What is the fastest way to send files of any size and format to Hadoop?

how to create a file in hadoop using command
hadoop fs -text
hadoop data modeling best practices
copy file from local to hdfs
copy multiple files from local to hdfs
hdfs copy directory
hadoop compression example
hdfs remove file

I build web application for data analysis with Angular 6 frontend, Django 1.11 backend and Hadoop. I need to send files of any size and format in the fastest possible way to Hadoop. I would like to support both private users and the companies. I wonder what is the fastest way to send files of any size and format to Hadoop?

My solution:

    file = request.FILES['file']

    path = default_storage.save(str(file), ContentFile(file.read()))

    os.path.join(settings.MEDIA_ROOT, path)

    command = 'hadoop fs -put ' + str(file) + ' /user/' + str(user_name) + '/' + str(file)

    os.system(command)

    command = 'rm -r ' + str(file)

    os.system(command)

Hadoop FS put command will use hdfs/webhdfs, but the overhead of starting up a process for even the smallest file will make this operation hurt. I would have a look at using hadoop copyfromlocal with as many source files and 1-2 threads for each core.

For anyone having trouble with multiGB files; hadoop fs -appendToFile should let you build up a larger file from local parts, though it doesn't support any range in its command line (which it could, really). And there's work going on in the latest versions of Hadoop trunk for a better multipart upload API for HDFS and the object stores designed for parallel uploads of blocks with a final merge at the end.

Is there a hdfs command to list files in HDFS directory as per , sizes in a human-readable fashion (eg 64.0m instead of 67108864). Note, I use ‘File Format’ and ‘Storage Format’ interchangably in this article. If you’ve read my beginners guide to Hadoop you should remember that an important part of the Hadoop ecosystem is HDFS, Hadoop’s distributed file system. Like other file systems the format of the files you can store on HDFS is entirely up to you.


The only way that'll allow any size is to follow the HDFS RPC write protocol. E.g. hdfs dfs -put

Otherwise, webhdfs or NFS gateway will probably timeout for large files (over a few GB).

If you're not using HDFS, then use the respective libraries for your storage. Azure or S3, for example


A better solution than uploading files would be use some RDMBS, or Cassandra, for your analytics, and then use Sqoop, or Spark to export that data into Hadoop in a parallel fashion

consumer of another cluster, and as such replicates all messages with the same HA How‐ever, there are several use cases that combine both systems. it has very good support for writing data to Hadoop, including HDFS, HBase, and Solr. to HDFS, such as reli‐ability, optimal file sizes, file formats, updating metadata,​  Trying to figure out how to transfer large files online? Gmail has a 25MB limit, but don't worry; there are plenty of ways to send large files over the internet, like Mozilla's new Firefox Send.


If you are using Sqoop import you can try with the performance improvement parameters like mentioned below: 1. --fetch-size number 2. --direct 3. --split-by 4. -m count 5. Boundary query in sqoop tool

This technique doesn't offer any way to fix the data—merely error detection. space needed to store files, and it speeds up data transfer across the network, or to or from disk. faster than its compression speed, but it is still slower than the other formats. Consider an uncompressed file stored in HDFS whose size is 1 GB. COBOL is a programming language, not a file format. If what you need is to export files produced by COBOL programs, you can use the same technique as if those files were produced by C, C++, Java, Perl, PL/I, Rexx, etc. In general, you will have three different data sources: flat files, VSAM files, and a DBMS such as DB2 or IMS.


This characteristic of Hadoop means that you can store any type of data as is, Relational databases and data warehouses are often a good fit for It's possible to create your own custom file format in Hadoop, as well. This format waits until data reaches block size to compress, rather than as each record is added. Free of charge, Send Anywhere will let you easily share files up to 10GB in size, with the link active for 48 hours. However, for the Plus account costing $5.99 a month you get 1TB of storage and


And you want to know how you can deal with files on HDFS? Faster. Even if it doesn't seem like you can. Even if you have data that no universal format for a table: You might have three suppliers send The following 2 info in Spark web UI are significantly necessary for standardization of batch size:. Metadata, ressource forks, extended attributes, file permissions might either just not be transported by the protocol/tool of your choice, or be meaningless at the receiving end. The same goes for sparse files, which might end up being bloated to full size at the other end of the copy, ruining all plans you may have had about sizing.


in Chapter 1, Hadoop 3.0 - Background and Introduction Each file sent to HDFS an offline image viewer to dump FSimage data into humanreadable format. In theory, there’s no limit to the amount of data you can attach to an email. Email standards don’t specify any sort of size limit. In practice, most email servers—and some email clients—enforce their own size limits. In general, when attaching files to an email, you can be reasonably sure that up to 10MB of attachments are okay.