使用 pyspark 插入數據塊

Question

我正在嘗試創建一個 df 並將其存儲為增量表並嘗試執行更新插入。 我在網上找到了這個函數，但只是修改了它以適合我嘗試使用的路徑。

delta_store='s3://raw_data/ETL_test/Delta/'

我創建的 df

Employee = Row("id", "FirstName", "LastName", "Email")
employee1 = Employee('1', 'Basher', 'armbrust', 'bash@gmail.com')
employee2 = Employee('2', 'Daniel', 'meng', 'daniel@stanford.edu')
employee3 = Employee('3', 'Muriel', None, 'muriel@waterloo.edu')
employee4 = Employee('4', 'Rachel', 'wendell', 'rach_3@imaginea.com')
employee5 = Employee('5', 'Zach', 'galifianakis', 'zach_g@pramati.co')
employee6 = Employee('6', 'Ramesh', 'Babu', 'ramesh@pramati.co')
employee7 = Employee('7', 'Bipul', 'Kumar', 'bipul@pramati.co')
employee8 = Employee('8', 'Sampath', 'Kumar', 'sam@pramati.co')
employee9 = Employee('9', 'Anil', 'Reddy', 'anil@pramati.co')
employee10 = Employee('10', 'Mageswaran', 'Dhandapani', 'mageswaran@pramati.co')

compacted_df = spark.createDataFrame([employee1, employee2, employee3, employee4, employee5, employee6, employee7, employee8, employee9, employee10])

display(compacted_df)

插入函數：

def upsert(df, path=DELTA_STORE, is_delete=False):
  """
  Stores the Dataframe as Delta table if the path is empty or tries to merge the data if found
  df : Dataframe 
  path : Delta table store path
  is_delete: Delete the path directory
  """
  if is_delete:
    dbutils.fs.rm(path, True)
  if os.path.exists(path):
    print("Modifying existing table...")
    delta_table = DeltaTable.forPath(spark,delta_store)
    match_expr = "delta.{} = updates.{}".format("id", "id")  and "delta.{} = updates.{}".format("FirstName", "FirstName")
    delta_table.alias("delta").merge(
              df.alias("updates"), match_expr) \
              .whenMatchedUpdateAll() \
              .whenNotMatchedInsertAll() \
              .execute()

  else:
    print("Creating new Delta table")
    df.write.format("delta").save(delta_store)

然后我運行以下代碼來修改數據並遇到如下錯誤：

employee14 = Employee('2', 'Daniel', 'Dang', 'ddang@stanford.edu')
employee15 = Employee('15', 'Anitha', 'Ramasamy', 'anitha@pramati.co')
ingestion_updates_df =  spark.createDataFrame([employee14, employee15])
upsert(df=ingestion_updates_df, is_delete=False) 

錯誤：

AnalysisException: s3://raw_data/ETL_test/Delta already exists.

有人可以解釋我在這里做錯了什么嗎？

Answer 1

這可能只是一個 python - S3 邏輯錯誤。

這個os.path.exists(path)可能總是返回 false 因為它只理解 posix 文件系統而不是 S3 blob 存儲路徑。

在第二次進入您的函數時，您的代碼將進入ELSE分支並最終嘗試在不使用.mode("OVERWRITE")選項的情況下（再次）保存到同一路徑。