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https://issues.apache.org/jira/browse/KAFKA-19403?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Matthias J. Sax updated KAFKA-19403:
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    Component/s:     (was: connect)

> We're facing issue in Kafka while reading data from Azure event hubs through 
> Azure Databricks
> ---------------------------------------------------------------------------------------------
>
>                 Key: KAFKA-19403
>                 URL: https://issues.apache.org/jira/browse/KAFKA-19403
>             Project: Kafka
>          Issue Type: Bug
>          Components: consumer, network
>    Affects Versions: 3.3.1
>         Environment: Production
>            Reporter: karthickthavasiraj09
>            Priority: Major
>
> * We are experiencing significant slowness while reading data from Azure 
> Event Hubs using Azure Databricks. After conducting initial analysis with the 
> Microsoft support team, they confirmed that the root cause appears to be 
> related to Kafka. We are reaching out for your assistance in investigating 
> and resolving this issue.
> Below are the key findings and debug logs provided by the Microsoft team:
>  ** The data read operation took *49 minutes* in total.
>  ** Out of this, only one task(spark task) {*}Task 143 alone took 46 
> minutes{*}, indicating a bottleneck in this specific task.
>  ** The job duration was {*}49 minutes and 30 seconds{*}.
> Relevant Log Snippets:
> 25/04/15 14:21:44 INFO KafkaBatchReaderFactoryWithRowBytesAccumulator:
> Creating Kafka reader topicPartition=<topic-name>-0 fromOffset=16511904 
> untilOffset=16658164,
> for queryId=dd660d4d-05cc-4a8e-8f93-d202ec78fec3 
> runId=af7eb711-7310-4788-85b7-0977fc0756b7 batchId=73 taskId=143 partitionId=0
> 25/04/15 15:07:21 INFO KafkaDataConsumer:
> From Kafka topicPartition=<topic-name>-0 
> groupId=spark-kafka-source-da79e0fc-8ee5-40f5-a127-7b31766b3022--1737876659-executor
> read 146260 records through 4314 polls (polled out 146265 records), taking 
> 2526471821132 ns,
> over a timespan of 2736294068630 ns.
>  
> Additionally, the thread stack trace indicates that the task was mostly 
> waiting on Kafka to respond. See the following thread details captured during 
> the slowness:
> Executor task launch worker for task 0.0 in stage 147.0 (TID 143)
> sun.nio.ch.EPollArrayWrapper.epollWait(Native Method)
> ...
> kafkashaded.org.apache.kafka.clients.consumer.KafkaConsumer.position(KafkaConsumer.java:1759)
> ...
> org.apache.spark.sql.kafka010.consumer.KafkaDataConsumer.fetchRecord(KafkaDataConsumer.scala:517)
> *We kindly request the Kafka team to look into this issue. The task appears 
> to be blocked for an extended period during Kafka polling. Any insights into 
> why Kafka is not responding promptly or recommendations for configuration 
> changes or optimizations would be greatly appreciated.*
> *Please let us know if any additional information or diagnostics are required 
> from our end.*
> *Thank you for your support.*



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