"cast(isGraduated as string) isGraduated", "cast(jobStartDate as string) jobStartDate") 1. 2. 3. 3 sql方法 df=spark.sql("SELECT STRING(age),BOOLEAN(isGraduated),DATE(jobStartDate) from CastExample") df=spark.sql("select cast(age as string),cast(isGraduated as boolean),cast(jobStart...
>>> output Data: >>> [('str', 'string'), ('int', 'bigint')] 方式一:withColumn 覆盖原字段 # cast df.withColumn('int', df.int.cast(DoubleType())).printSchema() >>> output Data: >>> root |-- str: string (nullable = true) |-- int: double (nullable = true) ...
CAST() 在PySpark 中,cast 函数用于将 DataFrame 或列中的数据类型转换为所需的数据类型。它可以用于将某个列的数据类型更改为其他类型,或者在查询中对特定表达式进行类型转换。 使用cast 函数的一般语法如下: df.withColumn("new_column", df["existing_column"].cast(StringType())) 其中,df 是一个 DataFrame...
我有一个多列的pyspark dataframe,我需要将字符串类型转换为正确的类型,例如: 我现在就是这样做的 df = df.withColumn(col_name, col(col_name).col_date, col(col_date).cast('date') \ .withColumn(col_code, col(col_code).cast('bigint') 有没有可能创建一个 浏览11提问于2021-07-10得...
# 将该流转换为String数据类型(key和value都是字节数组形式) # kvstream = dataDF.selectExpr("CAST(key as string)", "CAST(value as string)") kvstream = dataDF.selectExpr("CAST(value as strin ... ... 抱歉,只有登录会员才可浏览!会员登录...
CAST((STOP_TIME - ORIG_TIME) as STRING) IN ('0 seconds','30 minutes')被 (unix_timestamp(STOP_TIME) - unix_timestamp(ORIG_TIME)) <=30*60取代 使用spark API Actual code from pyspark.sql import functions as F from pyspark.sql import Window next_stop_window = Window().partitionBy("US...
我尝试强制转换它:DF.Filters.tostring()和DF.Filters.cast(StringType()),但两种解决方案都会为过滤器列中的每一行生成错误消息: org.apache.spark.sql.catalyst.expressions.UnsafeArrayData@56234c19 代码如下 from pyspark.sql.types import StringType
+---+ |length(CAST(language AS STRING))| +---+ | 3| | 2| | 2| | 2| | 2| | 2| | 2| | 2| | 2| +---+ 10.行的最大值以及最小值 求每一行的最大最小值,相当于axis=1 # 测试数据 df=[(1,1000),(2,2000),(3,3000),(4,4000)] df=spark.createDataFrame(df, schema=...
strap_servers="your_kafka_broker:9092"kafka_topic="your_topic"# 读取 Kafka 数据df=spark.read \.format("kafka")\.option("kafka.bootstrap.servers",kafka_bootstrap_servers)\.option("subscribe",kafka_topic)\.load()# 显示数据df.selectExpr("CAST(key AS STRING)","CAST(value AS STRING)")....
("data.csv") # 将数据写入Kafka主题 data.selectExpr("CAST(column1 AS STRING) AS key", "to_json(struct(*)) AS value") \ .write \ .format("kafka") \ .option("kafka.bootstrap.servers", "kafka_server:9092") \ .option("topic", "topic_name") \ .save() # 关闭SparkSession spark....