I understand the general concept behind it, but I would like more clarification and a clear-cut definition of what a "client" is.
For example, if I just write an hdfs command on the Terminal, is it still a "client" ?
Client in Hadoop refers to the Interface used to communicate with the Hadoop Filesystem. There are different type of Clients available with Hadoop to perform different tasks.
The basic filesystem client hdfs dfs is used to connect to a Hadoop Filesystem and perform basic file related tasks. It uses the ClientProtocol to communicate with a NameNode daemon, and connects directly to DataNodes to read/write block data.
To perform administrative tasks on HDFS, there is hdfs dfsadmin. For HA related tasks, hdfs haadmin.
There are similar clients available for performing YARN related tasks.
These Clients can be invoked using their respective CLI commands from a node where Hadoop is installed and has the necessary configurations and libraries required to connect to a Hadoop Filesystem. Such nodes are often referred as Hadoop Clients.
For example, if I just write an hdfs command on the Terminal, is it
still a "client" ?
Technically, Yes. If you are able to access the FS using the hdfs command, then the node has the configurations and libraries required to be a Hadoop Client.
PS: APIs are also available to create these Clients programmatically.
Edge nodes are the interface between the Hadoop cluster and the outside network. This node/host will have all the libraries and client components present, as well as current configuration of the cluster to connect to the hdfs.
This thread discusses same
Related
Is there a way to allow a developer to access a hadoop command line without SSH? I would like to place some hadoop clusters in a specific environment where SSH is not permitted. I have searched for alternatives such as a desktop client but so far have not seen anything. I will also need to federate sign on info for developers.
If you're asking about hadoop fs and similar commands, you don't need SSH for this.
You just need to download Hadoop clients and configure the hdfs-site.xml file to point at a remote cluster. However, this is an administrative security hole, so setting up an edge node that does have trusted and audited SSH access is preferred.
Similarly, Hive or HBase or Spark jobs can be ran with the appropriate clients or configuration files without any SSH access, just local libraries
You don't need SSH to use Hadoop. Also Hadoop is a combination of different stacks, which part of Hadoop are you referring to specifically? If you are talking about HDFS you can use web HDFS. If you are talking about YARN you can use API call. There are also various UI tools such as HUE you can use. Notebook apps such as Zeppelin or Jupiter can also be helpful.
My question is pretty trivial but didnt find anyone actually asking it.
We have a ambari cluster with spark storm hbase and hdfs(among other things).
I dont understand how a user that want to use that cluster use it.
for example, a user want to copy a file to hdfs, run a spark-shell or create new table in hbase shell.
should he get a local account on the server that run the cooresponded service? shouldn't he use a 3rd party machine(his own laptop for example)?
If so ,how one should use hadoop fs, there is no way to specify the server ip like spark-shell has.
what is the normal/right/expected way to run all these tasks from a user prespective.
Thanks.
The expected way to run the described tasks from the command line is as follows.
First, gain access to the command line of a server that has the required clients installed for the services you want to use, e.g. HDFS, Spark, HBase et cetera.
During the process of provisioning a cluster via Ambari, it is possible to define one or more servers where the clients will be installed.
Here you can see an example of an Ambari provisioning process step. I decided to install the clients on all servers.
Afterwards, one way to figure out which servers have the required clients installed is to check your hosts views in Ambari. Here you can find an example of an Ambari hosts view: check the green rectangle to see the installed clients.
Once you have installed the clients on one or more servers, these servers will be able to utilize the services of your cluster via the command line.
Just to be clear, the utilization of a service by a client is location-independent from the server where the service is actually running.
Second, make sure that you are compliant with the security mechanisms of your cluster. In relation to HDFS, this could influence which users you are allowed to use and which directories you can access by using them. If you do not use security mechanisms like e.g. Kerberos, Ranger and so on, you should be able to directly run your stated tasks from the command line.
Third, execute your tasks via command line.
Here is a short example of how to access HDFS without considering security mechanisms:
ssh user#hostxyz # Connect to the server that has the required HDFS client installed
hdfs dfs -ls /tmp # Command to list the contents of the HDFS tmp directory
Take a look on Ambari views, especially on Files view that allows browsing 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
I'm loading 28 GB file in hadoop hdfs using webhdfs and it takes ~25 mins to load.
I tried loading same file using hdfs put and It took ~6 mins. Why there is so much difference in performance?
What is recommended to use? Can somebody explain or direct me to some good link it will be really helpful.
Below us the command I'm using
curl -i --negotiate -u: -X PUT "http://$hostname:$port/webhdfs/v1/$destination_file_location/$source_filename.temp?op=CREATE&overwrite=true"
this will redirect to a datanode address which I use in next step to write the data.
Hadoop provides several ways of accessing HDFS
All of the following support almost all features of the filesystem -
1. FileSystem (FS) shell commands: Provides easy access of Hadoop file system operations as well as other file systems that Hadoop
supports, such as Local FS, HFTP FS, S3 FS.
This needs hadoop client to be installed and involves the client to write blocks
directly to one Data Node. All versions of Hadoop do not support all options for copying between filesystems.
2. WebHDFS: It defines a public HTTP REST API, which permits clients to access Hadoop from multiple languages without installing
Hadoop, Advantage being language agnostic way(curl, php etc....).
WebHDFS needs access to all nodes of the cluster and when some data is
read, it is transmitted from the source node directly but **there is a overhead
of http ** (1)FS Shell but works agnostically and no problems with different hadoop cluster and versions.
3. HttpFS. Read and write data to HDFS in a cluster behind a firewall. Single node will act as GateWay node through which all the
data will be transfered and performance wise I believe this can be
even slower but preferred when needs to pull the data from public source into a secured cluster.
So choose rightly!.. Going down the list will always be an alternative when the choice above it is not available to you.
Hadoop provides a FileSystem Shell API to support file system operations such as create, rename or delete files and directories, open, read or write file.
The FileSystem shell is a java application that uses java FileSystem class to
provide FileSystem operations. FileSystem Shell API creates RPC connection for the operations.
If the client is within the Hadoop cluster, then this is useful because it use hdfs URI scheme to connect with the hadoop distributed FileSystem and hence client makes a direct RPC connection to write data into HDFS.
This is good for applications running within the Hadoop cluster but there may be use cases where an external application needs to manipulate HDFS like it needs to create directories and write files to that directory or read the content of a file stored on HDFS. Hortonworks developed an API to support these requirements based on standard REST functionality called WebHDFS.
WebHDFS provides the REST API functionality where any external application can connect the DistributedFileSystem over HTTP connection. No matter that the external application is Java or PHP.
WebHDFS concept is based on HTTP operations like GET, PUT, POST and DELETE.
Operations like OPEN, GETFILESTATUS, LISTSTATUS are using HTTP GET, others like CREATE, MKDIRS, RENAME, SETPERMISSIONS are relying on HTTP PUT
It provides secure read-write access to HDFS over HTTP. It is basically intended
as a replacement of HFTP(read only access over HTTP) and HSFTP(read only access over HTTPS).It used webhdfs URI scheme to connect with Distributed file system.
If the client is outside the Hadoop Cluster and trying to access HDFS. WebHDFS is usefull for it.Also If you are trying to connect the two difference version of Hadoop cluster then WebHDFS is usefull as it used REST API so it is independent of MapReduce or HDFS version.
The difference between HDFS access and WebHDFS is scalability due to the design of HDFS and the fact that a HDFS client decomposes a file into splits living in different nodes. When an HDFS client access file content, under the covers it goes to the NameNode and gets a list of file splits and their physical location on a Hadoop cluster.
It then can go do DataNodes living on all those locations to fetch blocks in the splits in parallel, piping the content directly to the client.
WebHDFS is a proxy living in the HDFS cluster and it layers on HDFS, so all data needs to be streamed to the proxy before it gets relayed on to the WebHDFS client. In essence it becomes a single point of access and an IO bottleneck.
You can you traditional java client api (which is being internally used by linux commands of hdfs).
From what I have read from here.
The performance of java client and Rest based approach have similar performance.
Assume that there is a Hadoop Cluster that has 20 machines. Out of those 20 machines 18 machines are slaves and machine 19 is for NameNode and machine 20 is for JobTracker.
Now i know that hadoop software has to be installed in all those 20 machines.
but my question is which machine is involved to load a file xyz.txt in to Hadoop Cluster. Is that client machine a separate machine . Do we need to install Hadoop software in that clinet machine as well. How does the client machine identifes Hadoop cluster?
I am new to hadoop, so from what I understood:
If your data upload is not an actual service of the cluster, which should be running on an edge node of the cluster, then you can configure your own computer to work as an edge node.
An edge node doesn't need to be known by the cluster (but for security stuff) as it does not store data nor compute job. This is basically what it means to be an edge-node: it is connected to the hadoop cluster but does not participate.
In case it can help someone, here is what I have done to connect to a cluster that I don't administer:
get an account on the cluster, say myaccount
create an account on you computer with the same name: myaccount
configure your computer to access the cluster machines (ssh w\out passphrase, registered ip, ...)
get the hadoop configuration files from an edge-node of the cluster
get a hadoop distrib (eg. from here)
uncompress it where you want, say /home/myaccount/hadoop-x.x
add the following environment variables: JAVA_HOME, HADOOP_HOME (/home/me/hadoop-x.x)
(if you'd like) add hadoop bin to your path: export PATH=$HADOOP_HOME/bin:$PATH
replace your hadoop configuration files by those you got from the edge node. With hadoop 2.5.2, it is the folder $HADOOP_HOME/etc/hadoop
also, I had to change the value of a couple $JAVA_HOME defined in conf files. To find them use: grep -r "export.*JAVA_HOME"
Then do hadoop fs -ls / which should list the root directory of the cluster hdfs.
Typically in case you have a multi tenant cluster (which most hadoop clusters are bound to be) then ideally no one other than administrators have access to the machines that are the part of the cluster.
Developers setup their own "edge-nodes". Edge Nodes basically have hadoop libraries and have the client configuration deployed to them (various xml files which tell the local installation where namenode, job tracker, zookeeper etc are core-site, mapred-site, hdfs-site.xml). But the edge node does not have any role as such in the cluster i.e. no persistent hadoop services are running on this node.
Now in case of a small development environment kind of setup you can use any one of the participating nodes of the cluster to run jobs or run shell commands.
So based on your requirement the definition and placement of client varies.
I recommend this article.
"Client machines have Hadoop installed with all the cluster settings, but are neither a Master or a Slave. Instead, the role of the Client machine is to load data into the cluster, submit Map Reduce jobs describing how that data should be processed, and then retrieve or view the results of the job when its finished."