[jira] [Updated] (SPARK-22782) Boost speed, use kafka010 consumer kafka

2017-12-14 Thread licun (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-22782?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

licun updated SPARK-22782:
--
Description: 
We use spark structured streaming to consumer kafka, but we find the 
consumer speed is too slow compare spark streaming . we set kafka 
"maxOffsetsPerTrigger": 1. 
   By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  found 
the following situation: 
 
   The debug code:
  
{code:scala}
private def poll(pollTimeoutMs: Long): Unit = {
val startTime = System.currentTimeMillis()
val p = consumer.poll(pollTimeoutMs)
val r = p.records(topicPartition)
val endTime = System.currentTimeMillis()
val delta = endTime - startTime
logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
${delta} ms")
fetchedData = r.iterator
  }
{code}

   The log:
   


  was:
We use spark structured streaming to consumer kafka, but we find the 
consumer speed is too slow compare spark streaming . we set kafka 
"maxOffsetsPerTrigger": 1. 
   By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  found 
the following situation: 
 
   The debug code:
   
{code:scala}
private def poll(pollTimeoutMs: Long): Unit = {
val startTime = System.currentTimeMillis()
val p = consumer.poll(pollTimeoutMs)
val r = p.records(topicPartition)
val endTime = System.currentTimeMillis()
val delta = endTime - startTime
logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
${delta} ms")
fetchedData = r.iterator
  }
{code}



> Boost speed, use kafka010 consumer kafka
> 
>
> Key: SPARK-22782
> URL: https://issues.apache.org/jira/browse/SPARK-22782
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.1.0, 2.2.0
> Environment: kafka-version:  0.10
> spark-version: 2.2.0
> schedule spark on yarn
>Reporter: licun
>Priority: Critical
>
> We use spark structured streaming to consumer kafka, but we find the 
> consumer speed is too slow compare spark streaming . we set kafka 
> "maxOffsetsPerTrigger": 1. 
>By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  
> found the following situation: 
>  
>The debug code:
>   
> {code:scala}
> private def poll(pollTimeoutMs: Long): Unit = {
> val startTime = System.currentTimeMillis()
> val p = consumer.poll(pollTimeoutMs)
> val r = p.records(topicPartition)
> val endTime = System.currentTimeMillis()
> val delta = endTime - startTime
> logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
> ${delta} ms")
> fetchedData = r.iterator
>   }
> {code}
>The log:
>



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Updated] (SPARK-22782) Boost speed, use kafka010 consumer kafka

2017-12-14 Thread licun (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-22782?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

licun updated SPARK-22782:
--
Description: 
We use spark structured streaming to consumer kafka, but we find the 
consumer speed is too slow compare spark streaming . we set kafka 
"maxOffsetsPerTrigger": 1. 
   By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  found 
the following situation: 
 
   The debug code:
   
{code:scala}
private def poll(pollTimeoutMs: Long): Unit = {
val startTime = System.currentTimeMillis()
val p = consumer.poll(pollTimeoutMs)
val r = p.records(topicPartition)
val endTime = System.currentTimeMillis()
val delta = endTime - startTime
logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
${delta} ms")
fetchedData = r.iterator
  }
{code}


  was:
We use spark structured streaming to consumer kafka, but we find the 
consumer speed is too slow compare spark streaming . we set kafka 
"maxOffsetsPerTrigger": 1. 
   By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  found 
the following situation: 
 
   The debug code:
   {color:red}private def poll(pollTimeoutMs: Long): Unit = {
val startTime = System.currentTimeMillis()
val p = consumer.poll(pollTimeoutMs)
val r = p.records(topicPartition)
val endTime = System.currentTimeMillis()
val delta = endTime - startTime
logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
${delta} ms")
fetchedData = r.iterator
  }{color}


> Boost speed, use kafka010 consumer kafka
> 
>
> Key: SPARK-22782
> URL: https://issues.apache.org/jira/browse/SPARK-22782
> Project: Spark
>  Issue Type: Improvement
>  Components: Structured Streaming
>Affects Versions: 2.1.0, 2.2.0
> Environment: kafka-version:  0.10
> spark-version: 2.2.0
> schedule spark on yarn
>Reporter: licun
>Priority: Critical
>
> We use spark structured streaming to consumer kafka, but we find the 
> consumer speed is too slow compare spark streaming . we set kafka 
> "maxOffsetsPerTrigger": 1. 
>By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  
> found the following situation: 
>  
>The debug code:
>
> {code:scala}
> private def poll(pollTimeoutMs: Long): Unit = {
> val startTime = System.currentTimeMillis()
> val p = consumer.poll(pollTimeoutMs)
> val r = p.records(topicPartition)
> val endTime = System.currentTimeMillis()
> val delta = endTime - startTime
> logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
> ${delta} ms")
> fetchedData = r.iterator
>   }
> {code}



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org

[jira] [Created] (SPARK-22782) Boost speed, use kafka010 consumer kafka

2017-12-14 Thread licun (JIRA) 
licun created SPARK-22782:
-

 Summary: Boost speed, use kafka010 consumer kafka
 Key: SPARK-22782
 URL: https://issues.apache.org/jira/browse/SPARK-22782
 Project: Spark
  Issue Type: Improvement
  Components: Structured Streaming
Affects Versions: 2.2.0, 2.1.0
 Environment: kafka-version:  0.10
spark-version: 2.2.0
schedule spark on yarn
Reporter: licun
Priority: Critical


We use spark structured streaming to consumer kafka, but we find the 
consumer speed is too slow compare spark streaming . we set kafka 
"maxOffsetsPerTrigger": 1. 
   By adding debug log in CachedKafkaConsumer.scala (kafka-0-10-sql), we  found 
the following situation: 
 
   The debug code:
   {color:red}private def poll(pollTimeoutMs: Long): Unit = {
val startTime = System.currentTimeMillis()
val p = consumer.poll(pollTimeoutMs)
val r = p.records(topicPartition)
val endTime = System.currentTimeMillis()
val delta = endTime - startTime
logError(s"Polled $groupId ${p.partitions()}, Size:${r.size}, spend: 
${delta} ms")
fetchedData = r.iterator
  }{color}



--
This message was sent by Atlassian JIRA
(v6.4.14#64029)

-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org