I am trying to read a file in Spark Shell that comes with CentOS distribution of Cloudera on my local machine. Following are the commands I have entered in Spark Shell.
spark-shell
val fileData = sc.textFile("hdfs://user/home/cloudera/cm_api.py");
fileData.count
I also tried this statment for reading file:
val fileData = sc.textFile("user/home/cloudera/cm_api.py");
However I am getting
org.apache.hadoop.mapred.InvalidInputException: Input path does not exist: hdfs://quickstart.cloudera:8020/user/cloudera/user/cloudera/cm_api.py
I haven't changed any settings or configurations. What am I doing wrong?
You are missing the leading slash in your url, so the path is relative. To make it absolute, use
val fileData = sc.textFile("hdfs:///user/home/cloudera/cm_api.py")
or
val fileData = sc.textFile("/user/home/cloudera/cm_api.py")
I think you need to put the file in hdfs first: hadoop fs -put, then check the file: hadoop fs -ls, then go spark-shell , val fileData = sc.textFile("cm_api.py")
In "hdfs://user/home/cloudera/cm_api.py", you are missing the hostname of the URI. You should have pass something like "hdfs://<host>:<port>/user/home/cloudera/cm_api.py", where <host> is Hadoop NameNode host and the <port> is, well, port number of Hadoop NameNode, which is 50070 by default.
The error message says hdfs://quickstart.cloudera:8020/user/cloudera/user/cloudera/cm_api.py does not exist. The path looks suspicious! The file you mean is probably at hdfs://quickstart.cloudera:8020/user/cloudera/cm_api.py.
If it is, you can access it by using that full path. Or, if the default file system is configured as hdfs://quickstart.cloudera:8020/user/cloudera/, you can use simply cm_api.py.
You may be confused between HDFS file paths and local file paths. By specifying
hdfs://quickstart.cloudera:8020/user/home/cloudera/cm_api.py
you are saying two things:
1) there is a computer by the name "quickstart.cloudera' reachable via the network (try ping to ensure that is the case), and it is running HDFS.
2) the HDFS file system contains a file at /user/home/cloudera/cm_api.py (try 'hdfs dfs -ls /user/home/cloudera/' to verify this
If you are trying to access a file on the local file system you have to use a different URI:
file:///user/home/cloudera/cm_api.py
Related
I am Learning spark to implement in my project. I want to run command in spark shell-
val rddFromFile = spark.sparkContext.textFile("abc");
where abc is file location. My file is on remote server and through that remote server I am opening spark shell, how should I specify file location.
I tried to put a text file in local C drive and provided the location to read that, it also did not worked. I am getting similar error for all the file location.
Error :
scala> val rddFromFile = spark.sparkContext.textFile("C:/Users/eee/Spark test/Testspark.txt")
rddFromFile: org.apache.spark.rdd.RDD[String] = C:/Users/eee/Spark test/Testspark.txt MapPartitionsRDD[1] at textFile at <console>:23
scala> rddFromFile.collect().foreach(f=>{
| println(f)
| })
org.apache.hadoop.fs.UnsupportedFileSystemException: No FileSystem for scheme "C"
at org.apache.hadoop.fs.FileSystem.getFileSystemClass(FileSystem.java:3281)
at org.apache.hadoop.fs.FileSystem.createFileSystem(FileSystem.java:3301)
at org.apache.hadoop.fs.FileSystem.access$200(FileSystem.java:124)
at org.apache.hadoop.fs.FileSystem$Cache.getInternal(FileSystem.java:3352)
at org.apache.hadoop.fs.FileSystem$Cache.get(FileSystem.java:3320)
at org.apache.hadoop.fs.FileSystem.get(FileSystem.java:479)
at org.apache.hadoop.fs.Path.getFileSystem(Path.java:361)
at org.apache.hadoop.mapred.FileInputFormat.singleThreadedListStatus(FileInputFormat.java:268)
at org.apache.hadoop.mapred.FileInputFormat.listStatus(FileInputFormat.java:239)
at org.apache.hadoop.mapred.FileInputFormat.getSplits(FileInputFormat.java:325)
Spark is expecting the file to be present in the Hadoop FS, as it looks like that's the default file system set in your app.
To load a file from local FS, you need to put it like
val rddFromFile = spark.sparkContext.textFile("file:///C:/Users/eee/Spark test/Testspark.txt")
That will work when you run Spark in local mode.
If you run Spark in the cluster, then the file would have to be present on all executor nodes.
Is there a known way using Hadoop api / spark scala to copy files from one directory to another on Hdfs ?
I have tried using copyFromLocalFile but was not helpful
Try Hadoop's FileUtil.copy() command, as described here: https://hadoop.apache.org/docs/r2.8.5/api/org/apache/hadoop/fs/FileUtil.html#copy(org.apache.hadoop.fs.FileSystem,%20org.apache.hadoop.fs.Path,%20org.apache.hadoop.fs.FileSystem,%20org.apache.hadoop.fs.Path,%20boolean,%20org.apache.hadoop.conf.Configuration)
val conf = new org.apache.hadoop.conf.Configuration()
val srcPath = new org.apache.hadoop.fs.Path("hdfs://my/src/path")
val dstPath = new org.apache.hadoop.fs.Path("hdfs://my/dst/path")
org.apache.hadoop.fs.FileUtil.copy(
srcPath.getFileSystem(conf),
srcPath,
dstPath.getFileSystem(conf),
dstPath,
true,
conf
)
As I've understand your question, the answer is as easy as abc. Actually, there is no difference between your OS filesystem and some other distributed versions in the fundamental concepts like copying files in them. That is true that each would have its own rules in commands. For instance, when you want to copy a file from one directory to another you can do something like:
hdfs dfs -cp /dir_1/file_1.txt /dir_2/file_1_new_name.txt
The first part of the example command is just to let the command to be routed to the true destination not the OS's own file system.
for further reading you can use: copying data in hdfs
I need to read a file using spark-sql, and the file is in the current directory.
I use this command to decompress a list of files I have stored on HDFS.
val decompressCommand = Seq(laszippath, "-i", inputFileName , "-o", "out.las").!!
The file is outputted in the current worker node directory, and I know this because executing "ls -a"!! through scala I can see that the file is there. I then try to access it with the following command:
val dataFrame = sqlContext.read.las("out.las")
I assumed that the sql context would try to find the file in the current directory, but it doesn't. Also, it doesn't throw an error but a warning stating that the file could not be found (so spark continues to run).
I attempted to add the file using: sparkContext.addFile("out.las") and then access the location using: val location = SparkFiles.get("out.las") but this didn't work either.
I even ran the command val locationPt = "pwd"!! and then did val fullLocation = locationPt + "/out.las" and attempted to use that value but it didn't work either.
The actual exception that gets thrown is the following:
User class threw exception: org.apache.spark.sql.AnalysisException: cannot resolve 'x' given input columns: [];
org.apache.spark.sql.AnalysisException: cannot resolve 'x' given input columns: []
And this happens when I try to access column "x" from a dataframe. I know that column 'X' exists because I've downloaded some of the files from HDFS, decompressed them locally and ran some tests.
I need to decompress files one by one because I have 1.6TB of data and so I cannot decompress it at one go and access them later.
Can anyone tell me what I can do to access files which are being outputted to the worker node directory? Or maybe should I be doing it some other way?
So I managed to do it now. What I'm doing is I'm saving the file to HDFS, and then retrieving the file using the sql context through hdfs. I overwrite "out.las" each time in HDFS so that I don't have take too much space.
I have used the hadoop API before to get to files, I dunno if it will help you here.
val filePath = "/user/me/dataForHDFS/"
val fs:FileSystem = FileSystem.get(new java.net.URI(filePath + "out.las"), sc.hadoopConfiguration)
And I've not tested the below, but I'm pretty sure I'm passing the java array to scala illegally. But just giving an idea of what to do afterward.
var readIn: Array[Byte] = Array.empty[Byte]
val fileIn: FSDataInputStream = fs.open(file)
val fileIn.readFully(0, readIn)
My flume spool directory contains non-"UTF-8" files.
So I get a Java.nio.charset.MalformedInputException error when I try to collect it.
Changing the encoding option of a .conf file will also cause an error.
And I have to use spooldir type.
How can I collecrt non-"UTF-8" files.
enter image description here
The encoding of our log files were Latin5 (which is Turkish)
Fixed it by adding the below line into the conf file:
AGENTNAME.sources.SOURCENAME.inputCharset = ISO-8859-9
I did set up the hadoop Ubuntu OS, followed all the necessary steps,
1.created the hdfs file system
2.Moved the text files to input directory
3.having privilege to access all the directories.
but when run the simple word count example, i got
Exception in thread "main" org.apache.hadoop.mapreduce.lib.input.InvalidInputException: Input path does not exist: file:/user/root/input
at org.apache.hadoop.mapreduce.lib.input.FileInputFormat.listStatus(FileInputFormat.java:224)
but, input path is valid and even can able view the files in that path from eclipse itself, so plz assist were i am wrong.
attached the screenshot for the reference
Add the following 2 lines in your code :
config.addResource(new Path("/HADOOP_HOME/conf/core-site.xml"));
config.addResource(new Path("/HADOOP_HOME/conf/hdfs-site.xml"));
Your client is looking into the local FS.
For hadoop-2.2.0 on windows 7, I added the below lines and it solved the issue (NOTE: My Hadoop Home is: C:\MyWork\MyProjects\Hadoop\hadoop-2.2.0)
Configuration conf = new Configuration();
conf.addResource(new Path("C:\MyWork\MyProjects\Hadoop\hadoop-2.2.0\etc\hadoop\core-site.xml"));
conf.addResource(new Path("C:\MyWork\MyProjects\Hadoop\hadoop-2.2.0\etc\hadoop\hdfs-site.xml"));