importorg.apache.spark.sql.SparkSession// 创建SparkSessionvalspark=SparkSession.builder().appName("DataFrameColumnAttributeChange").getOrCreate()// 加载CSV文件valdf=spark.read.option("header","true")// 文件包含列名.option("inferSchema","true")// 推断列的数据类型.csv("path/to/file.csv") 1....
为什么Dataframe不是类型安全的, 而Dataset确实类型安全的 从Apache Spark 2.0开始,这两组API已经被统一然后Dataframe被称为Dataset的别名,这里的Row是一个通用的无类型的JVM对象。然而相反,Dataset是强类型的JVM对象的合集。 Spark是在运行时检查DataFrame的类型的,比如这篇文章。因为DataFrame是Row的集合,Row是一个通用...
DataFrame df = sqlContext.read().load("examples/src/main/resources/users.parquet"); DataFrame df = sqlContext.read().format("json").load("main/resources/people.json"); 1. 2. 旧API 已经被废弃 DataFrame df2 =sqlContext.jsonFile("/xxx.json"); DataFrame df2 =sqlContext.parquetFile("/xxx...
// dataFrame.map => dataSet 转变成DataSet val str = df.select("id", "orddate") .map(x=>{ (daychange(x(1).toString), x(0).toString) }) .rdd.groupByKey().foreach(x=>println(x._1,x._2.size)) __EOF__ 标签:spark PEAR2020 ...
core:负责处理数据的输入/输出,从数据源获取数据,输出 DataFrame; catalyst:SQL 的解析,绑定,优化以及生成物理计划 hive:负责对 hive 数据的处理 hive-thriftserver:提供 CLI 和 JDBC 接口等。 论论文 SparkSQL Catalyst 的解析流程图: SQL 语句经过Antlr4解析,生成Unresolved Logical Plan ...
appName("queryDataFromHudi") .getOrCreate() //读取的数据路径下如果有分区,会自动发现分区数据,需要使用 * 代替,指定到parquet格式数据上层目录即可。 val frame: DataFrame = session.read.format("org.apache.hudi").load("/hudi_data/person_infos/*/*") frame.createTempView("personInfos") //查询...
We can change the order of rows based on the values in columns |2.1 select and selectExpr select and selectExpr allow you to do the DataFrame equivalent of SQL queries on a table of data: # Pythondf.select("DEST_COUNTRY_NAME").show(2)# in SQLSELECTDEST_COUNTRY_NAME,ORIGIN_COUNTRY_NAME...
type DataFrame = Dataset[Row] /** * 元数据键,用于在以下情况下写入Spark版本: * - Parquet文件元数据 * - ORC文件元数据 * - Avro文件元数据 * * 需要注意的是,Hive表属性`spark.sql.create.version`也包含了Spark版本。 */ private[sql] val SPARK_VERSION_METADATA_KEY = "org.apache.spark.version...
Data Wrangler automatically converts Spark DataFrames to pandas samples for performance reasons. However, all the code generated by the tool is ultimately translated to PySpark when it exports back to the notebook. As with any pandas DataFrame, you can customize the default sample by selecting "...
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