I am trying to clear the content of fileA, and then copy the content from one fileB to fileA, how can I do it?
Thanks in advance!
Just delete and copy
hadoop fs -rm URI_A
hadoop fs -cp URI_B URI_A
FileSystem.create(), FileSystem.delete(), FileSystem.rename(). You obtain the FileSystem usually via the static .get(Conf). FileSystem is abstract and can operate on HDFS or other filesystems (eg. wasb://).
Related
for example if my input fie has 500MB i want this to split 250MB each, if my input file is 600MB block size should be 300MB
If you are loading files into hdfs you can put with dfs.blocksize oprtion, you can calculate parameter in a shell depending on size.
hdfs dfs -D dfs.blocksize=268435456 -put myfile /some/hdfs/location
If you already have files in HDFS and want to change it's block size, you need to rewrite it.
(1) move file to tmp location:
hdfs dfs -mv /some/hdfs/location/myfile /tmp
(2) Copy it back with -D dfs.blocksize=268435456
hdfs dfs -D dfs.blocksize=268435456 -cp /tmp/myfile /some/hdfs/location
In a cluster of hdfs, i receive multiple files on a daily basis which can be of 3 types :
1) product_info_timestamp
2) user_info_timestamp
3) user_activity_timestamp
The number of files received can be of any number but they will belong to one of these 3 categories only.
I want to merge all the files(after checking whether they are less than 100mb) belonging to one category into a single file.
for eg: 3 files named product_info_* should be merged into one file named product_info.
How do i achieve this?
You can use getmerge toachieve this, but the result will be stored in your local node (edge node), so you need to be sure you have enough space there.
hadoop fs -getmerge /hdfs_path/product_info_* /local_path/product_inf
You can move them back to hdfs with put
hadoop fs -put /local_path/product_inf /hdfs_path
You can use hadoop archive (.har file) or sequence file. It is very simple to use - just google "hadoop archive" or "sequence file".
Another set of commands along the similar lines as suggested by #SCouto
hdfs dfs -cat /hdfs_path/product_info_* > /local_path/product_info_combined.txt
hdfs dfs -put /local_path/product_info_combined.txt /hdfs_path/
I have the multiple text files.
The total size of them exceeds the largest disk size available to me (~1.5TB)
A spark program reads a single input text file from HDFS. So I need to combine those files into one. (I cannot re-write the program code. I am given only the *.jar file for execution)
Does HDFS have such a capability? How can I achieve this?
What I understood from your question is you want to Concatenate multiple files into one. Here is a solution which might not be the most efficient way of doing it but it works. suppose you have two files: file1 and file2 and you want to get a combined file as ConcatenatedFile
.Here is the script for that.
hadoop fs -cat /hadoop/path/to/file/file1.txt /hadoop/path/to/file/file2.txt | hadoop fs -put - /hadoop/path/to/file/Concatenate_file_Folder/ConcatenateFile.txt
Hope this helps.
HDFS by itself does not provide such capabilities. All out-of-the-box features (like hdfs dfs -text * with pipes or FileUtil's copy methods) use your client server to transfer all data.
In my experience we always used our own written MapReduce jobs to merge many small files in HDFS in distributed way.
So you have two solutions:
Write your own simple MapReduce/Spark job to combine text files with
your format.
Find already implemented solution for such kind of
purposes.
About solution #2: there is the simple project FileCrush for combining text or sequence files in HDFS. It might be suitable for you, check it.
Example of usage:
hadoop jar filecrush-2.0-SNAPSHOT.jar crush.Crush -Ddfs.block.size=134217728 \
--input-format=text \
--output-format=text \
--compress=none \
/input/dir /output/dir 20161228161647
I had a problem to run it without these options (especially -Ddfs.block.size and output file date prefix 20161228161647) so make sure you run it properly.
You can do a pig job:
A = LOAD '/path/to/inputFiles' as (SCHEMA);
STORE A into '/path/to/outputFile';
Doing a hdfs cat and then putting it back to hdfs means, all this data is processed in the client node and will degradate your network
Do we need to verify checksum after we move files to Hadoop (HDFS) from a Linux server through a Webhdfs ?
I would like to make sure the files on the HDFS have no corruption after they are copied. But is checking checksum necessary?
I read client does checksum before data is written to HDFS
Can somebody help me to understand how can I make sure that source file on Linux system is same as ingested file on Hdfs using webhdfs.
If your goal is to compare two files residing on HDFS, I would not use "hdfs dfs -checksum URI" as in my case it generates different checksums for files with identical content.
In the below example I am comparing two files with the same content in different locations:
Old-school md5sum method returns the same checksum:
$ hdfs dfs -cat /project1/file.txt | md5sum
b9fdea463b1ce46fabc2958fc5f7644a -
$ hdfs dfs -cat /project2/file.txt | md5sum
b9fdea463b1ce46fabc2958fc5f7644a -
However, checksum generated on the HDFS is different for files with the same content:
$ hdfs dfs -checksum /project1/file.txt
0000020000000000000000003e50be59553b2ddaf401c575f8df6914
$ hdfs dfs -checksum /project2/file.txt
0000020000000000000000001952d653ccba138f0c4cd4209fbf8e2e
A bit puzzling as I would expect identical checksum to be generated against the identical content.
Checksum for a file can be calculated using hadoop fs command.
Usage: hadoop fs -checksum URI
Returns the checksum information of a file.
Example:
hadoop fs -checksum hdfs://nn1.example.com/file1
hadoop fs -checksum file:///path/in/linux/file1
Refer : Hadoop documentation for more details
So if you want to comapre file1 in both linux and hdfs you can use above utility.
I wrote a library with which you can calculate the checksum of local file, just the way hadoop does it on hdfs files.
So, you can compare the checksum to cross check.
https://github.com/srch07/HDFSChecksumForLocalfile
If you are doing this check via API
import org.apache.hadoop.fs._
import org.apache.hadoop.io._
Option 1: for the value b9fdea463b1ce46fabc2958fc5f7644a
val md5:String = MD5Hash.digest(FileSystem.get(hadoopConfiguration).open(new Path("/project1/file.txt"))).toString
Option 2: for the value 3e50be59553b2ddaf401c575f8df6914
val md5:String = FileSystem.get(hadoopConfiguration).getFileChecksum(new Path("/project1/file.txt"))).toString.split(":")(0)
It does crc check. For each and everyfile it create .crc to make sure there is no corruption.
Is there an HDFS API that can copy an entire local directory to the HDFS? I found an API for copying files but is there one for directories?
Use the Hadoop FS shell. Specifically:
$ hadoop fs -copyFromLocal /path/to/local hdfs:///path/to/hdfs
If you want to do it programmatically, create two FileSystems (one Local and one HDFS) and use the FileUtil class
I tried copying from the directory using
/hadoop/core/bin/hadoop fs -copyFromLocal /home/grad04/lopez/TPCDSkew/ /export/hadoop1/lopez/Join/TPCDSkew
It gave me an error saying Target is a directory . I then modified it to
/hadoop/core/bin/hadoop fs -copyFromLocal /home/grad04/lopez/TPCDSkew/*.* /export/hadoop1/lopez/Join/TPCDSkew
it works .
In Hadoop version:
Hadoop 2.4.0.2.1.1.0-390
(And probably later; I have only tested this specific version as it is the one I have)
You can copy entire directories recursively without any special notation using copyFromLocal e.g.,:
hadoop fs -copyFromLocal /path/on/disk /path/on/hdfs
which works even when /path/on/disk is a directory containing subdirectories and files.
You can also use the put command:
$ hadoop fs -put /local/path hdfs:/path
For programmer, you also can use copyFromLocalFile. Here is an example:
import org.apache.hadoop.conf.Configuration
import org.apache.hadoop.fs.FileSystem
import org.apache.hadoop.fs.Path
val hdfsConfig = new Configuration
val hdfsURI = "hdfs://127.0.0.1:9000/hdfsData"
val hdfs = FileSystem.get(new URI(hdfsURI), hdfsConfig)
val oriPath = new Path("#your_localpath/customer.csv")
val targetFile = new Path("hdfs://your_hdfspath/customer.csv")
hdfs.copyFromLocalFile(oriPath, targetFile)