AI检测代码解析 frompyspark.sqlimportSparkSessionfrompyspark.sql.functionsimportwhen# 创建Spark会话spark=SparkSession.builder \.appName("Replace Character Values in DataFrame")\.getOrCreate()# 创建样本数据data=[("Alice","active"),("Bob","inactive"),("Charlie","banned"),("David","active")]co...
SparkSession spark = SparkSession.builder() .appName("Replace Column Value") .master("local") .getOrCreate(); 读取数据源文件并创建DataFrame: 代码语言:txt 复制 Dataset<Row> data = spark.read() .format("csv") .option("header", "true") .load("path/to/input/file.csv"); 使用withColumn...
// 创建临时视图 df.createOrReplaceTempView("tempTable") // 使用SQL语句修改字段值 val modifiedDf = spark.sql("SELECT oldColumn * 2 as newColumn FROM tempTable") 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. AI检测代码解析 ##示例假设我们有一个包含学生成绩信息的DataFrame,包括学生姓名...
columnName = ((Column) value).getColumnName(); }elseif(value instanceofFunction) { columnName = ((Function) value).toString(); }else{// 增加对select 'aaa' from table; 的支持if(value !=null) { columnName = value.toString(); columnName = columnName.replace("'",""); columnName = ...
df = df.filter(df["column_name"] != value) 复制代码 使用DataFrame的where()方法:可以通过where()方法来过滤数据,也可以实现删除数据的效果。示例如下: df = df.where(df["column_name"] != value) 复制代码 使用SQL语句:可以使用Spark SQL来执行SQL语句来删除数据。示例如下: df.createOrReplaceTempV...
ApplicationMaster 通过该地址向 RM 申请资源、释放资源等 --><property><name>yarn.resourcemanager.scheduler.address</name><value>satori001:8030</value></property><!-- ResourceManager 对 NodeManager暴露的地址 NodeManager 通过该地址向 RM 汇报心跳,领取任务等 --><property><name>yarn.resourcemanager.resource...
("string_column",StringType,nullable=true),StructField("date_column",DateType,nullable=true)))val rdd=spark.sparkContext.parallelize(Seq(Row(1,"First Value",java.sql.Date.valueOf("2010-01-01")),Row(2,"Second Value",java.sql.Date.valueOf("2010-02-01")))val df=spark.createDataFrame(...
[User] // 将UDAF函数转换为查询的列对象 val udafCol: TypedColumn[User, Double] = new MyAvgUDAF().toColumn userDs.select(udafCol.name("avg_age")).show(false) //新版本用法,支持sql中使用 //userDF.createOrReplaceTempView("user") //spark.udf.register("ageAvg", functions.udaf(new MyAvg...
option("header", value = true) .csv("dataset/pm_final.csv") import org.apache.spark.sql.functions._ pmFinal.createOrReplaceTempView("pm_final") val result = spark.sql("select source, year, avg(pm) as pm from pm_final group by source, year " + "grouping sets ((source, year), (...
// 注册DataFrame为临时表df.createOrReplaceTempView("my_temp_table")// 执行查询val resultDF = spark.sql("SELECT * FROM my_temp_table") 3. 使用参数化的SQL查询: // 使用问号占位符val paramValue = "some_value"val resultDF = spark.sql("SELECT * FROM table_name WHERE column_name = ?",...