Org.apache.spark.sparkexception exception thrown in awaitresult - I have a spark set up in AWS EMR. Spark version is 2.3.1. I have one master node and two worker nodes. I am using sparklyr to run xgboost model for a classification problem. My job ran for over six...

 
Feb 25, 2019 · Add the dependencies on the /jars directory on your SPARK_HOME for each worker in the cluster and the driver (if you didn't do so). I used the second approach. During my docker image creation, I added the libs so when I start my cluster, all containers already have the libraries required. . 2 bedroom apartments in orlando under dollar700

Hi! I run 2 to spark an option SPARK_MAJOR_VERSION=2 pyspark --master yarn --verbose spark starts, I run the SC and get an error, the field in the table exactly there. not the problem SPARK_MAJOR_VERSION=2 pyspark --master yarn --verbose SPARK_MAJOR_VERSION is set to 2, using Spark2 Python 2.7.12 ...Summary. org.apache.spark.SparkException: Exception thrown in awaitResult and java.util.concurrent.TimeoutException: Futures timed out after [300 seconds] while running huge spark sql job.spark-shell exception org.apache.spark.SparkException: Exception thrown in awaitResult Ask Question Asked 1 year, 10 months ago Modified 1 year, 5 months ago Viewed 1k times 2 Facing below error while starting spark-shell with yarn master. Shell is working with spark local master.Invalidates the cached entries for Apache Spark cache, which include data and metadata of the given table or view. The invalidated cache is populated in lazy manner when the cached table or the query associated with it is executed again. REFRESH [TABLE] table_name Manually restart the cluster.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: Exception thrown in awaitResult Use the below points to fix this - Check the Spark version used in the project - especially if it involves a Cluster of nodes (Master , Slave). The Spark version which is running in the Slave nodes should be same as the Spark version dependency used in the Jar compilation. Nov 28, 2017 · I am new to spark and have been trying to run my first java spark job through a standalone local master. Now my master is up and one worker gets registered as well, but when run below spark program I got org.apache.spark.SparkException: Exception thrown in awaitResult. My program should work as it runs fine when master is set to local. My Spark ... Converting a dataframe to Panda data frame using toPandas() fails. Spark 3.0.0 Running in stand-alone mode using docker containers based on jupyter docker stack here: ... setting spark.driver.maxResultSize = 0 solved my problem in pyspark. I was using pyspark standalone on a single machine, and I believed it was okay to set unlimited size. – Thamme GowdaNov 5, 2016 · A guess: your Spark master (on 10.20.30.50:7077) runs a different Spark version (perhaps 1.6?): your driver code uses Spark 2.0.1, which (I think) doesn't even use Akka, and the message on the master says something about failing to decode Akka protocol - can you check the version used on master? I am trying to store a data frame to HDFS using the following Spark Scala code. All the columns in the data frame are nullable = true Intermediate_data_final.coalesce(100).write .option("...3. I am very new to Apache Spark and trying to run spark on my local machine. First I tried to start the master using the following command: ./sbin/start-master.sh. Which got successfully started. And then I tried to start the worker using. ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://localhost:7077 -c 1 -m 512M.However, after running for a couple of days in production, the spark application faces some network hiccups from S3 that causes an exception to be thrown and stops the application. It's also worth mentioning that this application runs on Kubernetes using GCP's Spark k8s Operator ."org.apache.spark.SparkException: Exception thrown in awaitResult" failing intermittently a Spark mapping that accesses Hive tables ERROR: "java.lang.OutOfMemoryError: Java heap space" while running a mapping in Spark Execution mode using InformaticaI have followed java.lang.IllegalArgumentException: The servlets named [X] and [Y] are both mapped to the url-pattern [/url] which is not permitted this and it works!!!!! 1 Answer. Sorted by: 1. You need to create an RDD of type RDD [Tuple [str]] but in your code, the line: rdd = spark.sparkContext.parallelize (comments) returns RDD [str] which then fails when you try to convert it to dataframe with that given schema. Try modifying that line to:Dec 28, 2017 · setting spark.driver.maxResultSize = 0 solved my problem in pyspark. I was using pyspark standalone on a single machine, and I believed it was okay to set unlimited size. – Thamme Gowda 解决方案：. 先telnet 10.45.66.176:7077是否能连通？. 检查在master主机检查7077端口属于什么IP，eg. 如下的7077端口则属于127.0.0.1，需要将其修改成其他主机能访问的ip；. image.png. 修改/etc/hosts文件即可，如下：. 127.0.0.1 iotsparkmaster localhost localhost.localdomain localhost4 localhost4 ...Jul 23, 2018 · org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205) at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100) 6066 is an HTTP port but via Jobserver config it's making an RPC call to 6066. I am not sure if I have missed anything or is an issue. "org.apache.spark.SparkException: Exception thrown in awaitResult" failing intermittently a Spark mapping that accesses Hive tables ERROR: "java.lang.OutOfMemoryError: Java heap space" while running a mapping in Spark Execution mode using InformaticaI am trying to run a pyspark program by using spark-submit: from pyspark import SparkConf, SparkContext from pyspark.sql import SQLContext from pyspark.sql.types import * from pyspark.sql importHere 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 ... Nov 9, 2022 · Saved searches Use saved searches to filter your results more quickly Nov 7, 2017 · 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 ... Converting a dataframe to Panda data frame using toPandas() fails. Spark 3.0.0 Running in stand-alone mode using docker containers based on jupyter docker stack here: ... org.apache.spark.SparkException: Exception thrown in awaitResult Use the below points to fix this - Check the Spark version used in the project - especially if it involves a Cluster of nodes (Master , Slave). The Spark version which is running in the Slave nodes should be same as the Spark version dependency used in the Jar compilation.Aug 21, 2018 · I'm new to Spark and I'm using Pyspark 2.3.1 to read in a csv file into a dataframe. I'm able to read in the file and print values in a Jupyter notebook running within an anaconda environment. This is the code I'm using: When a job starts, a script called launch_container.sh would be executing org.apache.spark.deploy.yarn.ApplicationMaster with the arguments passed to spark-submit and the ApplicationMaster returns with an exit code of 1 when any argument to it is invalid. More information heresetting spark.driver.maxResultSize = 0 solved my problem in pyspark. I was using pyspark standalone on a single machine, and I believed it was okay to set unlimited size. – Thamme Gowda1、查找原因. 网上有很多的解决方法，但是基本都不太符合我的情况。. 罗列一下其他的解决方法. sparkSql的需要手动添加 。. option ("driver", "com.mysql.jdbc.Driver" ) 就是驱动的名字写错了（逗号 、分号、等等）. 驱动缺失，去spark集群添加mysql的驱动，或者提交任务的 ...Used Spark version Spark:2.2.0 (in Ambari) Used Spark Job Server version (Released version, git branch or docker image version) Spark-Job-Server:0.9 / 0.8 Deployed mode (client/cluster on Spark Sta...In the traceback it says: Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 43.0 failed 1 times, most recent failure: Lost task 0.0 in stage 43.0 (TID 97) (ip-10-172-188- 62.us-west-2.compute.internal executor driver): java.lang.OutOfMemoryError: Java heap spaceYarn throws the following exception in cluster mode when the application is really small:I run this command: display(df), but when I try to download the dataframe I obtain the following error: SparkException: Exception thrown in awaitResult: Caused by: java.io. Stack Overflow AboutNov 28, 2017 · I am new to spark and have been trying to run my first java spark job through a standalone local master. Now my master is up and one worker gets registered as well, but when run below spark program I got org.apache.spark.SparkException: Exception thrown in awaitResult. My program should work as it runs fine when master is set to local. My Spark ... Summary. org.apache.spark.SparkException: Exception thrown in awaitResult and java.util.concurrent.TimeoutException: Futures timed out after [300 seconds] while running huge spark sql job.Hi there, Just wanted to check - was the above suggestion helpful to you? If yes, please consider upvoting and/or marking it as answer. This would help other community members reading this thread.org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205) at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100) 6066 is an HTTP port but via Jobserver config it's making an RPC call to 6066. I am not sure if I have missed anything or is an issue.Yarn throws the following exception in cluster mode when the application is really small:Aug 21, 2018 · I'm new to Spark and I'm using Pyspark 2.3.1 to read in a csv file into a dataframe. I'm able to read in the file and print values in a Jupyter notebook running within an anaconda environment. This is the code I'm using: 解决方案：. 先telnet 10.45.66.176:7077是否能连通？. 检查在master主机检查7077端口属于什么IP，eg. 如下的7077端口则属于127.0.0.1，需要将其修改成其他主机能访问的ip；. image.png. 修改/etc/hosts文件即可，如下：. 127.0.0.1 iotsparkmaster localhost localhost.localdomain localhost4 localhost4 ...Oct 27, 2022 · I am trying to find similarity between two texts by comparing them. For this, I can calculate the tf-idf values of both texts and get them as RDD correctly. calling o110726.collectToPython. : org.apache.spark.SparkException: Job aborted due to stage failure: Task 7 in stage 1971.0 failed 4 times, most recent failure: Lost task 7.3 in stage 1971.0 (TID 31298) (10.54.144.30 executor 7):1. you don't need to use withColumn to add date to DynamicFrame. This can also be done with "from datetime import datetime def addDate (d): d ["date"] = datetime.today () return d datasource1 = Map.apply (frame = datasource0, f = addDate)" – Prabhakar Reddy.Aug 28, 2018 · Pyarrow 4.0.1. Jupyter notebook. Spark cluster on GCS. When I try to enable Pyarrow optimization like this: spark.conf.set ('spark.sql.execution.arrow.enabled', 'true') I get the following warning: createDataFrame attempted Arrow optimization because 'spark.sql.execution.arrow.enabled' is set to true; however failed by the reason below ... org.apache.spark.SparkException: Exception thrown in awaitResult Use the below points to fix this - Check the Spark version used in the project - especially if it involves a Cluster of nodes (Master , Slave). The Spark version which is running in the Slave nodes should be same as the Spark version dependency used in the Jar compilation.3. I am very new to Apache Spark and trying to run spark on my local machine. First I tried to start the master using the following command: ./sbin/start-master.sh. Which got successfully started. And then I tried to start the worker using. ./bin/spark-class org.apache.spark.deploy.worker.Worker spark://localhost:7077 -c 1 -m 512M.Broadcasting is when you send small data frames to all nodes in the cluster. This allows for the Spark engine to perform a join without reshuffling the data in the large stream. By default, the Spark engine will automatically decide whether or not to broadcast one side of a join.Mar 5, 2020 · I run this command: display(df), but when I try to download the dataframe I obtain the following error: SparkException: Exception thrown in awaitResult: Caused by: java.io. Stack Overflow About An Azure analytics service that brings together data integration, enterprise data warehousing, and big data analytics. Previously known as Azure SQL Data Warehouse.Summary. org.apache.spark.SparkException: Exception thrown in awaitResult and java.util.concurrent.TimeoutException: Futures timed out after [300 seconds] while running huge spark sql job. install the spark chart. port-forward the master port. submit the app. Output of helm version: Write the 127.0.0.1 r-spark-master-svc into /etc/hosts. Execute kubectl port-forward --namespace default svc/r-spark-master-svc 7077:7077.Jul 28, 2016 · I am running SPARK locally (I am not using Mesos), and when running a join such as d3=join(d1,d2) and d5=(d3, d4) am getting the following exception "org.apache.spark.SparkException: Exception thrown in awaitResult”. Googling for it, I found the following two related links: Converting a dataframe to Panda data frame using toPandas() fails. Spark 3.0.0 Running in stand-alone mode using docker containers based on jupyter docker stack here: ... 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 ...1、查找原因. 网上有很多的解决方法，但是基本都不太符合我的情况。. 罗列一下其他的解决方法. sparkSql的需要手动添加 。. option ("driver", "com.mysql.jdbc.Driver" ) 就是驱动的名字写错了（逗号 、分号、等等）. 驱动缺失，去spark集群添加mysql的驱动，或者提交任务的 ...Jan 24, 2022 · We use databricks runtime 7.3 with scala 2.12 and spark 3.0.1. In our jobs we first DROP the Table and delete the associated delta files which are stored on an azure storage account like so: DROP TABLE IF EXISTS db.TableName dbutils.fs.rm(pathToTable, recurse=True) Exception logs: 2018-08-26 16:15:02 INFO DAGScheduler:54 - ResultStage 0 (parquet at ReadDb2HDFS.scala:288) failed in 1008.933 s due to Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, master, executor 4): ExecutorLostFailure (executor 4 exited caused by one of the ...org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:205) at org.apache.spark.rpc.RpcEnv.setupEndpointRefByURI(RpcEnv.scala:100) 6066 is an HTTP port but via Jobserver config it's making an RPC call to 6066. I am not sure if I have missed anything or is an issue.Hi I am facing a problem related to pyspark, I use df.show() it still give me a result but when I use some function like count(), groupby() v..v it show me error, I think the reason is that 'df' is...Spark报错处理. 1、 问题： org.apache.spark.SparkException: Exception thrown in awaitResult. 分析：出现这个情况的原因是spark启动的时候设置的是hostname启动的，导致访问的时候DNS不能解析主机名导致。 问题解决： Dec 13, 2021 · Using PySpark, I am attempting to convert a spark DataFrame to a pandas DataFrame using the following: # Enable Arrow-based columnar data transfers spark.conf.set(&quot;spark.sql.execution.arrow.en... Converting a dataframe to Panda data frame using toPandas() fails. Spark 3.0.0 Running in stand-alone mode using docker containers based on jupyter docker stack here: ...Spark报错处理. 1、 问题： org.apache.spark.SparkException: Exception thrown in awaitResult 分析：出现这个情况的原因是spark启动的时候设置的是hostname启动的，导致访问的时候DNS不能解析主机名导致。I have an app where after doing various processes in pyspark I have a smaller dataset which I need to convert to pandas before uploading to elasticsearch. I have res = result.select("*").toPandas() On my local when I use spark-submit --master "local[*]" app.py It works perfectly fine. I also ...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. Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: The default spark.sql.broadcastTimeout is 300 Timeout in seconds for the broadcast wait time in broadcast joins. To overcome this problem increase the timeout time as per required example--conf "spark.sql.broadcastTimeout= 1200" 3. “org.apache.spark.rpc ...I am trying to store a data frame to HDFS using the following Spark Scala code. All the columns in the data frame are nullable = true Intermediate_data_final.coalesce(100).write .option("... 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 ... Hi! I run 2 to spark an option SPARK_MAJOR_VERSION=2 pyspark --master yarn --verbose spark starts, I run the SC and get an error, the field in the table exactly there. not the problem SPARK_MAJOR_VERSION=2 pyspark --master yarn --verbose SPARK_MAJOR_VERSION is set to 2, using Spark2 Python 2.7.12 ...When a job starts, a script called launch_container.sh would be executing org.apache.spark.deploy.yarn.ApplicationMaster with the arguments passed to spark-submit and the ApplicationMaster returns with an exit code of 1 when any argument to it is invalid. More information hereFeb 4, 2019 · I have Spark 2.3.1 running on my local windows 10 machine. I haven't tinkered around with any settings in the spark-env or spark-defaults.As I'm trying to connect to spark using spark-shell, I get a failed to connect to master localhost:7077 warning. In the traceback it says: Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 43.0 failed 1 times, most recent failure: Lost task 0.0 in stage 43.0 (TID 97) (ip-10-172-188- 62.us-west-2.compute.internal executor driver): java.lang.OutOfMemoryError: Java heap spacespark-shell exception org.apache.spark.SparkException: Exception thrown in awaitResult Ask Question Asked 1 year, 10 months ago Modified 1 year, 5 months ago Viewed 1k times 2 Facing below error while starting spark-shell with yarn master. Shell is working with spark local master.An Azure service that provides an enterprise-wide hyper-scale repository for big data analytic workloads and is integrated with Azure Blob Storage.Apr 23, 2020 · 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. I have Spark 2.3.1 running on my local windows 10 machine. I haven't tinkered around with any settings in the spark-env or spark-defaults.As I'm trying to connect to spark using spark-shell, I get a failed to connect to master localhost:7077 warning.Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in ...Yarn throws the following exception in cluster mode when the application is really small: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 ...at org.apache.spark.scheduler.local.LocalSchedulerBackend.start(LocalSchedulerBackend.scala:126)1 Answer. Sorted by: 1. You need to create an RDD of type RDD [Tuple [str]] but in your code, the line: rdd = spark.sparkContext.parallelize (comments) returns RDD [str] which then fails when you try to convert it to dataframe with that given schema. Try modifying that line to:I have an app where after doing various processes in pyspark I have a smaller dataset which I need to convert to pandas before uploading to elasticsearch. I have res = result.select("*").toPandas() On my local when I use spark-submit --master "local[*]" app.py It works perfectly fine. I also ...Sep 22, 2016 · The above scenario works with spark 1.6 (which is quite surprising that what's wrong with spark 2.0 (or with my installation , I will reinstall, check and update here)). Has anybody tried this on spark 2.0 and got success , by following Yaron's answer below??? SPARK Exception thrown in awaitResult Ask Question Asked 7 years, 1 month ago Modified 2 years, 2 months ago Viewed 21k times 5 I am running SPARK locally (I am not using Mesos), and when running a join such as d3=join (d1,d2) and d5= (d3, d4) am getting the following exception "org.apache.spark.SparkException: Exception thrown in awaitResult”.org.apache.spark.SparkException: Job aborted due to stage failure: Hot Network Questions How to draw 3 equal circles inside a circle in tikz or other way?Dec 12, 2022 · The cluster version Im using is the latest: 3.3.1\Hadoop 3. The master node is starting without an issue and Im able to register the workers on each worker node using the following comand: spark-class org.apache.spark.deploy.worker.Worker spark://<Master-IP>:7077 --host <Worker-IP>. When I register the worker , its able to connect and register ... org.apache.spark.sql.execution.joins.BroadcastHashJoin.doExecute(BroadcastHashJoin.scala:110) BroadcastHashJoin physical operator in Spark SQL uses a broadcast variable to distribute the smaller dataset to Spark executors (rather than shipping a copy of it with every task).The text was updated successfully, but these errors were encountered:When a job starts, a script called launch_container.sh would be executing org.apache.spark.deploy.yarn.ApplicationMaster with the arguments passed to spark-submit and the ApplicationMaster returns with an exit code of 1 when any argument to it is invalid. More information here

I run this command: display(df), but when I try to download the dataframe I obtain the following error: SparkException: Exception thrown in awaitResult: Caused by: java.io. Stack Overflow About. Trihealth corporate offices norwood wall street

org.apache.spark.sparkexception exception thrown in awaitresult

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.Aug 31, 2018 · I have a spark set up in AWS EMR. Spark version is 2.3.1. I have one master node and two worker nodes. I am using sparklyr to run xgboost model for a classification problem. My job ran for over six... org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3) (10.139.64.6 executor 0): org.apache.spark.SparkException: Exception thrown in awaitResult: Go to the Executor 0 and check why it failedJun 21, 2019 · You can do either of the below to solve this problem. set spark configuration spark.sql.files.ignoreMissingFiles to true. run fsck repair table tablename on your underlying delta table (run fsck repair table tablename DRY RUN first to see the files) Share. Improve this answer. Follow. answered Dec 22, 2022 at 15:16. Feb 25, 2019 · Add the dependencies on the /jars directory on your SPARK_HOME for each worker in the cluster and the driver (if you didn't do so). I used the second approach. During my docker image creation, I added the libs so when I start my cluster, all containers already have the libraries required. Dec 12, 2022 · The cluster version Im using is the latest: 3.3.1\Hadoop 3. The master node is starting without an issue and Im able to register the workers on each worker node using the following comand: spark-class org.apache.spark.deploy.worker.Worker spark://<Master-IP>:7077 --host <Worker-IP>. When I register the worker , its able to connect and register ... Mar 29, 2020 · 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 ... Dec 28, 2017 · setting spark.driver.maxResultSize = 0 solved my problem in pyspark. I was using pyspark standalone on a single machine, and I believed it was okay to set unlimited size. – Thamme Gowda Converting a dataframe to Panda data frame using toPandas() fails. Spark 3.0.0 Running in stand-alone mode using docker containers based on jupyter docker stack here: ...2. Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: The default spark.sql.broadcastTimeout is 300 Timeout in seconds for the broadcast wait time in broadcast joins. To overcome this problem increase the timeout time as per required example--conf "spark.sql.broadcastTimeout= 1200" 3. “org.apache.spark.rpc ...Apr 8, 2019 · Create cluster with spark memory settings that change the ratio of memory to CPU: gcloud dataproc clusters create --properties spark:spark.executor.cores=1 for example will change each executor to only run one task at a time with the same amount of memory, whereas Dataproc normally runs 2 executors per machine and divides CPUs accordingly. On 4 ... I'm new to Spark and I'm using Pyspark 2.3.1 to read in a csv file into a dataframe. I'm able to read in the file and print values in a Jupyter notebook running within an anaconda environment. This...My first reaction would be to forget about it as you're running your Spark app in sbt so there could be a timing issue between threads of the driver and the executors. Unless you show what led to Nonzero exit code: 1, there's nothing I'd worry about. – Jacek Laskowski. Jan 28, 2019 at 18:07. Ok thanks but my app don't read a file like that.Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Serialized task 2:0 was 155731289 bytes, which exceeds max allowed: spark.rpc.message.maxSize (134217728 bytes). Consider increasing spark.rpc.message.maxSize or using broadcast variables for large values..

Popular Topics