CODEWITHSUNDEEP
pythonapache-sparkamazon-s3pyspark
Viv
Viv

Reputation: 1584

How to read parquet data from S3 to spark dataframe Python?

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

Answers (2)

eliasah
eliasah

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

Artem
Artem

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

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