Apache spark SCD-2在数据块中使用增量
我正在尝试构建SCD-2转换,但无法在Databricks中使用Delta实现 例如:Apache spark SCD-2在数据块中使用增量,apache-spark,databricks,delta-lake,Apache Spark,Databricks,Delta Lake,我正在尝试构建SCD-2转换,但无法在Databricks中使用Delta实现 例如: //Base Table val employeeDf = Seq((1,"John","CT"), (2,"Mathew","MA"), (3,"Peter","CA"),
//Base Table
val employeeDf = Seq((1,"John","CT"),
(2,"Mathew","MA"),
(3,"Peter","CA"),
(4,"Joel","NY"))
.toDF("ID","NAME","ADDRESS")
val empBaseDf = employeeDf.withColumn("IS_ACTIVE",lit(1))
.withColumn("EFFECTIVE_DATE",current_date())
.withColumn("TERMINATION_DATE",lit(null).cast(StringType))
empBaseDf.write.format("delta").mode("overwrite").saveAsTable("empBase")
empbaseTable
.as(“基础”)
.merge(processRec.as(“batch1”),“base.ID=mergeKey”)
.whenMatched(“base.IS\u ACTIVE=true和base.address batch1.address”)
.updateExpr(地图(
“是否处于活动状态”->“错误”,
“终止日期”->“当前日期()”)
.whennot匹配()
.insertExpr((映射(“ID”->“batch1.ID”,
“名称”->“batch1.NAME”,
“地址”->“批处理1.地址”,
“是否处于活动状态”->“为真”,
“生效日期”->“当前日期()”,
“终止日期”->“空”))
.execute()
//通过多次运行上述代码,将插入重复记录。我需要限制delta表中的重复条目。
ID名称地址为\u活动生效日期\u终止日期\u
1约翰新罕布什尔州1 2020-06-25零
1约翰CT 0 2020-06-25 2020-06-25
1约翰新罕布什尔州1 2020-06-25零
2马修MA 1 2020-06-25空
3彼得CA 1 2020-06-25零
4 Joel NY 1 2020-06-25无效
5 Adam NJ 1 2020-06-25无效
6菲利普CT 1 2020-06-25无效
我遵循了databricks为SCD-2转换提供的文档,但没有为我工作
任何建议都是有用的。当您为员工记录接收的更新创建新条目时,您必须通过添加谓词
emp.is_ACTIVE=true
,确保更新记录应根据员工表中员工的最新条目进行验证,这将避免重复
// Rows to INSERT new addresses of existing customers
val newAddressesToInsert = empBatch
.as("batch")
.join(empbaseTable.toDF.as("emp"), "ID")
.where("emp.IS_ACTIVE = true and batch.ADDRESS <> emp.ADDRESS").selectExpr("batch.*")
//插入现有客户新地址的行
val newAddressesToInsert=empBatch
.作为(“批次”)
.join(empbaseTable.toDF.as(“emp”),“ID”)
。其中(“emp.IS\u ACTIVE=true和batch.ADDRESS emp.ADDRESS”)。选择expr(“batch.*”)
import io.delta.tables._
val empbaseTable: DeltaTable = DeltaTable.forName("empBase")
val empBatch = table("empBatch")
// Rows to INSERT new addresses of existing customers
val newAddressesToInsert = empBatch
.as("batch")
.join(empbaseTable.toDF.as("emp"), "ID")
.where("batch.ADDRESS <> emp.ADDRESS").selectExpr("batch.*")
newAddressesToInsert.show()
val processRec = newAddressesToInsert
.selectExpr("NULL as mergeKey", "*")
.union(empBatch.selectExpr("ID as mergeKey", "*") )
processRec.show()
empbaseTable
.as("base")
.merge(processRec.as("batch1"),"base.ID = mergeKey")
.whenMatched("base.IS_ACTIVE = true AND base.address <> batch1.address")
.updateExpr(Map(
"IS_ACTIVE" -> "false",
"TERMINATION_DATE" -> "current_date()"))
.whenNotMatched()
.insertExpr((Map("ID" -> "batch1.ID",
"NAME" -> "batch1.NAME",
"ADDRESS" -> "batch1.ADDRESS",
"IS_ACTIVE" -> "true",
"EFFECTIVE_DATE" -> "current_date()",
"TERMINATION_DATE" -> "null" )))
.execute()
//With multiple run of the above code duplicate records are getting inserted. I need to restrict the duplicate entry into the delta table.
ID NAME ADDRESS IS_ACTIVE EFFECTIVE_DATE TERMINATION_DATE
1 John NH 1 2020-06-25 null
1 John CT 0 2020-06-25 2020-06-25
1 John NH 1 2020-06-25 null
2 Mathew MA 1 2020-06-25 null
3 Peter CA 1 2020-06-25 null
4 Joel NY 1 2020-06-25 null
5 Adam NJ 1 2020-06-25 null
6 Philip CT 1 2020-06-25 null
// Rows to INSERT new addresses of existing customers
val newAddressesToInsert = empBatch
.as("batch")
.join(empbaseTable.toDF.as("emp"), "ID")
.where("emp.IS_ACTIVE = true and batch.ADDRESS <> emp.ADDRESS").selectExpr("batch.*")