cast函数可以将一个列的值转换为指定的数据类型。 python from pyspark.sql import SparkSession from pyspark.sql.types import IntegerType, StringType # 初始化SparkSession spark = SparkSession.builder.appName("DataTypeConversion").getOrCreate() # 创建一个DataFrame data = [("123", "abc"), ("456...
frompyspark.sql.functionsimportcol# 类型转换df_cleaned=df_cleaned.withColumn("age",col("age").cast("integer"))# 特征选择df_features=df_cleaned.select("age","salary","department") 1. 2. 3. 4. 5. 6. 7. withColumn(): 增加或修改一列的值。 cast(): 转换列的数据类型。 select(): 选取...
cast 改变数据类型 from pyspark.sql.types import * """ __all__ = [ "DataType", "NullType", "StringType", "BinaryType", "BooleanType", "DateType", "TimestampType", "DecimalType", "DoubleType", "FloatType", "ByteType", "IntegerType", "LongType", "ShortType", "ArrayType", "Ma...
def cast_all_to_int(input_df): return input_df.select([col(col_name).cast("int") for col_name in input_df.columns]) def sort_columns_asc(input_df): return input_df.select(*sorted(input_df.columns)) df.transform(cast_all_to_int).transform(sort_columns_asc).show() def add_n(in...
要将age列的数据类型从 integer 改为 double,我们可以使用 Spark 中的cast方法。我们需要从pyspark.types:导入DoubleType [In]:frompyspark.sql.typesimportStringType,DoubleType [In]: df.withColumn('age_double',df['age'].cast(DoubleType())).show(10,False) ...
schema = "orderID INTEGER, customerID INTEGER, productID INTEGER, state STRING, 支付方式 STRING, totalAmt DOUBLE, invoiceTime TIMESTAMP" first_row_is_header = "True" delimiter = "," #将 CSV 文件读入 DataFrame df = spark.read.format(file_type) \ ...
'mile' columnflights_km=flights.withColumn('km',round(flights.mile*1.60934,0))\.drop('mile')# Create 'label' column indicating whether flight delayed (1) or not (0)flights_km=flights_km.withColumn('label',(flights_km.delay>=15).cast('integer'))# Check first five recordsflights_km....
# convert to numeric type data.withColumn("oldCol",data.oldCol.cast("integer")) (2)类别变量处理- onehot encoding # create StringIndexer A_indexer = StringIndexer(inputCol = "A", outputCol = "A_index") A_encoder = OneHotEncoder(inputCol = "A_index", outputCol = "A_fact") (3)将...
cast(IntegerType())) # 计算编码向量大小 indexSize = genreIndexSamples.agg(max(F.col("genreIndexInt"))).head()[0] + 1 # 根据 movieId 聚合genreIndexInt processedSamples = genreIndexSamples.groupBy('movieId').agg( F.collect_list('genreIndexInt').alias('genreIndexes')).withColumn("index...
# 错误日志示例2023-10-1212:35:12ERROR org.apache.spark.sql.execution.datasources.Dataset:Error converting column AgefromStringType to IntegerType. 1. 2. 3. 生态扩展 为了利用 PySpark,通常与其他技术栈联动,例如与 Hadoop 和 Hive 进行集成。以下是生态关系图展示 PySpark 与其他技术的依赖关系。