if value < 3: return 'low' else: return 'high' #convert to a UDF Function by passing in the function and return type of function udfsomefunc = F.udf(somefunc, StringType()) ratings_with_high_low = ratings.withColumn("high_low", udfsomefunc("rating")) ratings_with_high_low.show()...
存储过程中有一个错误,如下所示: Msg 156,级别15,状态1,过程K2_CHECKENTRYINFILELOG,第27行在关键字'if‘附近不正确的语法。Msg 102,15级,状态1,过程K2_CHECKENTRYINFILELOG,第42行错误语法接近'>'.Msg 156,第15级,状态1,过程K2_CHECKENTRYINFILELOG,第55行不正确的语法靠近关键字‘Level’。Msg 156,第15...
import pyspark.sql.functions as Ffrom pyspark.sql.types import * defsomefunc(value):if value < 3:return 'low'else:return 'high' #convert to a UDF Function by passing in the function and return type of functionudfsomefunc = F.udf(somefunc, StringType())ratings_with_high_low = ratings....
The withColumn function in pyspark enables you to make a new variable with conditions, add in the when and otherwise functions and you have a properly working if then else structure. For all of this you would need to import the sparksql functions, as you will see that the followi...
="./bin/spark-submit.cmd"ifon_windowselse"./bin/spark-submit" command = [os.path.join(SPARK_HOME, )] 然后创建 JavaGateway 并 import 一些关键的 class: gateway = JavaGateway( gateway_parameters=GatewayParameters(port=gateway_port, auth_token=gateway_secret, ...
我假设posted数据示例中的"x"像布尔触发器一样工作。那么，为什么不用True替换它，用False替换空的空间...
if((df3.name==df3.KEY) and (df3.id==df3.seq_id)): print("hey") else: print("hey1") 哪里df3 是Dataframe。它抛出以下错误: raise ValueError("Cannot convert column into bool: please use '&' for 'and', '|' for 'or', " ValueError: Cannot convert column into bool: please use...
(day): if day==None: return datetime.datetime.now() else: return datetime.datetime.strptime(day,"%y-%m-%d") # 返回类型为字符串类型 udfday = udf(today, DateType()) df.withColumn('date', udfday(df.date)) # 对每行的指定列进行变换 print(df.show(3)) # 填充缺失值 df=df.fillna('...
when(), else() case(), when() when(), otherwise() if(), else() 第7个问题 What will be the output of the following statement? ceil(2.33, 4.6, 1.09, 10.9) (2, 4, 1, 0) (3, 5, 2, 11) (2.5, 4.5, 1.5, 10.5) (0,0,0,10) ...
If I check the results of the above without the.selectstatement, I get 9 rows with no nulls in thecol(category_name)column but once I add the.selectclause, I get 10 rows with aNULLentry incol(category_name). Why is this happening and how can I fix it (minus adding a.whereclause ...