Fixes compilation error introduced while rebasing

sql/core/src/main/scala/org/apache/spark/sql/parquet/CatalystWriteSupport.scala

@@ -154,8 +154,8 @@ private[parquet] class CatalystWriteSupport extends WriteSupport[InternalRow] wi
         (row: InternalRow, ordinal: Int) =>
           recordConsumer.addBinary(Binary.fromByteArray(row.getBinary(ordinal)))
 
-      case DecimalType.Fixed(precision, _) =>
-        makeDecimalWriter(precision)
+      case DecimalType.Fixed(precision, scale) =>
+        makeDecimalWriter(precision, scale)
 
       case t: StructType =>
         val fieldWriters = t.map(_.dataType).map(makeWriter)
@@ -185,7 +185,7 @@ private[parquet] class CatalystWriteSupport extends WriteSupport[InternalRow] wi
     }
   }
 
-  private def makeDecimalWriter(precision: Int): ValueWriter = {
+  private def makeDecimalWriter(precision: Int, scale: Int): ValueWriter = {
     assert(
       precision <= DecimalType.MAX_PRECISION,
       s"Precision overflow: $precision is greater than ${DecimalType.MAX_PRECISION}")
@@ -194,18 +194,18 @@ private[parquet] class CatalystWriteSupport extends WriteSupport[InternalRow] wi
 
     val int32Writer =
       (row: InternalRow, ordinal: Int) =>
-        recordConsumer.addInteger(row.getDecimal(ordinal).toUnscaledLong.toInt)
+        recordConsumer.addInteger(row.getDecimal(ordinal, precision, scale).toUnscaledLong.toInt)
 
     val int64Writer =
       (row: InternalRow, ordinal: Int) =>
-        recordConsumer.addLong(row.getDecimal(ordinal).toUnscaledLong)
+        recordConsumer.addLong(row.getDecimal(ordinal, precision, scale).toUnscaledLong)
 
     val binaryWriterUsingUnscaledLong =
       (row: InternalRow, ordinal: Int) => {
         // When the precision is low enough (<= 18) to squeeze the decimal value into a `Long`, we
         // can build a fixed-length byte array with length `numBytes` using the unscaled `Long`
         // value and the `decimalBuffer` for better performance.
-        val unscaled = row.getDecimal(ordinal).toUnscaledLong
+        val unscaled = row.getDecimal(ordinal, precision, scale).toUnscaledLong
         var i = 0
         var shift = 8 * (numBytes - 1)
 
@@ -220,14 +220,15 @@ private[parquet] class CatalystWriteSupport extends WriteSupport[InternalRow] wi
 
     val binaryWriterUsingUnscaledBytes =
       (row: InternalRow, ordinal: Int) => {
-        val bytes = row.getDecimal(ordinal).toJavaBigDecimal.unscaledValue().toByteArray
+        val decimal = row.getDecimal(ordinal, precision, scale)
+        val bytes = decimal.toJavaBigDecimal.unscaledValue().toByteArray
         val fixedLengthBytes = if (bytes.length == numBytes) {
           // If the length of the underlying byte array of the unscaled `BigInteger` happens to be
           // `numBytes`, just reuse it, so that we don't bother copying it to `decimalBuffer`.
           bytes
         } else {
           // Otherwise, the length must be less than `numBytes`.  In this case we copy contents of
-          // the underlying bytes with enough sign bytes to `decimalBuffer` to form the result
+          // the underlying bytes with padding sign bytes to `decimalBuffer` to form the result
           // fixed-length byte array.
           val signByte = if (bytes.head < 0) -1: Byte else 0: Byte
           util.Arrays.fill(decimalBuffer, 0, numBytes - bytes.length, signByte)
@@ -250,7 +251,7 @@ private[parquet] class CatalystWriteSupport extends WriteSupport[InternalRow] wi
 
       // All other cases:
       //  - Standard mode, writes decimals with precision > 18 as FIXED_LEN_BYTE_ARRAY
-      //  - Legacy mode, writes decimals with all precision as FIXED_LEN_BYTE_ARRAY
+      //  - Legacy mode, writes decimals with precision > 18 as FIXED_LEN_BYTE_ARRAY
       case _ => binaryWriterUsingUnscaledBytes
     }
   }

sql/core/src/main/scala/org/apache/spark/sql/parquet/ParquetRelation.scala

@@ -38,12 +38,11 @@ import org.apache.parquet.schema.MessageType
 import org.apache.parquet.{Log => ParquetLog}
 
 import org.apache.spark.broadcast.Broadcast
-import org.apache.spark.rdd.{SqlNewHadoopPartition, SqlNewHadoopRDD, RDD}
 import org.apache.spark.rdd.RDD._
+import org.apache.spark.rdd.{RDD, SqlNewHadoopPartition, SqlNewHadoopRDD}
 import org.apache.spark.sql._
 import org.apache.spark.sql.catalyst.InternalRow
 import org.apache.spark.sql.execution.datasources.PartitionSpec
-import org.apache.spark.sql.execution.{SqlNewHadoopPartition, SqlNewHadoopRDD}
 import org.apache.spark.sql.sources._
 import org.apache.spark.sql.types.{DataType, StructType}
 import org.apache.spark.util.{SerializableConfiguration, Utils}