I have a directory of directories on HDFS, and I want to iterate over the directories. Is there any easy way to do this with Spark using the SparkContext object?
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you mean 'iterate' like get the list of sub-directories and files within? or getting all files across all subdirectories? – maasg Nov 19 '14 at 19:23
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Iterate as in list all the sub-directories. Each subdirectory contains a bunch of text files that I want to process in different ways. – Jon Nov 19 '14 at 19:27
9 Answers
You can use org.apache.hadoop.fs.FileSystem. Specifically, FileSystem.listFiles([path], true)
And with Spark...
FileSystem.get(sc.hadoopConfiguration).listFiles(..., true)
Edit
It's worth noting that good practice is to get the FileSystem that is associated with the Path's scheme.
path.getFileSystem(sc.hadoopConfiguration).listFiles(path, true)
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really nice! [I had this question](http://stackoverflow.com/questions/34738296/spark-spark-submit-jars-arguments-wants-comma-list-how-to-declare-a-directory/35550151#35550151), granted, I guess this wouldn't work in the original spark-submit call – JimLohse Feb 23 '16 at 13:46
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How can I create a list of the files using the RemoteIterator this creates? – horatio1701d Jan 27 '18 at 13:58
Here's PySpark version if someone is interested:
hadoop = sc._jvm.org.apache.hadoop
fs = hadoop.fs.FileSystem
conf = hadoop.conf.Configuration()
path = hadoop.fs.Path('/hivewarehouse/disc_mrt.db/unified_fact/')
for f in fs.get(conf).listStatus(path):
print(f.getPath(), f.getLen())
In this particular case I get list of all files that make up disc_mrt.unified_fact Hive table.
Other methods of FileStatus object, like getLen() to get file size are described here:
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import org.apache.hadoop.fs.{FileSystem,Path}
FileSystem.get( sc.hadoopConfiguration ).listStatus( new Path("hdfs:///tmp")).foreach( x => println(x.getPath ))
This worked for me.
Spark version 1.5.0-cdh5.5.2
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This worked fine for me, for a single folder. Is there some way to get this to run at the level of the parent folder, and get all files in all subfolders? That would be VERY helpful/useful for me. – ASH Jun 28 '19 at 15:03
this did the job for me
FileSystem.get(new URI("hdfs://HAservice:9000"), sc.hadoopConfiguration).listStatus( new Path("/tmp/")).foreach( x => println(x.getPath ))
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@Tagar didn't say how to connect remote hdfs, but this answer did:
URI = sc._gateway.jvm.java.net.URI
Path = sc._gateway.jvm.org.apache.hadoop.fs.Path
FileSystem = sc._gateway.jvm.org.apache.hadoop.fs.FileSystem
Configuration = sc._gateway.jvm.org.apache.hadoop.conf.Configuration
fs = FileSystem.get(URI("hdfs://somehost:8020"), Configuration())
status = fs.listStatus(Path('/some_dir/yet_another_one_dir/'))
for fileStatus in status:
print(fileStatus.getPath())
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Scala FileSystem (Apache Hadoop Main 3.2.1 API)
import org.apache.hadoop.fs.{FileSystem, Path}
import scala.collection.mutable.ListBuffer
val fileSystem : FileSystem = {
val conf = new Configuration()
conf.set( "fs.defaultFS", "hdfs://to_file_path" )
FileSystem.get( conf )
}
val files = fileSystem.listFiles( new Path( path ), false )
val filenames = ListBuffer[ String ]( )
while ( files.hasNext ) filenames += files.next().getPath().toString()
filenames.foreach(println(_))
I had some issues with other answers(like 'JavaObject' object is not iterable), but this code works for me
fs = self.spark_contex._jvm.org.apache.hadoop.fs.FileSystem.get(spark_contex._jsc.hadoopConfiguration())
i = fs.listFiles(spark_contex._jvm.org.apache.hadoop.fs.Path(path), False)
while i.hasNext():
f = i.next()
print(f.getPath())
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You can try with globStatus status as well
val listStatus = org.apache.hadoop.fs.FileSystem.get(new URI(url), sc.hadoopConfiguration).globStatus(new org.apache.hadoop.fs.Path(url))
for (urlStatus <- listStatus) {
println("urlStatus get Path:"+urlStatus.getPath())
}
You can use below code to iterate recursivly through a parent HDFS directory, storing only sub-directories up to a third level. This is useful, if you need to list all directories that are created due to the partitioning of the data (in below code three columns were used for partitioning):
val fs = FileSystem.get(spark.sparkContext.hadoopConfiguration)
def rememberDirectories(fs: FileSystem, path: List[Path]): List[Path] = {
val buff = new ListBuffer[LocatedFileStatus]()
path.foreach(p => {
val iter = fs.listLocatedStatus(p)
while (iter.hasNext()) buff += iter.next()
})
buff.toList.filter(p => p.isDirectory).map(_.getPath)
}
@tailrec
def getRelevantDirs(fs: FileSystem, p: List[Path], counter: Int = 1): List[Path] = {
val levelList = rememberDirectories(fs, p)
if(counter == 3) levelList
else getRelevantDirs(fs, levelList, counter + 1)
}
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