2. Drop Duplicate Columns After Join If you notice above Join DataFrameemp_idis duplicated on the result, In order to remove this duplicate column, specify the join column as an array type or string. The below example uses array type. Note:In order to use join columns as an array, you ...
resulting in null values in the “dept” columns. Similarly, the “dept_id” 30 does not have a record in the “emp” dataset, hence you observe null values in the “emp” columns. Below is the output of the provided join example. ...
To join two or more DataFrames, use the join method. You can specify how you would like the DataFrames to be joined in the how (the join type) and on (on which columns to base the join) parameters. Common join types include:
Join with automatic suffix handling joined_df = df1.join(df2, df1["Id"] == df2["Id"], how="inner") # Check columns with suffixes (e.g., 'Id', 'col1', 'Id_1', 'col1_1') print("Original columns:", joined_df.columns) # Drop duplicate column clean_df = joined_df.drop("...
ns))2、删除列.drop(''<字段名>'')删除库DROPDATABASEIFEXISTS]< 库名>;DELETEDATABASE<库名>ALL;在Parquet文件中:importsubprocess?subpro cess.check_call(''rm-r<存储路径>''),shell=True)在Hive表中:frompyspark.s qlimportHiveContexthive=HiveContext(spark.sparkContext)hive.s ...
>>> df.join(df2,'name','inner').drop('age','height').collect()[Row(name=u'Bob')] New in version 1.4. dropDuplicates(subset=None)[source] Return a new DataFrame with duplicate rows removed, optionally only considering certain columns. ...
To join two or more DataFrames, use the join method. You can specify how you would like the DataFrames to be joined in the how (the join type) and on (on which columns to base the join) parameters. Common join types include:
Select columns from PySpark DataFrame PySpark Collect() – Retrieve data from DataFrame PySpark withColumn to update or add a column PySpark using where filter function PySpark – Distinct to drop duplicate rows PySpark orderBy() and sort() explained PySpark Groupby Explained with Example PySpark...
Select columns from PySpark DataFrame PySpark Collect() – Retrieve data from DataFrame PySpark withColumn to update or add a column PySpark using where filter function PySpark – Distinct to drop duplicate rows PySpark orderBy() and sort() explained PySpark Groupby Explained with Example PySpark...
df.join(df2, df.name == df2.name, 'inner').drop('name').sort('age').show() #创建新的column或更新重名column,指定column不存在不操作 df.withColumn('age2', df.age + 2).show() df.withColumns({'age2': df.age + 2, 'age3': df.age + 3}).show() #重命名column,指定column不存...