使用Scala编写spark工程代码，将MySQL的shtd_store库中表user_info、sku_info、base_province、base_region、order_info、order_detail的数据增量抽取到Hive的ods库中对应表user_info、sku_info、base_province、base_region、order_info、order_detail中。 抽取shtd_store库中user_info的增量数据进入Hive的ods库中表user_info。根据ods.user_info表中operate_time或create_time作为增量字段(即MySQL中每条数据取这两个时间中较大的那个时间作为增量字段去和ods里的这两个字段中较大的时间进行比较)，只将新增的数据抽入，字段名称、类型不变，同时添加静态分区，分区字段类型为String，且值为当前2023年4月16的前一天日期（分区字段格式为yyyyMMdd）。

import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.functions._
import java.time.LocalDate
import java.time.format.DateTimeFormatter

object IncrementalDataExtraction {
def main(args: Array[String]): Unit = {

// Create Spark session
val spark = SparkSession.builder()
.appName("Incremental Data Extraction")
.enableHiveSupport()
.getOrCreate()

// Set date format for partition column
val dateFormat = DateTimeFormatter.ofPattern("yyyyMMdd")
val partitionDate = LocalDate.of(2023, 4, 15).format(dateFormat)

// Load MySQL tables
val user_info = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "user_info")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

val sku_info = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "sku_info")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

val base_province = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "base_province")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

val base_region = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "base_region")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

val order_info = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "order_info")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

val order_detail = spark.read.format("jdbc")
.option("url", "jdbc:mysql://localhost:3306/shtd_store")
.option("driver", "com.mysql.jdbc.Driver")
.option("dbtable", "order_detail")
.option("user", "your_user_name")
.option("password", "your_password")
.load()

// Add partition column
val user_info_with_static_partition = user_info.withColumn("partition_date", lit(partitionDate))

// Extract incremental data for user_info
val max_operate_time = user_info.select(max("operate_time")).first().getTimestamp(0)
val max_create_time = user_info.select(max("create_time")).first().getTimestamp(0)

val user_info_incremental = user_info_with_static_partition.filter(
col("operate_time") > max_operate_time || col("create_time") > max_create_time
)

// Write incremental data to Hive table
user_info_incremental.write.mode("append").insertInto("ods.user_info")

// Drop temporary tables
user_info.unpersist()
sku_info.unpersist()
base_province.unpersist()
base_region.unpersist()
order_info.unpersist()
order_detail.unpersist()

// Stop Spark session
spark.stop()
}
}