Kafka Request handler pool decreases when writing using Spark












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I have a spark job. When it starts writing to Kafka, its request handler pool reduces so much that spark tasks start failing. Currently, Spark is creating around 410 tasks to write to Kafka. Is there a tuning parameter to increase the request handler pool. How much is considered a safe number for request handler pool?. I have a Kafka v2.0 cluster of 6 brokers all have 8 cores and 16 GB. All are running on default tuning parameters.










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    I have a spark job. When it starts writing to Kafka, its request handler pool reduces so much that spark tasks start failing. Currently, Spark is creating around 410 tasks to write to Kafka. Is there a tuning parameter to increase the request handler pool. How much is considered a safe number for request handler pool?. I have a Kafka v2.0 cluster of 6 brokers all have 8 cores and 16 GB. All are running on default tuning parameters.










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      I have a spark job. When it starts writing to Kafka, its request handler pool reduces so much that spark tasks start failing. Currently, Spark is creating around 410 tasks to write to Kafka. Is there a tuning parameter to increase the request handler pool. How much is considered a safe number for request handler pool?. I have a Kafka v2.0 cluster of 6 brokers all have 8 cores and 16 GB. All are running on default tuning parameters.










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      I have a spark job. When it starts writing to Kafka, its request handler pool reduces so much that spark tasks start failing. Currently, Spark is creating around 410 tasks to write to Kafka. Is there a tuning parameter to increase the request handler pool. How much is considered a safe number for request handler pool?. I have a Kafka v2.0 cluster of 6 brokers all have 8 cores and 16 GB. All are running on default tuning parameters.







      apache-spark apache-kafka






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      asked Nov 13 at 5:19









      guru107

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