObject(i + 1, finalObj)
          }
        } else {
          statement.setNull(i + 1, c.getSqlType)
        }
      }
    }
  }

  override def readFields(resultSet: ResultSet): Unit = {
    val rs = resultSet.asInstanceOf[PhoenixResultSet]
    val table = rs.getContext.getCurrentTable.getTable
    val conn = rs.getContext.getConnection
    val metadata = rs.getMetaData
    for(i <- 1 to metadata.getColumnCount) {

      // Return the contents of a PhoenixArray, if necessary
      val value = resultSet.getObject(i) match {
        case x: PhoenixArray => x.getArray
        case y => y
      }

      // Put a (ColumnLabel -> value) entry in the result map
      val columnLabel = metadata.getColumnLabel(i)
      if (table.getType == PTableType.INDEX) {
        val tableFullName = SchemaUtil.getTableName(table.getParentSchemaName.getString, table.getParentTableName.getString)
        val parentTable = conn.getTable(new PTableKey(conn.getTenantId, tableFullName))
        val columnInfo = PhoenixRuntime.getColumnInfo(parentTable, columnLabel)
        resultMap(columnInfo.getDisplayName)= value
      } else {
        val columnInfo = PhoenixRuntime.getColumnInfo(table, columnLabel)
        resultMap(columnInfo.getDisplayName)= value
      }
    }
  }

  def add(value: Any): Unit = {
    upsertValues.append(value)
  }

  // Empty constructor for MapReduce
  def this() = {
    this(List[ColumnInfo]())
  }

}