DropDuplicates() 返回一个新的DataFrame,它仅包含此DataFrame中的唯一行。 这是 Distinct () 的别名。 DropDuplicates(String, String[]) 返回一个新的DataFrame,其中删除了重复行,仅考虑列的子集。 C# publicMicrosoft.Spark.Sql.DataFrameDropDuplicates(stringcol,paramsstring[] cols); ...
|2. Intro to SparkDataFrame how to create a spark data frame # create an rdd objectstringJSONRDD=sc.parallelize(("""{ "id": "123","name": "Katie","age": 19,"eyeColor": "brown"}""","""{"id": "234","name": "Michael","age": 22,"eyeColor": "green"}""","""{"id":...
Drop(Int32, IEnumerable<String>) 返回一个新 DataFrame 值,该值删除指定列中包含小于 minNonNulls 非null 和非 NaN 值的行。 Drop(String, IEnumerable<String>) 返回一个新 DataFrame 值,该值删除指定列中包含任何 null 或 NaN 值的行。Drop() 返回一个新 DataFrame 值,该值删除包含任何 null ...
3. withColumnRenamed: 它是DataFrame的API, 可以对DF中的列进行改名, 一次改一个列, 改多个列 可以链式调用 4. orderBy: DataFrame的API, 进行排序, 参数1是被排序的列, 参数2是 升序(True) 或 降序 False 5. first: DataFrame的API, 取出DF的第一行数据, 返回值结果是Row对象. # Row对象 就是一个数...
True>>> spark.catalog.dropTempView("people") New in version 2.0. createTempView(name) 根据dataframe创建一个临时视图 这个视图的生命周期是由创建这个dataframe的SparkSession决定的。如果这个视图已经存在于catalog将抛出TempTableAlreadyExistsException异常。
As shown in the following example, you can use Spark DataFrame transformations to discard columns that you won’t use, filter out anomalous or outlier values such as fare amounts below 0, and calculate the trip time. For more information about the complete code, see thenvidia/spark...
* "value", and followed by partitioned columns if there are any. * The text files must be encoded as UTF-8. * * By default, each line in the text files is a new row in the resulting DataFrame. For example: * {{{ * // Scala: * spark.read.text("/path/to/spark/README.md"...
.drop("Mindate","Maxdate","MinMonday","MaxMonday")) def maskedvalue(col) : return f"""CASE WHEN weekdiff <=1 THEN {col} ELSE 0 END""" out = (df.alias("left").join(tmp.alias("right"), on=[df['id1']==tmp['id1'],df['id2']==tmp['id2'],df['date']<=tmp['Seq'...
Here is an example of updating multiple columns' metadata fields using Spark's Scala API: importorg.apache.spark.sql.types.MetadataBuilder//Specify the custom width of each columnvalcolumnLengthMap=Map("language_code"->2,"country_code"->2,"url"->2083)vardf=...//the dataframe you'll want...
Pipeline: A pipeline chains multiple Transformers and Estimators together to specify an ML workflow. Evaluator: An Evaluator measures the accuracy of a trained Model on label and prediction DataFrame columns. Example Use Case Dataset In this example, we’ll be using the California housing prices dat...