Hi Alexey,
First of all, thank you for the response! Yes I did have it in Consumer
configuration and try to increase "session.timeout".
>From consumer side so far I've following settings:
props.put("sasl.mechanism", SASL_MECHANISM);
props.put("security.protocol", SECURITY_PROTOCOL);
props.put("sasl.jaas.config", saslJaasConfig);
props.put("request.timeout.ms", 60000);
props.put("session.timeout.ms", 60000);
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, AUTO_OFFSET_RESET_CONFIG);
props.put(ConsumerConfig.GROUP_ID_CONFIG, consumerGroup);
It works fine using following code in Databricks Notebook. The problem has
been occurring when I run it through Apache beam and KafkaIO (Just
providing more context if that may help you to understand problem)
val df = spark.readStream
.format("kafka")
.option("subscribe", TOPIC)
.option("kafka.bootstrap.servers", BOOTSTRAP_SERVERS)
.option("kafka.sasl.mechanism", "PLAIN")
.option("kafka.security.protocol", "SASL_SSL")
.option("kafka.sasl.jaas.config", EH_SASL)
.option("kafka.request.timeout.ms", "60000")
.option("kafka.session.timeout.ms", "60000")
.option("failOnDataLoss", "false")
//.option("kafka.group.id", "testsink")
.option("startingOffsets", "latest")
.load()
Utkarsh
On Tue, Feb 1, 2022 at 6:20 AM Alexey Romanenko <aromanenko....@gmail.com>
wrote:
> Hi Utkarsh,
>
> Can it be related to this configuration problem?
>
> https://docs.microsoft.com/en-us/azure/event-hubs/apache-kafka-troubleshooting-guide#no-records-received
>
> Did you check timeout settings?
>
> —
> Alexey
>
>
> On 1 Feb 2022, at 02:27, Utkarsh Parekh <utkarsh.s.par...@gmail.com>
> wrote:
>
> Hello,
>
> I'm doing POC with KafkaIO and spark runner on Azure Databricks. I'm
> trying to create a simple streaming app with Apache Beam, where it reads
> data from an Azure event hub and produces messages into another Azure event
> hub.
>
> I'm creating and running spark jobs on Azure Databricks.
>
> The problem is the consumer (uses SparkRunner) is not able to read data
> from Event hub (queue). There is no activity and no errors on the Spark
> cluster.
>
> I would appreciate it if anyone could help to fix this issue.
>
> Thank you
>
> Utkarsh
>
>
>
