Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about Teamsone can solve this job aborted error, either changing the "spark configuration" in the cluster or either use "try_cast" function when you are getting this error while inserting data from one table to another table in databricks. use dbr version : 10.4 LTS (includes Apache Spark 3.2.1, Scala 2.12)Jan 16, 2023 · If issue persists, please contact Microsoft support for further assistance","Details":"org.apache.spark.SparkException: Job aborted due to stage failure: Task 320 in stage 21.0 failed 1 times, most recent failure: Lost task 320.0 in stage 21.0 (TID 1297, vm-42929650, executor 1): ExecutorLostFailure (executor 1 exited caused by one of the ... Pyspark. spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, java.net.SocketException: Connection reset Hot Network Questions Does America, like non-democratic countries like China, also have factions?Here are some ideas to fix this error: Serializable the class. Declare the instance only within the lambda function passed in map. Make the NotSerializable object as a static and create it once per machine. Call rdd.forEachPartition and create the NotSerializable object in there like this: rdd.forEachPartition (iter -> { NotSerializable ...SparkException: Python worker failed to connect back when execute spark action 4 Pyspark. spark.SparkException: Job aborted due to stage failure: Task 0 in stage 15.0 failed 1 times, java.net.SocketException: Connection resetorg.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 0.0 failed 4 times, most recent failure: Lost task 2.3 in stage 0.0 Updating the dependancy in SBT solved the problem.Stack Overflow Public questions & answers; Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Talent Build your employer brandJun 25, 2020 · Apache Spark; koukou. ... org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 30.0 failed 1 times, most recent failure: Lost task 0.0 ... hello everyone I am working on PySpark Python and I have mentioned the code and getting some issue, I am wondering if someone knows about the following issue? windowSpec = Window.partitionBy(Jan 3, 2022 · Based on the code , am not seeing anything wrong . Still you can analysis this issue based on the following data related . Make sure 4th line lines rdd has the data based on the collect(). org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 20 (repartition at data_prep.scala:87) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.MetadataFetchFailedException: Missing an output location for shuffle 9I installed apache-spark and pyspark on my machine (Ubuntu), and in Pycharm, I also updated the environment variables (e.g. spark_home, pyspark_python). I'm trying to do: import os, sys os.environ['org.apache.spark.SparkException: Job aborted due to stage failure: 8 Databricks Exception: Total size of serialized results is bigger than spark.driver.maxResultsSizeTeams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsData collection is indirect, with data being stored both on the JVM side and Python side. While JVM memory can be released once data goes through socket, peak memory usage should account for both. Plain toPandas implementation collects Rows first, then creates Pandas DataFrame locally. This further increases (possibly doubles) memory usage. Exception in thread "main" org.apache.spark.SparkException : Job aborted due to stage failure: Task 3 in stage 0.0 failed 4 times, most recent failure: Lost task 3.3 in stage 0.0 (TID 14, 192.168.10.38): ExecutorLostFailure (executor 3 lost) Driver stacktrace:Data collection is indirect, with data being stored both on the JVM side and Python side. While JVM memory can be released once data goes through socket, peak memory usage should account for both. Plain toPandas implementation collects Rows first, then creates Pandas DataFrame locally. This further increases (possibly doubles) memory usage. 2. I am running my code in production and it runs successfully most of the time but some times it fails with following error: catch exceptionorg.apache.spark.SparkException: Job aborted due to stage failure: Task 14 in stage 9.1 failed 4 times, most recent failure: Lost task 14.3 in stage 9.1 (TID 3825, xxxprd0painod02.xxxprd.local): java.io ...Solve : org.apache.spark.SparkException: Job aborted due to stage failure 1 Spark Error: Executor XXX finished with state EXITED message Command exited with code 1 exitStatus 1Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question.Provide details and share your research! But avoid …. Asking for help, clarification, or responding to other answers.不知道是什么原因。. （利用 Spark-submit 提交 参数都正常）. 但是 集群上的版本是1.5，和2.0都无法跑出来结果，但是1.3就能出结果， 所以目前确定是 Spark 1.5以上的版本对协同过滤算法不兼容引起，具体原因不详。. task倾斜原因比较多，网络io,cpu,mem都有可能造成 ...The copy activity was interrupted part way through as the source database went offline which then caused the failure to complete writing the files properly. These were easily found as they were the most recently modified files.1 Answer. PySpark DF are lazy loading. When you call .show () you are asking the prior steps to execute and anyone of them may not work, you just can't see it until you call .show () because they haven't executed. I go back to earlier steps and call .collect () on each operation of the DF. This will at least allow you to isolate where the bad ...If absolutely necessary you can set the property spark.driver.maxResultSize to a value <X>g higher than the value reported in the exception message in the cluster Spark config ( AWS | Azure ): spark.driver.maxResultSize < X > g. The default value is 4g. For details, see Application Properties. If you set a high limit, out-of-memory errors can ...If I had a penny for every time I asked people "have you tried increasing the number of partitions to something quite large like at least 4 tasks per CPU - like even as high as 1000 partitions?"I am doing it using spark code. But when i try to run the code I get following exception org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 1.0 failed 4 times, most recent failure: Lost task 2.3 in stage 1.0 (TID 9, XXXX.XXX.XXX.local): org.apache.spark.SparkException: Task failed while writing rows.Check your data for null where not null should be present and especially on those columns that are subject of aggregation, like a reduce task, for example. In your case, it may be the id field. Your rdd is getting empty somewhere. The null pointer exception indicates that an aggregation task is attempted against of a null value. Check your data ...Solution 1. Check your environment variables. You are getting “py4j.protocol.Py4JError: org.apache.spark.api.python.PythonUtils.getEncryptionEnabled does not exist in the JVM” due to Spark environemnt variables are not set right. If I had a penny for every time I asked people "have you tried increasing the number of partitions to something quite large like at least 4 tasks per CPU - like even as high as 1000 partitions?"Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Aborting TaskSet 0.0 because task 0 (partition 0) cannot run anywhere due to node and executor blacklist.Based on the code , am not seeing anything wrong . Still you can analysis this issue based on the following data related . Make sure 4th line lines rdd has the data based on the collect().2 Answers. df.toPandas () collects all data to the driver node, hence it is very expensive operation. Also there is a spark property called maxResultSize. spark.driver.maxResultSize (default 1G) --> Limit of total size of serialized results of all partitions for each Spark action (e.g. collect) in bytes. Should be at least 1M, or 0 for unlimited.Jul 7, 2019 · 1 I'm trying to use Linear Regression on a simple dataframe with one feature and one label using Python pyspark in Databricks. However, I'm running into some issues with stage failure. I've reviewed many similar problems, but most of them are in Scala or are out of the scope of what I'm doing here. Versions: Nov 28, 2019 · According to the content of README.md of GitHub repo Azure/azure-cosmosdb-spark as the figure below, you may should switch to use the latest jar file azure-cosmosdb-spark_2.4.0_2.11-1.4.0-uber.jar in it. And the maven repo for Azure CosmosDB Spark has released to 1.4.1 version, as the figure below. >>Job aborted due to stage failure: Total size of serialized results of 19 tasks (4.2 GB) is bigger than spark.driver.maxResultSize (4.0 GB)'.. The exception was raised by the IDbCommand interface. Please take a look at following document about maxResultsize issue:Nov 1, 2017 · Saved searches Use saved searches to filter your results more quickly Feb 6, 2019 · I am new to PySpark. I have been writing my code with a test sample. Once I run the code on the larger file(3gb compressed). My code is only doing some filtering and joins. I keep getting errors org.apache.spark.SparkException: **Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1 ...Sep 1, 2022 · use dbr version : 10.4 LTS (includes Apache Spark 3.2.1, Scala 2.12) for spark configuartion edit the spark tab by editing the cluster and use below code there. "spark.sql.ansi.enabled false" SparkException: Job aborted due to stage failure: Task 58 in stage 13.0 failed 4 times, most recent failure: Lost task 58.3 in stage 13.0 (TID 488, 10.32.14.43, executor 4): java.lang.IllegalArgumentException: Illegal pattern character 'Q'Aug 12, 2021 · SparkException：执行 spark 操作时 Python 工作线程无法连接回spark.SparkException: Python worker failed to connect back.问问题当我尝试在 pyspark 执行此命令行时from pyspark import SparkConf, SparkContext# 创建SparkConf和SparkContextconf = SparkConf().setMaster("local").setAppName("lic Here is the full list of commands creating the list, writing it to HDFS and finally printing out the results on the console using hdfs: spark-shell. After the shell has started you type: val nums = sc.parallelize (List (1,2,3,4,5)) nums.saveAsTextFile ("/tmp/simple_list") :quit. Now we read the data from HDFS (Hadoop File System):I am doing it using spark code. But when i try to run the code I get following exception org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 1.0 failed 4 times, most recent failure: Lost task 2.3 in stage 1.0 (TID 9, XXXX.XXX.XXX.local): org.apache.spark.SparkException: Task failed while writing rows.Sep 21, 2021 · I am trying to solve the problems from O'Reilly book of Learning Spark. Below part of code is working fine from pyspark.sql.types import * from pyspark.sql import SparkSession from pyspark.sql.func... : org.apache.spark.SparkException: Job aborted due to stage failure: Task 9 in stage 47.0 failed 4 times, most recent failure: Lost task 9.3 in stage 47.0 (TID 2256, ip-172-31-00-00.eu-west-1.compute.internal, executor 10): org.apache.spark.sql.execution.QueryExecutionException: Parquet column cannot be converted in file s3a://bucket/prod ...Nov 2, 2020 · Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about Teams org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1486.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1486.0 (TID 1665) (10.116.129.142 executor 0): org.apache.spark.SparkException: Failed to store executor broadcast spark_join_relation_469_-315473829 in BlockManager.In my project i am using spark-Cassandra-connector to read the from Cassandra table and process it further into JavaRDD but i am facing issue while processing Cassandra row to javaRDD.: org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 302987:27 was 139041896 bytes, which exceeds max allowed: spark.akka.frameSize (134217728 bytes) - reserved (204800 bytes).Go into the cluster settings, under Advanced select spark and paste spark.driver.maxResultSize 0 (for unlimited) or whatever the value suits you. Using 0 is not recommended. You should optimize the job by re partitioning. For more details, refer "Spark Configurations - Application Properties". Hope this helps. Do let us know if you any further ...If absolutely necessary you can set the property spark.driver.maxResultSize to a value <X>g higher than the value reported in the exception message in the cluster Spark config ( AWS | Azure ): spark.driver.maxResultSize < X > g. The default value is 4g. For details, see Application Properties. If you set a high limit, out-of-memory errors can ...Here are some ideas to fix this error: Serializable the class. Declare the instance only within the lambda function passed in map. Make the NotSerializable object as a static and create it once per machine. Call rdd.forEachPartition and create the NotSerializable object in there like this: rdd.forEachPartition (iter -> { NotSerializable ...Here is a method to parallelize serial JDBC reads across multiple spark workers... you can use this as a guide to customize it to your source data ... basically the main prerequisite is to have some kind of unique key to split on.Go into the cluster settings, under Advanced select spark and paste spark.driver.maxResultSize 0 (for unlimited) or whatever the value suits you. Using 0 is not recommended. You should optimize the job by re partitioning. For more details, refer "Spark Configurations - Application Properties". Hope this helps. Do let us know if you any further ...2. I am running my code in production and it runs successfully most of the time but some times it fails with following error: catch exceptionorg.apache.spark.SparkException: Job aborted due to stage failure: Task 14 in stage 9.1 failed 4 times, most recent failure: Lost task 14.3 in stage 9.1 (TID 3825, xxxprd0painod02.xxxprd.local): java.io ...Apr 8, 2019 · scala - org.apache.spark.SparkException: Job aborted due to stage failure: Task 98 in stage 11.0 failed 4 times - Stack Overflow org.apache.spark.SparkException: Job aborted due to stage failure: Task 98 in stage 11.0 failed 4 times Ask Question Asked 4 years, 4 months ago Modified 4 years, 4 months ago Viewed 46k times Feb 6, 2019 · I am new to PySpark. I have been writing my code with a test sample. Once I run the code on the larger file(3gb compressed). My code is only doing some filtering and joins. I keep getting errors Sep 14, 2020 · Hi Team, I am writing a Delta file in ADL-Gen2 from ADF for multiple files dynamically using Dataflows activity. For the initial run i am able to read the file from Azure DataBricks . But when i rerun the pipeline with truncate and load i am getting… Feb 6, 2019 · I am new to PySpark. I have been writing my code with a test sample. Once I run the code on the larger file(3gb compressed). My code is only doing some filtering and joins. I keep getting errors Feb 23, 2022 · I am running spark jobs using datafactory in azure databricks. My cluster vesion is 9.1 LTS ML (includes Apache Spark 3.1.2, Scala 2.12). I am writing data on azure blob storage. While writing job ... Check the Availability of Free RAM - whether it matches the expectation of the job being executed. Run below on each of the servers in the cluster and check how much RAM & Space they have in offer. free -h. If you are using any HDFS files in the Spark job , make sure to Specify & Correctly use the HDFS URL.Dec 29, 2020 · When I run the demo : from pyspark.ml.linalg import Vectors import tempfile conf = SparkConf().setAppName('ansonzhou_test').setAll([ ('spark.executor.memory', '8g ... May 15, 2017 · : org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 302987:27 was 139041896 bytes, which exceeds max allowed: spark.akka.frameSize (134217728 bytes) - reserved (204800 bytes). Apr 15, 2021 · The copy activity was interrupted part way through as the source database went offline which then caused the failure to complete writing the files properly. These were easily found as they were the most recently modified files. May 8, 2021 · org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 6.0 failed 1 times, most recent failure: Lost task 3.0 in stage 6.0 (TID 62, LAPTOP-H7MM9952, executor driver): org.apache.spark.SparkException: Task failed while writing rows. Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsWhen I run the demo : from pyspark.ml.linalg import Vectors import tempfile conf = SparkConf().setAppName('ansonzhou_test').setAll([ ('spark.executor.memory', '8g ...Exception in thread "main" org.apache.spark.SparkException : Job aborted due to stage failure: Task 3 in stage 0.0 failed 4 times, most recent failure: Lost task 3.3 in stage 0.0 (TID 14, 192.168.10.38): ExecutorLostFailure (executor 3 lost) Driver stacktrace:Solve : org.apache.spark.SparkException: Job aborted due to stage failure Load 7 more related questions Show fewer related questions 0org.apache.spark.SparkException: Job aborted due to stage failure: Task XXX in stage YYY failed 4 times, most recent failure: Lost task XXX in stage YYY (TID ZZZ, ip-xxx-xx-x-xxx.compute.internal, executor NNN): ExecutorLostFailure (executor NNN exited caused by one of the running tasks) Reason: ... 解決方法 理由コードの検索 org.apache.spark.SparkException: Job aborted due to stage failure: ShuffleMapStage 20 (repartition at data_prep.scala:87) has failed the maximum allowable number of times: 4. Most recent failure reason: org.apache.spark.shuffle.MetadataFetchFailedException: Missing an output location for shuffle 9>>Job aborted due to stage failure: Total size of serialized results of 19 tasks (4.2 GB) is bigger than spark.driver.maxResultSize (4.0 GB)'.. The exception was raised by the IDbCommand interface. Please take a look at following document about maxResultsize issue:org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 1486.0 failed 4 times, most recent failure: Lost task 0.3 in stage 1486.0 (TID 1665) (10.116.129.142 executor 0): org.apache.spark.SparkException: Failed to store executor broadcast spark_join_relation_469_-315473829 in BlockManager.Mar 30, 2020 · org.apache.spark.SparkException: Job aborted due to stage failure: Task 29 in stage 0.0 failed 4 times, most recent failure: Lost task 29.3 in stage 0.0 (TID 92, 10.252.252.125, executor 23): ExecutorLostFailure (executor 23 exited caused by one of the running tasks) Reason: Remote RPC client disassociated. The copy activity was interrupted part way through as the source database went offline which then caused the failure to complete writing the files properly. These were easily found as they were the most recently modified files.Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Aborting TaskSet 0.0 because task 0 (partition 0) cannot run anywhere due to node and executor blacklist.Apr 8, 2019 · scala - org.apache.spark.SparkException: Job aborted due to stage failure: Task 98 in stage 11.0 failed 4 times - Stack Overflow org.apache.spark.SparkException: Job aborted due to stage failure: Task 98 in stage 11.0 failed 4 times Ask Question Asked 4 years, 4 months ago Modified 4 years, 4 months ago Viewed 46k times @Tim, actually no I have set of operations like val source_primary_key = source.map(rec => (rec.split(",")(0), rec)) source_primary_key.persist(StorageLevel.DISK_ONLY) val extra_in_source = source_primary_key.subtractByKey(destination_primary_key) var pureextinsrc = extra_in_source.count() extra_in_source.cache()and so on but before this its throwing out of memory exception while im fetching ...You may not have right permissions. I have the same problem when I use a docker image jupyter/pyspark-notebook to run an example code of pyspark, and it was solved by using root within the container.Feb 4, 2022 · Currently I'm doing PySpark and working on DataFrame. I've created a DataFrame: from pyspark.sql import * import pandas as pd spark = SparkSession.builder.appName(&quot;DataFarme&quot;).getOrCreate... Exception in thread "main" org.apache.spark.SparkException : Job aborted due to stage failure: Task 3 in stage 0.0 failed 4 times, most recent failure: Lost task 3.3 in stage 0.0 (TID 14, 192.168.10.38): ExecutorLostFailure (executor 3 lost) Driver stacktrace:org.apache.spark.SparkException: Job aborted due to stage failure: Task 3 in stage 6.0 failed 1 times, most recent failure: Lost task 3.0 in stage 6.0 (TID 62, LAPTOP-H7MM9952, executor driver): org.apache.spark.SparkException: Task failed while writing rows.org.apache.spark.SparkException: Job aborted due to stage failure: Task 73 in stage 979.0 failed 1 times, most recent failure: Lost task 73.0 in stage 979.0 (TID 32624, localhost, executor driver): org.apache.spark.SparkException: Failed to execute user defined function($anonfun$4: (struct<other_double_VectorAssembler_a2059b1f0691:double ...strange org.apache.spark.SparkException: Job aborted due to stage failure again. I'm trying to deploy spark application on standalone mode. In this application I'm training Naive Bayes classifier by using tf-idf vectors. I wrote application in similar manner to this post ( Spark MLLib TFIDF implementation for LogisticRegression ) The difference ...org.apache.spark.SparkException: **Job aborted due to stage failure: Task 0 in stage 1.0 failed 1 times, most recent failure: Lost task 0.0 in stage 1.0 (TID 1 ...Jul 7, 2019 · 1 I'm trying to use Linear Regression on a simple dataframe with one feature and one label using Python pyspark in Databricks. However, I'm running into some issues with stage failure. I've reviewed many similar problems, but most of them are in Scala or are out of the scope of what I'm doing here. Versions: Check Apache Spark installation on Windows 10 steps. Use different versions of Apache Spark (tried 2.4.3 / 2.4.2 / 2.3.4). Disable firewall windows and antivirus that I have installed. Tried to initialize the SparkContext manually with sc = spark.sparkContext (found this possible solution at this question here in Stackoverflow, didn´t work for ...Oct 6, 2017 · @Tim, actually no I have set of operations like val source_primary_key = source.map(rec => (rec.split(",")(0), rec)) source_primary_key.persist(StorageLevel.DISK_ONLY) val extra_in_source = source_primary_key.subtractByKey(destination_primary_key) var pureextinsrc = extra_in_source.count() extra_in_source.cache()and so on but before this its throwing out of memory exception while im fetching ... Check Apache Spark installation on Windows 10 steps. Use different versions of Apache Spark (tried 2.4.3 / 2.4.2 / 2.3.4). Disable firewall windows and antivirus that I have installed. Tried to initialize the SparkContext manually with sc = spark.sparkContext (found this possible solution at this question here in Stackoverflow, didn´t work for ...2. I am running my code in production and it runs successfully most of the time but some times it fails with following error: catch exceptionorg.apache.spark.SparkException: Job aborted due to stage failure: Task 14 in stage 9.1 failed 4 times, most recent failure: Lost task 14.3 in stage 9.1 (TID 3825, xxxprd0painod02.xxxprd.local): java.io ...Aug 23, 2021 · org.apache.spark.SparkException: Job aborted due to stage failure: Total size of serialized results of 69 tasks (4.0 GB) is bigger than spark.driver.maxResultSize (4.0 GB) 08-23-2021 07:48 AM. set spark.conf.set ("spark.driver.maxResultSize", "20g") get spark.conf.get ("spark.driver.maxResultSize") // 20g which is expected in notebook , I did ... 不知道是什么原因。. （利用 Spark-submit 提交 参数都正常）. 但是 集群上的版本是1.5，和2.0都无法跑出来结果，但是1.3就能出结果， 所以目前确定是 Spark 1.5以上的版本对协同过滤算法不兼容引起，具体原因不详。. task倾斜原因比较多，网络io,cpu,mem都有可能造成 ...In my project i am using spark-Cassandra-connector to read the from Cassandra table and process it further into JavaRDD but i am facing issue while processing Cassandra row to javaRDD.Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsTeams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsAug 20, 2018 · 报错如下： : org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 3.0 failed 4 times, most recent failure: ... Currently I'm doing PySpark and working on DataFrame. I've created a DataFrame: from pyspark.sql import * import pandas as pd spark = SparkSession.builder.appName(&quot;DataFarme&quot;).getOrCreate...For Spark jobs submitted with --deploy-mode cluster, run the following command on the master node to find stage failures in the YARN application logs. Replace application_id with the ID of your Spark application (for example, application_1572839353552_0008 ). yarn logs -applicationId application_id | grep "Job aborted due to stage failure" -A 10. Nov 2, 2020 · Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about Teams 2 Answers. df.toPandas () collects all data to the driver node, hence it is very expensive operation. Also there is a spark property called maxResultSize. spark.driver.maxResultSize (default 1G) --> Limit of total size of serialized results of all partitions for each Spark action (e.g. collect) in bytes. Should be at least 1M, or 0 for unlimited.May 15, 2017 · : org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 302987:27 was 139041896 bytes, which exceeds max allowed: spark.akka.frameSize (134217728 bytes) - reserved (204800 bytes). Mar 31, 2019 · org.apache.spark.SparkException: Job aborted due to stage failure: Task in stage failed，Lost task in stage : ExecutorLostFailure (executor 4 lost) Ask Question Asked 4 years, 5 months ago Jan 10, 2020 · Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about Teams You may not have right permissions. I have the same problem when I use a docker image jupyter/pyspark-notebook to run an example code of pyspark, and it was solved by using root within the container.org.apache.spark.SparkException: Job aborted due to stage failure: Task 2 in stage 0.0 failed 4 times, most recent failure: Lost task 2.3 in stage 0.0 Updating the dependancy in SBT solved the problem..