Re: [PYSPARK] df.collect throws exception for MapType with ArrayType as key

ing to the PySpark documentation, it should be possible to have a > MapType column with ArrayType keys. MapType supports keys of type DataType > and ArrayType inherits from DataType. > When i try that with PySpark 3.5.3, the show() method of the DataFrame > works as aspected, but

[PYSPARK] df.collect throws exception for MapType with ArrayType as key

as aspected, but the collect() method throws an exception: from pyspark.sql import SparkSession from pyspark.sql.types import MapType, ArrayType, StringType schema = MapType(ArrayType(StringType()), StringType()) data = [{("A", "B"): "foo", ("X", "

[QUESTION] Issue with "column -1 out of bounds" exception using sqlite JDBC

Hello, I'm experiencing an issue that I have already described in detail here: https://github.com/xerial/sqlite-jdbc/issues/1221 The main points are: Using newer versions of sqlite JDBC driver for testing purposes, spark/jdbc throws "java.sql.SQLException: column -1 out of bounds"

Re: [Spark SQL] [DISK_ONLY Persistence] getting "this.inMemSorter" is null exception

Thanks for the response. Seems like a limitation. If resources are available then why bother about splitting the jobs in smaller durations(performance is not the concern). This issue is not about the performance optimization but rather the job is failing with null pointer exception. Do you have

Re: [Spark SQL] [DISK_ONLY Persistence] getting "this.inMemSorter" is null exception

g review the >>> data Transformations, verify that data transformations don't introduce >>> inconsistencies or null values. >>> >>> regards, >>> Guru >>> >>> On Mon, Nov 11, 2024 at 6:06 PM Ashwani Pundir >>> wrote: &g

Re: [Spark SQL] [DISK_ONLY Persistence] getting "this.inMemSorter" is null exception

es or null values. regards, Guru On Mon, Nov 11, 2024 at 6:06 PM Ashwani Pundir wrote: > > Dear Spark Devs, > > I am reaching out because I am struggling to find the root cause of the below > exception > (I have spent almost 4 days trying to figure out the root cause of this >

Example UDAF fails with "not serializable" exception

https://spark.apache.org/docs/3.3.2/sql-ref-functions-udf-aggregate.html I'm trying to run this example on Databricks, and it fails with the stacktrace below. It's literally a copy-paste from the example, what am I missing? Job aborted due to stage failure: Task not serializable: java.io.Not

Re: Null pointer exception while replying WAL

OK Getting Null pointer exception while replying WAL! One possible reason is that the messages RDD might contain null elements, and attempting to read JSON from null values can result in an NPE. To handle this, you can add a filter before processing the RDD to remove null elements

Re: Null pointer exception while replying WAL

h wrote: > Hi, > > It is challenging to make a recommendation without further details. I am > guessing you are trying to build a fault-tolerant spark application (spark > structured streaming) that consumes messages from Solace? > To address *NullPointerException* in the context

Re: Null pointer exception while replying WAL

to review the part of the code where the exception is thrown and identifying which object or method call is resulting in *null* can help the debugging process plus checking the logs. HTH Mich Talebzadeh, Dad | Technologist | Solutions Architect | Engineer London United Kingdom view my

Null pointer exception while replying WAL

Hi Users, I am trying to build fault tolerant spark solace consumer. Issue :- we have to take restart of the job due to multiple issue load average is one of them. At that time whatever spark is processing or batches in the queue is lost. We can't replay it because we already had send ack while c

Re: Spark-SQL - Concurrent Inserts Into Same Table Throws Exception

k trace in the application UI. In the snippets > I saved, it looks like the exception being thrown was from Hive. Given the > feedback you've provided, I suspect the issue is with how the Hive > components are handling concurrent writes. > > While using a different format wo

Re: Spark-SQL - Concurrent Inserts Into Same Table Throws Exception

Hi Mich and Pol, Thanks for the feedback. The database layer is Hadoop 3.3.5. The cluster restarted so I lost the stack trace in the application UI. In the snippets I saved, it looks like the exception being thrown was from Hive. Given the feedback you've provided, I suspect the issue is wit

Re: Spark-SQL - Concurrent Inserts Into Same Table Throws Exception

Hi Patrick, You can have multiple writers simultaneously writing to the same table in HDFS by utilizing an open table format with concurrency control. Several formats, such as Apache Hudi, Apache Iceberg, Delta Lake, and Qbeast Format, offer this capability. All of them provide advanced features t

Re: Spark-SQL - Concurrent Inserts Into Same Table Throws Exception

It is not Spark SQL that throws the error. It is the underlying Database or layer that throws the error. Spark acts as an ETL tool. What is the underlying DB where the table resides? Is concurrency supported. Please send the error to this list HTH Mich Talebzadeh, Solutions Architect/Engineeri

Spark-SQL - Concurrent Inserts Into Same Table Throws Exception

Hello, I'm building an application on Spark SQL. The cluster is set up in standalone mode with HDFS as storage. The only Spark application running is the Spark Thrift Server using FAIR scheduling mode. Queries are submitted to Thrift Server using beeline. I have multiple queries that insert rows

Raise exception whilst casting instead of defaulting to null

so coupled. Enabling ANSI also comes with other consequences that fall outside casting behaviour, and not all Spark operations are done via the SQL interface (i.e. spark.sql("") ). I can imagine it's a pretty useful feature to have something like an extra arg that would raise an

Re: Spark-on-Yarn ClassNotFound Exception

one, so can't compare with the Spark source, but that looks >>> to me like it should be well after the ctx loader has been set. You could >>> try printing the classpath of the loader >>> Thread.currentThread().getThreadContextClassLoader(), or try to load your >>

Re: Spark-on-Yarn ClassNotFound Exception

the loader >> Thread.currentThread().getThreadContextClassLoader(), or try to load your >> class from that yourself to see if you get the same error. >> >> Can you see which thread is throwing the exception? If it is a different >> thread than the "main" ap

Re: Spark-on-Yarn ClassNotFound Exception

your > class from that yourself to see if you get the same error. > > Can you see which thread is throwing the exception? If it is a different > thread than the "main" application thread it might not have the thread ctx > loader set correctly. I can't see any of your class

Re: Spark-on-Yarn ClassNotFound Exception

to see if you get the same error. Can you see which thread is throwing the exception? If it is a different thread than the "main" application thread it might not have the thread ctx loader set correctly. I can't see any of your classes in the stacktrace - I assume that is because

Re: Spark-on-Yarn ClassNotFound Exception

I can't immediately tell how your error might arise, unless there is some > timing issue with the Spark and Hadoop setup. Can you share the full > stacktrace of the ClassNotFound exception? That might tell us when Hadoop > is looking up this class. > > Good luck! > - scrypso >

Re: Spark-on-Yarn ClassNotFound Exception

e ClassNotFound exception? That might tell us when Hadoop is looking up this class. Good luck! - scrypso On Tue, Dec 13, 2022, 17:05 Hariharan wrote: > Missed to mention it above, but just to add, the error is coming from the > driver. I tried using *--driver-class-path /path/to/my/jar* a

Re: Spark-on-Yarn ClassNotFound Exception

Missed to mention it above, but just to add, the error is coming from the driver. I tried using *--driver-class-path /path/to/my/jar* as well, but no luck. Thanks! On Mon, Dec 12, 2022 at 4:21 PM Hariharan wrote: > Hello folks, > > I have a spark app with a custom implementation of > *fs.s3a.s3

Spark-on-Yarn ClassNotFound Exception

Hello folks, I have a spark app with a custom implementation of *fs.s3a.s3.client.factory.impl* which is packaged into the same jar. Output of *jar tf* *2620 Mon Dec 12 11:23:00 IST 2022 aws/utils/MyS3ClientFactory.class* However when I run the my spark app with spark-submit in cluster mode, it

Re: WARN ProcfsMetricsGetter: Exception

you should be able to check details from spark logs. Surya Gopisetty wrote: I am getting this warning I tried to solve this but not sure of the solution, -- Simple Mail https://simplemail.co.in/ - To unsubscribe e-mail: user-

WARN ProcfsMetricsGetter: Exception

Hi Team, I am getting this warning I tried to solve this but not sure of the solution, Can you please look into this? [image: image.png] Thanks and Regards Surya.

Driver throws exception every few hours

: io.fabric8.kubernetes.api.model.PodList["items"]->java.util.ArrayList[0]- More detailed stack trace Uncaught exception in thread kubernetes-executor-pod-polling-sync io.fabric8.kubernetes.client.KubernetesClientException: An error has occurred. a

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

> == SQL == >>> CREATE OR REPLACE TABLE >>> >>> >>> On Mon, Aug 1, 2022 at 8:32 PM Sean Owen wrote: >>> >>>> Pretty much what it says? you are creating a table over a path that >>>> already has data in it. You can't do that

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

te: >> >>> Pretty much what it says? you are creating a table over a path that >>> already has data in it. You can't do that without mode=overwrite at least, >>> if that's what you intend. >>> >>> On Mon, Aug 1, 2022 at 7:29 PM Kumba Jan

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

at's what you intend. >> >> On Mon, Aug 1, 2022 at 7:29 PM Kumba Janga wrote: >> >>> >>> >>>- Component: Spark Delta, Spark SQL >>>- Level: Beginner >>>- Scenario: Debug, How-to >>> >>> *Python in J

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

. >> >> On Mon, Aug 1, 2022 at 7:29 PM Kumba Janga wrote: >> >>> >>> >>> - Component: Spark Delta, Spark SQL >>>- Level: Beginner >>>- Scenario: Debug, How-to >>> >>> *Python in Jupyter:* >>> >

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

: Beginner >>- Scenario: Debug, How-to >> >> *Python in Jupyter:* >> >> import pyspark >> import pyspark.sql.functions >> >> from pyspark.sql import SparkSession >> spark = ( >> SparkSession >> .builder >>

Re: [pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

ession.sql(sqlQuery), self._wrapped)650 651 > @since(2.0) > \Users\kyjan\spark-3.0.3-bin-hadoop2.7\python\lib\py4j-0.10.9-src.zip\py4j\java_gateway.py > in __call__(self, *args) 13021303 answer = > self.gateway_client.send_command(command)-> 1304

[pyspark delta] [delta][Spark SQL]: Getting an Analysis Exception. The associated location (path) is not empty

t;""--> 649 return DataFrame(self._jsparkSession.sql(sqlQuery), self._wrapped)650 651 @since(2.0) \Users\kyjan\spark-3.0.3-bin-hadoop2.7\python\lib\py4j-0.10.9-src.zip\py4j\java_gateway.py in __call__(self, *args) 13021303 answer = self.gateway_client.send_command(command)->

RE: [EXTERNAL] Re: Spark on K8s - repeating annoying exception

Hi Martin, Thanks for the help :) I tried to set those keys to high value but the error persists every 90 seconds. Shay From: Martin Grigorov Sent: Friday, May 13, 2022 4:15 PM To: Shay Elbaz Cc: user@spark.apache.org Subject: [EXTERNAL] Re: Spark on K8s - repeating annoying exception

Re: Spark on K8s - repeating annoying exception

Hi, On Mon, May 9, 2022 at 5:57 PM Shay Elbaz wrote: > Hi all, > > > > I apologize for reposting this from Stack Overflow, but it got very little > attention and now comment. > > > > I'm using Spark 3.2.1 image that was built from the official distribution > via `docker-image-tool.sh', on Kubern

Spark on K8s - repeating annoying exception

Hi all, I apologize for reposting this from Stack Overflow, but it got very little attention and now comment. I'm using Spark 3.2.1 image that was built from the official distribution via `docker-image-tool.sh', on Kubernetes 1.18 cluster. Everything works fine, except for this error message on

Accumulator null pointer exception

I;m getting an interesting null pointer exception when trying to add any value in a custom accumulator. *code*: object StagingFacade { //Accumulator declared var filesAccumulator : CollectionAccumulator[(String, String, String)] = _ def apply(appArgs: Array[String], spark

Spark Phoenix Connection Exception while loading from Phoenix tables

[01/09/21 11:55:51,861 WARN pool-1-thread-1](Client) Exception encountered while connecting to the server : java.lang.NullPointerException [01/09/21 11:55:51,862 WARN pool-1-thread-1](Client) Exception encountered while connecting to the server : java.lang.NullPointerException [01/09/21 11

Re: Spark Null Pointer Exception

Could also be transient object being referenced from within the custom code. When serialized the reference shows up as null even though you had set it in the parent object. > On Jun 30, 2021, at 4:44 PM, Sean Owen wrote: > > The error is in your code, which you don't show. You are almost certa

Re: Spark Null Pointer Exception

The error is in your code, which you don't show. You are almost certainly incorrectly referencing something like a SparkContext in a Spark task. On Wed, Jun 30, 2021 at 3:48 PM Amit Sharma wrote: > Hi , I am using spark 2.7 version with scala. I am calling a method as > below > > 1. val rddBackl

Spark Null Pointer Exception

Hi , I am using spark 2.7 version with scala. I am calling a method as below 1. val rddBacklog = spark.sparkContext.parallelize(MAs) // MA is list of say city 2. rddBacklog.foreach(ma => doAlloc3Daily(ma, fteReview.forecastId, startYear, endYear)) 3.doAlloc3Daily method just doing a database cal

Re: ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception

ELL *** 21/03/18 22:14:13 ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception java.util.ConcurrentModificationException at java.util.Hashtable$Enumerator.next(Hashtable.java:1387) at scala.collection.convert.Wrappers$JPropertiesWrapper$$ano

Re: ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception

wse/SPARK-34731 On Fri, Mar 19, 2021 at 5:00 AM Mich Talebzadeh wrote: > > Recall this was the error > > 21/03/18 16:53:38 ERROR org.apache.spark.scheduler.AsyncEventQueue: > Listener EventLoggingListener threw an exception > > java.util.ConcurrentModificationExceptio

Re: ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception

Recall this was the error 21/03/18 16:53:38 ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception java.util.ConcurrentModificationException at java.util.Hashtable$Enumerator.next(Hashtable.java:1387) I resolved this error message by setting

Re: ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception

This is an intermittent error. Full error is this 21/03/18 17:35:12 ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception java.util.ConcurrentModificationException at java.util.Hashtable$Enumerator.next(Hashtable.java:1387) at

ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception

Hi, Does anyone know about the cause of this error in Spark structured streaming? Spark version 3.1.1 21/03/18 16:53:38 ERROR org.apache.spark.scheduler.AsyncEventQueue: Listener EventLoggingListener threw an exception java.util.ConcurrentModificationException at

Re: spark on k8s driver pod exception

driver pod persists logs and remains in “completed” state in > the Kubernetes API until it’s eventually garbage collected or manually > cleaned up. On Mon, Mar 15, 2021 at 8:45 AM 040840219 wrote: > > when driver pod throws exception , driver pod still running ？ > >

Re: spark on k8s driver pod exception

when driver pod throws exception , driver pod still running ？ kubectl logs wordcount-e3141c7834d3dd68-driver 21/03/15 07:40:19 DEBUG Analyzer$ResolveReferences: Resolving 'value1 to 'value1 Exception in thread "main" org.apache.spark.sql.AnalysisException: cann

Re: spark on k8s driver pod exception

gt; when run the code in k8s , driver pod throw AnalysisException , but the >> spark-submit log still running , then how to get the exception and stop >> pods ? >> >> val spark = SparkSession.builder().getOrCreate() >> import spark.implicits._ >>

Re: spark on k8s driver pod exception

k8s , driver pod throw AnalysisException , but the > spark-submit log still running , then how to get the exception and stop > pods ? > > val spark = SparkSession.builder().getOrCreate() > import spark.implicits._ > val df = (0 until 10).toDF("id&

spark on k8s driver pod exception

when run the code in k8s , driver pod throw AnalysisException , but the spark-submit log still running , then how to get the exception and stop pods ? val spark = SparkSession.builder().getOrCreate() import spark.implicits._ val df = (0 until 10).toDF("id").sele

Re: Exception on Avro Schema Object Serialization

erter -- OK 3. Create a data frame by using the StructType as the schema when loading a csv file -- OK 4. Doing other SQL operations with the data frame -- OK 5. Use the data frame in a UDF -- exception occurred. We didn't have any exception when manually creating the struct type in s

Re: Exception on Avro Schema Object Serialization

Your function is somehow capturing the actual Avro schema object, which won't seiralize. Try rewriting it to ensure that it isn't used in the function. On Tue, Feb 2, 2021 at 2:32 PM Artemis User wrote: > We tried to standardize the SQL data source management using the Avro > schema, but encount

Exception on Avro Schema Object Serialization

We tried to standardize the SQL data source management using the Avro schema, but encountered some serialization exceptions when trying to use the data.  The interesting part is that we didn't have any problems in reading the Avro schema JSON file and converting the Avro schema into a SQL Struc

Re: EOF Exception Spark Structured Streams - Kubernetes

Hi Prashant, Yes I understand that will be available from Spark 3.0.2 . But I am using Spark3.0.1 Could you please suggest any way to mitigate this exception? Will it cause any issues from this exception in the spark application? Thanks Sachit On Mon, 1 Feb 2021, 13:57 Prashant Sharma, wrote

Re: EOF Exception Spark Structured Streams - Kubernetes

Sun, Jan 31, 2021 at 6:38 PM Sachit Murarka > wrote: > >> Hi Users, >> >> I am running Spark application on Kubernetes and getting the following >> exception in the driver pod. Though it is not affecting the output. >> >> This exception is coming every

Re: EOF Exception Spark Structured Streams - Kubernetes

wrote: > Hi Users, > > I am running Spark application on Kubernetes and getting the following > exception in the driver pod. Though it is not affecting the output. > > This exception is coming every 5 minutes and this is a structured > streaming job. > > Could anyone plea

EOF Exception Spark Structured Streams - Kubernetes

Hi Users, I am running Spark application on Kubernetes and getting the following exception in the driver pod. Though it is not affecting the output. This exception is coming every 5 minutes and this is a structured streaming job. Could anyone please advise ? 21/01/29 06:33:15 WARN

Odd NoClassDefFoundError exception

arkSession builder pattern to create one. Can you help? Thanks in advance and let me know if there's more information I can provide. ~ Shawn PS Spark 3.0.0 The Exception Exception occurred in target VM: Could not initialize class org.apache.spark.sql.catalyst.util

Re: Spark Exception

of an exception or something. On Fri, Nov 20, 2020 at 10:52 AM Amit Sharma wrote: > Russell i increased the rpc timeout to 240 seconds but i am still getting > this issue once a while and after this issue my spark streaming job stuck > and do not process any request then i need to restart this e

Re: Spark Exception

Sharma wrote: > Hi, we are running a spark streaming job and sometimes it throws below > two exceptions . I am not understanding what is the difference between > these two exception for one timeout is 120 seconds and another is 600 > seconds. What could be the reason for these > >

Re: Spark Exception

Please help. Thanks Amit On Wed, Nov 18, 2020 at 12:05 PM Amit Sharma wrote: > Hi, we are running a spark streaming job and sometimes it throws below > two exceptions . I am not understanding what is the difference between > these two exception for one timeout is 120 seconds and a

Spark Exception

Hi, we are running a spark streaming job and sometimes it throws below two exceptions . I am not understanding what is the difference between these two exception for one timeout is 120 seconds and another is 600 seconds. What could be the reason for these Error running job streaming job

spark-sql on windows throws Exception in thread "main" java.lang.UnsatisfiedLinkError:

;). 20/11/16 21:12:34 INFO SharedState: Warehouse path is '/tmp/hive/warehouse'. 20/11/16 21:12:34 INFO SessionState: Created HDFS directory: /tmp/hive/admin/e32257b3-6c6b-46d7-921e-2782e2c15546 Exception in thread "main" java.lang.UnsatisfiedLinkError:

Memory exception Issue at the time of inferring schema from huge json

Hi, I am reading a json part files using Spark, it has 1.4 Million records and the input size is closer to 200 GB. At the time of reading/infering schema, (spark.read.json) its throwing out of memory Exception. The job is running in the cluster, where i am providing 22g executor memory, 4

Re: Exception handling in Spark throws recursive value for DF needs type error

ssword). >> >> option("partitionColumn", partitionColumn). >> >> option("lowerBound", lowerBound). >> >> option("upperBound", upperBound). >> >> option("numPartitions", numPartitions). >> >> load()) match { >> >>case Success(df) => df >> >>case Failure(e) => throw new Exception("Error >> Encountered reading Hive table") >> >> } >> >> Are there any performance implications of having Try, Success, Failure >> enclosure around DF? >> >>>

Re: Exception handling in Spark throws recursive value for DF needs type error

ot;, partitionColumn). > > option("lowerBound", lowerBound). > > option("upperBound", upperBound). > > option("numPartitions", numPartitions). > > load()) match { > >case Success(df) => df > >case Failure(e) => throw new Exception("Error > Encountered reading Hive table") > > } > > Are there any performance implications of having Try, Success, Failure > enclosure around DF? > >>

Re: Exception handling in Spark throws recursive value for DF needs type error

uot;, lowerBound). option("upperBound", upperBound). option("numPartitions", numPartitions). load()) match { case Success(df) => df case Failure(e) => throw new Exception("Error Encountered reading Hive table")

Re: Exception handling in Spark throws recursive value for DF needs type error

ot;password", HybridServerPassword). load()) match { *case Success(df) => df* case Failure(e) => throw new Exception("Error Encountered reading Hive table") } HiveDF: org.apache.spark.sql.DataFrame = [id: int, clustered: int ... 5 more fields] Appreci

Re: Exception handling in Spark throws recursive value for DF needs type error

("url", jdbcUrl). option("dbtable", HiveSchema+"."+HiveTable). option("user", HybridServerUserName). option("password", HybridServerPassword). load()) match { *case Success(validDf) => validDf* ca

Re: Exception handling in Spark throws recursive value for DF needs type error

t;password", HybridServerPassword). load()) match { *case Success(DF) => HiveDF* case Failure(e) => throw new Exception("Error Encountered reading Hive table") } Still getting the error :74: error: recursive method DF needs typ

Re: Exception handling in Spark throws recursive value for DF needs type error

> format("jdbc"). > > option("url", jdbcUrl). > > option("dbtable", HiveSchema+"."+HiveTable). > > option("user", HybridServerUserName). > > option("password", HybridServerPassword). &g

Exception handling in Spark throws recursive value for DF needs type error

t;password", HybridServerPassword). load()) match { case Success(HiveDF) => HiveDF case Failure(e) => throw new Exception("Error Encountered reading Hive table") } However, with Try I am getting the following error :66: error: recursive value

WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped

I am running Apache Spark Core using Scala 2.12.12 on IntelliJ IDEA 2020.2 with Docker 2.3.0.5 I am running Windows 10 build 2004 Can somebody explain me why am I receiving this w

Re: spark exception

there wasn't enough working ram to handle the heap requested. If the log ends with some other kind of exception then you need to look into why that occured. On Fri, Jul 24, 2020, 7:42 AM Amit Sharma wrote: > Hi All, sometimes i get this error in spark logs. I notice few executors > are

spark exception

Hi All, sometimes i get this error in spark logs. I notice few executors are shown as dead in the executor tab during this error. Although my job get success. Please help me out the root cause of this issue. I have 3 workers with 30 cores each and 64 GB RAM each. My job uses 3 cores per executor an

WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped

I installed Spark and run it, then I get an error "WARN ProcfsMetricsGetter: Exception when trying to compute pagesize, as a result reporting of ProcessTree metrics is stopped" Something like:

RE: PyArrow Exception in Pandas UDF GROUPEDAGG()

() function takes a numPartitions column. What other options can I explore? --gautham -Original Message- From: ZHANG Wei Sent: Thursday, May 7, 2020 1:34 AM To: Gautham Acharya Cc: user@spark.apache.org Subject: Re: PyArrow Exception in Pandas UDF GROUPEDAGG() CAUTION: This email origina

Re: PyArrow Exception in Pandas UDF GROUPEDAGG()

> fewer rows. However, when run on a dataset with 3 million rows, I see the > following exception: > > 20/05/05 23:36:27 ERROR Executor: Exception in task 66.1 in stage 12.0 (TID > 2358) > org.apache.spark.api.python.PythonException: Traceback (most recent call > last):

PyArrow Exception in Pandas UDF GROUPEDAGG()

bel_a | 3.1| 6.2 | 5.444 | My job runs fine on smaller datasets, with the same number of columns but fewer rows. However, when run on a dataset with 3 million rows, I see the following exception: 20/05/05 23:36:27 ERROR Executor: Exception in task 66

Re: Exception handling in Spark

Sure, just do case Failure(e) => throw e From: Mich Talebzadeh Date: Tuesday, May 5, 2020 at 6:36 PM To: Brandon Geise Cc: Todd Nist , "user @spark" Subject: Re: Exception handling in Spark Hi Brandon. In dealing with df case Failure(e) => throw new Exception

Re: Exception handling in Spark

Hi Brandon. In dealing with df case Failure(e) => throw new Exception("foo") Can one print the Exception message? Thanks Dr Mich Talebzadeh LinkedIn * https://www.linkedin.com/profile/view?id=AAEWh2gBxianrbJd6zP6AcPCCdOABUrV8Pw <https://www.linkedin.com

Re: Exception handling in Spark

t").load("/tmp/broadcast.xml")) match {case Success(df) => df case Failure(e) => throw new Exception("foo")} df: org.apache.spark.sql.DataFrame = [brand: string, ocis_party_id: bigint ... 6 more fields] regards, Dr Mich Talebzadeh LinkedIn * https

Re: Exception handling in Spark

Match needs to be lower case “match” From: Mich Talebzadeh Date: Tuesday, May 5, 2020 at 6:13 PM To: Brandon Geise Cc: Todd Nist , "user @spark" Subject: Re: Exception handling in Spark scala> import scala.util.{Try, Success, Failure} import scala.util.{Try, Success, Fa

Re: Exception handling in Spark

broadcast.xml")) Match {case Success(df) => df case Failure(e) => throw new Exception("foo")} :48: error: value Match is not a member of scala.util.Try[org.apache.spark.sql.DataFrame] val df = Try(spark.read.format("com.databricks.spark.xml").option("rootTag&

Re: Exception handling in Spark

Import scala.util.Try Import scala.util.Success Import scala.util.Failure From: Mich Talebzadeh Date: Tuesday, May 5, 2020 at 6:11 PM To: Brandon Geise Cc: Todd Nist , "user @spark" Subject: Re: Exception handling in Spark This is what I get scala> val df = Try(spar

Re: Exception handling in Spark

This is what I get scala> val df = Try(spark.read.format("com.databricks.spark.xml").option("rootTag", "hierarchy").option("rowTag", "sms_request").load("/tmp/broadcast.xml")) Match {case Success(df) => df case Failure(e) => th

Re: Exception handling in Spark

This is what I had in mind.  Can you give this approach a try? val df = Try(spark.read.csv("")) match {   case Success(df) => df   case Failure(e) => throw new Exception("foo")   } From: Mich Talebzadeh Date: Tuesday, May 5, 2020 at 5:17 PM To: To

Re: Exception handling in Spark

quot;rootTag", "hierarchy"). option("rowTag", "sms_request"). load("/tmp/broadcast.xml") df } catch { case ex: FileNotFoundException => { println (s"\nFile /tmp/broadcast.xml not found\n") None

Re: Exception handling in Spark

; arise from relying on this email's technical content is explicitly >> disclaimed. The author will in no case be liable for any monetary damages >> arising from such loss, damage or destruction. >> >> >> >> >> On Tue, 5 May 2020 at 16:41, Brandon Geis

Re: Exception handling in Spark

Date: Tuesday, May 5, 2020 at 12:45 PM To: Brandon Geise Cc: "user @spark" Subject: Re: Exception handling in Spark Thanks Brandon! i should have remembered that. basically the code gets out with sys.exit(1) if it cannot find the file I guess there is no easy way

Re: Exception handling in Spark

r destruction. > > > > > On Tue, 5 May 2020 at 16:41, Brandon Geise wrote: > >> You could use the Hadoop API and check if the file exists. >> >> >> >> *From: *Mich Talebzadeh >> *Date: *Tuesday, May 5, 2020 at 11:25 AM >> *To: *"user

Re: Exception handling in Spark

use the Hadoop API and check if the file exists. > > > > *From: *Mich Talebzadeh > *Date: *Tuesday, May 5, 2020 at 11:25 AM > *To: *"user @spark" > *Subject: *Exception handling in Spark > > > > Hi, > > > > As I understand exception handling in

Re: Exception handling in Spark

You could use the Hadoop API and check if the file exists. From: Mich Talebzadeh Date: Tuesday, May 5, 2020 at 11:25 AM To: "user @spark" Subject: Exception handling in Spark Hi, As I understand exception handling in Spark only makes sense if one attempts an action as

Exception handling in Spark

Hi, As I understand exception handling in Spark only makes sense if one attempts an action as opposed to lazy transformations? Let us assume that I am reading an XML file from the HDFS directory and create a dataframe DF on it val broadcastValue = "123456789" // I assume this will

Exception during writing a spark Dataframe to Redshift

This is where the exception occurs: myAppDes.coalesce(1) .write .format("com.databricks.spark.redshift") .option("url", redshiftURL) .option("dbtable", redshiftTableName) .option("forward_spark_s3_credentials", "

Java Spark UDF cast exception

*Facing casting issues while working with the spark UDF* UDF1 mode1 = new UDF1>, String>() { @Override public String call(WrappedArray> maps) throws Exception { List> lis = (List>) JavaConverters.seqAsJavaListConverter(maps).asJava(); java.util.Map a= lis.strea

Spark Mllib logistic regression setWeightCol illegal argument exception

Hi Spark Users, I am trying to solve a class imbalance problem, I figured out, spark supports setting weight in its API but I get IIlegal Argument exception weight column do not exist, but it do exists in the dataset. Any recommedation to go about this problem ? I am using Pipeline API with

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