Reputation: 1584
I am new to Spark and I am not able to find this... I have a lot of parquet files uploaded into s3
at location :
s3://a-dps/d-l/sco/alpha/20160930/parquet/
The total size of this folder is 20+ Gb
,. How to chunk and read this into a dataframe
How to load all these files into a dataframe?
Allocated memory to spark cluster is 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/*")
Error :
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)
Upvotes: 33
Views: 112043
Reputation: 40380
The file schema (s3
)that you are using is not correct. You'll need to use the s3n
schema or s3a
(for bigger s3 objects):
// use sqlContext instead for spark <2
val df = spark.read
.load("s3n://bucket-name/object-path")
I suggest that you read more about the Hadoop-AWS module: Integration with Amazon Web Services Overview.
Upvotes: 26
Reputation: 1217
You've to use SparkSession instead of sqlContext since Spark 2.0
spark = SparkSession.builder
.master("local")
.appName("app name")
.config("spark.some.config.option", true).getOrCreate()
df = spark.read.parquet("s3://path/to/parquet/file.parquet")
Upvotes: 29