read.csv("data.csv", header=True, inferSchema=True) # 获取列数据类型 column_types = df.dtypes # 遍历列数据类型列表 for column_name, data_type in column_types: print(f"列名: {column_name}, 数据类型: {data_type}") 上述代码中,首先创建了一个Sp
Column.cast(dataType: Union[pyspark.sql.types.DataType, str]) → pyspark.sql.column.Column 将列强制转换为dataType类型。 sp_df.select(sp_df.linkid.cast("string").alias('linkid_str')).show() 1. 11.contains包含筛选 Column.contains(other: Union[Column, LiteralType, DecimalLiteral, DateTime...
frompyspark.sqlimportSparkSessionfrompyspark.sql.typesimportIntegerType,StringType 1. 2. SparkSession: 创建与Spark数据库的连接。 IntegerType和StringType: 用于定义数据类型。 步骤2: 创建 SparkSession 创建一个 SparkSession 实例,这是使用 PySpark 的入口。 spark=SparkSession.builder \.appName("Data Type ...
from pyspark.sql import SparkSession from pyspark.sql.functions import col from pyspark.sql.types import StringType, IntegerType, DoubleType 创建SparkSession对象: 代码语言:txt 复制 spark = SparkSession.builder.getOrCreate() 加载数据集: 代码语言:txt 复制 df = spark.read.csv("path/to/dataset.csv...
PySpark 提供pyspark.sql.types import StructField类来定义列,包括列名(String)、列类型(DataType)、可空列(Boolean)和元数据(MetaData)。 将PySpark StructType & StructField 与 DataFrame 一起使用 在创建 PySpark DataFrame 时,我们可以使用 StructType 和 StructField 类指定结构。StructType 是 StructField 的集合...
defarrow_to_pandas(self,arrow_column):frompyspark.sql.typesimport_check_series_localize_timestamps#Ifthegivencolumnisadatetypecolumn,createsaseriesofdatetime.datedirectly#insteadofcreatingdatetime64[ns]asintermediatedatatoavoidoverflowcausedby#datetime64[ns]typehandling.s=arrow_column.to_pandas(date_as_obj...
from pyspark.sql import types as stdef ratio(a, b): if a is None or b is None or b == 0: r = -1.0 else: r = 1.0 * a / b return r col_ratio = udf(ratio, st.DoubleType()) df_udf = df.withColumn("ratio", col_ratio(df.age, df.height)) print df_udf.show() """...
from pyspark.sql import DataFrame, SparkSessionimport pyspark.sql.types as Timport pandera.pyspark as paspark = SparkSession.builder.getOrCreate()class PanderaSchema(DataFrameModel): """Test schema""" id: T.IntegerType() = Field(gt=5) product_name: T.StringType() = Field(str_s...
new column name, expression for the new column 第3个问题(多选) Which of the following data types are incompatible with Null values calculations? Boolean Integer Timestamp String 第4 个问题 To remove a column containing NULL values, what is the cut-off of average number of NULL values beyond...
DataFrame column operations withcolumn select when Partitioning and lazy processing cache 计算时间 集群配置 json PYSPARK学习笔记 Defining a schema # Import the pyspark.sql.types library from pyspark.sql.types import * # Define a new schema using the StructType method people_schema = StructType([ # ...