Spark学习笔记——读写HDFS
Posted tags:
篇首语：本文由小常识网(cha138.com)小编为大家整理，主要介绍了Spark学习笔记——读写HDFS相关的知识，希望对你有一定的参考价值。
使用Spark读写HDFS中的parquet文件
文件夹中的parquet文件
build.sbt文件
name := "spark-hbase" version := "1.0" scalaVersion := "2.11.8" libraryDependencies ++= Seq( "org.apache.spark" %% "spark-core" % "2.1.0", "mysql" % "mysql-connector-java" % "5.1.31", "org.apache.spark" %% "spark-sql" % "2.1.0", "org.apache.hbase" % "hbase-common" % "1.3.0", "org.apache.hbase" % "hbase-client" % "1.3.0", "org.apache.hbase" % "hbase-server" % "1.3.0", "org.apache.hbase" % "hbase" % "1.2.1" )
Scala实现方法
import org.apache.spark.{SparkConf, SparkContext}
import org.apache.spark.sql._
import java.util.Properties
import com.google.common.collect.Lists
import org.apache.spark.sql.types.{ArrayType, StringType, StructField, StructType}
import org.apache.hadoop.hbase.HBaseConfiguration
import org.apache.hadoop.hbase.client.{Result, Scan}
import org.apache.hadoop.hbase.io.ImmutableBytesWritable
import org.apache.hadoop.hbase.mapreduce.TableInputFormat
/**
* Created by mi on 17-4-11.
*/
case class resultset(name: String,
info: String,
summary: String)
case class IntroItem(name: String, value: String)
case class BaikeLocation(name: String,
url: String = "",
info: Seq[IntroItem] = Seq(),
summary: Option[String] = None)
case class MewBaikeLocation(name: String,
url: String = "",
info: Option[String] = None,
summary: Option[String] = None)
object MysqlOpt {
def main(args: Array[String]): Unit = {
val conf = new SparkConf().setAppName("WordCount").setMaster("local")
val sc = new SparkContext(conf)
val sqlContext = new SQLContext(sc)
import sqlContext.implicits._
//定义数据库和表信息
val url = "jdbc:mysql://localhost:3306/baidubaike?useUnicode=true&characterEncoding=UTF-8"
val table = "baike_pages"
//读取parquetFile，并写入Mysql
val sparkSession = SparkSession.builder()
.master("local")
.appName("spark session example")
.getOrCreate()
val parquetDF = sparkSession.read.parquet("/home/mi/coding/coding/baikeshow_data/baikeshow")
// parquetDF.collect().take(20).foreach(println)
//parquetDF.show()
//BaikeLocation是读取的parquet文件中的case class
val ds = parquetDF.as[BaikeLocation].map { line =>
//把info转换为新的case class中的类型String
val info = line.info.map(item => item.name + ":" + item.value).mkString(",")
//注意需要把字段放在一个case class中，不然会丢失列信息
MewBaikeLocation(name = line.name, url = line.url, info = Some(info), summary = line.summary)
}.cache()
ds.show()
// ds.take(2).foreach(println)
//写入Mysql
// val prop = new Properties()
// prop.setProperty("user", "root")
// prop.setProperty("password", "123456")
// ds.write.mode(SaveMode.Append).jdbc(url, "baike_location", prop)
//写入parquetFile
ds.repartition(10).write.parquet("/home/mi/coding/coding/baikeshow_data/baikeshow1")
}
}
df.show打印出来的信息，如果没放在一个case class中的话，name,url,info,summary这列信息会变成1,2,3,4
使用spark-shell查看写回去的parquet文件的信息
#进入spark-shell import org.apache.spark.sql.SQLContext val sqlContext = new SQLContext(sc) val path = "file:///home/mi/coding/coding/baikeshow_data/baikeshow1" val df = sqlContext.parquetFile(path) df.show df.count
如果只想显示某一列的话，可以这么做
df.select("title").take(100).foreach(println) //只显示title这一列的信息
以上是关于Spark学习笔记——读写HDFS的主要内容，如果未能解决你的问题，请参考以下文章