Data ingestion in Hadoop using Distcp - hadoop

I understand that distcp is used for inter/intra cluster transfer of data. Is it possible to use distcp to ingest data from the local file system to HDFS. I understand that you can use file:///....
to point to a local file outside of HDFS but how reliable and fast is that compared to the inter/intra cluster transfer.

Distcp is a mapreduce job that is executed inside the hadoop cluster. For hadoop cluster perspective, your local machine is not a local file system. Then you can't use your local file sytem with distcp. An alternative could be configure a FTP server in your machine that hadoop cluster can read. The performance depends on the network and the protocol used (ftp with hadoop has a very bad performance).
Use hdfs dfs -put command could be better for small amount of data but it isn't work in parallel like distcp.

Related

nifi putHDFS writes to local filesystem

Challenge
I currently have two hortonworks clusters, a NIFI cluster and a HDFS cluster, and want to write to HDFS using NIFI.
On the NIFI cluster I use a simple GetFile connected to a PutHDFS.
When pushing a file through this, the PutHDFS terminates in success. However, rather than seeing a file dropped on my HFDS (on the HDFS cluster) I just see a file being dropped onto the local filesystem where I run NIFI.
This confuses me, hence my question:
How to make sure PutHDFS writes to HDFS, rather than to the local filesystem?
Possibly relevant context:
In the PutHDFS I have linked to the hive-site and core-site of the HDFS cluster (I tried updating all server references to the HDFS namenode, but with no effect)
I don't use Kerberos on the HDFS cluster (I do use it on the NIFI cluster)
I did not see anything looking like an error in the NIFI app log (which makes sense as it succesfully writes, just in the wrong place)
Both clusters are newly generated on Amazon AWS with CloudBreak, and opening all nodes to all traffic did not help
Can you make sure that you are able move file from NiFi node to Hadoop using below command:-
hadoop fs -put
If you are able move your file using above command then you must check your Hadoop config file which you are passing in your PutHDFS processor.
Also, check that you don't have anyother flow running to make sure that no other flow is processing that file.

How can i copy files from external Hadoop cluster to Amazon S3 without running any commands on the cluster

I have scenario in which i have to pull data from Hadoop cluster into AWS.
I understand running dist-cp on the hadoop cluster is a way to copy the data into s3, but i have a restriction here, i wont be able to run any commands in the cluster. I should be able to pull the files from hadoop cluster into AWS. The data is available in hive.
I thought of the below options:
1) Sqoop data from Hive ? Is it possible ?
2) S3-distcp (running it on aws), if so what would be the configuration needed ?
Any Suggestions ?
If the hadoop cluster is visible from EC2-land, you could run a distcp command there, or, if it's a specific bit of data, some hive query which uses hdfs:// as input and writes out to s3. You'll need to deal with kerberos auth though: you cannot use distcp in an un-kerberized cluster to read data from a kerberized one, though you can go the other way.
You can also run distcp locally in 1+ machine, though you are limited by the bandwidth of those individual systems. distcp is best when it schedules the uploads on the hosts which actually have the data.
Finally, if it is incremental backup you are interested in, you can use the HDFS audit log as a source of changed files...this is what incremental backup tools tend to use

Is it possible to write to a remote HDFS?

As title, is it possible to write to a remote HDFS?
E.g. I have installed a HDFS cluster on AWS EC2, and I want to write a file from my local computer to the HDFS cluster.
Two ways you could write to remote HDFS,
Use the WebHDFS api available.It supports the systems running outside
Hadoop clusters to access and manipulate the HDFS contents. It
doesn't require the client systems to have hadoop binaries installed.
Configure the client system as Hadoop edge node to interact with the
Hadoop cluster/HDFS.
Please refer,
https://hadoop.apache.org/docs/r1.2.1/webhdfs.html
http://www.dummies.com/how-to/content/edge-nodes-in-hadoop-clusters.html

Effective ways to load data from hdfs to local system?

I'm trying to load terabytes of data from hdfs to local using hadoop fs -get but it takes hours to complete this task. Is there an alternate effective way to get data from hdfs to local?
How fast you copy to a local filesystem is dependent on many factors including:
Are you copying in parallel or in serial.
Is the file splittable (can a mapper potentially deal with a block of data rather than a file, usually a problem if you have certain kinds of compressed files on HDFS)
Network bandwidth of course because you will likely be pulling from many DataNodes
Option 1: DistCp
In any case, since you state your files are on HDFS, we know each hadoop slave node can see the data. You can try to use the DistCp command (distributed copy) which will make your copy operation into a parallel MapReduce job for you WITH ONE MAJOR CAVEAT!.
MAJOR CAVEAT: This will be a distributed copy process so the destination you specify on the command line needs to be a place visible to all nodes. To do this you can mount a network share on all nodes and specify a directory in that network share (NFS, Samba, Other) as the destination for your files. This may take getting a system admin involved, but the result may be a faster file copy operation so the cost-benefit is up to you.
DistCp documentation is here: http://hadoop.apache.org/docs/r0.19.0/distcp.html
DistCp example: YourShell> hadoop distcp -i -update /path/on/hdfs/to/directoryOrFileToCopy file:///LocalpathToCopyTo
Option 2: Multi-threaded Java Application with HDFS API
As you found, the hadoop fs -get is a sequential operation. If your java skills are up to the task, you can write your own multithreaded copy program using the hadoop file system API calls.
Option 3: Multi-threaded Program in any language with HDFS REST API
If you know a different language than Java, you can similarly write a multi-threaded program that accesses HDFS through the HDFS REST API or as an NFS mount

Writing to local file during map phase in hadoop

Hadoop writes the intermediate results to the local disk and the results of the reducer to the HDFS. what does HDFS mean. What does it physically translate to
HDFS is the Hadoop Distributed File System. Physically, it is a program running on each node of the cluster that provides a file system interface very similar to that of a local file system. However, data written to HDFS is not just stored on the local disk but rather is distributed on disks across the cluster. Data stored in HDFS is typically also replicated, so the same block of data may appear on multiple nodes in the cluster. This provides reliable access so that one node's crashing or being busy will not prevent someone from being able to read any particular block of data from HDFS.
Check out http://en.wikipedia.org/wiki/Hadoop_Distributed_File_System#Hadoop_Distributed_File_System for more information.
As Chase indicated, HDFS is Hadoop Distributed File System.
If I may, I recommend this tutorial and video of how HDFS and the Map/Reduce framework works and will serve you as a guide into the world of Hadoop: http://www.cloudera.com/resource/introduction-to-apache-mapreduce-and-hdfs/

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