guixiaowen opened a new pull request, #46620:
URL: https://github.com/apache/spark/pull/46620
… retries may not be successful
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### What changes were proposed in this pull request?
In yarn cluster mode, spark.yarn.maxAppAttempts will be configured. In our
production environment, it is configured as 2 If the first execution fails, AM
will retry. However, in some scenarios, even attempting a second task may fail.
For example:
org. apache. park. SQL AnalysisException: Table or view not found:
test.testxxxx_xxxxx; Line 1 pos 14;
Project
+-Unresolved Relationship [bigdata_qa, testxxxxx_xxxxx], [], false
Other example:
Caused by: org. apache. hadoop. hdfs. protocol NSQuotaExceededException: The
NameSpace quota (directories and files) of directory/tmp/xxx_file/xxxx is
exceeded: quota=1000000 file count=1000001
Would it be more appropriate to try capturing these exceptions and stopping
retry?
### Why are the changes needed?
In some scenarios, even attempting a second task may fail.
### Does this PR introduce _any_ user-facing change?
The user can throw a SparkStopAMRetryException, and the Application Master
will catch the exception and stop retry
For examle
val spark = SparkSession
.builder()
.appName("Spark SQL basic example")
.enableHiveSupport()
.config("spark.some.config.option", "some-value")
.getOrCreate()
try {
spark.sql("select * from test.testxxxx_xxxxx;").show
} catch {
case e:AnalysisException => throw new SparkStopAMRetryException("this
is a test", e)
} finally {
spark.stop()
}
### How was this patch tested?
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