.toDF()// Register the DataFrame as a temporary viewpeopleDF.createOrReplaceTempView("people")// SQL statements can be run by using the sql methods provided by Sparkval teenagersDF = spark.sql("SELECT name, age FROM people WHERE age BETWEEN 13 AND 19")// The columns of a row in the ...
# Create a simple DataFrame, stored into a partition directory df1 = sqlContext.createDataFrame(sc.parallelize(range(1, 6))\ .map(lambda i: Row(single=i, double=i * 2))) df1.save("data/test_table/key=1", "parquet") # Create another DataFrame in a new partition directory, # adding...
在 Scala 和 Java 中,DataFrame 由一个元素为 Row 的 Dataset 表示。在 Scala API 中,DataFrame 只是 Dataset[Row] 的别名。在 Java API 中,类型为 Dataset。 在本文剩余篇幅中,会经常使用 DataFrame 来代指 Scala/Java 元素为 Row 的 Dataset。 开始 起始点:SparkSession SparkSession是spark2.0所有功能的新...
Learn how to load and transform data using the Apache Spark Python (PySpark) DataFrame API, the Apache Spark Scala DataFrame API, and the SparkR SparkDataFrame API in Databricks.
val teenagers = sqlContext.sql("SELECT name FROM people WHERE age >= 13 AND age <= 19")// 另一种方法是,用一个包含JSON字符串的RDD来创建DataFrameval anotherPeopleRDD = sc.parallelize("""{"name":"Yin","address":{"city":"Columbus","state":"Ohio"}}""":: Nil)...
把得到的schema应用于包含Row对象的RDD,调用这个方法来实现这一步:SQLContext.createDataFrame For example: 例如: // sc 是已有的SparkContext对象 val sqlContext = new org.apache.spark.sql.SQLContext(sc) // 创建一个RDD val people = sc.textFile("examples/src/main/resources/people.txt") // 数据的...
val df2: DataFrame = spark.createDataFrame( sparkContext.parallelize(Row(nestedStructValues2) :: Nil), StructType(Seq(StructField("topLevelCol", nestedStructType2))) val union = df1.unionByName(df2, allowMissingColumns = true) checkAnswer(union, Row(Row(null, "b")) :: Row(Row("a", "...
社区小助手是spark中国社区的管理员，我会定期更新直播回顾等资料和文章干货，还整合了大家在钉群提出的...
Spark ML uses DataFrame from Spark SQL to support a variety of datatypes under a unified dataset concept.Another feature that simplifies handling data that is included in the Spark ML API is the concept of Transformers, by implementing a method - transform() - which helps in data transformation...
创建DataFrame Scala语言 使用SparkSession,应用程序可以从现有的RDD,Hive表的或Spark数据源创建DataFrame 。 例如,以下内容基于JSON文件的内容创建一个DataFrame: valdf = spark.read.json("examples/src/main/resources/people.json")// Displays the content of the DataFrame to stdoutdf.show()// +---+---+...