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) [Out]: 因此,上面的命令创建了一个新列(age_double),它将年龄值从整数转换为双精度类型。 过滤数据 根据条件筛选记录是处理...
尽管它是用Scala开发的，并在Java虚拟机(JVM)中运行，但它附带了Python绑定，也称为PySpark，其API深受...
We can use thelpadandrpadfunctions for left and right padding, respectively. These functions pad a string column with a specified character or characters to a specified length. In certain data formats or systems, fields may need to be of fixed length. The padding ensures that the strings have...
以下代码片段是数据框的一个快速示例: # spark is an existing SparkSessiondf = spark.read.json("examples/src/main/resources/people.json")# Displays the content of the DataFrame to stdoutdf.show()#+---+---+#| age| name|#+---+---+#+null|Jackson|#| 30| Martin|#| 19| Melvin|#+-...
根据c3字段中的空格将字段内容进行分割,分割的内容存储在新的字段c3_中,如下所示 jdbcDF.explode( "c3" , "c3_" ){time: String => time.split(...返回当前DataFrame中不重复的Row记录。...(pandas_df) 转化为pandas,但是该数据要读入内存,如果数据量大的话,很难跑得动两者的异同: Pyspark DataFrame是...
df= spark.createDataFrame(rdd, ['name','age'])print(df)# DataFrame[name: string, age: bigint]print(type(df.toPandas()))# <class 'pandas.core.frame.DataFrame'># 传入pandas DataFrameoutput = spark.createDataFrame(df.toPandas()).collect()print(output)# [Row(name='Alice', age=1)] ...
data1= hive_context.sql("select col_name from schema_def where data_type<>'string'") colum_names_as_python_list_of_rows= data1.collect() 6)如何按照一定的条件选择某一list中的值: 转变成: 这一思路有如下两种方法: 第一种: df.select("index", f.expr("valuelist[CAST(index AS integer)]...
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...
34. //Create empty hosts array for zero length files 35. 0, length, new String[0])); 36. } 37. } 38. // Save the number of input files for metrics/loadgen 39. job.getConfiguration().setLong(NUM_INPUT_FILES, files.size()); ...
from pyspark.sql.functions import format_string df = spark.createDataFrame([(5, "hello")], ['a', 'b']) df.select(format_string('%d %s', df.a, df.b).alias('v')).withColumnRenamed("v","vv").show() 1. 2. 3. 4.查找字符串的位置 from pyspark.sql.functions import instr df =...