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This code allows parallel loading of data from S3 to Spark RDD. Support multiple paths to load from. Based on http://tech.kinja.com/how-not-to-pull-from-s3-using-apache-spark-1704509219
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val s3Paths = "s3://yourbucket/path/to/file1.txt,s3://yourbucket/path/to/directory" | |
val pageLength = 100 | |
val key = "YOURKEY" | |
val secret = "YOUR_SECRET" | |
import com.amazonaws.services.s3._, model._ | |
import com.amazonaws.auth.BasicAWSCredentials | |
import com.amazonaws.services.s3.model.ObjectListing | |
import scala.collection.JavaConverters._ | |
import scala.io.Source | |
import java.io.InputStream | |
import org.apache.spark.rdd.RDD | |
def s3 = new AmazonS3Client(new BasicAWSCredentials(key, secret)) | |
var inputLinesRDD_raw:RDD[String] = sc.emptyRDD[String] | |
s3Paths.split(",").foreach{ s3Path => | |
val regex = """(?i)^s3://([^/]+)/(.*)""".r | |
val bucket = regex.findFirstMatchIn(s3Path).map(_ group 1).getOrElse(null) | |
val prefix = regex.findFirstMatchIn(s3Path).map(_ group 2).getOrElse(null) | |
println("Processing s3 resource: bucket '%s', prefix '%s'".format(bucket, prefix)) | |
@transient val request = new ListObjectsRequest() | |
request.setBucketName(bucket) | |
request.setPrefix(prefix) | |
request.setMaxKeys(pageLength) | |
@transient var listing = s3.listObjects(request) | |
var proceed = true | |
while (proceed){ | |
if (listing.getObjectSummaries.isEmpty){ | |
proceed = false | |
}else{ | |
@transient val s3FileKeys = listing.getObjectSummaries.asScala.map(_.getKey).toList | |
val inputLines = sc.parallelize(s3FileKeys).flatMap { key => Source.fromInputStream(s3.getObject(bucket, key).getObjectContent: InputStream).getLines } | |
inputLinesRDD_raw = inputLinesRDD_raw.union(inputLines) | |
listing = s3.listNextBatchOfObjects(listing) | |
} | |
} | |
} | |
// TODO do something with inputLinesRDD_raw |
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This worked for me. Thanks @hamishdickson !