Currently i have 2 machines one of them is the Horton sandbox i have configured it as name node and decommissioned the data node from it and other machine which i have made and made it as a data node and i have installed hive server on it.
Also and assigned the slave role to it and i used Ambari to finish it .
My question is as its my first time ever to use hadoop my plan is to transfer data from sql database to the hadoop so does this mean i have to install mysql on datanode while i will be using sqoop and other thing what will the name node do ?shall i query it and it passes the queries to the datanode am really very much confused and really having huge pressure to finish so forgive me as am newbie the installations of the machines are all default i have chosen datanode for the First machine and nodemanager for the second one with no special configurations appreciate if You have a simple example from which i can understand .
Thanks alot fellows
Sqoop is a tool designed to transfer data between Hadoop and relational database servers. It is used to import data from relational databases such as MySQL, Oracle to Hadoop HDFS, and export from Hadoop file system to relational databases.
example like- you have some data in mysql in other machine and you have to transfer the data into your hadoop hdfs. In this condition sqoop will be used
NameNode stores MetaData(No of Blocks, On Which Rack which DataNode the data is stored and other details) about the data being stored in DataNodes whereas the DataNode stores the actual Data.
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I was doing a case study on Spotify. I found out that Spotify uses Cassandra as a DB and also Hadoop. My question is, how is Hadoop different from a database. What type of files does Hadoop datanode stores? Why every corporation has DB and Hadoop as well. I know Hadoop is not a DB but what is it used for if there is DB cluster to save data?
Hadoop is not a database at all. Hadoop is a set of tools for distributed storage and processing, such as distributed filesystem (HDFS), MapReduce framework libraries, YARN resource manager.
Other tools like Hive, Spark, Pig, Giraph, sqoop, etc, etc can use Hadoop or it's components. For example Hive is a database. It uses HDFS for storing it's data and MapReduce framework primitives for building query execution graph.
I am new to Hadoop / Pig and I have just started reading the docs.
There are lots of blogs on installing Hadoop in cluster mode.
I know that Pig runs on top of Hadoop.
My question is: Hadoop is installed on all the cluster nodes.
Should I also install Pig on all the cluster nodes or only on the master node?
You would want to install Hive Metastore and Hive Server on 2 different nodes. By default, hive uses derby database, but most of the people choose to go with MySQL so there will be a MYSQL server daemon also.
So not to confuse you anymore :
Install HiveServer and WebHcat Server on one node
Install Hive Metastore and MySQL server on another node.
This is the best practice. If you have any other doubt you can ask!
I cannot tell if the question is about Hive or Pig, but there's a difference between clients and servers.
For Hive, the master services are the Metastore and HiveServer2. You can install these daemons on the same server to improve network traffic between the metastore and the Hive query compiler. You only need one client to communicate with those masters.
For Pig, it communicates directly to YARN and HDFS (optionally Hive, if you use Hcatalog). Again, it's only a client, so only one hosts needs it.
It is generally preferred to have a dedicated set of machines for Hive and the backing RDBMS for the metastore (Mysql or Postgres being the more popular options)
You also don't need to "install Pig in the cluster". For example, I could grab the Hadoop XML configs and run some Pig code against the YARN cluster from any outside computer after downloading Pig locally (same applies to Spark)
Sorry that I don't have the resource to set up a cluster to test it, I'm just wondering to know:
Can I deploy hbase region server on a separated machine other than the hadoop data node machine? I guess the answer is yes, but I'm not sure.
Is it good or bad to deploy hbase region server and hadoop data node on different machines?
When putting some data into hbase, where is this data eventually stored in, data node or region server? I guess it's data node, but what is the StoreFile and HFile in region server, isn't it the physical file to store our data?
Thank you!
RegionServers should always run alongside DataNodes in distributed clusters if you want decent performance.
Very bad, that will work against the data locality principle (If you want to know a little more about data locality check this: http://www.larsgeorge.com/2010/05/hbase-file-locality-in-hdfs.html)
Actual data will be stored in the HDFS (DataNode), RegionServers are responsible of serving and managing regions.
For more information about HBase architecture please check this excelent post from Lars' blog: http://www.larsgeorge.com/2009/10/hbase-architecture-101-storage.html
BTW, as long as you have a PC with decent RAM you can set up a demo cluster with virtual machines. Do not ever try to set up a production environment without properly test the platform first in a development environment.
To go in more detail about this answer:
RegionServers should always run alongside? DataNodes in distributed clusters if you want decent performance."
I'm not sure how anyone would interpet the term alongside, so let's try to be even more precise:
What makes any physical server an "XYZ" server is that it's running a program called a daemon (think "eternally-running background event-handling" program);
What makes a "file" server is that it's running a file-serving daemon;
What makes a "web" server is that it's running a web-serving daemon;
AND
What makes a "data node" server is that it's running the HDFS data-serving daemon;
What makes a "region" server then is that it's running the HBase region-serving daemon (program);
So, in all Hadoop Distributions (eg Cloudera, MAPR, Hortonworks, others), the general best practice is that for HBase, the "RegionServers" are "co-located" with the "DataNodeServers".
This means that the actual slave (datanode) servers which form the HDFS cluster are each running the HDFS data-serving daemon (program)
and they're also running the HBase region-serving daemon (program) as well!
This way we ensure locality - the concurrent processing and storing of data on all the individual nodes in an HDFS cluster, with no "movement" of gigantic loads of big data from "storage" locations to "processing" locations. Locality is vital to the success of a Hadoop cluster, such that HBase region servers (data nodes running the HBase daemon as well) must also do all their processing (putting/getting/scanning) on each data node containing the HFiles which make up HRegions which make up HTables which make up HBases (Hadoop-dataBases) ... .
So, servers (VMs or physical on Windows, Linux, ..) can run multiple daemons concurrently, often, they run dozens of them regularly.
I'm having a problem about hive server that I don't understand. I've just set up a hadoop cluster and want to access to it from a hive service. First try I did was running the hive server in one of the cluster machines.
Everything worked nicely but I wanted to move the hive service to another machine outside the hadoop cluster.
So I just started a new machine outside this hadoop cluster. I've just install hive (+ hadoop libraries) and copied the hadoop config from the cluster. When I run the hiveserver almost everything goes ok. I can connect with the hive cli from a different machine to my hiveserver, create new tables in the hive warehouse within the hdfs filesystem in the hadoop cluster, query then and so on.
The thing I don't understand is that hiveserver seems to not recognize old tables which were created in my first try.
Some notes about my config are that all tables are handled by Hive and stored in HDFS. Hive configuration is the default one. I suppose that it has to do with my hive metastore but it couldn't say what.
Thank you!!
I am a newbie to Hadoop / Hive and I have just started reading the docs. There are lots of blogs on installing Hadoop in cluster mode. Also, I know that Hive runs on top of Hadoop.
My question is: Hadoop is installed on all the cluster nodes. Should I also install Hive on all the cluster nodes or only on the master node?
No, it is not something you install on worker nodes. Hive is a Hadoop client. Just run Hive according to the instructions you see at the Hive site.
From Cloudera's Hive installation Guide:
Install Hive on your client machine(s) from which you submit jobs; you do not need to install it on the nodes in your Hadoop cluster.
Hive is basically used for processing structured and semi-structured data in Hadoop. We can also perform Analysis of large datasets which is present in HDFS and also in Amazon S3 filesystem using Hive. In order to query data hive also provides query language known as HiveQL which is similar to SQL. Using Hive one can easily run Ad-hoc queries for the data analysis. Using Hive we don’t need to write complex Map-Reduce jobs, we just need to submit SQL queries. Hive converts these SQL queries into MapReduce jobs.
Finally Hive SQL will get converted to MapReduce jobs and we don't have to submit MapReduce job from all node in a Hadoop cluster, in the same way we don't need Hive to be installed in all node of Hadoop cluster