from pyspark.sql import types as T schema = T.ArrayType(T.StructType([ T.StructField('to', T.StringType()), T.StructField('position', T.StringType()) ])) (df .withColumn('temp', F.explode(F.from_json('col1', schema=schema))) .select( F.col('col2'), F.col('temp.to')....
Filter rows from DataFrame Sort DataFrame Rows Using xplode array and map columns torows Explode nested array into rows Using External Data Sources In real-time applications, Data Frames are created from external sources, such as files from the local system, HDFS, S3 Azure, HBase, MySQL table,...
from pyspark.sql import functions as SF df = spark.read.option("multiline", "true").json('/home/abhishek.tirkey/Documents/test') Records = df.withColumn("Records", SF.explode(SF.col("Records"))) Rows = Records.select( "Records.column1", "Records.column2", "Records.column3", "Record...
PySpark Convert String to Array Column PySpark – Convert array column to a String PySpark – explode nested array into rows PySpark Explode Array and Map Columns to Rows PySpark Get Number of Rows and Columns PySpark NOT isin() or IS NOT IN Operator ...
压缩JSON -完全在PySpark中处理还是先解压缩？1.解压缩的文件有多大？Gzip在压缩json和文本方面做得很好...
1、将一个字符或数字列转换为vector/array from pyspark.sql.functions import col,udf from pyspark.ml.linalg import Vectors, _convert_to_vector, VectorUDT, DenseVector # 数字的可转为vector,但字符串转为vector会报错 to_vec = udf(lambda x: DenseVector([x]), VectorUDT()) ...
Scala - flatten array within a Dataframe in Spark, How can i flatten array into dataframe that contain colomns [a,b,c,d,e] root |-- arry: array (nullable = true) | |-- element: struct (containsNull = true) create a Spark DataFrame from a nested array of struct element? 3. Flatt...
将JSON字符串分成多行PySpark看一下您问题中的示例，不清楚addresses列的类型以及输出列中需要的类型。
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