Re: Need help about how hadoop works.
Thanks Mayur. So without Hadoop and any other distributed file systems, by running: val doc = sc.textFile(/home/scalatest.txt,5) doc.count we can only get parallelization within the computer where the file is loaded, but not the parallelization within the computers in the cluster (Spark can not automatically duplicate the file to the other computers in the cluster), is this understanding correct? Thank you. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4734.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
Re: Need help about how hadoop works.
Prashant Sharma On Thu, Apr 24, 2014 at 12:15 PM, Carter gyz...@hotmail.com wrote: Thanks Mayur. So without Hadoop and any other distributed file systems, by running: val doc = sc.textFile(/home/scalatest.txt,5) doc.count we can only get parallelization within the computer where the file is loaded, but not the parallelization within the computers in the cluster (Spark can not automatically duplicate the file to the other computers in the cluster), is this understanding correct? Thank you. Spark will not distribute that file for you on other systems, however if the file(/home/scalatest.txt) is present on the same path on all systems it will be processed on all nodes. We generally use hdfs which takes care of this distribution. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4734.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
Re: Need help about how hadoop works.
Thank you very much for your help Prashant. Sorry I still have another question about your answer: however if the file(/home/scalatest.txt) is present on the same path on all systems it will be processed on all nodes. When presenting the file to the same path on all nodes, do we just simply copy the same file to all nodes, or do we need to split the original file into different parts (each part is still with the same file name scalatest.txt), and copy each part to a different node for parallelization? Thank you very much. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4738.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
Re: Need help about how hadoop works.
It is the same file and hadoop library that we use for splitting takes care of assigning the right split to each node. Prashant Sharma On Thu, Apr 24, 2014 at 1:36 PM, Carter gyz...@hotmail.com wrote: Thank you very much for your help Prashant. Sorry I still have another question about your answer: however if the file(/home/scalatest.txt) is present on the same path on all systems it will be processed on all nodes. When presenting the file to the same path on all nodes, do we just simply copy the same file to all nodes, or do we need to split the original file into different parts (each part is still with the same file name scalatest.txt), and copy each part to a different node for parallelization? Thank you very much. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4738.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
RE: Need help about how hadoop works.
Thank you very much Prashant. Date: Thu, 24 Apr 2014 01:24:39 -0700 From: ml-node+s1001560n4739...@n3.nabble.com To: gyz...@hotmail.com Subject: Re: Need help about how hadoop works. It is the same file and hadoop library that we use for splitting takes care of assigning the right split to each node.Prashant Sharma On Thu, Apr 24, 2014 at 1:36 PM, Carter [hidden email] wrote: Thank you very much for your help Prashant. Sorry I still have another question about your answer: however if the file(/home/scalatest.txt) is present on the same path on all systems it will be processed on all nodes. When presenting the file to the same path on all nodes, do we just simply copy the same file to all nodes, or do we need to split the original file into different parts (each part is still with the same file name scalatest.txt), and copy each part to a different node for parallelization? Thank you very much. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4738.html Sent from the Apache Spark User List mailing list archive at Nabble.com. If you reply to this email, your message will be added to the discussion below: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4739.html To unsubscribe from Need help about how hadoop works., click here. NAML -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638p4746.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
Re: Need help about how hadoop works.
As long as the path is present available on all machines you should be able to leverage distribution. HDFS is one way to make that happen, NFS is another simple replication is another. Mayur Rustagi Ph: +1 (760) 203 3257 http://www.sigmoidanalytics.com @mayur_rustagi https://twitter.com/mayur_rustagi On Wed, Apr 23, 2014 at 12:12 PM, Carter gyz...@hotmail.com wrote: Hi, I am a beginner of Hadoop and Spark, and want some help in understanding how hadoop works. If we have a cluster of 5 computers, and install Spark on the cluster WITHOUT Hadoop. And then we run the code on one computer: val doc = sc.textFile(/home/scalatest.txt,5) doc.count Can the count task be distributed to all the 5 computers? Or it is only run by 5 parallel threads of the current computer? On th other hand, if we install Hadoop on the cluster and upload the data into HDFS, when running the same code will this count task be done by 25 threads? Thank you very much for your help. -- View this message in context: http://apache-spark-user-list.1001560.n3.nabble.com/Need-help-about-how-hadoop-works-tp4638.html Sent from the Apache Spark User List mailing list archive at Nabble.com.
