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peay edited comment on SPARK-27019 at 3/1/19 1:06 PM: ------------------------------------------------------ Sure does. I've done one more test, using no executors and running the same command: {code:java} spark.range(1024 * 1024 * 1024 * 10).toPandas() {code} The SQL tab directly shows the wrong output, even though no task has started - i.e., my assumption above that this was because of failing tasks appears wrong. This actually seems consistent with the 'submitted date' somehow being wrong. was (Author: peay): Sure does. I've done one more test, using no executors and running the same command: spark.range(1024 * 1024 * 1024 * 10).toPandas() The SQL tab directly shows the wrong output, even though no task has started - i.e., my assumption above that this was because of failing tasks appears wrong. This actually seems consistent with the 'submitted date' somehow being wrong. > Spark UI's SQL tab shows inconsistent values > -------------------------------------------- > > Key: SPARK-27019 > URL: https://issues.apache.org/jira/browse/SPARK-27019 > Project: Spark > Issue Type: Bug > Components: SQL, Web UI > Affects Versions: 2.4.0 > Reporter: peay > Priority: Major > Attachments: query-1-details.png, query-1-list.png, query-job-1.png, > screenshot-spark-ui-details.png, screenshot-spark-ui-list.png > > > Since 2.4.0, I am frequently seeing broken outputs in the SQL tab of the > Spark UI, where submitted/duration make no sense, description has the ID > instead of the actual description. > Clicking on the link to open a query, the SQL plan is missing as well. > I have tried to increase `spark.scheduler.listenerbus.eventqueue.capacity` to > very large values like 30k out of paranoia that we may have too many events, > but to no avail. I have not identified anything particular that leads to > that: it doesn't occur in all my jobs, but it does occur in a lot of them > still. -- 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