I 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!!!!!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 ...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 .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: 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("DataFarme").getOrCreate...Jan 28, 2019 · 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. "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 InformaticaNov 9, 2021 · 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 space. 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 ...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 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 ...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.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.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)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: ...May 18, 2022 · "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 Informatica 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.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.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. 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 ... Spark程序优化所需要关注的几个关键点——最主要的是数据序列化和内存优化. 问题1：reduce task数目不合适. 解决方法 ：需根据实际情况调节默认配置，调整方式是修改参数 spark.default.parallelism 。. 通常，reduce数目设置为core数目的2到3倍。. 数量太大，造成很多小 ...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 hereThe 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 ...public static <T> T awaitResult(scala.concurrent.Awaitable<T> awaitable, scala.concurrent.duration.Duration atMost) throws SparkException Preferred alternative to Await.result() . This method wraps and re-throws any exceptions thrown by the underlying Await call, ensuring that this thread's stack trace appears in logs.Jul 25, 2020 · Exception message: Exception thrown in awaitResult: .Retrying 1 more times. 2020-07-24 22:01:18,988 WARN [Thread-9] redshift.RedshiftWriter (RedshiftWriter.scala:retry$1(135)) - Sleeping 30000 milliseconds before proceeding to retry redshift copy 2020-07-24 22:01:45,785 INFO [spark-dynamic-executor-allocation] spark.ExecutorAllocationManager ... 这样再用这16个TPs取分别执行其 c.seekToEnd (TP)时,遇到这8个已经分配到consumer-B的TPs,就会抛此异常; 个人理解: 这个实现应是Spark-Streaming-Kafak这个框架的要求,即每个Spark-kafak任务, consumerGroup必须是专属 (唯一的); 相关原理和源码. DirectKafkaInputDStream.latestOffsets(){ val parts ...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: ...Nov 15, 2021 · Solve : org.apache.spark.SparkException: Job aborted due to stage failure 0 Spark Session Problem: Exception: Java gateway process exited before sending its port number 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. 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.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 ... 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 ... 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 ...Stack Overflow Public questions & answers; Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Talent Build your employer brandIn 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 spaceApr 11, 2016 · Yes, this solved my problem. I was using spark-submit --deploy-mode cluster, but when I changed it to client, it worked fine. In my case, I was executing SQL scripts using a python code, so my code was not "spark dependent", but I am not sure what will be the implications of doing this when you want multiprocessing. – 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: ... 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 ...Stack Overflow Public questions & answers; Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Talent Build your employer brandorg.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 failedInvalidates 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.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. Hi! I am having the same problem here. Exception in thread "main" java.lang.reflect.UndeclaredThrowableException at org.apache.hadoop.security.UserGroupInformation ...If you are trying to run your spark job on yarn client/cluster. Don't forget to remove master configuration from your code .master("local[n]"). For submitting spark job on yarn, you need to pass --master yarn --deploy-mode cluster/client. Having master set as local was giving repeated timeout exception.What's going on in the driver at the time of this failure? It could be due to memory pressure on the driver causing it to be unresponsive. If I recall correctly, the MapOutputTracker that it's trying to get to when it calls GetMapOutputStatuses is running in the Spark driver driver process.at org.apache.spark.scheduler.local.LocalSchedulerBackend.start(LocalSchedulerBackend.scala:126)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 ... 它提供了低级别、轻量级、高保真度的2D渲染。. 该框架可以用于基于路径的绘图、变换、颜色管理、脱屏渲染，模板、渐变、遮蔽、图像数据管理、图像的创建、遮罩以及PDF文档的创建、显示和分析等。. 为了从感官上对这些概念做一个入门的认识，你可以运行 ...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. 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. Nov 3, 2021 · Check the YARN application logs for more details. 21/11/03 15:52:35 ERROR YarnClientSchedulerBackend: Diagnostics message: Uncaught exception: org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226) at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala ... 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: 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: 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...Mar 20, 2023 · Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:226) at org.apache.spark.sql.execution.exchange.BroadcastExchangeExec.doExecuteBroadcast(BroadcastExchangeExec.scala:146) at org.apache.spark.sql.execution.InputAdapter.doExecuteBroadcast ... spark-shell exception org.apache.spark.SparkException: Exception thrown in awaitResult Ask Question Asked 1 year, 10 months ago Modified 1 year, 5 months ago Viewed 1k times 2 Facing below error while starting spark-shell with yarn master. Shell is working with spark local master.Solution When the Spark engine runs applications and broadcast join is enabled, Spark Driver broadcasts the cache to the Spark executors running on data nodes in the Hadoop cluster. The 'autoBroadcastJoinThreshold' will help in the scenarios, when one small table and one big table is involved.org.apache.spark.SparkException: Job aborted due to stage failure: Hot Network Questions How to draw 3 equal circles inside a circle in tikz or other way?org.apache.spark.sql.execution.joins.BroadcastHashJoin.doExecute(BroadcastHashJoin.scala:110) BroadcastHashJoin physical operator in Spark SQL uses a broadcast variable to distribute the smaller dataset to Spark executors (rather than shipping a copy of it with every task).Aug 28, 2018 · Pyarrow 4.0.1. Jupyter notebook. Spark cluster on GCS. When I try to enable Pyarrow optimization like this: spark.conf.set ('spark.sql.execution.arrow.enabled', 'true') I get the following warning: createDataFrame attempted Arrow optimization because 'spark.sql.execution.arrow.enabled' is set to true; however failed by the reason below ... Caused by: org.apache.spark.SparkException: Exception thrown in awaitResult: Caused by: org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in ...An error occurred while calling o466.getResult. : org.apache.spark.SparkException: Exception thrown in awaitResult: at org.apache.spark.util.ThreadUtils$.awaitResult (ThreadUtils.scala:428) at org.apache.spark.security.SocketAuthServer.getResult (SocketAuthServer.scala:107) at org.apache.spark.security.SocketAuthServer.getResult (SocketAuthSe...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.My program runs fine in client mode ,but when I try to run in cluster mode if fails ,the reason for that is the python version on the cluster nodes is different I am trying to set the python driver...Teams. Q&A for work. Connect and share knowledge within a single location that is structured and easy to search. Learn more about TeamsI 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!!!!!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 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.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 ...I 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 importConverting 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: ... Jan 14, 2023 · 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 failed 它提供了低级别、轻量级、高保真度的2D渲染。. 该框架可以用于基于路径的绘图、变换、颜色管理、脱屏渲染，模板、渐变、遮蔽、图像数据管理、图像的创建、遮罩以及PDF文档的创建、显示和分析等。. 为了从感官上对这些概念做一个入门的认识，你可以运行 ... 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 ...Saved searches Use saved searches to filter your results more quicklyConverting 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: ... I am trying to setup hadoop 3.1.2 with spark in windows. i have started hdfs cluster and i am able to create,copy files in hdfs. When i try to start spark-shell with yarn i am facing ERROR cluster.Jul 18, 2020 · I 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 import 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... Nov 9, 2022 · Saved searches Use saved searches to filter your results more quickly An Azure service that provides an enterprise-wide hyper-scale repository for big data analytic workloads and is integrated with Azure Blob Storage.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 AboutApr 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 ... We are trying to implement master and slave in 2 different laptops using apache spark, however the worker is not connecting to the master, even though it is on the same network and the following er...Stack Overflow Public questions & answers; Stack Overflow for Teams Where developers & technologists share private knowledge with coworkers; Talent Build your employer brand@Hugo Felix. Thank you for sharing the tutorial. I was able to replicate the issue and I found the issue to be with incompatible jars. I am using the following precise versions that I pass to spark-shell.Apr 15, 2021 · An Azure service that provides an enterprise-wide hyper-scale repository for big data analytic workloads and is integrated with Azure Blob Storage.
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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 ...Hi! I am having the same problem here. Exception in thread "main" java.lang.reflect.UndeclaredThrowableException at org.apache.hadoop.security.UserGroupInformation ...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: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?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 19, 2021 · at org.apache.spark.scheduler.local.LocalSchedulerBackend.start(LocalSchedulerBackend.scala:126) Jan 19, 2021 · at org.apache.spark.scheduler.local.LocalSchedulerBackend.start(LocalSchedulerBackend.scala:126) 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.Feb 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. 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.Yes, this solved my problem. I was using spark-submit --deploy-mode cluster, but when I changed it to client, it worked fine. In my case, I was executing SQL scripts using a python code, so my code was not "spark dependent", but I am not sure what will be the implications of doing this when you want multiprocessing. –@Hugo Felix. Thank you for sharing the tutorial. I was able to replicate the issue and I found the issue to be with incompatible jars. I am using the following precise versions that I pass to spark-shell.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 ...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 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 errorsI am trying to setup hadoop 3.1.2 with spark in windows. i have started hdfs cluster and i am able to create,copy files in hdfs. When i try to start spark-shell with yarn i am facing ERROR cluster.I have 2 data frames one with 10K rows and 10,000 columns and another with 4M rows with 50 columns. I joined this and trying to find mean of merged data set, at org.apache.spark.scheduler.local.LocalSchedulerBackend.start(LocalSchedulerBackend.scala:126)I ran into the same problem when I tried to join two DataFrames where one of them was GroupedData. It worked for me when I cached the GroupedData DataFrame before the inner join.The text was updated successfully, but these errors were encountered: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....