我是Spark的新手,我无法找到这个...我有很多镶木地板文件上传到 s3
的位置:
s3://a-dps/d-l/sco/alpha/20160930/parquet/
此文件夹的总大小为 20+ Gb
,.如何将其分块并将其读入数据帧如何将所有这些文件加载到数据帧中?
分配给火花集群的内存为6 GB .
from pyspark import SparkContext
from pyspark.sql import SQLContext
from pyspark import SparkConf
from pyspark.sql import SparkSession
import pandas
# SparkConf().set("spark.jars.packages","org.apache.hadoop:hadoop-aws:3.0.0-alpha3")
sc = SparkContext.getOrCreate()
sc._jsc.hadoopConfiguration().set("fs.s3.awsAccessKeyId", 'A')
sc._jsc.hadoopConfiguration().set("fs.s3.awsSecretAccessKey", 's')
sqlContext = SQLContext(sc)
df2 = sqlContext.read.parquet("s3://sm/data/scor/alpha/2016/parquet/*")
错误:
Py4JJavaError: An error occurred while calling o33.parquet.
: java.io.IOException: No FileSystem for scheme: s3
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:2660)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:2667)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:94)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:2703)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:2685)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:373)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:295)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:372)
at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$14.apply(DataSource.scala:370)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.TraversableLike$$anonfun$flatMap$1.apply(TraversableLike.scala:241)
at scala.collection.immutable.List.foreach(List.scala:381)
at scala.collection.TraversableLike$class.flatMap(TraversableLike.scala:241)
at scala.collection.immutable.List.flatMap(List.scala:344)
2 回答
您使用的文件架构(
s3
)不正确 . 您需要使用s3n
架构或s3a
(对于更大的s3对象):我建议你阅读更多关于Hadoop-AWS module: Integration with Amazon Web Services Overview的内容 .
自Spark 2.0以来,你必须使用SparkSession而不是sqlContext