[jira] [Assigned] (SPARK-27852) One updateBytesWritten operaton may be missed in DiskBlockObjectWriter.scala
[
https://issues.apache.org/jira/browse/SPARK-27852?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-27852:
Assignee: (was: Apache Spark)
> One updateBytesWritten operaton may be missed in DiskBlockObjectWriter.scala
>
>
> Key: SPARK-27852
> URL: https://issues.apache.org/jira/browse/SPARK-27852
> Project: Spark
> Issue Type: Question
> Components: Spark Core
>Affects Versions: 2.4.3
>Reporter: Shuaiqi Ge
>Priority: Major
>
> In *_DiskBlockObjectWriter.scala_*, there are 2 overload *_write_*
> functions, the first of which executes _*updateBytesWritten*_ function while
> the other doesn't. I think writeMetrics should record all the information
> about writing operations, some data of which will be displayed in the Spark
> jobs UI such as the data size of shuffle read and shuffle write.
> {code:java}
> def write(key: Any, value: Any) {
>if (!streamOpen) {
> open()
>}
>objOut.writeKey(key)
>objOut.writeValue(value)
>recordWritten()
> }
> override def write(kvBytes: Array[Byte], offs: Int, len: Int): Unit = {
>if (!streamOpen) {
> open()
>}
>bs.write(kvBytes, offs, len)
>// updateBytesWritten() // the function is missed
> }
> **
> * Notify the writer that a record worth of bytes has been written with
> OutputStream#write.
> */
> def recordWritten(): Unit = {
>numRecordsWritten += 1
>writeMetrics.incRecordsWritten(1)
>if (numRecordsWritten % 16384 == 0) {
> updateBytesWritten()
>}
> }
> /**
> * Report the number of bytes written in this writer's shuffle write metrics.
> * Note that this is only valid before the underlying streams are closed.
> */
> private def updateBytesWritten() {
>val pos = channel.position()
>writeMetrics.incBytesWritten(pos - reportedPosition)
>reportedPosition = pos
> }
> {code}
>
>
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
[jira] [Assigned] (SPARK-27852) One updateBytesWritten operaton may be missed in DiskBlockObjectWriter.scala
[
https://issues.apache.org/jira/browse/SPARK-27852?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Apache Spark reassigned SPARK-27852:
Assignee: Apache Spark
> One updateBytesWritten operaton may be missed in DiskBlockObjectWriter.scala
>
>
> Key: SPARK-27852
> URL: https://issues.apache.org/jira/browse/SPARK-27852
> Project: Spark
> Issue Type: Question
> Components: Spark Core
>Affects Versions: 2.4.3
>Reporter: Shuaiqi Ge
>Assignee: Apache Spark
>Priority: Major
>
> In *_DiskBlockObjectWriter.scala_*, there are 2 overload *_write_*
> functions, the first of which executes _*updateBytesWritten*_ function while
> the other doesn't. I think writeMetrics should record all the information
> about writing operations, some data of which will be displayed in the Spark
> jobs UI such as the data size of shuffle read and shuffle write.
> {code:java}
> def write(key: Any, value: Any) {
>if (!streamOpen) {
> open()
>}
>objOut.writeKey(key)
>objOut.writeValue(value)
>recordWritten()
> }
> override def write(kvBytes: Array[Byte], offs: Int, len: Int): Unit = {
>if (!streamOpen) {
> open()
>}
>bs.write(kvBytes, offs, len)
>// updateBytesWritten() // the function is missed
> }
> **
> * Notify the writer that a record worth of bytes has been written with
> OutputStream#write.
> */
> def recordWritten(): Unit = {
>numRecordsWritten += 1
>writeMetrics.incRecordsWritten(1)
>if (numRecordsWritten % 16384 == 0) {
> updateBytesWritten()
>}
> }
> /**
> * Report the number of bytes written in this writer's shuffle write metrics.
> * Note that this is only valid before the underlying streams are closed.
> */
> private def updateBytesWritten() {
>val pos = channel.position()
>writeMetrics.incBytesWritten(pos - reportedPosition)
>reportedPosition = pos
> }
> {code}
>
>
--
This message was sent by Atlassian JIRA
(v7.6.3#76005)
-
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
