Read specific column from Parquet without using Spark

问题

I am trying to read Parquet files without using Apache Spark and I am able to do it but I am finding it hard to read specific columns. I am not able to find any good resource of Google as almost all the post is about reading the parquet file using. Below is my code:

import org.apache.hadoop.fs.{FileSystem, Path}
import org.apache.avro.generic.GenericRecord
import org.apache.parquet.hadoop.ParquetReader
import org.apache.parquet.avro.AvroParquetReader

object parquetToJson{
  def main (args : Array[String]):Unit= {
 //case class Customer(key: Int, name: String, sellAmount: Double, profit: Double, state:String)
val parquetFilePath = new Path("data/parquet/Customer/")
val reader = AvroParquetReader.builder[GenericRecord](parquetFilePath).build()//.asInstanceOf[ParquetReader[GenericRecord]]
val iter = Iterator.continually(reader.read).takeWhile(_ != null)
val list = iter.toList
list.foreach(record => println(record))
}
}

The commented out case class represents the schema of my file and write now the above code reads all the columns from the file. I want to read specific columns.

回答1:

If you just want to read specific columns, then you need to set a read schema on the configuration that the ParquetReader builder accepts. (This is also known as a projection).

In your case you should be able to call .withConf(conf) on the AvroParquetReader builder class, and in the conf you pass in, invoke conf.set(ReadSupport.PARQUET_READ_SCHEMA, schema) where schema is a avro schema in String form.

来源：https://stackoverflow.com/questions/42613403/read-specific-column-from-parquet-without-using-spark