spark-shell --conf "spark.serializer=org.apache.spark.serializer.KryoSerializer" --conf "spark.sql.hive.convertMetastoreParquet=false" --jars /usr/lib/hudi/hudi-spark-bundle.jar,/usr/lib/spark/external/lib/spark-avro.jar

import org.apache.spark.sql.SaveMode
import org.apache.spark.sql.functions._
import org.apache.hudi.DataSourceWriteOptions
import org.apache.hudi.config.HoodieWriteConfig
import org.apache.hudi.hive.MultiPartKeysValueExtractor

//Set up various input values as variables
val inputDataPath = "s3://weather-raw-bucket/delta_parquet/"
val hudiTableName = "weather_hudi_cow"
val hudiTablePath = "s3://athena-hudi-bucket/hudi_weather/" + hudiTableName

// Set up our Hudi Data Source Options
val hudiOptions = Map[String,String](
    DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "city_id",
	DataSourceWriteOptions.RECORDKEY_FIELD_OPT_KEY -> "timestamp",
    DataSourceWriteOptions.PARTITIONPATH_FIELD_OPT_KEY -> "date", 
    HoodieWriteConfig.TABLE_NAME -> hudiTableName, 
    DataSourceWriteOptions.OPERATION_OPT_KEY ->
        DataSourceWriteOptions.INSERT_OPERATION_OPT_VAL, 
    DataSourceWriteOptions.PRECOMBINE_FIELD_OPT_KEY -> "timestamp", 
    DataSourceWriteOptions.HIVE_SYNC_ENABLED_OPT_KEY -> "true", 
    DataSourceWriteOptions.HIVE_TABLE_OPT_KEY -> hudiTableName, 
    DataSourceWriteOptions.HIVE_PARTITION_FIELDS_OPT_KEY -> "date", 
    DataSourceWriteOptions.HIVE_PARTITION_EXTRACTOR_CLASS_OPT_KEY ->
        classOf[MultiPartKeysValueExtractor].getName)

// Read data from S3 and create a DataFrame with Partition and Record Key
val inputDF = spark.read.format("parquet").load(inputDataPath)

// Write data into the Hudi dataset
inputDF.write.format("org.apache.hudi").options(hudiOptions).mode(SaveMode.Append).save(hudiTablePath)