df.filter( df.age.isin([1,2,3])).show()+---+---+|age| name|+---+---+| 2|Alice|+---+---+ when 与 otherwise 配合使用 如果未调用Column.otherwise(),则对于不匹配的条件将返回None df = spark.createDataFrame( [(2, "Alice"), (5, "Bob")], ["age", "name"])df.show()+...
filter(condition) 根据条件对DataFrame进行过滤 where(condition)和filter(condition)是同一个函数 (1.3版本新增) 1. 2. 3. 参数: condition ——– 一个由types.BooleanType组成的Column对象,或一个内容为SQL表达式的字符串 >>> df.filter(df.age > 3).collect() [Row(age=5, name=u'Bob')] >>> df...
val rdd = lines.rdd.filter(line => !line.toString.contains("SECURITIES|")) .map(line => line.toString().split("\\|")) .map(line => Row( line(0), line(1),line(2),line(3),line(4), line(5),line(6),line(7),line(8) )) // Scame,这里先全部以 String 类型处理 val schema...
因此,返回到 PySpark 终端;我们已经将原始数据作为文本文件加载,就像我们在之前的章节中看到的那样。 我们将编写一个filter函数来查找所有包含单词normal的行,指示 RDD 数据,如下面的屏幕截图所示: contains_normal = raw_data.filter(lambdaline:"normal."inline) 让我们分析一下这意味着什么。首先,我们正在为 RDD ...
spark.sql("CREATE TABLE IF NOT EXISTS src (key INT, value STRING) USING hive")spark.sql("LOAD DATA LOCAL INPATH 'data/kv1.txt' INTO TABLE src")df=spark.sql("SELECT key, value FROM src WHERE key < 10 ORDER BY key")df.show(5)#5.2读取mysql数据 ...
accept_value= when(col("column1") < 0.9, 1).otherwise(0) 浏览3提问于2022-03-29得票数 1 1回答 在多行语句之间插入注释(行续写) 、、 当我编写以下pyspark命令时:df = df.withColumn('explosion', explode(col('col1'))).filter(col('explosion')['sub_col1'] == 'some_string') \ ...
value – 一个文字值或一个Column表达式 >>> df.select(when(df['age'] == 2, 3).otherwise(4).alias("age")).collect() [Row(age=3), Row(age=4)] >>> df.select(when(df.age == 2, df.age + 1).alias("age")).collect() [Row(age=3), Row(age=None)] df3 = df.withColumn(...
DataFrame column operations 对数据框列的操作 筛选操作 # Show the distinct VOTER_NAME entries voter_df.select(voter_df['VOTER_NAME']).distinct().show(40, truncate=False) 去除重复值 # Filter voter_df where the VOTER_NAME is 1-20 characters in length voter_df = voter_df.filter('length(VOT...
# keep rows with certain length data.filter("length(col) > 20") # get distinct value of the column data.select("col").distinct() # remove row which has certain character data.filter(~F.col('col').contains('abc')) 列值处理 (1)列值分割 # split column based on space data = data...
Filter rowsTo filter rows, use the filter or where method on a DataFrame to return only certain rows. To identify a column to filter on, use the col method or an expression that evaluates to a column.Python Копирај from pyspark.sql.functions import col df_that_one_customer =...