fix file size

src/main/scala/net/snowflake/spark/snowflake/io/CloudStorageOperations.scala

@@ -43,6 +43,7 @@ import net.snowflake.spark.snowflake.Parameters.MergedParameters
 import net.snowflake.spark.snowflake.io.SupportedFormat.SupportedFormat
 import net.snowflake.spark.snowflake.DefaultJDBCWrapper.DataBaseOperations
 import net.snowflake.spark.snowflake.test.{TestHook, TestHookFlag}
+import org.apache.avro.Schema
 import org.apache.avro.file.DataFileWriter
 import org.apache.avro.generic.{GenericData, GenericDatumWriter, GenericRecord}
 import org.apache.commons.io.IOUtils
@@ -485,6 +486,8 @@ sealed trait CloudStorage {
   protected val sfURL: String = param.sfURL
   protected val useExponentialBackoff: Boolean = param.useExponentialBackoff
 
+  protected var avroSchema: Option[String] = None
+
   // The first 10 sleep time in second will be like
   // 3, 6, 12, 24, 48, 96, 192, 300, 300, 300, etc
   protected def retrySleepTimeInMS(retry: Int): Int = {
@@ -658,7 +661,7 @@ sealed trait CloudStorage {
       try {
         format match {
           case SupportedFormat.PARQUET =>
-            val avroSchema = io.ParquetUtils.convertStructToAvro(schema)
+            val avroSchema = new Schema.Parser().parse(this.avroSchema.get)
             val config = new Configuration()
             config.setBoolean("parquet.avro.write-old-list-structure", false)
             val writer = AvroParquetWriter.builder[GenericData.Record](
@@ -672,7 +675,6 @@ sealed trait CloudStorage {
                 writer.write(ParquetUtils.rowToAvroRecord(row, avroSchema, schema, param))
                 rowCount += 1
             }
-            dataSize += writer.getDataSize
             writer.close()
           case _ =>
             val rows = input.asInstanceOf[Iterator[String]]
@@ -728,11 +730,12 @@ sealed trait CloudStorage {
       )
     }
 
+    val dataSizeStr = if (dataSize == 0) "N/A" else Utils.getSizeString(dataSize)
     CloudStorageOperations.log.info(
       s"""${SnowflakeResultSetRDD.WORKER_LOG_PREFIX}:
          | Finish writing partition ID:$partitionID $fileName
          | write row count is $rowCount.
-         | Uncompressed data size is ${Utils.getSizeString(dataSize)}.
+         | Uncompressed data size is $dataSizeStr.
          | $processTimeInfo
          |""".stripMargin.filter(_ >= ' '))
 
@@ -758,6 +761,16 @@ sealed trait CloudStorage {
          | partitions: directory=$directory ${format.toString} $compress
          |""".stripMargin.filter(_ >= ' '))
 
+    // 1. Avro Schema is not serializable in Spark 3.1.1.
+    // 2. Somehow, the Avro Schema can be created only one time with Schema builder.
+    // Therefore, if we create schema in the mapPartition function, we will get some error.
+    // e.g. cannot process decimal data.
+    // Alternatively, we create schema only one time here, and serialize the Json string to
+    // each partition, and then deserialize the Json string to avro schema in the partition.
+    if (format == SupportedFormat.PARQUET) {
+      this.avroSchema = Some(io.ParquetUtils.convertStructToAvro(schema).toString())
+    }
+
     // Some explain for newbies on spark connector:
     // Bellow code is executed in distributed by spark FRAMEWORK
     // 1. The master node executes "data.mapPartitionsWithIndex()"

src/main/scala/net/snowflake/spark/snowflake/io/StageWriter.scala

@@ -562,10 +562,11 @@ private[io] object StageWriter {
         totalSize += fileUploadResult.fileSize
         totalRowCount += fileUploadResult.rowCount
       })
+    val fileSizeStr = if (totalSize == 0) "N/A" else Utils.getSizeString(totalSize)
     logAndAppend(progress, s"Total file count is ${fileUploadResults.size}, " +
       s"non-empty files count is ${expectedFileSet.size}, " +
-      s"total file size is ${Utils.getSizeString(totalSize)}, " +
-      s"total row count is ${Utils.getSizeString(totalRowCount)}.")
+      s"total file size is $fileSizeStr, " +
+      s"total row count is $totalRowCount.")
 
     // Indicate whether to use FILES clause in the copy command
     var useFilesClause = false