If you open up the driver UI (running on 4040), you can see multiple tasks
per stage which will be happening concurrently. If it is a single task, and
you want to increase the parallelism, then you can simply do a re-partition.
Thanks
Best Regards
On Tue, May 26, 2015 at 8:27 AM, <luohui20...@sina.com> wrote:
> I am right trying to run some shell script in my spark app, hoping it runs
> more concurrently in my spark cluster.
>
> However I am not sure whether my codes will run concurrently in my
> executors.
>
> Dive into my code, you can see that I am trying to
>
> 1.splite both db and sample into 21 small files. That will generate total
> 42 files. By spliting db I will get "chr1" ,"chr2",..."chr21", and spliting
> sample I will get "samplechr1","samplechr2",..."samplechr21".
>
> 2.merge those splited files from hdfs and save to local path.Those merged
> file will be "chr1.txt" ,"chr2.txt",..."chr21.txt" and
> "samplechr1.txt","samplechr2.txt",..."samplechr21.txt"
>
> 3.run modify.sh to clean the data, that means to delete some charactors
> not useful.
>
> 4.run shellcompare.sh to compare chr1.txt and samplechr1.txt, get a
> result1.txt. And looping it from 1 to 21 so that those 42 file are compared
> and I can get 21 files like result1.txt,result2.txt...result21.txt.
>
> Sorry for not adding some comments for my code.
>
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>
> ----- 原始邮件 -----
> 发件人：Akhil Das <ak...@sigmoidanalytics.com>
> 收件人：罗辉 <luohui20...@sina.com>
> 抄送人：user <user@spark.apache.org>
> 主题：Re: Re: Re: how to distributed run a bash shell in spark
> 日期：2015年05月25日 22点41分
>
> Can you can tell us what exactly you are trying to achieve?
>
> Thanks
> Best Regards
>
> On Mon, May 25, 2015 at 5:00 PM, <luohui20...@sina.com> wrote:
>
> thanks, madhu and Akhil
>
> I modified my code like below,however I think it is not so distributed.
> Have you guys better idea to run this app more efficiantly and distributed?
>
> So I add some comments with my understanding:
>
> import org.apache.spark._
> import www.celloud.com.model._
>
> object GeneCompare3 {
> def main(args: Array[String]) {
> val conf = new
> SparkConf().setAppName("GeneCompare").setMaster("spark://master:7077").set("spark.executor.memory",
> "6g").set("hive.metastore.warehouse.dir", "/user/hive/warehouse")
> val sc = new SparkContext(conf)
> val sqlContext = new org.apache.spark.sql.SQLContext(sc)
> import sqlContext.implicits._
>
> val db = sc.textFile("/data/db.txt").map(_.split("\t")).map(x =>
> Database(x(0),
> x(1).trim().toInt,
> x(2).trim().toInt,
> x(3).trim().toInt,
> x(4).trim().toInt)).toDF()
> val sample = sc.textFile("/data/sample.txt").map(_.split("\t")).map(x
> => Sample(x(0),
> x(1).trim().toInt,
> x(2),
> x(3).trim().toInt,
> x(4).trim().toInt,
> x(5))).toDF()
>
> //using Akhil Das's idea,1to21 is a file with 21lines,each line is a
> single number
> // val test = sc.textfile("1to21.txt").foreach{i
> => //running on driver manager
> // db.filter("chrname = 'chr" + i +
> "'").rdd.saveAsTextFile("/data/chr" + i) //running on driver
> executor
> // db.rdd.pipe("hadoop fs -getmerge /data/chr" + i + "
> /opt/data/shellcompare/chr" + i + ".txt")
> // sample.filter("name = 'chr" + i +
> "'").rdd.saveAsTextFile("/data/samplechr" + i)
> // db.rdd.pipe("hadoop fs -getmerge /data/samplechr" + i + "
> /opt/data/shellcompare/samplechr" + i + ".txt") //running on driver
> executor
> // }.collect() //running on driver manager
>
> //using madhu's method
>
> //running on driver manager
>
> for (i <- 1 to 21) {
> db.filter("chrname = 'chr" + i + "'").rdd.saveAsTextFile("/data/chr"
> + i)
> db.rdd.pipe("hadoop fs -getmerge /data/chr" + i + "
> /opt/data/shellcompare/chr" + i + ".txt").collect()
> sample.filter("name = 'chr" + i +
> "'").rdd.saveAsTextFile("/data/samplechr" + i)
> db.rdd.pipe("hadoop fs -getmerge /data/samplechr" + i + "
> /opt/data/shellcompare/samplechr" + i + ".txt").collect()
> }
>
>
>
> //running on driver manager
>
> val runmodifyshell=List("run","modify.sh")
> val runmodifyshellRDD = sc.makeRDD(runmodifyshell)
> val pipeModify = runmodifyshellRDD.pipe("sh
> /opt/data/shellcompare/modify.sh")
>
> pipeModify.collect()
>
>
>
> //running on driver manager
> val shellcompare = List("run","sort.sh")
> val shellcompareRDD = sc.makeRDD(shellcompare)
> val result = List("aggregate","result")
> val resultRDD = sc.makeRDD(result)
> for(j <- 1 to 21){
> shellcompareRDD.pipe("sh /opt/sh/bin/sort.sh
> /opt/data/shellcompare/chr" + j + ".txt /opt/data/shellcompare/samplechr" +
> j + ".txt /opt/data/shellcompare/result" + j + ".txt 600").collect()
> if (j > 1) resultRDD.pipe("cat result" + j + ".txt >>
> result1.txt").collect()
> }
> }
> }
>
>
> And I know there are some problems in my code, such as "modify.sh" will
> not be executed.
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>
> ----- 原始邮件 -----
> 发件人：madhu phatak <phatak....@gmail.com>
> 收件人：luohui20...@sina.com
> 抄送人：Akhil Das <ak...@sigmoidanalytics.com>, user <user@spark.apache.org>
> 主题：Re: Re: how to distributed run a bash shell in spark
> 日期：2015年05月25日 14点11分
>
> Hi,
> You can use pipe operator, if you are running shell script/perl script on
> some data. More information on my blog
> <http://blog.madhukaraphatak.com/pipe-in-spark/>.
>
>
>
>
> Regards,
> Madhukara Phatak
> http://datamantra.io/
>
> On Mon, May 25, 2015 at 8:02 AM, <luohui20...@sina.com> wrote:
>
> Thanks Akhil,
>
> your code is a big help to me,'cause perl script is the exactly
> thing i wanna try to run in spark. I will have a try.
>
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>
> ----- 原始邮件 -----
> 发件人：Akhil Das <ak...@sigmoidanalytics.com>
> 收件人：罗辉 <luohui20...@sina.com>
> 抄送人：user <user@spark.apache.org>
> 主题：Re: how to distributed run a bash shell in spark
> 日期：2015年05月25日 00点53分
>
> You mean you want to execute some shell commands from spark? Here's
> something i tried a while back. https://github.com/akhld/spark-exploit
>
> Thanks
> Best Regards
>
> On Sun, May 24, 2015 at 4:53 PM, <luohui20...@sina.com> wrote:
>
> hello there
>
> I am trying to run a app in which part of it needs to run a
> shell.how to run a shell distributed in spark cluster.thanks.
>
>
> here's my code:
>
> import java.io.IOException;
> import java.util.ArrayList;
> import java.util.List;
>
> import org.apache.spark.SparkConf;
> import org.apache.spark.api.java.JavaRDD;
> import org.apache.spark.api.java.JavaSparkContext;
> import org.apache.spark.sql.DataFrame;
> import org.apache.spark.sql.Row;
> import org.apache.spark.sql.SQLContext;
> import org.apache.spark.sql.types.DataType;
> import org.apache.spark.sql.types.StructField;
> import org.apache.spark.sql.types.StructType;
>
> public class ShellCompare {
> public static void main(String[] args) {
> // TODO Auto-generated method stub
> SparkConf conf = new
> SparkConf().setAppName("ShellCompare").setMaster("spark://master:7077").set("spark.executor.memory",
> "6g");
> JavaSparkContext sc = new JavaSparkContext(conf);
>
> for(int i=1;i<=21;i++){
> execShell(i);
> }
> // execShell(1);
> sc.stop();
> }
>
> private static void execShell(int i) {
> String shpath="/opt/sh/bin/sort.sh";
> Process process =null;
>
> String var="/opt/data/shellcompare/chr" + i +".txt
> /opt/data/shellcompare/samplechr" + i +".txt
> /opt/data/shellcompare/result.txt 600";
> // String var="/opt/data/chr1.txt /opt/data/chr1sample.txt
> /opt/sh/bin/result.txt 600";
> String command2 = "sh " + shpath + " " + var;
> try {
> process = Runtime.getRuntime().exec(command2);
> process.waitFor();
> } catch (InterruptedException e1) {
> // TODO Auto-generated catch block
> e1.printStackTrace();
> } catch (IOException e) {
> // TODO Auto-generated catch block
> e.printStackTrace();
> }
> }
>
> }
>
>
>
> --------------------------------
>
> Thanks&Best regards!
> San.Luo
>
>
>
>
>
