Parquet中读写Parquet文件的操作是什么？
写回答
// Encoders for most common types are automatically provided by importing spark.implicits._import spark.implicits._
val peopleDF = spark.read.json("examples/src/main/resources/people.json")
// DataFrames can be saved as Parquet files, maintaining the schema informationpeopleDF.write.parquet("people.parquet")
// Read in the parquet file created above// Parquet files are self-describing so the schema is preserved// The result of loading a Parquet file is also a DataFrameval parquetFileDF = spark.read.parquet("people.parquet")
// Parquet files can also be used to create a temporary view and then used in SQL statementsparquetFileDF.createOrReplaceTempView("parquetFile")val namesDF = spark.sql("SELECT name FROM parquetFile WHERE age BETWEEN 13 AND 19")namesDF.map(attributes => "Name: " + attributes(0)).show()// +------------+// | value|// +------------+// |Name: Justin|// +------------+
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