2024 Spark java.lang.outofmemoryerror gc overhead limit exceeded

Nov 22, 2021 · 1 Answer. You are exceeding driver capacity (6GB) when calling collectToPython. This makes sense as your executor has much larger memory limit than the driver (12Gb). The problem I see in your case is that increasing driver memory may not be a good solution as you are already near the virtual machine limits (16GB). . I 2 red pill oval

Sep 1, 2015 · Sorted by: 2. From the logs it looks like the driver is running out of memory. For certain actions like collect, rdd data from all workers is transferred to the driver JVM. Check your driver JVM settings. Avoid collecting so much data onto driver JVM. Share. Improve this answer. Follow. The first approach works fine, the second ends up in another java.lang.OutOfMemoryError, this time about the heap. So, question: is there any programmatic alternative to this, for the particular use case (i.e., several small HashMap objects)? Exception in thread thread_name: java.lang.OutOfMemoryError: GC Overhead limit exceeded 原因: 「GC overhead limit exceeded」という詳細メッセージは、ガベージ・コレクタが常時実行されているため、Javaプログラムの処理がほとんど進んでいないことを示しています。Apr 14, 2020 · When calling on the read operation, spark first does a step where it lists all underlying files in S3, which is executed successfully. After this it does an initial load of all the data to construct a composite json schema for all files. Apr 12, 2016 · Options that come to mind are: Specify more memory using the JAVA_OPTS enviroment variable, try something in between like - Xmx1G. You can also tune your GC manually by enabling -XX:+UseConcMarkSweepGC. For more options on GC tuning refer Concurrent Mark Sweep. Increasing the HEAP size should fix your routes limit problem. The default behavior for Apache Hive joins is to load the entire contents of a table into memory so that a join can be performed without having to perform a Map/Reduce step. If the Hive table is too large to fit into memory, the query can fail.We have a spark SQL query that returns over 5 million rows. Collecting them all for processing results in java.lang.OutOfMemoryError: GC overhead limit exceeded (eventually).Spark seems to keep all in memory until it explodes with a java.lang.OutOfMemoryError: GC overhead limit exceeded. I am probably doing something really basic wrong but I couldn't find any pointers on how to come forward from this, I would like to know how I can avoid this.We have a spark SQL query that returns over 5 million rows. Collecting them all for processing results in java.lang.OutOfMemoryError: GC overhead limit exceeded (eventually).We have a spark SQL query that returns over 5 million rows. Collecting them all for processing results in java.lang.OutOfMemoryError: GC overhead limit exceeded (eventually).Oct 24, 2017 · I'm running a Spark application (Spark 1.6.3 cluster), which does some calculations on 2 small data sets, and writes the result into an S3 Parquet file. Here is my code: public void doWork( Feb 12, 2012 · Java Spark - java.lang.OutOfMemoryError: GC overhead limit exceeded - Large Dataset Load 7 more related questions Show fewer related questions 0 When I train the spark-nlp CRF model, emerged java.lang.OutOfMemoryError: GC overhead limit exceeded error Description I found the training process only run on driver ...4) If the new generation size is explicitly defined with JVM options (e.g. -XX:NewSize, -XX:MaxNewSize), decrease the size or remove the relevant JVM options entirely to unconstrain the JVM and provide more space in the old generation for long lived objects.java.lang.OutOfMemoryError: GC overhead limit exceeded. System specs: OS osx + boot2docker (8 gig RAM for virtual machine) ubuntu 15.10 inside docker container. Oracle java 1.7 or Oracle java 1.8 or OpenJdk 1.8. Scala version 2.11.6. sbt version 0.13.8. It fails only if I am running docker build w/ Dockerfile.Sep 26, 2019 · The same application code will not trigger the OutOfMemoryError: GC overhead limit exceeded when upgrading to JDK 1.8 and using the G1GC algorithm. 4) If the new generation size is explicitly defined with JVM options (e.g. -XX:NewSize, -XX:MaxNewSize), decrease the size or remove the relevant JVM options entirely to unconstrain the JVM and ... I've narrowed down the problem to only 1 of 8 excel files. I can consistently reproduce it on that particular excel file. It opens up just fine using microsoft excel, so I'm puzzled why only 1 particular excel file gives me an issue.So, the key is to " Prepend that environment variable " (1st time seen this linux command syntax :) ) HADOOP_CLIENT_OPTS="-Xmx10g" hadoop jar "your.jar" "source.dir" "target.dir". GC overhead limit indicates that your (tiny) heap is full. This is what often happens in MapReduce operations when u process a lot of data.Sep 23, 2018 · Spark: java.lang.OutOfMemoryError: GC overhead limit exceeded Hot Network Questions AI tricks space pirates into attacking its ship; kills all but one as part of effort to "civilize" space Aug 4, 2014 · I got a 40 node cdh 5.1 cluster and attempting to run a simple spark app that processes about 10-15GB raw data but I keep running into this error: java.lang.OutOfMemoryError: GC overhead limit exceeded. Each node has 8 cores and 2GB memory. I notice the heap size on the executors is set to 512MB with total set to 2GB. Exception in thread "yarn-scheduler-ask-am-thread-pool-9" java.lang.OutOfMemoryError: GC overhead limit exceeded ... spark.executor.memory to its max ...The first approach works fine, the second ends up in another java.lang.OutOfMemoryError, this time about the heap. So, question: is there any programmatic alternative to this, for the particular use case (i.e., several small HashMap objects)?But if your application genuinely needs more memory may be because of increased cache size or the introduction of new caches then you can do the following things to fix java.lang.OutOfMemoryError: GC overhead limit exceeded in Java: 1) Increase the maximum heap size to a number that is suitable for your application e.g. -Xmx=4G.Hi, everybody! I have a hadoop cluster on yarn. There are about Memory Total: 8.98 TB VCores Total: 1216 my app has followinng config (python api): spark = ( pyspark.sql.SparkSession .builder .mast...Oct 17, 2013 · 7. I am getting a java.lang.OutOfMemoryError: GC overhead limit exceeded exception when I try to run the program below. This program's main method access' a specified directory and iterates over all the files that contain .xlsx. This works fine as I tested it before any of the other logic. We have a spark SQL query that returns over 5 million rows. Collecting them all for processing results in java.lang.OutOfMemoryError: GC overhead limit exceeded (eventually).In summary, 1. Move the test execution out of jenkins 2. Provide the output of the report as an input to your performance plug-in [ this can also crash since it will need more JVM memory when you process endurance test results like an 8 hour result file] This way, your tests will have better chance of scaling. Spark DataFrame java.lang.OutOfMemoryError: GC overhead limit exceeded on long loop run 6 Pyspark: java.lang.OutOfMemoryError: GC overhead limit exceededjava.lang.OutOfMemoryError: GC overhead limit exceeded. My solution: set high values in >Settings >Build, Execution, Deployment >Build Tools >Maven >Importing - e.g. -Xmx1g and. change the maven implementation under >Settings >Build, Execution, Deployment >Build Tools >Maven (Maven home directory) from (Bundled) Maven 3 to my local maven ...The first approach works fine, the second ends up in another java.lang.OutOfMemoryError, this time about the heap. So, question: is there any programmatic alternative to this, for the particular use case (i.e., several small HashMap objects)? 此次异常是在集群上运行的spark程序日志中发现的。由于这个异常导致sparkcontext被终止，以致于任务失败：出现的一些原因参考：GC overhead limit exceededjava.lang.OutOfMemoryError有几种分类的，这次碰到的是java.lang.OutOfMemoryError: GC overhead limit exceeded，下面就来说说这种类型的内存溢出。I've set the overhead memory needed for spark_apply using spark.yarn.executor.memoryOverhead. I've found that using the by= argument of sfd_repartition is useful and using the group_by= in spark_apply also helps.May 24, 2023 · scala.MatchError: java.lang.OutOfMemoryError: Java heap space (of class java.lang.OutOfMemoryError) Cause. This issue is often caused by a lack of resources when opening large spark-event files. The Spark heap size is set to 1 GB by default, but large Spark event files may require more than this. In summary, 1. Move the test execution out of jenkins 2. Provide the output of the report as an input to your performance plug-in [ this can also crash since it will need more JVM memory when you process endurance test results like an 8 hour result file] This way, your tests will have better chance of scaling.Mar 22, 2018 · When I train the spark-nlp CRF model, emerged java.lang.OutOfMemoryError: GC overhead limit exceeded error Description I found the training process only run on driver ... Oct 31, 2018 · For Windows, I solved the GC overhead limit exceeded issue, by modifying the environment MAVEN_OPTS variable value with: -Xmx1024M -Xss128M -XX:MetaspaceSize=512M -XX:MaxMetaspaceSize=1024M -XX:+CMSClassUnloadingEnabled. Share. Improve this answer. Follow. Sorted by: 1. The difference was in available memory for driver. I found out it by zeppelin-interpreter-spark.log: memorystore started with capacity .... When I used bult-in spark it was 2004.6 MB for external spark it was 366.3 MB. So, I increased available memory for driver by setting spark.driver.memory in zeppelin gui. It solved the problem.Created on ‎08-04-2014 10:38 AM - edited ‎09-16-2022 02:04 AM. I got a 40 node cdh 5.1 cluster and attempting to run a simple spark app that processes about 10-15GB raw data but I keep running into this error: java.lang.OutOfMemoryError: GC overhead limit exceeded. Each node has 8 cores and 2GB memory. I notice the heap size on the ...Dec 24, 2014 · Spark seems to keep all in memory until it explodes with a java.lang.OutOfMemoryError: GC overhead limit exceeded. I am probably doing something really basic wrong but I couldn't find any pointers on how to come forward from this, I would like to know how I can avoid this. May 24, 2023 · scala.MatchError: java.lang.OutOfMemoryError: Java heap space (of class java.lang.OutOfMemoryError) Cause. This issue is often caused by a lack of resources when opening large spark-event files. The Spark heap size is set to 1 GB by default, but large Spark event files may require more than this. Excessive GC Time and OutOfMemoryError. The parallel collector will throw an OutOfMemoryError if too much time is being spent in garbage collection: if more than 98% of the total time is spent in garbage collection and less than 2% of the heap is recovered, an OutOfMemoryError will be thrown. This feature is designed to prevent applications ...java.lang.OutOfMemoryError: GC Overhead limit exceeded; java.lang.OutOfMemoryError: Java heap space. Note: JavaHeapSpace OOM can occur if the system doesn’t have enough memory for the data it needs to process. In some cases, choosing a bigger instance like i3.4x large(16 vCPU, 122Gib ) can solve the problem.Sep 1, 2015 · Sorted by: 2. From the logs it looks like the driver is running out of memory. For certain actions like collect, rdd data from all workers is transferred to the driver JVM. Check your driver JVM settings. Avoid collecting so much data onto driver JVM. Share. Improve this answer. Follow. Sparkで大きなファイルを処理する際などに「java.lang.OutOfMemoryError: GC overhead limit exceeded」が発生する場合があります。この際の対処方法をいかに記述します. GC overhead limit exceededとは. 簡単にいうと. GCが処理時間全体の98%以上を占める; GCによって確保されたHeap ...Jul 29, 2016 · If I had to guess your using Spark 1.5.2 or earlier. What is happening is you run out of memory. I think youre running out of executor memory, so you're probably doing a map-side aggregate. Dec 24, 2014 · Spark seems to keep all in memory until it explodes with a java.lang.OutOfMemoryError: GC overhead limit exceeded. I am probably doing something really basic wrong but I couldn't find any pointers on how to come forward from this, I would like to know how I can avoid this. – java.lang.OutOfMemoryError: GC overhead limit exceeded – org.apache.spark.shuffle.FetchFailedException Possible Causes and Solutions An executor might have to deal with partitions requiring more memory than what is assigned. Consider increasing the –executor memory or the executor memory overhead to a suitable value for your application.Why does Spark fail with java.lang.OutOfMemoryError: GC overhead limit exceeded? Related questions. 11 ... Spark memory limit exceeded issue. 2How do I resolve "OutOfMemoryError" Hive Java heap space exceptions on Amazon EMR that occur when Hive outputs the query results?Spark seems to keep all in memory until it explodes with a java.lang.OutOfMemoryError: GC overhead limit exceeded. I am probably doing something really basic wrong but I couldn't find any pointers on how to come forward from this, I would like to know how I can avoid this.In this article, we examined the java.lang.OutOfMemoryError: GC Overhead Limit Exceeded and the reasons behind it. As always, the source code related to this article can be found over on GitHub . Course – LS (cat=Java)Sorted by: 2. From the logs it looks like the driver is running out of memory. For certain actions like collect, rdd data from all workers is transferred to the driver JVM. Check your driver JVM settings. Avoid collecting so much data onto driver JVM. Share. Improve this answer. Follow.Spark DataFrame java.lang.OutOfMemoryError: GC overhead limit exceeded on long loop run 0 Java Spark - java.lang.OutOfMemoryError: GC overhead limit exceeded - Large Dataset@Sandeep Nemuri. I have resolved this issue with increasing spark_daemon_memory in spark configuration . Advanced spark2-env.Jan 20, 2020 · Problem: The job executes successfully when the read request has less number of rows from Aurora DB but as the number of rows goes up to millions, I start getting "GC overhead limit exceeded error". I am using JDBC driver for Aurora DB connection. Dec 16, 2020 · java.lang.OutOfMemoryError: GC Overhead limit exceeded; java.lang.OutOfMemoryError: Java heap space. Note: JavaHeapSpace OOM can occur if the system doesn’t have enough memory for the data it needs to process. In some cases, choosing a bigger instance like i3.4x large(16 vCPU, 122Gib ) can solve the problem. Aug 4, 2014 · I got a 40 node cdh 5.1 cluster and attempting to run a simple spark app that processes about 10-15GB raw data but I keep running into this error: java.lang.OutOfMemoryError: GC overhead limit exceeded. Each node has 8 cores and 2GB memory. I notice the heap size on the executors is set to 512MB with total set to 2GB. Dec 13, 2022 · Spark DataFrame java.lang.OutOfMemoryError: GC overhead limit exceeded on long loop run 1 sparklyr failing with java.lang.OutOfMemoryError: GC overhead limit exceeded From docs: spark.driver.memory "Amount of memory to use for the driver process, i.e. where SparkContext is initialized. (e.g. 1g, 2g). Note: In client mode, this config must not be set through the SparkConf directly in your application, because the driver JVM has already started at that point.Sep 8, 2009 · Excessive GC Time and OutOfMemoryError. The parallel collector will throw an OutOfMemoryError if too much time is being spent in garbage collection: if more than 98% of the total time is spent in garbage collection and less than 2% of the heap is recovered, an OutOfMemoryError will be thrown. This feature is designed to prevent applications ... GC Overhead limit exceeded exceptions disappeared. However, we still had the Java heap space OOM errors to solve . Our next step was to look at our cluster health to see if we could get any clues.Apr 11, 2012 · So, the key is to " Prepend that environment variable " (1st time seen this linux command syntax :) ) HADOOP_CLIENT_OPTS="-Xmx10g" hadoop jar "your.jar" "source.dir" "target.dir". GC overhead limit indicates that your (tiny) heap is full. This is what often happens in MapReduce operations when u process a lot of data. Two comments: xlConnect has the same problem. And more importantly, telling somebody to use a different library isn't a solution to the problem with the one being referenced.In summary, 1. Move the test execution out of jenkins 2. Provide the output of the report as an input to your performance plug-in [ this can also crash since it will need more JVM memory when you process endurance test results like an 8 hour result file] This way, your tests will have better chance of scaling.Options that come to mind are: Specify more memory using the JAVA_OPTS enviroment variable, try something in between like - Xmx1G. You can also tune your GC manually by enabling -XX:+UseConcMarkSweepGC. For more options on GC tuning refer Concurrent Mark Sweep. Increasing the HEAP size should fix your routes limit problem.Exception in thread "Spark Context Cleaner" java.lang.OutOfMemoryError: GC overhead limit exceeded Exception in thread "task-result-getter-2" java.lang.OutOfMemoryError: GC overhead limit exceeded . What can I do to fix this? I'm using Spark on YARN and spark memory allocation is dynamic. Also my Hive table is around 70G. Does it mean that I ...I've set the overhead memory needed for spark_apply using spark.yarn.executor.memoryOverhead. I've found that using the by= argument of sfd_repartition is useful and using the group_by= in spark_apply also helps. 1. To your first point, @samthebest, you should not use ALL the memory for spark.executor.memory because you definitely need some amount of memory for I/O overhead. If you use all of it, it will slow down your program. The exception to this might be Unix, in which case you have swap space. – makansij. GC overhead limit exceeded is thrown when the cpu spends more than 98% for garbage collection tasks. It happens in Scala when using immutable data structures since that for each transformation the JVM will have to re-create a lot of new objects and remove the previous ones from the heap.Duration of Excessive GC Time in "java.lang.OutOfMemoryError: GC overhead limit exceeded" 2 Why am I getting 'java.lang.OutOfMemoryError: GC overhead limit exceeded' if I have tons of free memory given to the JVM?May 28, 2013 · A new Java thread is requested by an application running inside the JVM. JVM native code proxies the request to create a new native thread to the OS The OS tries to create a new native thread which requires memory to be allocated to the thread. The OS will refuse native memory allocation either because the 32-bit Java process size has depleted ... The detail message "GC overhead limit exceeded" indicates that the garbage collector is running all the time and Java program is making very slow progress. Can be fixed in 2 ways 1) By Suppressing GC Overhead limit warning in JVM parameter Ex- -Xms1024M -Xmx2048M -XX:+UseConcMarkSweepGC -XX:-UseGCOverheadLimit. I have some data on postgres and trying to read that data on spark dataframe but i get error java.lang.OutOfMemoryError: GC overhead limit exceeded. I am using ...1. To your first point, @samthebest, you should not use ALL the memory for spark.executor.memory because you definitely need some amount of memory for I/O overhead. If you use all of it, it will slow down your program. The exception to this might be Unix, in which case you have swap space. – makansij. Hi, everybody! I have a hadoop cluster on yarn. There are about Memory Total: 8.98 TB VCores Total: 1216 my app has followinng config (python api): spark = ( pyspark.sql.SparkSession .builder .mast...How do I resolve "OutOfMemoryError" Hive Java heap space exceptions on Amazon EMR that occur when Hive outputs the query results?Mar 20, 2019 · WARN TaskSetManager: Lost task 4.1 in stage 6.0 (TID 137, 192.168.10.38): java.lang.OutOfMemoryError: GC overhead limit exceeded 解决办法：由于我们在执行Spark任务是，读取所需要的原数据，数据量太大，导致在Worker上面分配的任务执行数据时所需要的内存不够，直接导致内存溢出了，所以 ... Why does Spark fail with java.lang.OutOfMemoryError: GC overhead limit exceeded? Related questions. 11 ... Spark memory limit exceeded issue. 2java.lang.OutOfMemoryError: GC overhead limit exceeded 17/09/13 17:15:52 WARN server.TransportChannelHandler: Exception in connection from spark2/192.168.155.3:57252 java.lang.OutOfMemoryError: GC overhead limit exceeded 17/09/13 17:15:52 INFO storage.BlockManagerMasterEndpoint: Removing block manager BlockManagerId(6, spark1, 54732)For debugging run through the Spark shell, Zeppelin adds over head and takes a decent amount of YARN resources and RAM. Run on Spark 1.6 / HDP 2.4.2 if you can. Allocate as much memory as possible.Jul 16, 2020 · Hi, everybody! I have a hadoop cluster on yarn. There are about Memory Total: 8.98 TB VCores Total: 1216 my app has followinng config (python api): spark = ( pyspark.sql.SparkSession .builder .mast... The first approach works fine, the second ends up in another java.lang.OutOfMemoryError, this time about the heap. So, question: is there any programmatic alternative to this, for the particular use case (i.e., several small HashMap objects)?The GC Overhead Limit Exceeded error is one from the java.lang.OutOfMemoryError family, and it’s an indication of a resource (memory) exhaustion. In this quick tutorial, we’ll look at what causes the java.lang.OutOfMemoryError: GC Overhead Limit Exceeded error and how it can be solved.Sep 26, 2019 · 4) If the new generation size is explicitly defined with JVM options (e.g. -XX:NewSize, -XX:MaxNewSize), decrease the size or remove the relevant JVM options entirely to unconstrain the JVM and provide more space in the old generation for long lived objects.

I'm trying to process, 10GB of data using spark it is giving me this error, java.lang.OutOfMemoryError: GC overhead limit exceeded. Laptop configuration is: 4CPU, 8 logical cores, 8GB RAM. Spark configuration while submitting the spark job.. Little ceasar

spark java.lang.outofmemoryerror gc overhead limit exceeded

May 28, 2013 · A new Java thread is requested by an application running inside the JVM. JVM native code proxies the request to create a new native thread to the OS The OS tries to create a new native thread which requires memory to be allocated to the thread. The OS will refuse native memory allocation either because the 32-bit Java process size has depleted ... Create a temporary dataframe by limiting number of rows after you read the json and create table view on this smaller dataframe. E.g. if you want to read only 1000 rows, do something like this: small_df = entire_df.limit (1000) and then create view on top of small_df. You can increase the cluster resources. I've never used Databricks runtime ...1. I had this problem several times, sometimes randomly. What helped me so far was using the following command at the beginning of the script before loading any other package! options (java.parameters = c ("-XX:+UseConcMarkSweepGC", "-Xmx8192m")) The -XX:+UseConcMarkSweepGC loads an alternative garbage collector which seemed to make less ...Aug 25, 2021 · Spark DataFrame java.lang.OutOfMemoryError: GC overhead limit exceeded on long loop run 6 Pyspark: java.lang.OutOfMemoryError: GC overhead limit exceeded Mar 22, 2018 · When I train the spark-nlp CRF model, emerged java.lang.OutOfMemoryError: GC overhead limit exceeded error Description I found the training process only run on driver ... I got a 40 node cdh 5.1 cluster and attempting to run a simple spark app that processes about 10-15GB raw data but I keep running into this error: java.lang.OutOfMemoryError: GC overhead limit exceeded. Each node has 8 cores and 2GB memory. I notice the heap size on the executors is set to 512MB with total set to 2GB.Jul 16, 2020 · Hi, everybody! I have a hadoop cluster on yarn. There are about Memory Total: 8.98 TB VCores Total: 1216 my app has followinng config (python api): spark = ( pyspark.sql.SparkSession .builder .mast... But if your application genuinely needs more memory may be because of increased cache size or the introduction of new caches then you can do the following things to fix java.lang.OutOfMemoryError: GC overhead limit exceeded in Java: 1) Increase the maximum heap size to a number that is suitable for your application e.g. -Xmx=4G.Create a temporary dataframe by limiting number of rows after you read the json and create table view on this smaller dataframe. E.g. if you want to read only 1000 rows, do something like this: small_df = entire_df.limit (1000) and then create view on top of small_df. You can increase the cluster resources. I've never used Databricks runtime ...Sep 13, 2015 · Exception in thread "Spark Context Cleaner" java.lang.OutOfMemoryError: GC overhead limit exceeded Exception in thread "task-result-getter-2" java.lang.OutOfMemoryError: GC overhead limit exceeded . What can I do to fix this? I'm using Spark on YARN and spark memory allocation is dynamic. Also my Hive table is around 70G. Does it mean that I ... In this article, we examined the java.lang.OutOfMemoryError: GC Overhead Limit Exceeded and the reasons behind it. As always, the source code related to this article can be found over on GitHub . Course – LS (cat=Java)and, when i run this script on spark-shell i got following error, after running line of code simsPerfect_entries.count(): java.lang.OutOfMemoryError: GC overhead limit exceeded Updated: I tried many solutions already given by others ,but i got no success. 1 By increasing amount of memory to use per executor process spark.executor.memory=1gA new Java thread is requested by an application running inside the JVM. JVM native code proxies the request to create a new native thread to the OS The OS tries to create a new native thread which requires memory to be allocated to the thread. The OS will refuse native memory allocation either because the 32-bit Java process size has depleted ...Oct 17, 2013 · 7. I am getting a java.lang.OutOfMemoryError: GC overhead limit exceeded exception when I try to run the program below. This program's main method access' a specified directory and iterates over all the files that contain .xlsx. This works fine as I tested it before any of the other logic. Create a temporary dataframe by limiting number of rows after you read the json and create table view on this smaller dataframe. E.g. if you want to read only 1000 rows, do something like this: small_df = entire_df.limit (1000) and then create view on top of small_df. You can increase the cluster resources. I've never used Databricks runtime ...Aug 18, 2015 · GC overhead limit exceeded is thrown when the cpu spends more than 98% for garbage collection tasks. It happens in Scala when using immutable data structures since that for each transformation the JVM will have to re-create a lot of new objects and remove the previous ones from the heap. .

I'm trying to process, 10GB of data using spark it is giving me this error, java.lang.OutOfMemoryError: GC overhead limit exceeded. Laptop configuration is: 4CPU, 8 logical cores, 8GB RAM. Spark configuration while submitting the spark job.. Little ceasar

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