Parquet檔案

Parquet是一欄位(columnar)格式，可以被許多其它的資料處理系统支援。 Spark SQL 提供支援讀和寫 Parquet 檔案的功能，這些檔案可以自動地保留原始資料的模式。

讀取資料

// sqlContext from the previous example is used in this example.
// createSchemaRDD is used to implicitly convert an RDD to a SchemaRDD.
import sqlContext.createSchemaRDD

val people: RDD[Person] = ... // An RDD of case class objects, from the previous example.

// The RDD is implicitly converted to a SchemaRDD by createSchemaRDD, allowing it to be stored using Parquet.
people.saveAsParquetFile("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 SchemaRDD.
val parquetFile = sqlContext.parquetFile("people.parquet")

//Parquet files can also be registered as tables and then used in SQL statements.
parquetFile.registerTempTable("parquetFile")
val teenagers = sqlContext.sql("SELECT name FROM parquetFile WHERE age >= 13 AND age <= 19")
teenagers.map(t => "Name: " + t(0)).collect().foreach(println)

配置

可以在 SQLContext 上使用 setConf 方法配置 Parquet ．或者在用 SQL 時使用 SET key=value 指令來配置 Parquet。